Proceeding Of 30th International Conference on

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Proceeding Of 30th International Conference on Cloud Computing Computer Science and Advances in Information Technology- ICCCCIT 2017 & 30th International Conference on Instrumentation, Electrical and Electronics Engineering- ICIEEE 2017 Date: 14th May 2017 Nagpur

Editor-in-Chief Prof. (Dr.) Arjun P. Ghatule Director, Sinhgad Institute of Computer Sciences (MCA), Solapur (MS)

Organized by:

TECHNICAL RESEARCH ORGANISATION INDIA Website: www.troindia.in

ISBN: 978-93-85225-92-5

About Conference Technical Research Organisation India (TROI) is pleased to organize 30th International Conference on Cloud Computing Computer Science and Advances in Information Technology- ICCCCIT 2017 & 30th International Conference on Instrumentation, Electrical and Electronics Engineering- ICIEEE 2017 ICCCCIT is a comprehensive conference covering all the various topics of Computer Science and Information Technology. The aim of the ICIEEE is to gather scholars from all over the world to present advances in the aforementioned fields and to foster an environment conducive to exchanging ideas and information. This conference will also provide a golden opportunity to develop new collaborations and meet experts on the fundamentals, applications, and products of Electrical and Electronics Engineering. We believe inclusive and wide-ranging conferences such as ICCCCIT can have significant impacts by bringing together experts from the different and often separated fields of Computer Science and In Information Technology. Topics of interest for submission include, but are not limited to: • Computer Science Engineering • Artificial Intelligence • Automated Software Engineering • Computational Intelligence • Information Technology • Computer Architecture and Embedded Systems • Information Retrieval • Information Systems • Internet and Web Applications • Knowledge Data Engineering • Mobile Computing • Electrical Engineering • Electronics Engineering • Radio-Frequency Integrated Circuits • Fiber Optics and Fiber Devices • 3D Semiconductor Device Technology • Advanced Electromagnetics • Adaptive Signal Processing • Software Specification And many more……

Organizing Committee Editor-in-Chief: Prof. (Dr.) Arjun P. Ghatule Director, Sinhgad Institute of Computer Sciences (MCA), Solapur (MS) & Dr. Anjini Kumar Tiwary E.C.E, Dept.BIT, Mesra, Ranchi

Programme Committee Members: Dr. A.Lakshmi Devi E &E Dept. SVU College of Engineering Dr. Bhasker Gupta E.C.E Dept. J.U.I.T, Himachal Pradesh Dr. G.SURESH BABU EEE, Dept. CBIT ,Hyderabad Dr.Manpreet Singh Manna Director,AICTE, New Delhi Dr.Punyaban patel C.S.E ,Dept. C.S.I.T,Durg Dr. S.P.Anandaraj C.S.E, Dept., S.R.E.C, Warangal Dr.G.Babu M.C.A, Dept.A.E.C, Melmaruvathur Dr.B.Rama C.S.E, Dept., Kakathiya University,Warangal Dr. Nagaraj V. Dharwadkar HOD, Associate Prof.. CS.E Dept., RIT, Islampur Dr.Pushpa Ravi kumar Head,C.S.E,A.I.T,Chikmagalur,Karnataka Dr.Poornima Selvaraj I.T, Dept., S.R.E.C, Warangal Dr.Mirza Mohammed Sajid Rub E.E.E Dept. B.I.E.T, Bhadrakh

Dr.A.Sasi Kumar I.T,Dept.S.C.S,Vels University,Chennai Dr. G.Suseendran School of Computing Sciences,Department of Information Technology,Vels University,Tamilnadu Dr. Dariusz Jakóbczak C.S.M, Dept., Technical university of Koszalin, Poland Dr.P.Vijayapal Reddy Professor in CSE Dept., GRIET,Hyderabad Prof. Levina.T CSE Dept. A.C.E, Bangalore Prof. Surjan Balwinder Singh E.E.E. Dept., PEC University of Technology, Chandigarh Prof. Hemant Kumar Soni Computer Science And Engineering Amity university,Madhya Pradesh Asst.Prof. Vineet Shekher E.E,Dept.,SRM University,Utter Pradesh Asst.Prof. Tejinder Singh Saggu E.E,Dept.,PEC University of University, Chandigarh Asst.Prof. I.Hameem Shanavasj ECE, Dept.,M.V.J.C.E,Bangalore Asst.Prof. Vishal J. Deshbhratar CSE Dept. ITM COE,Kamptee, Nagpur Asst.Prof. Megha Garg CSE Dept. J.E.R.C, Jodhpur Asst.Prof. Srinivas Aluvala CSE Dept. S.R.E.C, Warangal Asst.Prof. Manish Kumar Aery MCA Dept. IET, Bhaddal

TABLE OF CONTENTS    SL NO                                         TOPIC                                                         PAGE NO    Editor‐in‐Chief  Prof. (Dr.) Arjun P. Ghatule       1. AUXILIO – A TUTOR BASED APP - Sailee Dalvi1, Shubham Dakhane2, Sana Khan3, Nabeel Shaikh4, Sonali Suryawanshi5 01-05 2. AUTOMATION OF LPG BASED HEATING SYSTEM - Anoop Kumar PKG1, Manu Venkatesh K2, Nishanth Martis3, Nishmitha S Naik4, Pooja S5

06-09

3. REMOTE VIDEO MONITORING SYSTEM USING RASPBERRY PI 3 BASED ON GPRS MODULE AND PPP PROTOCOL 10-14 - S. N. Kale1, Prof. R. D. Patil2   4. CONVERTER FOR UNIVERSAL MOTOR DRIVE SYSTEMS WITH FUZZY LOGIC CONTROLLER - Anju V.T.1, Dr. R. Senthilkumar2 15-20 5. OPTIMAL PATH SEQUENCES OF MAPREDUCE JOBS USING HADOOP - Juliet A Murali1, Tiny Molly V2

21-23

6. PERFORMANCE OF UNIFIED POWER QUALITY CONDITIONER IN DISTRIBUTION SYSTEM FOR POWER QUALITY IMPROVEMENT 24-35 - 1Shital V. Raut, 2Dr. Hari Kumar Naidu 7. PRODUCTIVE ANALYSIS OF ROUTING PROTOCOLS IN MANETS: PROACTIVE VS REACTIVE CATEGORIES 36-42 - Udaya Kumar Addanki1, Swathi Sambangi2 8. POTENTIAL NODULE DETECTION FROM POSTERIOR AND ANTERIOR CHEST RADIO GRAPH USING RESTRICTED BOLTZMANN MACHINE AND SVM CLASSIFIER - 1Dr.T.Satya Savithri, 2S.K.Chaya Devi 43-50 9. A SURVEY ON SECURITY AND PRIVACY CHALLENGES IN MOBILE GRID COMPUTING - 1Malwinder Kaur, 2Mrs. Meenakshi Bansal 51-57

10. INVESTIGATIONS ON THE PERFORMANCE OF FUZZY LOGIC SYSTEM WHEN EVOLVED USING GENETIC ALGORITHM FOR DIFFERENT NUMBER OF FUZZY RULES 58-64 - Shivani Kakkar1, Satvir Singh2, Sarabjeet Singh3,Vijay Kumar Banga4 11. THE ADAPTIVE CONTENTION RESOLUTION MECHANISM FOR OPTICAL BURST SWITCHED NETWORK 65-72 - Dilip Patel 1, Dr. Kiritkumar Bhatt 2, Dr. Jaymin Bhalani 3 12. SECURE P2P VOICE OVER IP USING DEEP PACKET INSPECTION - 1Satish N. Gujar, 2Dr. V.M.Thakare

73-78

13. DESIGN OF STATCOM CONTROL SCHEME TO MITIGATE THE POWER QUALITY PROBLEMS - 1Rakesh S. Kumbhare, 2Dr. Hari Kumar Naidu 79-90 14.. EFFICIENT AND DYNAMIC HYBRID KEY CRYPTOGRAPHY FOR IDS MANAGEMENT SYSTEM IN MANETS 91-96 - 1Kavyashree J,2Bhaskar G

Editorial The conference is designed to stimulate the young minds including Research Scholars, Academicians, and Practitioners to contribute their ideas, thoughts and nobility in these two integrated disciplines. Even a fraction of active participation deeply influences the magnanimity of this international event. I must acknowledge your response to this conference. I ought to convey that this conference is only a little step towards knowledge, network and relationship. The conference is first of its kind and gets granted with lot of blessings. I wish all success to the paper presenters. I congratulate the participants for getting selected at this conference. I extend heart full thanks to members of faculty from different institutions, research scholars, delegates, TROI Family members, members of the technical and organizing committee. Above all I note the salutation towards the almighty.

Editor-in-Chief Prof. (Dr.) Arjun P. Ghatule Director, Sinhgad Institute of Computer Sciences (MCA), Solapur (MS)

AUXILIO – A TUTOR BASED APP 1

Sailee Dalvi , Shubham Dakhane2, Sana Khan3, Nabeel Shaikh4, Sonali Suryawanshi5 Computer Engineering, Mumbai University, Rizvi College of Engineering Abstract This paper tells in detail about our application i.e Android application for finding tutors. In today’s world the increasing trend of private/tuitions has made it difficult for any parent to find a perfect tutor for his/her child. The process of finding a tutor is time consuming because of the competition going on. The rise in educational standards has led to the need for additional coaching. An Android application for finding tutors can help a parent find tutors without consulting any third party. We all know and have experienced this in our school and college life - ‘a friend teaching before exam is the best teacher who teaches the whole subject in one day’ and you understand better when you try to teach another individual. In this paper, we focus on making learning and teaching experience of an individual better. An individual who loves his/her field and has expertise in his field or in few subjects can provide a helping hand to another individual who is weak in the same subject. A tutor can be a graduate and working employee in some company or an under-graduate studying in some college. As android applications have become more and more powerful and distributive, mobile computing has greatly changed our daily life. Hence our android app ‘Auxilio’ which means ‘Helping Hand’ will connect a student who is in search for a tutor with affordable fees rather than expensive classes and a tutor who wants to earn a second pocket money by helping a junior in his/her particular expertise. Keywords: Tutoring, Android, Sql Lite, Data Mining, Schedule, Timetable

I. INTRODUCTION Every student often face difficulties in some or the other subject and opt for coaching classes. Out of these students few of them find the fees not affordable and some don’t appreciate the teaching in classes. Such students don’t opt for classes, start hating that particular subject, start getting low marks consistently. The way a particular student doesn’t like a subject, another student may like it. If a student who is good at one subject and the other student is weak in the same subject, the first student can help or teach the second student. The student who has experienced the same subject can share his experience, the way he/she studied the subject and coped up with everything related to the subject in college life. For a new student to know a senior student’s point of view is always helpful. Engineering exams are conducted in such a way that exams of two subjects are scheduled which have four to five days break in between them. This makes students to procrastinate that we will study in those five days break. In the end students study less which results in scoring low grades, some even tend to fail. To solve this problem a day wise personalized study schedule should be made for the preparation leave before the exams. Auxilio is a platform for collaboration and interaction between students, where one can help the other in academics, providing a cheaper substitute for tuitions and educational classes. An individual who needs help in a particular subject can use this app to search for a tutor who can help him/her. The individual can filter the search by the subject he/she wants to help, area preferable, credits earned by tutor, fees offered by the tutor. The individual can also sort his/her search. The individual can go to any tutor’s profile and check tutor’s qualifications and history. He can

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 1

AUXILIO – A Tutor Based App

contact the tutor and ask him if he/she can help. Auxilio also has extra feature to create a day wise personalized study schedule. A user needs to input the starting date of his study plan, date of last exam, list of exams with the respected dates, priority of exams and type of study time. II. LITERATURE SURVEY A. Tutor.com Tutor.com is an online tutoring company that connects students to tutors in an online classroom. The service offers on-demand and schedule tutoring to students in grades 4 through 12 and college. Users can connect with live tutors online in more than 40 subjects including math, science, essay writing, foreign language and test prep. Since launching in 1998, the company has facilitated over 11 million tutoring sessions with approximately 3,000 tutors. Features: On-demand and schedule tutoring to students in grades 4 through 12 and college. Users can connect with live tutors online in more than 40 subjects including math, science, essay writing, foreign language and test prep.

upload their college’s term test question papers, viva questions. One can sell his/her notes through app (like OLX or Quikr). Student can take help for free from the tutor if both agree on the app. B. Need for this Proposed Plan Here are some statistics of a small survey conducted amongst few FE, SE, TE & BE students of Rizvi College of Engineering. Here are some statistics or results we got:

Students who prefer going  coaching classes 18.1 81.9 No

4.8

Number of Subjects a Student  finds Difficult in any Semester 13.3

website

15.7 25.3

Completely online tutoring. Available online as Android/iOS as apps

Yes

41

and

on

Gooroo.com Gooroo is a mobile app that connects tutors and students. We’re a trusted community marketplace for users to share their talents and discover new ones – all from their mobile phones. Features Helps you get connected to students or tutors near you. Tutor can teach online and offline, both are possible. III. PROPOSED PLAN A. Proposed Idea An undergraduate student also can become a tutor and help a junior in preferred subject. App will provide personalized study schedule for preparation leave before exams by entering starting date (to start studying), date of last exam, list of exams with dates, priority of dates & type of study time. One can refer previous question papers of Mumbai University. One can

None

1

2

3

More than 4

Number of Subjects a  Student finds Easy in any  Semester 7.2 22.9

12

26.5

31.3

None

1

2

3

More than  3

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 2

AUXILIO – A Tutor Based App

A link will be provided to a Google page in which the user will:

Students who agree  'When you teach  someone, you get better  in that topic/subject'

4.8

1. Give his credentials (or not, if he is already logged on Gmail for instance) 2. Give the authorization to Google to give you some his personal data that you request:

95.2 Yes

No

Students who will be able  to help a junior in studies  to earn or for free  10.8 42.2 32.5 14.5 Yes (for free)

Yes (not free)

Both

No

Then the user will be redirect to a page of the website, that you chose, and you will be able to retrieve his personal data. B. Profile creation Profile creation means creating a profile where people can see your information and access it for their use. In this module we have two categories: IV.

Module Description

A. Direct Registration: OpenID provides a safe, elegant and easy way for people to login into your website without having to fill in a registration form. They just have to have an account to one OpenID provider, a Google account for instance, and they will login into your site with this account.

