Reliability Assessment of Complex Power Systems ...

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Reliability Assessment of Complex Power Systems and the Use of NEPLAN Tool

Master Thesis by:

Shima Mousavi Gargari

Master thesis written at the School of Electrical Engineering, Royal Institute of Technology, KTH, 2005/2006. Supervisors: Dr. Lina Bertling, KTH, School of Electrical Engineering Dr. Gabriel Olguin, ABB Corporate Research Examiner: Dr. Lina Bertling, KTH, School of Electrical Engineering XR-EE-ETK 2006:011

Abstract Consumers of electrical energy expect a network to support their apparatuses with continuous and reliable supply. That is the supply should be continuously available on demands. Such an expectation from the power systems makes planners to consider the reliability studies as an important task besides all the other analyses required for assessing the system performance. Results from such kind of studies equip the planners with an appropriate knowledge over a system performance at different load points and consequently help them to identify weak points of the system and decide on possible available solutions for improving the system reliability e.g. more investments at the weak points. Until fairly recent, the inherent reliability of a power system was specified in term of N-1 criterion known as deterministic approach which says that the system must withstand a simple contingency or loss of equipment. As it is clear, such evaluation approach is based on determined system behaviors, however the power system behaviors are stochastic and the failures may occur randomly. Therefore, it is of necessity to consider the possible random behavior of the systems to perform an accurate and precise reliability assessment. New techniques and consequently new computer software packages have been recently developed in which, in contrast to deterministic approach, the idea of using historical performance of the power system components and modeling the stochastic behavior of faults have been considered. As mentioned previously, from customers’ point of views the supply should be always available i.e. no interruption is expected, while practically, due to such stochastic behaviors of the system, supplying the load centers with 100% reliable power source is somehow impossible, however, the probability of the supply interruptions to the load centers can be reduced with more investment at the planning phase. Blackouts events in North America and Europe are good examples for showing that not always the system can guarantee the continuous supply to its customers. It is evident that there is a confliction between reliability and economical constraints which in case may lead to difficult managerial decisions. Therefore, it is important to find out if a certain load point or a specific part of the system deserves more investment or not. Such information can be provided by reliability studies. The power system comprises several complex subsystems. Each subsystem has its own relevant impact on the reliability of the overall system. Transmission systems reliability is not an exception in this category. Busbars, transmission lines and switches functioning may have an extreme influence on the overall system performance. Researches indicate that stations configurations and their fundamental components are important factors which should not be ignored in reliability studies. Failures of station components lead to