1- Profile creation for a Tutor Here the tutor has to enter his Name, Address, contact number qualifications, achievements (if any), teaching experience (if any), his subject expertise, preferred subjects, salary/ stipend expected, internships, photograph, passing certificates of each semester, recommendation letters. Free teaching(according to choice/ student)

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 3

AUXILIO – A Tutor Based App

2-Profile creation for a Student Here the student will have to enter his Name, Address and contact number, number of KT's so far( also Golden kt if any), sgpa, college/university, current year of learning. Profile will help the student as well as the tutor to get to know about each other in a jiffy. They need not call or text to get to know each other’s grades or scores. The tutors profile will be public whereas the students profile will be private unless he selects a tutor for himself. C. Searching for matching profiles This searching for matching module is the module/part where the student will search and find a tutor according to his personal needs and preferences. This module appears after the user has created his account as a STUDENT and later wants to search a tutor for himself. The searching technique/filters used here should be as simple as possible so as to help the student find the best tutor to his specific needs. It will search the whole domain/list of tutors available on the application. Just like any normal searching techniques, this will also contain some categories on the basis of which the search will take place, these categories are called as FILTERS. Later on basis of these filters the list available can be modified by redefining it. Filters such as Name, Area(Location), Subject/Topic Preference and Credits. Along with these filter, list can be redefined by sorting them according to Price/Cost: Low to High & High to Low, Credits: Low to High & High to Low OR Range of credits, Popularity. Searching techniques used will be Linear Search, Binary Search and Sequential Search. Sorting techniques used will be Bubble Sort, Quick Sort and Insertion Sort. D. Payment: When a student selects a tutor who charges some fee and the tutor agrees to help the student, the student can pay the fee first to the app through payment gateway. In the beginning the 25% amount will be further transferred to the tutor and after the student confirms that the tutor has helped him/her successfully then the other 75% amount of the fee will be transferred from the app to the tutor.

A payment gateway is a merchant service provided by an e-commerce application service provider that authorizes credit card or direct payments processing for ebusinesses, online retailers, bricks and clicks, or traditional brick and mortar. The payment gateway may be provided by a bank to its customers, but can be provided by a specialized financial service provider as a separate service. A payment gateway facilitates a payment transaction by the transfer of information between a payment portal (such as a website, mobile phone or interactive voice response service) and the front end processor or acquiring bank. E. Security: This module is used to encrypt and decrypt data to maintain the user’s privacy. We are proposing to use algorithms like blowfish, AES, DES, etc. Certain personal details of any type of user will be kept private from other user. V. REQUIREMENTS Hardware Requirements : i. Android 4.1 : 32-bit ARMv7, MIPS or x86 architecture processor. ii.

Android 4.1 : 512 MB RAM for devices with low density screens & 1 GB for devices with high density screens.

iii.

Storage Space : 500 MB.

iv.

Camera : Minimum 5 Mega-Pixels.

Software Requirements : i. Android 4.1 Jelly Bean (API level 16). ii. Google Account (GMAIL). iii.

Java Runtime Environment 1.6.

iv.

Java SE JDK v6.0.

v.

Android SDK tools 22.0.5.

VI.

CONCLUSION AND FUTURE SCOPE In future this app could very well expand its domain and increase its range of reachability towards the customers. Since this app is currently limited to only one specific operating system, it will further expand and become available to other major operating systems such as iOS, Blackberry OS, Windows etc. Further

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 4

AUXILIO – A Tutor Based App

advancements could be major UI changes, the interface can be made more interactive and innovative as app should look good and user friendly. The more it is good in all aspects the more it will be used by people which will increase its popularity among the users and more and more users will be using the app. This app could also be later used for other educational fields. Not only limiting it to engineering field and its aspects, but also get into other fields/streams such as science, commerce, arts, architecture, law, management and so on. VII. REFERENCES 1. Journal Papers: i. Automated Timetable Generator, Ansari Ahmed, Ansari Aamir and Ansari Zaeem, M. H. Saboo Siddik College of Engineering, IJIRST – International Jounral for Innovative Research in Science & Technology in Volume 1 – Issue 11 - April 2015 ii. ONLINE EDUCATIONAL SYSTEM (e- learning) - Dr. P. Nagarajan and Dr. G. Wiselin Jiji, Dr. Sivanthi Aditanar College of Engineering, International Journal of U- and E-Service, Science and Technology in Volume 3 - No 4 – December 2010 2.Website: i. www.tutor.com ii. https://www.gooroo.com/ iii. http://www.tutorvista.co.in/index.ph p iv. https://www.etutorworld.com/ v. http://e-tutor.com/ vi. http://www.transtutor.com/ vii. http://www.tutornext.com/ viii. https://www.wiziq.com/ ix. https://www.udemy.com/ 3.APPs: i. Engineeringbuddy ii. Collegedunia iii. Collegedekho

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 5

 

AUTOMATION OF LPG BASED HEATING SYSTEM Anoop Kumar PKG1, Manu Venkatesh K2, Nishanth Martis3, Nishmitha S Naik4, Pooja S5 Canara Engineering College, Manguluru, India Abstract The system is designed to detect the LPG gas leakage and prevention of the same for home safety. The detection of gas leakage is done by using gas sensor and prevention is done by turning off of the main power supply on detecting the leakage. The additional feature of the system includes the automation of the gas stove which involves implementation of the timer based system of induction stove to the LPG stove. The design also includes displaying a message on LCD display when the weight of the gas cylinder goes below a certain threshold in order to replace the cylinder. The system is implemented using ARDUINOMEGA which uses ATmega2560 microcontroller. Keywords: LPG Automation,Smart LPG Regulator,GAS Automation 1. Introduction: The main focus to develop our system was to make it a real time system which involves both detection of gas leakage and prevention. The increase in the development of technology has led to use LPG gas for cooking at home and also hotels. LPG primarily consists of propane and butane which are highly flammable chemical compounds. In the natural state, LPG and natural gas are all odourless. The distinctive smell that people associate with these gases is actually added to them as safety measure .LPG smells because of an odorant, Ethyl Mercaptan is added to the gas to make it easier to detect a leak .Since the sense of smell in a person varies, it is not reliable. Therefore, we use a gas sensor which detects the leakage. The paper refers [1] to the detection of the leakage and alerting the customer about the same and switches on the exhaust fan. In [2],

with the help of microcontroller they display the amount toxic gases being leaked along with detection and alerting system. [3] Refers to locating the area of leakage. In [5] the leakage is detected and alerted by sending SMS to the owner using GSM interface. All these existing research papers involve in detection of leakage and alerting system. The system which we have proposed aims on not only detection and alerting, but also includes prevention of any electrical interferences or accidents due to the leakage. This prevention is implemented by switching off the main power supply when the leakage is detected. The leakage detection is done by using a MQ6 gas sensor. Along with leakage detection and prevention, there lies an idea of weighing the gas cylinder with the help of load cell. Sometimes we return the cylinder to the gas agent assuming it to be empty, which may not be the case. This problem is overcome by using weighing mechanism which weighs the cylinder and displays a message to replace the cylinder when the weight is below the threshold value. We also implement timer concept in the proposed device for cooking the food for required amount of time. 2. Literature Survey The system detects the leakage of the LPG and alerts the consumer about the leak and as an emergency measure the system will switch on the exhaust fan and also checks the leakage. Sunithaa.J, Sushmitha.D, “Embedded control system for LPG leakage detection and prevention” International Conference on Computing and Control Engineering (ICCCE 2012), 12 & 13 April, 2012. The main objective of the work is design in microcontroller based toxic gas detecting and

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 6

Automation Of LPG Based Heating System

alerting system. The hazardous gases like LPG and propane were sensed and displayed each and every second in the LCD display and alerts with the help of an alert message. V.Ramya, B. Palaniappan, “Embedded system for hazardous gas detection and alerting” International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.3, May 2012.

3. Hardware Description: This prototype consists of leakage detection and prevention module, weighing mechanism and timer circuitry. It uses Arduino Mega 2560 which is a microcontroller board based on the ATmega2560. It has 54 digital input/output pins (of which 14 can be used as PWM outputs), 16 analog inputs, 4 UARTs (hardware serial ports), a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a reset button. It contains everything needed to support the microcontroller; it can be simply connected to a computer with a USB cable or power it with an AC to DC adapter or battery to get started. The leakage detection module consists of the MQ-6 gas sensor which is highly sensitive to LPG. MQ-6 gives fast response time at the output and has a stable and longer life. The sensitivity of the gas sensor can be adjusted using external circuitry. The sensor is insensitive to air. The sensor output is analog resistance. The output of sensor module is connected to ADC of the microcontroller. The microcontroller digitizes the voltage and checks if the concentration of LPG is within safe levels. If the concentration of LPG which is a combustible gas and is beyond safe levels (the safety level is programmable) the microcontroller immediately activates the LCD and turns off the main power supply and further it is interfaced with the load cell to implement additional functionality of displaying the weight of the cylinder approximation of the percentage of total weight is displayed using an LCD. The load cell can translate 10kg of pressure into an electrical signal. The load cell is capable of measuring the electrical resistance that changes in response to, and proportional of the strain applied to the load cell. Further a timer is installed in order to help the user to cook for certain amount of time. The important function of gas detection module is to detect the change in composition of LPG gas when there is a leakage and turn off the main power supply. To detect the leakage MQ6 gas sensor is used. The sensitive material in MQ6 is SnO2 with lower conductivity in low clean air. When the target combustible gas is present, the sensor’s conductivity is higher along with rise in gas concentration and the resistance of sensor changes with the concentration of combustible gases. Figure 2

This system gives real time detective of potential risk area, collect the data of leak accident and locate leakage point. This system having protection circuitry consists of exhaust fan and a Liquefied Petroleum Gas Safe Solenoid Valve. In this system MQ-6 gas sensor used to sense poisonous gas. Mr.SagarShinde, Mr.S.B.Patil, Dr.A.J.Patil, “Development of movable gas tanker leakage detection using wireless sensor network based on embedded system”, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.1180-1183. The objective of this work is to present the design of a cost effective automatic alarming system, which can detect liquefied petroleum gas leakage in various premises. In particular, the alarming system designed has a high sensitivity for primarily butane, which is also individually sold bottled as a fuel for cooking and camping. A. Mahalingam, R. T. Naayagi, N. E. Mastorakis, “Design and Implementation of an Economic Gas Leakage Detector”, Recent Researches in Applications of Electrical and Computer Engineering. The system detects the leakage of the LPG using gas sensor and alerts the consumer about the gas leakage by sending SMS. The proposed system uses the GSM to alert the person about the gas leakage via SMS and alert the people at home by activating the alarm which includes the LED, Buzzer simultaneously and display the message on LCD display to take the necessary action and switch on the exhaust fan. M. B. Fish, R.T. Wainer, “Standoff Gas Leakage detectors based on tunable diodes laser absorption spectroscopy”.

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur



Automation Of LPG Based Heating System

done by interfacing a load cell with microcontroller. The load cell will produce an analog voltage corresponding to the change in weight this is in terms of millivolts a suitable circuitry is used to amplify and filter this analog voltage . This will be displayed in a Liquid Crystal Display interfaced with the microcontroller. If found empty a message is displayed on LCD to replace the cylinder. The Arduino Mega 2560 forms the heart of the entire system controlling all processes that take place. A timer is interfaced to for the users to set a particular amount of time depending on their need of time for cooking is displayed on the LCD display.

shows the gas leakage sensing circuitry. A simple electronic circuit can be used to convert the change in resistance to change in terms of concentration of combustible gases.MQ6 gas sensor has high sensitivity to Propane, LPG and Butane. Low cost and long life are the first advantages of using this sensor. Secondly it has simple drive circuit. For the sensor to function properly the sensor needs to be heated for specific amount of time called the preheat time. The sensor works with 5volt power supply. Addition feature is to indicate about the approximate weight of the cylinder is given as full, medium or empty. This measurement is

  LCD    Stove   

       

Hex   keypad   

Cylinder   

Arduino

Tripper   

Regulator   

     

Gas   sensor   

Pipe line   

   

Load   sensor   

 

LCD. When the weight of the gas is less than or equal to a threshold value, a logic high pulse is fed to a port pin of microcontroller. As this pin goes high, microcontroller will display the message to replace the cylinder on LCD. Along with the above facility inbuilt timer is also provided to turn off the stove after certain duration of time. The timing pulse is fed into microcontroller when a key in hex keypad is pressed and accordingly the digital output is displayed on LCD.

4. System Operation: In this prototype, gas leakage detection is performed using MQ6 gas sensor, which is placed in the vicinity of the gas cylinder. At the occurrence of leakage, the resistance of the sensor decreases increasing its conductivity. Corresponding pulse is fed to microcontroller and simultaneously the main power supply is turned off in order to prevent accidents. The load cell continuously monitors the weight of the gas in cylinder and displays the weight on

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur



Automation Of LPG Based Heating System

5.

Future Scope

  Check if  the gas is leaking

 

True

  False

 

Check the weight of the cylinder  

Off the regulator and power supply  

     

Timer   

False   

Weight is  greater  then 

True

Display change the cylinder   

 

ENGINEERING Vol. 2, Issue 2, February 2014 [2]Sagar Shinde, S.B.Patil, Dr.A.J.Patil “Development of Movable Gas Tanker Leakage Detection Using Wireless Sensor Network Based on Embedded System” International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, NovemberDecember 2012, pp.1180-1183

6. Future Scope 1. By making this product to operate for many cylinders together we can use it in the flats. 2. Can detecting the location and amount of leakage we can use the device for industrial purpose. 7. Conclusion This system detects the leakage of the LPG and alerts the consumer about the leak and as an emergency measure the system will turn off the power supply, while activating the alarm. Real time weight measurement of the gas and its display on LCD makes it an efficient home security system and also can be used in industries and other places to detect gas leaks. This project is implemented using the Arduino mega processor. The cost involved in developing the system is significantly low and is much less than the cost of gas detectors commercially available in the market.

[3]A. MAHALINGAM, R. T. NAAYAGI, N. E. MASTORAKIS “Design and Implementation of an Economic Gas Leakage Detector” Recent Researches in Applications of Electrical and Computer Engineering [4]S.RAJITHA ,T.SWAPNA “A SECURITY ALERT SYSTEM USING GSM FOR GAS LEAKAGE” International Journal of VLSI and Embedded Systems-IJVES Vol 03, Issue 04; September-October 2012

8. Reference [1] K.Padma Priya, M.Surekha, R.Preethi, T.Devika, N.Dhivya “SMART GAS CYLINDER USING EMBEDDED SYSTEM” INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur

 9

REMOTE VIDEO MONITORING SYSTEM USING RASPBERRY PI 3 BASED ON GPRS MODULE AND PPP PROTOCOL S. N. Kale1, Prof. R. D. Patil2 ME Electronics Engineering, Associate Professor Abstract video monitoring has played important role now in day to day life for security purpose. With wireless technology we can connect to remote area. Also due to development in embedded technology, it is possible to build inexpensive system for remote area monitoring. This paper presents implementation of remote video monitoring system using Raspberry Pi 3 based on GPRS (General Packet Radio Service) network and PPP protocol. Transmitter hardware takes Raspberry Pi 3 with ARM Cortex-A53 (64 Bit) processor as centralized unit along with 1GB LPDDR2 SDRAM, USB camera and GPRS module for internet connectivity which again reduces overall cost of the system. Application program is used to capture images using USB camera and compressed through libjpeg library for JPEG compression. Captured images are transmitted via SIM900A dual band GSM/GPRS module using PPP protocol to FTP server. This system is supported by Raspbian Linux operating system based on Dabian. Monitoring center downloads image data from FTP server by using curl client utility and displays using MJPG streamer. In this system we can view images as well as can store images sent by transmitter for future use. With the combination of Raspberry Pi and GPRS module, the monitoring system has the advantage of low cost and low power consumption. Index Terms: Raspberry Pi, USB Camera, GPRS, PPP, MJPG streamer

I. INTRODUCTION Recent years monitoring facilities are required and useful for our daily life security. From small firms to many large companies some kinds of video capturing systems have introduced to keep their security. Traditional video surveillance system can generally achieve close distance monitoring, by using the computer system as a monitoring unit connected to surveillance camera with coaxial cable. But today in this digital world, the video surveillance systems based on embedded technology are more advantageous compared to the traditional surveillance systems. It provides high performance at low cost and good stability. Meanwhile, it provides many advantages, such as enhanced design simplicity, compact construct, portable, low power consumption, long-distance transmission. For wide coverage areas and hard-to-wire locations for remote monitoring such as traditional river monitoring systems, it is difficult to construct a system because river environments are not well suitable for wire or fiber transmission lines. Here wireless GPRS technology gives an excellent alternative for this. As it is easy to set up and configure, the cost of operating a GPRS monitoring system can be substantially lower, since the cost is directly proportional to the volume of the data and the frequency with which it is transmitted. II. SYSTEM ARCHITECTURE In this system, frames are captured from a USB camera which is connected to Raspberry Pi. Captured frames are compressed into JPEG format. These frames are transferred by the GPRS network under the control of the Raspberry pi to FTP server.

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 10

Remote Video Monitoring System Using Raspberry PI 3 Based On GPRS Module And PPP Protocol

USB Camera

Raspberry Pi 3 (BCM2837 )

SIM900 A GPRS module

Internet FTP Server

Computer System (MJPG Streamer)

WiFi/ Internet connection

Fig 1 Block diagram of overall system Video frames are downloaded using client utility program such as curl. The monitor client will receive these frames which are streamed using MJPG Streamer. Wireless video monitor system provide a practical solution for remote wireless monitoring with low cost. III. RASPBERRY PI 3 SYSTEM In this system we have used RASPBERRY PI 3 model B with1.2GHz Quad-Core ARM Cortex-A53 processor. The raspberry pi is a very powerful, minicomputer with the dimensions of credit card. It Boots from Micro SD card, running a version of the Linux operating system or Windows 10 IoT. This system is very easy to operate and user friendly as it comes with GUI and command prompt. The brain of the Raspberry pi is the Broadcom BCM2837 “system on chip,” which includes the main components needed for a computer system. These include the central processing unit (processor), which handles the main workload; the graphics processing unit (GPU) such as Dual Core VideoCore IV® Multimedia Co-Processor which provides Open GL ES 2.0, hardware-accelerated OpenVG, and 1080p30 H.264 high-profile decode , which accelerates the process of producing the complicated graphics to see on screen; and the random access memory (RAM) 1GB LPDDR2 memory module which acts as somewhere for the CPU to keep the information that it is working on.

The Raspberry Pi 3 has four USB ports, allowing connect it to keyboards, mice, WiFi dongles, USB camera and USB sticks containing files. This system comprises the general purpose input/output (GPIO) pins. They’re a set of connections that have various functions, but their main one is to allow you to connect to the Raspberry Pi with an electronic circuit. The Raspberry Pi 3 features the same 40-pin general-purpose input-output (GPIO) header as all the Pis going back to the Model B+ and Model A+. Any existing GPIO hardware will work without modification; the only change is a switch to which UART is exposed on the GPIO’s pins, but that’s handled internally by the operating system. A. Preparation of operating system for Raspberry Pi 3 This device supports Raspbian, a Debian-based Linux distribution, Windows 10 IOT Core, RISC OS, and specialized media center distributions. It promotes Python and Scratch as the main programming language, with support for many other languages. Raspbian operating system is selected to control functioning of Pi. First it is required to prepare SD card with operating system which is installed using WIN32DISKIMAGER utility in Windows operating system. After preparation, pi is booted using SD card and configured by using raspi-config configuration menu.

Fig 2 configuration tool window EXPAND FILE SYSTEM option is enabled so that all of the SD card storage is available to the OS. Password can be changed using CHANGE USER PASSWORD option. With ENABLE BOOT TO DESKTOP/SCRATCH, booting into a desktop environment, Scratch, or the command

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 11

Remote Video Monitoring System Using Raspberry PI 3 Based On GPRS Module And PPP Protocol

line is selected. INTERNATIONALISATION Options sets up the language and regional settings to match location. In advanced option SERIAL option is enabling for shell and kernel messages on the serial connection.

D. YUV to RGB conversion: captured frames are converted into RGB format. YUV format are used for television broadcast however many displays (almost all DVI inputs) only except RGB.

IV. APPLICATION PROGRAM DESIGN FRAME CAPTURE AND COMPRESSION

E. JPEG compression: The JPEG compression encoding scheme is used in the this system which is based on the DCT (Discrete Cosine Transform) sequence. The JPEG encoding under Linux can use the library Libjpeg, which is used under linux standard library, and its function is to compress the picture in accordance with a certain percentage of compressed into JPEG format pictures. Most of the software operating on JPEG are based on this library. In this system libjpeg8 library package is installed using sudo apt-get install libjpeg8-dev on command line.

FOR

To capture frames an application program is written in C language which is based on Video For Linux Two API. V4L2 drivers are implemented as kernel modules, loaded manually by the system administrator or automatically when a device is first opened. The driver modules plug into the "videodev" kernel module. Driver supports video capturing through /dev/vide0. To open and close V4L2 devices application program uses the open() and close() function, respectively. A. Open the video equipment: The device name of USB camera in Linux is /dev/video0. The Linux kernel supports UVC (USB video device class) based cameras. UVC is a USB device class that describes devices capable of streaming video like webcams, digital camcorders, transponders, analog video converters, television tuners, and still-image cameras. Logitech c 170, 5 Mp web camera is connected to Pi which is UVC based so that there is no requirement for drivers needed to capture images from the camera. B. Initialization of video device: Devices are programmed using the ioctl() function. The VIDIOC_QUERYCAP ioctl is available to check if the kernel device is compatible with specification given by V4L2 API, and to query the functions and I/O methods supported by the device. Applications can use the VIDIOC_G_CROP and VIDIOC_S_CROP ioctls to get and set top left corner, width and height of image. The v4l2_pix_format structure defines the format and layout of an image in memory. Image formats are negotiated with the VIDIOC_S_FMT ioctl. YUYV image format is selected using V4L2_PIX_FMT_YUYV function. C. Frame capture: memory mapped streaming I/O method is used to map buffers in device memory into the application’s address space. To allocate device buffers applications call the VIDIOC_REQBUFS ioctl with the desired number of buffers and buffer type.

DESIGN FOR V. PROGRAM NETWORKING A. sim900A GSM/GPRS module GSM/GPRS Modem-RS232 is built with Dual Band GSM/GPRS engine- SIM900A, works on frequencies 900/ 1800 MHz. It features GPRS multi-slot class 10/class 8(optional) and support GPRS coding schemes CS-1,CS-2, CS-3,CS-4.The Modem is coming with RS232 interface, which allows connect PC as well as microcontroller with RS232 Chip(MAX232). The baud rate is configurable from 9600-115200 through AT command. The GSM/GPRS Modem is having internal TCP/IP stack to enable to connect with internet via GPRS. It is suitable for SMS, Voice as well as DATA transfer application in M2M interface. There is GPRS data transfer (PPP or TCP or UDP) in progress. In this case, power consumption is related with network settings (e.g. power control level), uplink / downlink data rates and GPRS configuration (e.g. used multi-slot settings).The onboard Regulated Power supply allows to connect wide range unregulated power supply. Using this modem can make audio calls, SMS, Read SMS; attend the incoming calls and internet through simple AT commands. The modem needed only 3 wires (Tx, Rx, GND) except Power supply to interface with microcontroller/Host PC. The built in Low Dropout Linear voltage regulator allows to connect wide range of unregulated power supply (4.2V -13V).

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 12

Remote Video Monitoring System Using Raspberry PI 3 Based On GPRS Module And PPP Protocol

Raspberry Pi is connected to the internet through a GPRS cellular data connection using GPRS module. The Raspberry Pi serial port consists of two signals (a 'transmit' signal, TxD and a 'receive' signal RxD) made available on the GPIO header. To connect to another serial device, the 'transmit' of pi is connected to the 'receive' of the GPRS module, and vice versa. The Ground pins of the two devices should be connected together. On the Raspberry Pi 3 the second serial port is called /dev/ttyS0 and is by default mapped to the GPIO pins 14 and 15.

Fig 3 Interfacing of USB camera and GPRS module to Raspberry Pi A. Access of the Internet using GSM / GPRS Modem (SIM900A) and PPP protocol PPP is most commonly used data link protocol. It is used to connect the Home PC to the server of ISP via a modem. PPP is the protocol used for establishing internet links over dial-up modems, DSL connections, and many other types of point-to-point links. The pppd daemon works together with the kernel PPP driver to establish and maintain a PPP link with another system (called the peer) and to negotiate Internet Protocol (IP) addresses for each end of the link. Pppd can also authenticate the peer and/or supply authentication information to the peer. PPP can be used with other network protocols besides IP. Chat is a program that can perform simple handshaking between a PPP client and server during connection setup, such as exchange usernames and passwords. Chat is also

responsible for causing your modem to dial the ISP's phone number and other simple tasks. Chat itself is automatically invoked by pppd when started. A simple shell script invokes chat to handle the negotiation. Script file should be placed in the /etc/ppp (as root). Required and previlaged options are defined in script file which is placed in /etc/ppp/peers directory B. Uploading images to FTP server Captured images with number of frames set by user are uploaded through FTP client utility to FTP server. Shell script is used to connect, upload images to FTP server. C. Multithreading in Application program In most modern operating systems it is possible for an application to split into many "threads" that all execute concurrently. In order to take full advantage of the capabilities provided by threads, a standardized programming interface was required. For UNIX systems, this interface has been specified by the IEEE POSIX 1003.1c standard (1995). Implementations adhering to this standard are referred to as POSIX threads, or Pthreads. Most hardware vendors now offer Pthreads in addition to their proprietary API's. The POSIX thread libraries are a standards based thread API for C/C++. It is most effective on multi-processor or multi-core systems where the process flow can be scheduled to run on another processor thus gaining speed through parallel or distributed processing. Threads require less overhead than "forking" or spawning a new process because the system does not initialize a new system virtual memory space and environment for the process. As Raspbian is Linux based dabian package, it also support multithreading via POSIX thread libraries. The function ‘pthread_create () can start execute a function as a separate thread within the main process which calls the ‘pthread_create (). The prototype of the function ‘pthread_create () is defined in the header file . Thread synchronization is achieved by using the function pthread_join( ).

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 13

Remote Video Monitoring System Using Raspberry PI 3 Based On GPRS Module And PPP Protocol

VI. MONITORING AT RECEIVER At receiver side we have computer system with Linux based Ubuntu operating system which is used to receive and display frames continuously by using application programs. Frames are received using internet via FTP client such as curl and frames are displayed using MJPG Streamer program. Internet connectivity is provided via Wi-Fi or 3G dongle. A. MjpgStreamer It is a simple utility to stream images or video via HTTP. MJPG-streamer", is a command line application that copied JPG-frame from a single input plug-in to multiple outputs plug-in. It can be used to stream JPEG files over an IP-based network from the webcam to a viewer like Firefox, and Video lan client or even to a Windows Mobile device running the TCPMP-Player. It uses hardware compression in order to reduce CPU cycles of the server. It is light and utilize less CPU hence ideal for embedded devices and regular servers. It recovers JPG images from UVC-compatible webcams, system files or other input plugins and distributes them as M-JPEG via HTTP to browsers, VLC or others. We can use input_file plugin to collect images from folder, ouput_http plugin to stream files and output plugin to store JPEG images of the input plug-in in a specified folder.

Fig 4 streaming of video at receiver side using MJPG Streamer

simultaneously which increases performance of the system. After compression, images are uploaded to FTP server in 5-7 seconds. This may vary according to strength of network signal. This system is a good solution in areas where continuous streaming is not required. We can reduce cost as it doesn’t require static IP and also GPRS system require less bandwidth as compared to 3g and next upgraded version network. As images are available to receiver side, we can use those images for future use. REFERENCES [1] Lihui Zhao,Chunbao Huo, Hongzhe Yang, “The Design of Remote Video Monitoring System Based on S3C2416 and GPRS,” IEEE Trans. on System Science and Engineering, , pp. 385-388, July 2012. [2]

Denan Li, Zhiyun Xiao,, “Design of Embedded Video Capture System Based on ARM9,” IEEE , 978-1-4244-8039-5/11, 2011.

[3]

Nagaraja G. and Sharada P.N., “ Design of Remote Security System Using Embedded Linux Based Video Streaming” (IJCAR) ISSN 2305-9184 Volume 2, Number 2 (April 2013), pp. 50-56.

[4]

Ruturaj Shete, Mayuri Sabale , “VIDEO SURVEILLANCE USING RASPBERRY PI ARCHITECTURE” Discovery ANALYSIS The International Daily journal ,ISSN 2278 – 5469,pp 37-43,Nov 2015

[5] Sanjana Prasad1, P.Mahalakshmi2, A.John Clement Sunder3, R.Swathi4, “Smart Surveillance Monitoring System Using Raspberry PI and PIR Sensor”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014, pp 7107-7109

VII. CONCLUSION With this system jpeg images are captured with size 320x240 and compressed by 15-20% of original image. Due to multithreading it is possible to capture images and connect to server 30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 14

CONVERTER FOR UNIVERSAL MOTOR DRIVE SYSTEMS WITH FUZZY LOGIC CONTROLLER Anju V.T.1, Dr. R. Senthilkumar2 1 PG Scholar, 2Professor, Department of Electrical and Electronics Engineering Vimal Jyothi Engineering College, Kannur

finally lead to diode reverse recovery problem. So, to overcome these disadvantages, transformers or coupled inductors are used. But due to the complexity of the circuit and as the leakage inductance is large, voltage spikes occur. Conventionally, PI, PD and PID controller are most popular controllers and widely used in most power electronic closed loop appliances. However recently many researchers successfully adopted Fuzzy Logic Controller (FLC) to become one of the intelligent controllers to their appliances. After classical converters, the different converter has been introduced. Boosting in done in a single stage for increasing the efficiency. So low cost and compact size can be obtained [1]. Converters with Single Pole Triple Throw Switch are used to increase the efficiency and reducing the cost [2]. By using a dead time between two switching commands in the multiinput converter makes the dynamic system gets improved [3]. An active ripple reduction technique is proposed in the fuel cell by adding a current loop control into the existing voltage loop control system thus reducing the ripple current [4]. A clamp mode converter with high step up voltage is proposed which adds two pairs of additional capacitors and diodes to achieve high step-up voltage gain. It has low conduction losses. Clamping circuit clamps the voltage across the circuits [5]. Non-isolated dc-dc converter with a voltage multiplier is proposed thus providing high static gain and high [6]. An interleaved high step up converter with voltage lift capacitor technique and voltage

Abstract A high gain multi-input dc-dc converter with a fuzzy logic controller is proposed in this paper. The converter can draw continuous current from two input sources. In this converter, diode and capacitor are cascaded together with four voltage multiplier stages. Thus it improves the gain of the converter. This converter which is controlled by a fuzzy logic controller is connected to the universal motor. The converter has several desirable features such as low ripple current and reduced voltage stress. The fuzzy logic controller has been implemented to the system by developing fuzzy logic control algorithm. The evaluation of the output has been carried out and compared by using MATLAB/ Simulink environment. Finally, prototype circuit is operated to verify its performance Index Terms:Modified Boost Converter, Voltage Multiplier, Switched Capacitor, Multi Input Converter, Fuzzy Logic Controller. I. INTRODUCTION Nowadays due to reduced environmental contamination and energy shortage, renewable sources such as photovoltaic, fuel cell etc received great attention. These renewable sources are used as input voltage in various applications. DC-DC converters are used to boost the low voltage dc to a high level. So, various converters such as boost, buck, etc., are used to boost the low voltage levels, but it contains large duty ratios. This result in high current stress and the efficiency is reduced so

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 15

Converter For Universal Motor Drive Systems With Fuzzy Logic Controller

multiplier module is proposed which extends the voltage gain and increases the voltage conversion ratio [7]. Then, a high step up converter with voltage multiplier module is proposed which contains a clamping circuit to obtain soft commutation, thus reducing the voltage stress and increases the flexibility [8]. Thus a conventional interleaved boost converter integrated with a voltage multiplier module. The voltage multiplier module is composed of switched capacitors and coupled inductors. To extend step up gain coupled inductors are used. Voltage conversion ratio is increased by using switched capacitors [9]. Thus an interleaved high step-up converter integrated with winding cross coupled inductors [WCCI] and voltage multiplier cells is proposed. Voltage stress can be reduced and voltage multiplier cells absorb the voltage spikes [10]. Because of these reasons, it is necessary to find new converters which have to overcome these various disadvantages. A modified boost converter which is used as a high gain dc-dc converter with diode and capacitor cascaded together to boost up the voltage are presented in this paper [11]. The major advantages are high voltage gain, low voltage stress, and low current ripple.

II. MULTI INPUT CONVERTER A. STRUCTURE A modified boost converter (shown in fig 2) with diode and capacitor cascaded together with four voltage multiplier stages are proposed in this paper. It has four boost stages which are integrated together at the input. An overlap time is present for the normal converter. So in order to avoid the overlap time the converter operates in three modes of operation.

Fig.2 Circuit diagram of modified boost converter B. OPERATION Mode 1: In this mode, as shown in Fig.3, S1 and S2 are ON at the same time. Vin1 and Vin2 input sources are used for charging the inductor. The diode is reverse biased and output capacitor is used for supplying to the load

The Fig.1 shows the block diagram of the proposed system. It consists of two input source i.e., battery and a PV panel. The output from the PV panel is given to the converter. The battery stores the charge from the PV panel using a boost converter during day time and utilizes the charge during night. The converter is controlled by a fuzzy logic controller. The converter output is given to the inverter for converting the dc into ac which is then connected to the universal motor.

Fig.3 Mode 1 operation Mode 2: In this mode, shown in Fig.4, switch S2 is ON and switch S1 is OFF. As there are four stages forward biasing the output diode thus charging the output capacitor.

Fig.1 Block Diagram

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 16

Converter For Universal Motor Drive Systems With Fuzzy Logic Controller

obtained is an error. These values are multiplied by the gain and fed to a fuzzy logic controller. The result will change in duty cycle. The change in duty cycle and the previous duty cycle are added and given to the MOSFET. Membership functions of input and output are decided in the first step of fuzzification. Membership functions to input and outputs are PB, PS, ZE, NS, NB. Where NB = Negative big, NS = Negative small, ZE = Zero equal, PS = Positive small, PB = Positive big. Following is rule Table.1 given which is used for change in duty cycle values TABLE 1 FUZZY CONTROL RULES

Fig.4 Mode 2 operation Mode 3: In this mode (shown in fig 5), S1 is ON and S2 is OFF. As there are four stages reverse biasing the output diode and output capacitor is used for supplying the load.

Error Chang e in Error PB PM PS ZE NS NM NB

Fig.5 Mode 3 operation

NB

NM

NS

ZE

PS

ZE NS NM NB NB NB NB

PS ZE NS NM NM NM NB

PM PS ZE NS NS NM NB

PB PM PS ZE NS NM NB

PB PM PS PS ZE NS NM

PM

PB PM PM PM PS ZE NS

IV. DESIGN CONSIDERATION The charge is transferred progressively from input to the output by charging the VM stage capacitors. For a converter with four level voltage multiplier the voltage can be derived by,

III. FUZZY LOGIC CONTROLLER In a fuzzy logic controller, controlling is done from a set of linguistic rules. A block diagram of fuzzy logic controller is shown in Fig 6.

Vc1 =

Vc2 = Vc3 = Vc 4 

Fig.6 Fuzzy Logic Controller It consists of four blocks in which fuzzifier is used to classify the input value into a certain linguistic values. The Knowledge base consists of certain control rule sets. Decision making is done in the interference engine. Defuzzifier converts the control action into crisp signals.

Vin1

(1)

(1 - d1)

Vin1

+

(1 - d1) 2Vin1

+

(1 - d1) 2Vin1



(1  d 1)

Vin2 (1 - d2) Vin2 (1 - d2) 2Vin 2 (1  d 2)

Vc1 = Vc3 - Vc2 =

Vin1 (1 - d1)

(2) (3) (4) (5)

If N is odd, Vout = VCN +

=

N +1 Vin1 2 (1- d1)

+

Vin1 (1 - d1)

N +1 Vin2 2 (1- d2)

(6)

If N is even,

Fuzzification consists of input error and change in error. By subtracting the output voltage and the desired voltage the result

Vout = VCN +

Vin1 (1 - d1)

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 17

PB

PB PB PB PB PM PS ZE

Converter For Universal Motor Drive Systems With Fuzzy Logic Controller

=

N + 2 Vin1 2

(1 - d1)

+

N Vin2

Table 1 Boost Converter Parameters

(7)

2 (1 - d2)

The output voltage equation of the voltage multiplier capacitor stages depends upon the number of N stages. If d1 and d2 have the same value, the equation for the output voltage is Vo =

 N + 1 Vin1 (1 - D)

Parameters Input voltage Output voltage Duty ratio, D Inductor, L Capacitor, C Switching frequency Output voltage ripple Inductor current ripple

(8)

The inductor currents in both the boost stages depend on the number of VM stages. The average inductor current in each boost is given by L=



[1 - d1 Vin1]



[( N + 2) IoutFsw]

(9)

40

ΔIout(1 - d) FswΔVc

Volatge(V)

The voltage multiplier stage capacitor is given by C=

Value 25V 30V 0.2593 1.7Mh 3300Μf 5KHz 0.0159V 0.48V

(10)

30 20 10 0

V. RESULTS AND DISCUSSION In open loop, the voltage will not be constant for load variations on the motor so a closed loop technique is implemented. For controlling the converter, a fuzzy logic controller is used shown in Fig.8. It consists of input error and change in error. By subtracting the output voltage and the desired voltage the result obtained is an error. These values are multiplied by the gain and fed to a fuzzy logic controller. The result will change in duty cycle. The change in duty cycle and the previous duty cycle are added and given to the MOSFET.

0

0.1

0.2 0.3 Time(sec)

0.4

0.5

0

0.1

0.2 0.3 Time(sec)

0.4

0.5

Current(A)

0.8 0.6 0.4 0.2 0

Fig.8 Simulation Result of Photovoltaic System The photovoltaic system supplies the power to the converter. Battery accumulates the excess energy created by the PV system. For charging and discharging the battery, a boost converter is used. So, by giving an input voltage of 25V, 30V output voltage can be obtained with a switching frequency of 5 kHz. Table 2 Modified Boost Converter Parameters Parameters Input voltage Output voltage Duty ratio, D Inductor, L1, L2 Capacitor, C1, C2, C3, C4 Switching frequency

Value 20V 400V 0.75 100μH 20μF 100KHz

The output voltage of the converter is 400V by giving an input voltage of 20V.For the voltage multiplier stage capacitors, the ripple current will be higher therefore a capacitor of

Fig.7 Simulation Model of Multi Input Dc-Dc Converter with High Gain for Solar Powered Systems

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Converter For Universal Motor Drive Systems With Fuzzy Logic Controller

20μF is selected. Thus the developed fuzzy logic controller is very efficient to suppress the fluctuations caused by the variations of the capacitor values and is able to maintain the constant voltage at the output. Voltage(V)

600 400 200 0 -200

0

0.1

0.2 0.3 Time(sec)

0.4

0.5

0

0.1

0.2 0.3 Time(sec)

0.4

0.5

Fig.11 Pulse waveform of converter

Current(A)

1.5 1 0.5 0 -0.5

Fig.9 Simulation Result of Multi Input Dc-Dc Converter with High Gain for Solar Powered Systems Fig.12 (a) Pulse waveform of inverter

The speed and torque waveform of the motor is shown in Fig.10. The noise produced in the PWM inverter is also observed in the electromagnetic waveform Te. However, motor inertia prevents this noise from appearing in the motor’s speed waveform

Speed(rpm)

1500 1000 500

Fig. 12(b) Pulse waveform of inverter

0 -500

0

0.1

0.2 0.3 0.4 Time(sec)

0

0.1

0.5

Torque(N-m)

150 100 50 0 -50

0.2 0.3 Time(sec)

0.4

0.5

Fig.10 Speed and Torque Waveform

Fig. 13 Output voltage of converter Fig.13 shows the output voltage of the converter. The output voltage is 67.6V which is obtained by giving an output voltage of 18V. The output voltage is obtained from MOSFET by giving pulse from the MOSFET driver.

VI. DESIGN AND EXPERIMENT OF PROPOSED CONVERTER A prototype of the multi input converter is tested. The design consideration of the converter is based on the components selections which are presented in the previous section. The Fig.11 shows the pulse waveforms of the converter and the Fig .12(a) and (b) shows the pulse waveform of the two legs of the inverter

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Converter For Universal Motor Drive Systems With Fuzzy Logic Controller

Fig.14 Inverter Phase voltage The Fig.14 shows the phase voltage from the inverter which is connected to the load which is used to drive the motor. Fig.15 shows the prototype of the converter

Fig. 15 Prototype photograph of the converter VII. CONCLUSION In this paper, high gain multi input dc-dc converter with a fuzzy logic controller is proposed. The converter consists of four diodecapacitor voltage multiplier stages. As the number of voltage multiplier stages are increased, the voltage gain is also increased. The converter which is controlled by a fuzzy logic controller is simulated and it is validated through hardware implementation. A simple algorithm based on the prediction of a fuzzy logic controller, possibly using the fuzzy rules parameters is showing to be more convenient. Thus it is observed that the output voltage of the system using a fuzzy logic controller is boosted and thus improves the efficiency of the converter. REFERENCES [1] S. Jain and V. Agarwal," A single-stage grid connected inverter topology for solar PV systems with maximum power point tracking", IEEE Trans. Power Electron., vol. 22, no. 5, pp. 19281940, Sep. 2007. [2] K. Gummi and M. Ferdowsi,"Synthesis of double-input dc-dc converters using single pole triple throw switch as a building block," Proc. IEEE Power Electronics Specialists Conf., 2008, pp. 2819-2823.

[3] V. A. K. Prabhala, D. Somayajula and M. Ferdowsi, "Power sharing in a double- input buck converter using dead-time control," in Proc. IEEE Energy Conversion Congress and Exposition (ECCE), San Jose, USA,2009, pp. 2621-2626. [4] C. Liu and J. S. Lai, \Low frequency current ripple reduction technique with active control in a fuel cell power system with inverter load" , IEEE Trans. Power Electron., vol. 22, no. 4, pp. 14291436, Jul. 2007. [5] Yi-Ping Hsieh, Jiann-Fuh Chen, Tsorng-Juu Liang, and Lung-Sheng Yang, “A novel high step-up DC–DC Converter for a micro grid system,” IEEE Trans. on Power Electronics, vol. 26, no. 4, pp. 1127-1136, Apr. 2011. [6] M. Prudente, L. L. P_tscher, G. Emmendoerfer, E. F. Romaneli, and R. Gules,-Voltage multiplier cells applied to non-isolated DC-DC converters, IEEE Trans. Power Electron., vol. 23, no. 2, pp. 871887, Mar.2008.. [7] Kuo-Ching Tseng, Chi-Chih Huang, and Wei-Yuan Shih,, \A high step-up converter with a voltage multiplier module for a photovoltaic system " , IEEE Trans. Power Electron., vol. 28, no. 6, pp. 3047-3057, Jun. 2013 [8] Sanghyuk Lee, Pyosoo Kim, and Sewan Choi, ,"High step-up soft-switched converters using voltage multiplier cells," IEEE Trans. Power Electron, vol. 28, no. 7, pp. 3379-3387, Jul. 2013. [9] Kuo-Ching Tseng and Chi-Chih Huang,High step-up high-efficiency interleaved converter with voltage multiplier module for renewable energy system, IEEE Trans. Ind Electron., vol. 61, no. 3, pp. 13111319, Jan. 2014 . [10] Wuhua Li, Yi Zhao, Jiande Wu, and Xiangning He, \Interleaved high step-up converter with winding-cross-coupled inductors and voltage multiplier cells " , IEEE Trans. Power Electron., vol. 27, no. 1, pp. 133-143, Jan. 2012 [11] V.A.K.Prabhala, Poria Fajri, V.S.P.Gouribhatla,, “A Dc-Dc Converter with High Voltage Gain and Two Input Boost Stages” IEEE Transactions on Power Electronics vol. 26, no. 4, pp. 1127-1136, Apr. 2015

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OPTIMAL PATH SEQUENCES OF MAPREDUCE JOBS USING HADOOP Juliet A Murali1, Tiny Molly V2 Assistant Professor ,Viswajyothi College of Engineering and Technology,Vazhakulam Abstract Big data analysis is one of the major issues in cloud computing. MapReduce has been widely used as a big data processing platform. Global MapReduce is a Hadoop based framework for cloud computing. GMR make use of GEO execution path. This paper deals with creation of optimal executing sequences of MapReduce jobs on geo-distributed data sets by incorporating Global MapReduce. Key Words: Cloud, MapReduce, GMR, DTG 1. Introduction Big data represents the large volume of both structured and unstructured data. It is very difficult to process the them by using traditional data processing applications. Other than processing, it also very difficult to capture manage and retrieve data from big data. Computer cluster consists of a set of loosely or tightly connected computers. It can be viewed as a single system. The clusters can be inter-connected to form cloud. Cloud computing, is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices on demand. A data center is a computer system having some functionality. Cloud computing provide host services in cost effective manner in association with large capacity data centers. Cloud computing includes both computational and storage services. MapReduce and Hadoop is an open source implementation by Apache .It can be used as a programming model for cloud- based data processing. 2. MapReduce MapReduce has been widely used as a big data processing platform ,proposed by google. It is a programming model and an associated

implementation for processing and generation large data sets. From the name itself , the data processes is done in two phases Map and Reduce. [2] The map function processes a key/value pair to get intermediate key/value pair. [6] The input to the map function is a split file contains key/value pair. The reduce function make use of an intermediate key. The reduce function merge all intermediate values. Figure 1 shows the MapReduce Model . Scheduling is one of the most critical aspects of MapReduce. The inbuilt MapReduce scheduling algorithms include FIFO (First Input First Output), Fair Scheduler and Capacity Scheduler. [7] FIFO is the default Hadoop scheduler. The FIFO scheduler schedules jobs based on their priorities in first come first-out of first serve order. The fair scheduler was developed by Facebook and capacity scheduler by yahoo. [1]

Figure 1: MapReduce Model The goal of the fair scheduler is to provide fast response times for small jobs . The capacity scheduler was developed by Yahoo. Capacity scheduling algorithm puts jobs into multiple queues in accordance with the conditions, and

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Optimal Path Sequences Of Mapreduce Jobs Using Hadoop

allocates certain system capacity for each queue. [3] , [4],[8] 3. Hadoop Hadoop is Java based open source implementation of the MapReduce platform. Hadoop runs over a distributed file system called Hadoop. Distributed File System (HDFS) which has the same architecture as Google File System [1]. HDFS has master/slave architecture. HDFS consists of one the master server, called NameNode and there are a number of slaves, called DataNodes. NameNode which controls several DataNodes, and the DataNodes store actual data. Namenode supervises metadata such as information of directories, access log from users, detail of data location, and system logs. Datanode keeps data in Blocks. A Block is a basic unit for data storing in HDFS. Figure 2 briefly describes the Hadoop Architecture. [5]

The JobTracker is the point of interaction between users and the framework. Users submit map/reduce jobs to the JobTracker, which puts them in a queue of pending jobs and executes them on a firstcome/first-served basis. The JobTracker manages the assignment of map and reduce tasks to the TaskTrackers. The TaskTrackers execute tasks upon instruction from the JobTracker and also handle data motion between the map and reduce phases.Figure 3 MapReduce Master/Slave Architecture. [2], [3] 4. Global MapReduce GMR is a Hadoop based framework for cloud computing. It operates on multiple datacenters instead of a single datacenter. They collect data from different datacenter and place it in the selected datacenter. A global MapReduce cluster is created from geographically distributed datanodes. [1],[9]

Figure 4 : G-MR Architecture Figure 2 : Hadoop Architecture The MapReduce framework has master/slave architecture. It has a single master server or JobTracker and several slave servers or TaskTrackers, one per node in the cluster. [5]

Figure 3: MapReduce Master/Slave Architecture

The collected data is stored into a global HDFS from different locations and run the MapReduce job over these global compute resources. Other than collecting data it can also execute instructions using Hadoop clusters. It provide sequence of map reducing , that means output of one job may become output of another one.GMR make use of data transformation graph algorithm DTG.DTG provides the optimal path for MapReduce sequencing. G-MR uses the DTG algorithm an optimized path to perform the sequence of MapReduce jobs and uses Hadoop MapReduce clusters. Figure 4 shows the G-MR Architecture. [3] The GMR mainly consists of GroupManager JobManagers .The GroupManager is the main component. Each JobManager uses CopyManager and AggregationManager during the processing time. Figure 5 shows G-MR Structured Architecture

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Cloud Environments “ , International Journal of Computer Applications (0975 – 8887) Volume 127 – No.6, October 2015

Figure 5: G-MR Structured Architecture

[2]A Dhineshkumar,M Sakthivel ,” Big Data Processing of Data Services in Geo Distributed Data Centers Using Cost Minimization Implementation“,International Journal of Innovative Research in Computer and Communications Engineering Vol. 3,Issue 3,March 2015

The GroupManager at any one of the Datacenter is initiated and it runs DTG algorithm. The DTG algorithm provides the optimal sequencing of MapReduce jobs. The GroupManager allocate MapReduce job to JobManagers corresponding to the Datacenter and also give information about subset of data to be processed. The Job Manager has the privilege to call CopyManager, when it need to copy data from other Datacenter. It can also call AggregationManager when it needs aggregation.

[3] Kirtimalini N. Kakade,T A Chavan ,” Improving Efficiency of GEO-Distributed Data Set using Pact“,International Journal of Current Engineering and Technology E-ISSN 2277-4106 P-ISSN 2347-5161June 2014

5. DTG Algorithm

[5] Jeffrey Dean,Sanjay Ghemawat ,” MapReduce:Simplified Data Processing on Large Clusters“,OSDI'04: Sixth Symposium on Operating System Design and Implementation, San Francisco, CA, December, 2004.

DTG creates a data transformation group,that contains all possible MapReduce path. Each node represents number of MapReduce phases. The edge is a weighted edge , it represents the execution time or cost. DTG uses Dijkstra’s shortest path algorithm inorder to determine optimal path. Te optimal path has lowest execution time or cost. [1] 6. Conclusion The GMR is a MapReduce framework , that make use of Hadoop. It also uses the features of the copy execution path and aggregation path. It uses DTG algorithm for sequencing MapReduce .GMR provide an optimal path having minimum execution time or cost. Reference [1] Hadi Yazdanpanah, Amin Shouraki, Abbas Ali Abshirini,”A Comprehensive View of MapReduce Aware Scheduling Algorithms in

[4] Chamikara Jayalath, Julian Stephen, and Patrick Eugster,” From the Cloud to the Atmosphere: Running MapReduce across Data Centers “ , IEEE Transactions on computers, vol. 63, no. 1, january 2014

[6] Hadoop, “Hadoop http://hadoop.apache.org/.

home

page.”

[7] M. Zaharia, A. Konwinski, A. D. Joseph, R. Katz and I. Stoica, "Improving MapReduce performance in heterogeneous environments", In: OSDI 2008: 8th USENIX Symposium on Operating Systems Design and Implementation, 2008. [8] Hadoop’s Fair Scheduler. https://hadoop.apache.org/docs/r1.2.1/fair_sche duler. [9] J. Chen, D. Wang and W. Zhao, "A Task Scheduling Algorithm for Hadoop Platform", JOURNAL OF COMPUTERS, VOL. 8, NO. 4, APRIL 2013, pp. 929-936.

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PERFORMANCE OF UNIFIED POWER QUALITY CONDITIONER IN DISTRIBUTION SYSTEM FOR POWER QUALITY IMPROVEMENT 1

1

Shital V. Raut, 2Dr. Hari Kumar Naidu Research Scholar, Department of Electrical Engineering, TGPCET, Mohgaon, Nagpur 2 HOD , Department of Electrical Engineering ,TGPCET ,Mohgaon ,Nagpur

Abstract The power quality is more concerned issue that is becoming increasingly important to electricity consumers at all levels of usage. The power quality is the combination of voltage and current quality. The main causes of a poor power quality are harmonic currents, poor power factor, supply voltage variations etc. The quality of power is affected by many factors like harmonic contamination due to non-linear loads such as thyristor power converters, rectifiers, voltage and current flickering due to arc in arc furnaces, sag and swell due to the switching of the loads etc. One of the many solutions is the use of a combined system of series and shunt active filter like unified power quality conditioner. The UPQC is one of the APF family members where series and shunt APF functionalities are integrated together to achieve superior control over several power quality problems simultaneously. This device mitigates any type of voltage and current fluctuations and power factor correction in a power distribution network. This paper proposes a new configuration that consist of series active power filter, shunt active power filter, photovoltaic system and wind generation system connected across DC link capacitor. The proposed system can compensate voltage sag/swell, voltage interruption and harmonics from current and also supply active power to the system. The performance of proposed system is evaluated by using MATLAB/SIMULINK software.

Index Terms: Unified Power Quality Conditioner (UPQC), Power Quality (PQ), Renewable Energy Resources (RES), Photovoltaic Array (PV),Wind Generation System (WGS). I. INTRODUCTION To provide quality power has become today’s most concerned area for both power suppliers and customers due to the deregulation of the electric power energy market. Efforts have been made to improve the power quality. Aspects on power quality can be classified into three categories that is, voltage stability, continuity of supplying power and voltage waveform. The power quality is the set of limits of electrical properties that allows electrical system to function in their intended manner without significant loss of performance or life. The use of non-linear loads in the power system will lead to the generation of current and voltage harmonics which in deteriorates the power quality. The Unified Power quality Conditioner is a custom power device that is employed in the distribution system to mitigate the disturbances .It is a type of hybrid APF and is the only versatile device which can mitigate several power quality problems related with voltage and current simultaneously. Therefore UPQC is multi functioning device that compensate various voltage disturbances of the power supply, to correct voltage fluctuations and to prevent harmonic load current from entering the power system. In other words ,the UPQC has the

30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 24

Performance Of Unified Power Quality Conditioner In Distribution System For Power Quality Improvement

capability of improving power quality at the point of installation on power distribution systems or industrial power system [7]. The market liberalization and government’s incentives have further accelerated the renewable energy sector growth. Long transmission lines are one of the main causes for electrical power losses. Therefore emphasis has increased on renewable energy systems which lead to energy efficiency and reduction in emissions [2]. PV system and wind energy systems are recognized as most mature, clean and cost efficient renewable energy sources in the electricity market. II.DEFINITION OF POWER QUALITY Power quality has different meanings to different people. Institute of Electrical and Electronic Engineers (IEEE) Standard IEEE1100 defines power quality as “the concept of powering and grounding sensitive electronic equipment in a manner suitable for the equipment”. There is a broad range of power quality problems associated with power systems based on time such as long duration variations, short duration variations and other disturbances. All electrical devices are prone to failure or malfunction when exposed to one or more power quality problems. The main reasons for concern with power quality (PQ) are as following: 1.End user devices become more sensitive to PQ due to many microprocessor based controls. 2.Large computer systems in many businesses facilities. 3.Power electronics equipment used for enhancing system stability, operation and efficiency. These are major sources of bad Power Quality. 4.Continuous development of high performance equipment: Such equipment is more susceptible to power disturbances. The users always demand higher power quality. Some basic criterions for power quality are constant rms value, constant frequency, symmetrical three-phases, pure sinusoidal wave shape and limited THD. III . SOURCES OF POOR POWER QUALITY Sources of poor Power Quality are listed as follows:  Adjustable –speed drives  Switching Power supplies

 Arc furnaces  Electronic Fluorescent lamp ballasts  Lightning Strike  L-G fault  Non- linear load  Starting of large motors  Power electronic devices IV. NEED OF POWER QUALITY There is an increased concern of power quality due to the following reasons: 1. New-generation loads that uses microprocessor and microcontroller based controls and power electronic devices, are more sensitive to power quality variations than that equipments used in the past. 2. The demand for increased overall power system efficiency resulted in continued growth of devices such as high-efficiency adjustable-speed motor drives and shunt capacitors for power factor correction to reduce losses. This is resulting in increasing harmonic level on power systems and has many people concerned about the future impact on system capabilities. 3. End users have an increased awareness of power quality issues. Utility customers are becoming better informed about such issues as interruptions, sags, and switching transients and are challenging the utilities to improve the quality of power delivered. 4. Most of the networks are interconnected these days. Integrated processes mean that the failure of any component has much more important consequences. V. POWER QUALITY PROBLEMS, CAUSES AND ITS CONSEQUENCES. Power quality is very important term that embraces all aspects associated with amplitude, phase and frequency of the voltage and current waveform existing in a power circuit. The increasing number of power electronics based equipment has produced a significant impact on the quality of electric power supply. Therefore, it is obvious to maintain high standards of power quality. The various power quality problems are:  Voltage sags  Micro-interruptions  Long interruptions  Voltage spikes  Voltage swells  Voltage fluctuations

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Performance Of Unified Power Quality Conditioner In Distribution System For Power Quality Improvement

 Voltage unbalance  Noise  Harmonic distortion The Power quality problems details are described below. 1. Voltage Sags: A decrease of the normal voltage level between 10 and 90% of the nominal rms voltage at the power frequency, for durations of 0, 5 cycle to 1 minute.

Fig. 1 Voltage Sags Causes: • Faults on the transmission or distribution network. • Faults in consumer’s installation. • Connection of heavy loads and start-up of large motors. Consequences: • Malfunction of microprocessor-based control systems (PCs, PLCs, ASDs, etc.) that may lead to a process stoppage. • Tripping of contactors and electromechanical relays. •Disconnection and loss of efficiency in electric rotating machines. 2. Micro-Interruptions: Total interruption of electrical supply for duration from few milliseconds to one or two seconds.

Fig.2 Micro-Interruptions Causes: • Opening and automatic reclosure of protection devices. • Insulation failure, lightning and insulator flashover. Consequences: •Tripping of protection devices. • Loss of information and malfunction of data processing equipment. • Stoppage of sensitive equipment (such as ASDs, PCs, PLCs).

3. Long Interruptions: Total interruption of electrical supply for duration greater than 1 to 2 seconds.

Fig.3 Long Interruptions Causes: • Equipment failure in the power system network. • Storms and objects (trees, cars, etc) striking lines or poles, fire. • Human error, bad coordination or failure of protection devices. Consequences: • Stoppage of all equipment. 4. Voltage Spikes: Very fast variation of the voltage value for durations from a several microseconds to few milliseconds.

Fig.4 Voltage Spikes Causes: • Lightning. • Switching of lines or power factor correction capacitors. • Disconnection of heavy loads. Consequences: • Destruction of components and of insulation materials. • Data processing errors or data loss. • Electromagnetic interference. 5. Voltage Swells: Momentary increase of the voltage, at the power frequency, outside the normal tolerances, with duration of more than one cycle and typically less than a few seconds.

Fig. 5 Voltage Swells

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Performance Of Unified Power Quality Conditioner In Distribution System For Power Quality Improvement

Causes: • Start/stop of heavy loads. • Poorly dimensioned power sources. • Poorly regulated transformers. Consequences: • Flickering of lighting and screens. • Damage or stoppage or damage of sensitive equipment. 6. Voltage fluctuation: Oscillation of voltage value, amplitude modulated by a signal with low frequency.

Fig.6 Voltage Fluctuations Causes: •Arc furnaces. • Frequent start/stop of electric motors (for instance elevators). • Oscillating loads. Consequences: • Most consequences are common to under voltages. • Flickering of lighting and screens. 7. Voltage Unbalance: A voltage variation in a three-phase system in which the three voltage magnitudes or the phase-angle differences between them are not equal.

Fig.7 Voltage Unbalance Causes: •Large single-phase loads (induction furnaces, traction loads). • Incorrect distribution of loads by the three phases of the system. Consequences: • The most affected loads are three-phase induction machines. • Increase in the losses.

8. Noise: Superimposing of high frequency signals on the waveform of the power-system Frequency.

Fig.8 Noise Causes: • Electromagnetic interferences. • Improper grounding may also because. Consequences: • Disturbances on sensitive electronic equipment. • May cause data loss and data processing errors. 9. Harmonic Distortion: Voltage or current waveforms assume non-sinusoidal shape.

Fig.9 Harmonic Distortion The waveform corresponds to the sum of different sine-waves with different magnitude and phase, having frequencies that are multiples of power-system frequency. Consequences: • Increased probability of occurrence of resonance. • Nuisance tripping of thermal protections. • Electromagnetic interference. • Increase in the losses. • Loss of efficiency in electric machines (e.g. 5th harmonic). VI.GENERALISED DIAGRAM OF UPQC SYSTEM

Fig.10 Generalised diagram of UPQC system 30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 27

Performance Of Unified Power Quality Conditioner In Distribution System For Power Quality Improvement

Fig.10 shows the generalised diagram of UPQC system. The UPQC is a combination of a series active power filters and shunt active power filter in cascade via a common DC link capacitor. Series active filter and shunt active filter compensate the power quality problems of the source voltages and source currents respectively. The series component of the UPQC is responsible for mitigation of supply side disturbances such as voltage sag/swells, flicker, voltage unbalance and harmonics. The shunt component is responsible for mitigating the current quality problem such as poor power factor, harmonics in the supply current and load voltage resp. VII. OPERATION OF UPQC The powers due to harmonic quantities are negligible as compared to the power at fundamental component, therefore, the harmonic power is neglected and the steady state operating analysis is done on the basis of fundamental frequency component only. The UPQC is controlled in such a way that the voltage at load bus is always sinusoidal and at desired magnitude. Therefore the voltage injected by series APF must be equal to the difference between the supply voltage and the ideal load voltage. Thus the series APF acts as controlled voltage source. The function of shunt APF is to maintain the dc link voltage at constant level. In addition to this the shunt APF provides the VAR required by the load, such that the input power factor will be unity and only fundamental active power will be supplied by the source. The equivalent circuit of UPQC was shown in the Fig.11

i L = load current vc = voltage injected by series APF ic = current injected by shunt APF

k = fluctuation of source voltage i.e.

vt  vL vL Case I The reactive power flow during the normal working condition when UPQC is not connected in the circuit is shown in the Fig. 12(a). In this condition the reactive power required by the load (QL) is completely supplied by the source only. When the UPQC is connected in the network and the shunt APF is put into the operation, the reactive power required by the load is now provided by the shunt APF alone; such that no reactive power burden is put on the mains. So as long as the shunt APF is ON, it is handling all the reactive power even during voltage sag, voltage swell and voltage harmonic compensation. The series APF does not take any active part in supplying the load reactive power demand. The reactive power flow during the entire operation of UPQC is shown in the Fig. 12 (b).

k=

Fig.12 (a)-(b) Reactive power flow QS =Source reactive power QL =Load reactive power QSh =Shunt APF reactive power Case II

Fig.11 Equivalent circuit of a UPQC Where, v S = source voltage v t = terminal voltage at PCC load

v L = load voltage i S = source current

If k, September 2007. [3] Blue Coat, White Paper – Best Practices for Controlling Skype within the Enterprise. Internet WWW page, at URL: February 2006. [4] Tapio Korpela, “IT Security Evaluation of Skype in Corporate Networks,” TKK T-110.5290 Seminar on Network Security, Helsinki University of Technology, December 2006. [5] Salman A. Basat and Henning Schulzrinne, “An Analysis of the Skype Peer-to-Peer Internet Telephony Protocol,” Department of Computer Science, Columbia University, September 2004. [6] Snort: Vulnerability Research Team. Internet WWW page, at URL: < http://www.snort.org/vrt//>, June 2008.

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DESIGN OF STATCOM CONTROL SCHEME TO MITIGATE THE POWER QUALITY PROBLEMS 1

Rakesh S. Kumbhare, 2Dr. Hari Kumar Naidu 1 Research Scholar, Department of Electrical Engineering, TGPCET, Mohgaon ,Nagpur 2 HOD, Department of Electrical Engineering ,TGPCET ,Mohgaon ,Nagpur Abstract— Power quality can be defined as any power quality problems manifested in voltage, current and frequency those results in failure or mal-operation of customer equipment. Injection of wind power into an electric grid affects the power quality. The work analyses the performance of Static Compensator (STATCOM) with a wind energy generating system at the point of common coupling to mitigate the power quality issues. During the Normal Operation, wind turbine produces a continuous variable output power. The main Power quality issues are voltage sag, swell, flickers, harmonics etc. The design of a Fuzzy logic controller using voltage as feedback for significantly improving the dynamic performance of converter. The performance is analysed with the help of PI controller and Fuzzy logic technique. The simulation studies have demonstrated the effective influence of the STATCOM on the improvement of the voltage using MATLAB/Simulink and make the wind turbine generator to be in service even under fault conditions. It also shows that fuzzy logic controller gives better result as compared to PI controller. Index terms- Fuzzy logic controller (FLC), Point of common coupling , PI Controller, Power Quality,, STATCOM, Total harmonic Distortion (THD), Wind Generating System . I. INTRODUCTION The power quality of power supply of an ideal power system means to supply electric energy with perfect sinusoidal waveform at a constant frequency of a specified voltage with least amount of disturbances. Power quality is an issue

that is becoming increasingly important to electricity consumers at all level of usage. Power quality is the combination of voltage quality and current quality, thus power quality is concerned with deviation of voltage and current from ideal. Power quality (PQ) related issues are of most concern nowadays. The widespread use of electronic equipment and electrical equipment susceptible to power quality or more appropriately lack of power quality would fall within a seemingly boundless domain. All electrical devices are prone to failure or malfunction when exposed to one or more power quality problems. The electrical device might be an electrical motor, a transformer, a generator, a computer, a printer, communication equipment, or household appliances. Here proposing a STATCOM based control technology for mitigating the power quality issues when we are integrating wind farms to the grid. In the event of increasing grid disturbances, a battery energy storage system is required to compensate the fluctuation generated by wind turbine. Here two control schemes for STATCOM is designed and compared: BangBang Current controller and fuzzy logic controller. PI controller plays an important role in reducing fluctuating voltage error signal efficiently. Simulation result shows that the proposed SVC and STATCOM with PI controller is efficient in mitigating voltage sags and thus improving the power quality of the power grid. Fuzzy logic technique has been used as it has advantage of robustness, easily adaptive fast technology is also used and best results are

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achieved when compared to conventional PI technique. II. POWER QUALITY CONSTRAINTS AND PROBLEMS Power system constraints are: 1. Random external factors  Whether  Human activities  Animals  Vegetation 2. Increasing share of Non-linear loads 3. Increasing demand of High PQ The various power quality problems are:  Harmonic distortion  Voltage spikes  Voltage swells  Voltage fluctuations  Voltage unbalance  Voltage sags  Micro-interruptions  Long interruptions  Noise

Fig.1.System operational schemes in grid system.

III. SYSTEM OPERATION The shunt connected STATCOM with battery energy storage is connected with the interface of the induction generator and nonlinear load at the PCC in the grid system. The STATCOM Compensator output is varied according to the controlled strategy, so as to maintain the power quality norms in the grid system. The current control strategy is included in the control scheme that defines the functional operation of the STATCOM compensator in the power system. A single STATCOM using insulated gate bipolar transistor is proposed to have a reactive power support, to the induction generator and to the nonlinear load in the grid system. The main block diagram of the system operational scheme is shown in fig.1.

Fig.2. Control system scheme

IV. STATCOM- PERFORMANCE UNDER VARIOUS LOAD VARIATIONS The wind energy generating system is connected with grid having the nonlinear load. The performance of the system is measured by switching the STATCOM at time t= 0.3 s in the system. When STATCOM controller is made ON, without change in any other load condition parameters, it starts to mitigate for reactive demand as well as harmonic current. This additional demand is fulfil by STATCOM compensator. Thus, STATCOM can regulate the available real power from source. The results of source current are shown in Fig. and respectively. While the result of injected current from STATCOM are shown in fig.3. 1. PI CONTROLLER The PI controller is traditionally suitable for second and lower order system. It can also be used for higher order plants with dominant second order behaviour. The Ziegler-Nichols (Z-

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N) methods rely on open-loop step response or closed loop frequency tests, are usually used to determine the values of PI controller. In our case, the values of tuning parameters obtained are Kp= 350 , Ki= 85. Usually, these obtained values are only initial values of PI controller and need to be adjusted repeatedly through computer simulation until the closed loop system performs or compromises are satisfied.

With the rule base, the value of the output is changed according to the value of the error signal ε, and the rate of error Δε. The structure and determination of the rule base is done using trial and error method and is also done through experimentation.

The STATCOM control block diagram is shown in Fig.2. The voltage regulator is of proportional plus integral type. The integral term in a PI controller causes the steady error to zero. The Proportional Integral (PI) algorithm computes and transmits a controller output signal every sample time to the final control element. The gains of the PI controller can be selected by trial and error method. It performs lack of derivative action may make the system steadier in the steady state in the case of the noisy data. PI controller to eliminate offset, a major weakness of a P-only controller. It is shown in fig.3 as below.

Fig.3 STATCOM model with PI – Voltage

Fig.4 Basic representation of the Fuzzy logic controller (FLC). The MATLAB/SIMULINK implementation of the fuzzy controller for one phase is shown in fig.4. All the variables fuzzy subsets for the inputs ε and Δε are defined as (NB, NM, NS, Z, PS, PM, PB). Taking into account of the coverage, sensitivity, robustness of universe, the fuzzy subsets of the membership functions use “Z” shaped membership function in the left, triangular membership function in the middle, and “S” shaped membership function curve in the right. The FLC with STATCOM input is shown in fig.5.

Regulator block diagram 2. FUZZY LOGIC CONTROLLER The disadvantage of PI controller is its inability to react to abrupt changes in error signal ε , because it is only capable of determining the instantaneous value of the error signal without considering the change of the rise and fall of the error, Which in mathematical terms is derivative of the error signal, denoted as Δε. To solve this problem, Fuzzy logic control as it is shown in fig. 4 is proposed. The determination of the output control signal, is done in an interference engine with a rule base having if-then rules in the form of If ε is …………. And Δε is …………, then output is ………..

Fig.5 STATCOM model with FLC- Voltage Regulator block diagram In a fuzzy logic controller, the control action is determined from the evaluation of a set of simple linguistic rules. The development of the rules requires a thorough understanding of the process to be controlled, but it does not require a mathematical model of the system. The objectives include excellent rejection of input supply variations both in utility and in wind generating system and load transients. Expert knowledge can also be participated with ease that

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

is significant when the rules developed are intuitively inappropriate. The rule base developed is reliable since it is complete and generated sophistically without using extrapolation. In this paper, fuzzy control is used to control the firing angle for the switches of the VSI of STATCOM. In this design, the fuzzy logic based STATCOM has two inputs ‘change in voltage(ΔV)’ and ‘change in current(ΔI)’ and one control output(ΔU). Firstly the input values will be converting to fuzzy variables. This is called fuzzification. After this, fuzzy inputs enter to rule base or interface engine and the outputs are sent to defuzzification to calculate the final outputs. These processes are demonstrated in Fig.6. Here seven fuzzy subsets have been used for two inputs. These are: PB (positive big), PM (positive medium), PS (positive small), ZE (zero), NS (negative small), NM (negative medium) and NB (negative big). We use Gaussian membership functions and 49 control rules are developed, which are shown in Table.I. Fuzzification: It is the process of representing the inputs as suitable linguistic variables .It is first block of controller and it converts each piece of input data to a degree of membership function. It matches the input data with conditions of rules and determines how well the particular input matches the conditions of each rule.

ZE PS

N

N

M

M

N

NS

NS

ZE

PS

PM

NS ZE

PB

M ZE

PS

PS

M PM

P P

PB

M ZE PS

PS P

P

P

M

M

PB

PB

PB

PB

PB

PB

M

The membership functions for the inputs (for ΔV and ΔI) are shown in Fig.7 and Fig.8 The number of fuzzy levels is not fixed and it depends on the input resolution needed in an application. The larger the number of fuzzy levels, the higher is the input resolution. The fuzzy control implemented here uses sinusoidal fuzzy-set values. Decision making: The control rules that associate the fuzzy output to the fuzzy inputs are derived from general knowledge of the system behaviour. However, some of the control actions in the rule table.1 are also developed using “trial and error” and from an “intuitive” feel of the process to be controlled. In this effort, the control rules for the STATCOM in Table1.resulted from the understanding of STATCOM’s behaviour and experimental tests of its VSI’s performance.

Fig.6 Fuzzy control block diagram ΔI/Δ V

TABLE. I Control Rules NB N NS ZE PS P M

NB NM NS

M

NB NB NB NB N

N

M

B

NS

ZE

PS

ZE

PS

P

NB NB N

N

M

M

NS

NS

NB N M

Fig.7 Membership function for ΔI

PB ZE

M

Fig.8 Membership function for ΔV Defuzzification: It is the Process of converting fuzzified output into a crisp value. In the defuzzification operation a logical sum of the

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

results from each of the rules performed. This logical sum is the fuzzy representation of the change in firing angle (output). A crisp value for the change in firing angle is calculated. Correspondingly the grid current changes and improves the power quality. V. POWER QUALITY IMPROVEMENT FORMULATION MODEL The wind energy generating system is connected with grid having the non-linear load. It is observed that the source current on the grid is affected due to the effects of nonlinear load and wind generator, thus purity of waveform may be lost on both sides in the system. The three phase injected current into the grid from STATCOM will cancel out the distortion caused by non-linear load and wind generator. The source current with and without STATCOM operation is shown in Fig. and . This shows that the unity power factor is maintained for the source power when the STATCOM is in operation. The current waveform before and after the STATCOM operation is analysed. The Fourier analysis is expressed and the THD of this source voltage at PCC with and without STATCOM Using Fuzzy logic Controller is 15.74% and 3.92% respectively, as shown in Fig. and respectively. The above tests with proposed scheme has not only power quality improvement feature but it also has sustain capability to support the load with the energy storage through the batteries. The proposed control scheme is simulated using MATLAB/SIMULINK in power system block set. The simulation parameters used for the system is given Table II. TABLE II System Parameters Sr.

Parameter

Ls=0.06H,Lr=0.06H . 3

Line Series

0.05 mH

inductance 4

Inverter

DC link voltage

parameter

=800V, Switching frequency =2KHz, DC Link Capacitance= 100 µf.

5

Load Parameter

Non Linear Load 25kW

6

IGBT Rating

Collector Voltage= 1200 V, Forward Current=50A, Gate Voltage=20V, Power Dissipation= 310W.

1. MATLAB SIMULINK MODEL:

Rating

No . 1 2

Grid voltage Induction Motor/Generato r

3phase ,415 volt

Fig.9 STATCOM Connected Wind Energy

50Hz

System for Power Quality Improvement Using

3.35 KVA , 415 volt

Fuzzy Logic Controller

50 Hz speed 1440 rpm P=4, Rs=0.01Ω, Rr=0.015 Ω,

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

2. WIND ENERGY GENERATING SYSTEM MODELLING:

Fig.10 Wind Energy Generating System Model The performance of the system is measured by switching ON the STATCOM at time T=0.3 s and an increase in additional load is given at time T=0.2s. The load current and source currents are shown in fig and fig. respectively. While the injected current from STATCOM is shown in fig.11.

maintained constant across the capacitor as in fig.10 System is analysed and performance of the system is evaluated. One of the easiest measurements of harmonic is the total harmonic distortion (THD) measurement through FFT analysis. The Fourier analysis of waveform with and without using PI controller is performed and the THD obtained for the source current without STATCOM is 2.30% and the THD of source current (grid current) is only 1.19% as shown in Table III. The injected currents also have harmonic and it cancel out reactive and harmonic part produced by the induction generator and the non-linear load. Thus it improves power quality. 4. CONTROL SCHEME USING PI CONTROLLER:

The STATCOM controller is made ON, it starts to mitigate the reactive demand as well as harmonic current. The additional demand is fulfil by STATCOM compensator with the help of BESS. This can be easily seen in the source current (grid current). Because whatever changes occurs in the load or induction generator occurs it can’t be seen in the source current and it is free from harmonics also. 3.

STATCOM

SIMULINK

MODEL

Fig.12 Control scheme of STATCOM Using PI

OF

Controller

SYSTEM:

5. CONTROL SCHEMES USING FUZZY LOGIC CONTROLLER:

Fig.11 STATCOM Model with Control Scheme of System Fig.13. STATCOM Control Scheme Using

The DC link voltage regulates the source current in the grid system, so the DC link voltage is

FUZZY Logic Controller

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

VI. SIMULATION WAVEFORM The current waveform before and after the STATCOM operation is analyzes. Without using fuzzy controller for STATCOM the source THD is 1.23% and using fuzzy controller the source current (grid current) THD is reduced to 0.81% as shown in Table. It indicates that when we are using fuzzy controller the harmonics are reduced more as compared to PI controller.

Fig.16 Load current with and without STATCOM using PI controller

A) SIMULATION WAVEFORM USING PI CONTROLLER All the below figure shows the Source Current, Wind generating Current, load current , source voltage , load voltage, real power and reactive power with conventional PI controller. Here compensator is tuned on at 0.3 seconds, before we get some harmonics coming from non-linear load, then distorts our parameter and get sinusoidal when compensator is in ON.

Fig.17 Source Voltage with and without STATCOM using PI Controller

Fig.14 Source Current with and without STATCOM using PI Controller Fig.18 Load voltage with and without STATCOM using PI controller

Fig.15 Current after connecting wind system with and without STATCOM using PI controller Fig.19 Real and Reactive Power at Source Side before and after STATCOM using PI Controller 30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

Fig.20 Real and Reactive Power at Load Side

Fig.23 Load current with and without

before and after STATCOM using PI Controller

STATCOM using Fuzzy logic Controller

B) USING FUZZY LOGIC CONTROLLER All the below figure shows the Current at PCC, Source Current, Wind generating Current, load current and Inverter injected Current with Fuzzy Logic controller. Here compensator is tuned on at 0.3 seconds, before we get some harmonics coming from non-linear load, then distorts our parameter and get sinusoidal when compensator is in ON. It is compared with PI controller and shows better results.

Fig.24 Source Voltage with and without STATCOM using Fuzzy Logic Controller

Fig.21 Source Current with and without

Fig.25 Load Voltage with and without

STATCOM using Fuzzy logic Controller

STATCOM using Fuzzy logic controller

Fig.22 Current after connecting wind system

Fig.26 Real and Reactive Power at Source Side before and after STATCOM using Fuzzy Logic Controller

with and without STATCOM using Fuzzy logic Controller

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

Fig.29 shows FFT analysis of Source Current for balanced Non-linear load, here we get 1.19%.

Fig.27 Real and Reactive Power at Load Side before and after STATCOM using Fuzzy Logic Controller C) COMPARATIVE ANALYSIS OF TWO CONTROL SCHEME FOR STATCOM Result of two control schemes are summarized in the table below. From this table we can conclude that the % THD reduces more with Fuzzy logic controller. Without load variations, by using PI controller the THD in the source current reduced to 1.19% and using Fuzzy logic controller the THD is reduced to 0.81%. a) THD analysis of System using PI controller.

Fig.30 Source voltage without STATCOM using PI controller Fig.30 shows FFT analysis of Source Voltage for balanced Non-linear lad without any compensation, here we get 16.64%.

Fig.31 Source voltage with STATCOM using PI controller

Fig.28 Source current without STATCOM

Fig.31 shows FFT analysis of Source Voltage for balanced Non-linear load, here we get 4.09%.

using PI controller Table.III % THD content in Source Current,

Fig.28 shows FFT analysis of Source Current for balanced Non-linear load without any compensation, here we get 2.30%.

Source voltage Total Harmonic Distortion % THD

Source

Without

With

STATCOM

STATCOM

2.30%

1.19%

16.64%

4.09%

Current Source Voltage Fig.29 Source current with STATCOM using PI controller

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

Table.III shows % THD content in Source Current and Source voltage without STATCOM and with STATCOM. It is observed from the Table 7.1 source current THD in phases are improved from 2.30%to 1.19%.Similarlly for the source voltage THD improved from 16.64% to 4.09%.

Fig.34 shows FFT analysis of Source Voltage for balanced

Non-linear

load

without

any

compensation, here we get 15.74%.

b) THD analysis of System using Fuzzy Logic Controller.

Fig.35 Source Voltage with STATCOM Using Fuzzy Logic Controller Fig.32 Source Current without STATCOM using Fuzzy Logic controller. Fig.32 shows FFT analysis of Source Current for balanced Non-linear load without any compensation, here we get 1.23%.

Fig.35 shows FFT analysis of Source Voltage for balanced Non-linear load without any compensation, here we get 3.92%. Table.IV % THD content in Source Current, Source voltage Total Harmonic Distortion % THD Without

With

STATCO

STATCOM

M Source Fig.33 Source Current with STATCOM using

Current

Fuzzy Logic controller.

Source

1.23%

0.81%

15.74%

3.92%

Voltage Fig.33 shows FFT analysis of Source Current for balanced Non-linear load, here we get 0.81%.

Table.IV shows % THD content in Source Current, Source voltage without STATCOM and with STATCOM. It is observed from the Table shows that source current THD in phases are improved from 1.23% to 0.81%.Similarlly for the source voltage THD improved from 15.74% to 3.92%.

Fig.34 Source Voltage without STATCOM Using Fuzzy Logic Controller 30th International Conference on Instrumentation, Electrical And Electronics Engineering (ICIEEE 2017) ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur

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Design Of Statcom Control Scheme To Mitigate The Power Quality Problems

 

CONCLUSION In this Project we present the STATCOM based control scheme for power quality improvement in wind generating system on integration to the grid and with nonlinear load. The power quality its effects on consumer utility are shown. The operation of the control system developed for the STATCOM in MATLAB/SIMULINK for maintaining the power quality is to be simulated. It has potentially to cancel out the harmonic parts of the load end current. It maintains the source voltage and current in phase and support the reactive power during demand for the wind generator and load at PCC in the wind grid system, thus it enhance the utilization factor of transmission line also. The operation of the STATCOM is simulated using two controllers: Bang-Bang current controller and Fuzzy controller. The proposed FLC based STATCOM have improved the power quality of source current significantly by reducing the THD from 1.19% to 0.81%. It is clearly presented that STATCOM with FLC gives better performance than STATCOM with conventional PI controller. For better voltage regulation FuzzyPI control technique showed better performance than the conventional controller. One of the major advantages of the proposed FLC is being less sensitive to the system parameter variation; in addition, it is characterized by a negligible response time. Simulation result analysis has shown that the proposed controller has fast dynamic response, high accuracy of tracking the DC-voltage reference, and strong robustness to load sudden variations compared to the conventional PI controller. REFERENCES 1. Sharad W. Mohod, Mohan V. Aware, “A STATCOM Control scheme for Grid connected wind energy for Power quality Improvement,” IEEE System Journal, vol.4, pp.346-352, Sep.2010. 2. Shiny K. George, Fossy M. Chacko, “Power Quality Improvement of grid connected wind Energy System by Fuzzy control strategies,”IEEE,pp.124-131, 2013.

3. B.T. Ramakrishnarao, B. Eswararao, L. Narendra, K. Pravallika, “A STATCOM Control Scheme for Power Quality Improvement of Grid Connected Wind Energy System,” International Journal of Engineering Science and Innovative Technology, vol.2, pp.12-16, May.2013. 4. A. Jeyamari. , B. Prabakaran, “Power Quality Improvement of Grid Connected Wind Power System Using STATCOM,” International Journal of Engineering Research and Technology, vol.2, pp.2902- 2908, june.2013. 5.S. Munishekhar, O. Hemakesavulu, Dr. M. Padmalalitha, “Wind Energy Conversion System Using Fuzzy Controlled STATCOM for Power Quality Improvement, ”International Journal of Electrical Engineering and Technology,vol.4,pp.108-117, August.2013. 6. Mallikarjuna Golla, I. Raghavendar, “Power Quality Improvement of Grid Connected Wind Energy System by PI & Fuzzy Based STATCOM Controller,” International Journal of Engineering Research and Technology, vol.2,pp.2851-2858, Sep.2013. 7. Dr. Y. Sreenivasa Rao, D. Mamatha, “Power Quality Improvement In Grid Connected Wind Energy Conversion System Using Hybrid Fuzzy Controller,”International Journal of Darshan Institute onEngineering Research Emerging Technologies, vol.3.pp.52-58, 2014. 8. B. Ashok Kumar, Dr. N. Kamaraj, C. K. Subasri, “Fuzzy Controller For Improving Voltage Profile in Grid Connected Wind Energy System with FACTS Devices,” Journal of Theoretical and Applied Information Technology,vol.63, pp.529-536, May 2014. 9. Supriya Tripathi, C.S. Verma, “Power Quality Improvement in Wind grid Energy system using STATCOM with BESS-Control Scheme,” International Journal on Innovation and Scientific Research, vol.9, pp.237-245, Sep 2014. 10. B. Sunil Kumar, A Anjaneyulu, “A Novel Improved Performance of Intelligence Based

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BESS-STATCOM for Power Quality Improving features,” International Journal and Magazine of Engineering Technology, Management and Research, vol.2, pp.109-118, Jan.2015. 11. D. Suhashini, A. Ambika, “Grid Power Quality Improvement and Battery Energy Storage in Wind Energy Storage in Wind Energy System by PI and Fuzzy Based STATCOM controller,” International Journal of Science and Research,vol.4,pp.1092-1098, Jan.2015. 12. Dr. K. Ravichandrudu, Ch. Manasa, P. Yohan Babu, “Novel Static Fuzzy Compensation scheme for grid Connected Wind Energy System for Power Quality Improvement,” ABHINAV National Monthly Refereed Journal of Research in Science and Technology, vol.2,pp.65-73.

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EFFICIENT AND DYNAMIC HYBRID KEY CRYPTOGRAPHY FOR IDS MANAGEMENT SYSTEM IN MANETS 1

Kavyashree J,2Bhaskar G Student,M.tech, CNE, 2Assistant professor Dept.of computer science, Siddaganga Institute of Technology Tumakuru, Karnataka, India Abstract-- A group of freely migrating nodes the transmitter and the receiver. Nodes called Mobile Ad hoc Network (MANET) is communicate directly with each other when they one of the most important and unique wireless are both within the communication range. The network architecture. In recent decade routing algorithm in MANET can be a singlemigrating to Manet i.e. wireless adhoc hop or multi–hop. Single-hop communication is in terms of structure and network has became a global trend. simpler Compared to contemporary wireless network implementations but has lesser functions and compared to multi-hop Manet is preferred mainly for its mobility and applications communication. In multi-hop communication, scalable characteristics. In mantes each device is free to move independently in any the destination is beyond the transmission direction and will therefore change its links to coverage of the source and hence the packets are other devices frequently. These networks can forwarded via one or more intermediate change locations and configure itself on the fly nodes. Fig.1 shows a MANET network they communicate via the radio waves. Each consisting of nodes and their transmission node in the Manet has a wireless interface to ranges. As shown in Fig.1, Node 2 and Node 3 communicate with each other. However the are neighbours of Node 1 whilst Node 4 and open medium and wide distributions of nodes Node 5 are not. Therefore, data transmission to make to various types of malicious attacks. In Node 4 and Node 5 will have to be relayed by the Existing system Enhanced adaptive Node2. acknowledgement approach (EAACK) Digital signature algorithm is used which causes the network overhead if more malicious node involves. Thus proposed system is used with AES and RSA algorithms as a Hybrid key cryptography to reduce the network overhead caused by digital signatures. Index Terms—Adhoc, AES, IDS, Manet, RSA Fig 1. Representation of Manet Manet is highly vulnerable to attacks because, I. INTRODUCTION Manet is continuously self-configuring, node configuration and maintenance are done on infrastructure-less network of mobile devices its own. Furthermore, because of MANET’s that are connected without wires [1]. These have distributed architecture and changing topology, a highly dynamic and autonomous topology. On traditional centralized monitoring technique is the contrary to traditional Network architecture, no longer feasible in MANETs. In such case, it Manet does not require a fixed network is crucial to develop efficient Intrusion detection infrastructure, every single node works as both 1

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Efficient And Dynamic Hybrid Key Cryptography For Ids Management System In MANETS

mechanisms (IDS) to protect MANET from attacks. II. LITERATURE SURVEY An intrusion detection system (IDS) is a device or software application that monitors network or system activities for malicious activities or policy violations and produces reports in to a Management Station. Due to the limitations of most MANET routing protocols, nodes in MANETs assume that other nodes always cooperate with each other to relay data. This assumption leaves the attackers with the opportunities to achieve significant impact on the network with just one or two compromised nodes. To address this problem, an IDS should be added to enhance the security level of MANETs [2]. If MANET can detect the attackers as soon as they enter the network, we will be able to completely eliminate the potential damages caused by compromised nodes at the first time. IDSs usually act as the second layer in MANETs, Next section, mainly concentrate on discussing the background information required for understanding EAACK better. Different IDS for MANET are: A. Watch dog Watchdog scheme is comprised of two sections, to be specific, Watchdog and Pathrater. Watchdog serves as an IDS for MANETs. It is in charge for detecting malicious node misbehaviours in the network. Watchdog detects malicious misbehaviours by indiscriminately hearing to its nesxt hop’s transmission. If a Watchdog node overhears that its next node fails to forward the packet within a certain time, it increases its failure counter. If node’s failure counter exceeds a predefined threshold, the Watchdog node reports it misbehaving [3]. B. TWO ACK In the Two-ACK, the rule is to let each three successive hub work in a group to find misbehaving nodes. For every three successive nodes in the route, the one which is the third hub has to send Two-ACK acknowledgment packet to the first node/hub [4]. The aim of presenting Two-ACK mode is to detect misbehaving nodes in the presence of receiver collision or limited transmission power.

C. AACK It is similar as TWO-ACK IDS, AACK IDS is an acknowledgment based network layer IDS. It can be treated as a combination of an ID called TACK (identical to TWO-ACK) and an end-toend acknowledgment IDS called Acknowledge (ACK). Compared to TWO-ACK IDS, AACK IDS reduced network overhead. III. EXISTING SYSTEM The existing system approach EAACK is intended to handle three of the six weaknesses of Watchdog scheme, specifically, false misbehaviour, limited transmission power and receiver collision. EAACK is based on both DSA and RSA algorithm. The three important parts of the EAACK scheme are ACK, Secure ACK (SACK), and Misbehaviour Report Authentication (MRA)[5]. EAACK is an acknowledgement based IDS. This scheme utilizes the digital signature method to prevent the attacker from forging acknowledgment packets. Prior to the acknowledgement packets sent out EAACK needs all the acknowledgement packets to be digitally signed and verified by its receiver till they are accepted. A. ACK ACK is an end to end acknowledgement. It is the basic approach in EAACK, for reducing network overhead in times where there is no misbehaviour in network.

PAC K1

A

ACK1

B

C

X

D

PACK1 PACK1 PAC PACK1 K1

ACK1

ACK1

ACK1

ACK1

Fig.2. ACK Scheme B. S-ACK In S-ACK (Secure-ACK) mode the successive nodes like A, B, C work in group to find the misbehaving nodes in the MANETs network. Node A sends the S-ACK packet i.e. Pack1 to C through the intermediate node B. The node C need to send back the S-ACK i.e., Ack1

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 92 

Efficient And Dynamic Hybrid Key Cryptography For Ids Management System In MANETS

acknowledgement packet to A. If in case node A has not received the S-ACK acknowledgement packet within certain predefined time both B and C are considered as malicious. The misbehaviour report will be produced by the node A and passes to the source node S. The source node immediately does not trust the misbehaviour report so EAACK requires the source node S to switch to MRA mode and confirm this misbehaviour report.

A

B

C

D

X

PACK1 PACK1

EAACK is an acknowledgement based IDS. All the parts of EAACK are acknowledgement based schemes. They are based on acknowledgement packets to detect the misbehaviour in the MANET [6]. It is extremely vital to ensure that acknowledgement packets in EAACK are authentic and confidential. If the attackers smart enough to forge acknowledgement packets, these three schemes will be vulnerable. So we incorporated digital signature in our existing system. To bring the integrity of the IDS, EAACK needs all the packets to be digitally signed before they encrypted and verified. IV. PROPOSED SYSTEM

ACK1 ACK1 Fig.2. S-ACK scheme C. MRA The MRA (Misbehaviour Report Authentication) scheme is to verify whether the destination node got the reported missing packet through any alternate route. To begin the MRA mode, the source node searches its local base and looks for an alternate way to destination route. If no other route exists, the source node starts a DSR routing used to find another alternative path. When the destination node receives the MRA packet, it finds the local knowledge base and compares if the reported packet which was received. If the packet is already received then that is the false misbehaviour report and who ever made this report is announced as malicious. If not the misbehaviour report is trusted and accepted. 1

2

3

4

sou rce 5

9

6

1

7

1 1

Here we propose a hybrid cryptography technique to reduce the network overhead caused by digital signature. In Some cases when more malicious nodes are present in the network more acknowledgement packets are required. Around then the ratio of digital signature in the whole network overhead increases. Hence used AES and RSA for data encryption and decryption SHA1 for hashing [7].

8

Desti natio n

D

1

Fig.3. MRA Scheme D. DIGITAL SIGNATURE

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Efficient And Dynamic Hybrid Key Cryptography For Ids Management System In MANETS

date, it is the only possible known attack against AES [8].

Node A

Node B

Node N

2. RSA: It is a public key cryptography can be used for encryption. The key management is an essential feature of RSA algorithm. 3. SHA1: SHA-1 a message digest function with a block size of 512- bit generates 160-bit message digest. It has a very conservative design.

Source route Presence of Malicious node

ACK

Signatu re validati on for securit

S-ACK/MRA

RS A AE S SH A1

Fig.4. System Architecture In Hybrid encryption and decryption we make use of RSA, AES and SHA1. The purpose behind selecting these algorithms is

The advantages of combining an asymmetrical with a symmetrical cryptosystem to hybrid cryptography are:  It increases speed  This scheme is vulnerable for collision attacks.  Thus in this way we can enhance the security of messages and better increase the performance of network. This hybrid encryption will protect data in the packets and will provide better security. A. Encryption Process Step1: An AES key ’K’ of 128-bit, 192-bit or 256-bit is chosen. Step2: Encrypt message (M) using AES algorithm and above selected key K. eM = AES-encryption (M) Step3: AES key K is encrypted by making use of RSA algorithm. eK = RSA-encryption (K) Step4: The cipher text (eM) is fed to SHA1 algorithm which generates a message digest of 160-bit. mD = SHA1 (eM) Step5: The message digest is signed by RSA algorithm using private key of sender. DS = RSA-sign (mD) Step6: The encrypted message (eM), digital signature (DS) and AES encrypted key (eK) is transmitted to the user over a network

1. AES-Rijndael algorithm: AES is symmetric secure cipher cryptography offers a very high performance and security. Not a single successful bruteforce attack on AES has been found till 30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 94 

Efficient And Dynamic Hybrid Key Cryptography For Ids Management System In MANETS

RSA privat e key

Message S

K

m D

AES

D S

RSA Digital

eM

e eK M

RSA

RSA public key Fig.5. Encyption process

B. Decryption Process This process is the reverse of encryption process and is having following steps: Step1: The encrypted AES key (eK) is decrypted with RSA algorithm. K = RSA-decryption (eK) Step2: Similarly the encrypted message (eM) is decrypted by AES algorithm using key K. M = AES-decryption (eM) Step3: The message digest of encrypted message (eM) is computed using SHA1. mD = SHA1 (eM) Step4: The digital signature is verified by RSA algorithm by employing use of public key of sender. DS = RSA-verify (mD) Step5: Thus we get message (M) of sender in step-2 which is verified by digital signature DS. Encrypted

e K

e M

AE

SH

D S

m D

RSA Signa

RSA Public key

RS M

RSA private key

e M

Yes:Veri fication No:Faile d

Fig.6. Decryption process First the secure route for data transmission should be found. The source sends a data to the destination for route identification to the destination. Route identification based on

AODV (Ad hoc On-demand Distance Vector routing protocol) protocol model. AODV protocol (Ad hoc On Demand Vector) protocol is implemented for finding routes in the MANET. The routing protocol is designed for use in mobile ad-hoc network of that even contains huge number of nodes. AODV refers to the class of Distance Vector Routing Protocol (DV). In a DV every node known its neighbours and the costs to reach them. The node contains its own routing table, storing all nodes in the network, distance and the next hop to them. If the node is not reachable the distance to it is set to infinity. After getting a secure route, the data send securely to the destination by using hybrid encryption cryptographic techniques. The data that send from the source node will be encrypted with RSA and AES techniques before its travelling to the destination node. The received data will be decrypted with RSA and AES in the destination node. After receiving the data at destination, the destination node required to send an acknowledgement packet to the source. In presence of malicious node, sender node cannot be defined the route. So that routing overhead is reduced in hybrid technique compared with DSA in EAACK. V.CONCLUSION Mobile Ad Hoc Network has always been prone to security attacks packet dropping has always been a major threat. EAACK Methods are concentrating only on detection of malicious nodes. So it can be further extended to include hybrid encryption to strengthen the security of nodes. Detection of malicious nodes can be done by using EAACK and Prevention of messages, nodes and reducing network overhead caused by EAACK can be taken care by hybrid encryption using AES-Rijandel and RSA Algorithm. In future security can be further enhanced by improving Hash algorithms. References [1] T.Anantvalee J.Wu “A Survey on Intrusion Detection in Mobile Ad-hoc Networks in wireless/mobile security”, provides survey of various Intrusion Detection implementation in mobile ad-hoc networks. [2] B. Sun, “Intrusion detection in mobile ad hoc networks,” Ph.D. dissertation, Texas A&M Univ., College Station, TX, 2004.

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 95 

Efficient And Dynamic Hybrid Key Cryptography For Ids Management System In MANETS

[3] J. Parker, J. Undercoffer, J. Pinkston, and A. Joshi, “On intrusion detection and response for mobile ad hoc networks” in Proc. IEEE Int. Conf. Perform., Comput., Commun., 2004, pp. 747– 752. [4] K. Liu, J. Deng, P. K. Varshney, and K. Balakrishnan, “An acknowledgment-based approach for the detection of routing misbehaviour in MANETs,” IEEE Trans. Mobile Comput., vol. 6, no. 5, pp. 536–550, May 2007. [5] Elhadi M. Shakshuki, Senior Member, IEEE, Nan Kang, and Tarek R. Sheltami, Member, IEEE “A Secure Intrusion-Detection System for MANETs” IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 60, NO. 3, MARCH 2013. [6] Nat. Inst. Std. Technol., “Digital Signature Standard (DSS)” Federal Information Processing Standards Publication, Gaithersburg, MD, 2009, Digital Signature Standard (DSS). [7] Amudha Bharathi.B, Dr.S.Usha “FORTIFY MANETs FROM INVASION USING HYBRID CRYPTOGRAPHIC TECHNIQUES” International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501 Vol.3, No5, October 2013. [8] Jan Mohammad Najar Shahid Bashir Dar b “ A New Design Of A Hybrid Encryption Algorithm” International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 3 Issue 11 November, 2014 Page No. 9169-9171.

30th International Conference on Cloud Computing Computer Science And Advances In Information Technology- ICCCCIT 2017, ISBN: 978-93-85225-92-5, Date: 14th May 2017, Nagpur 96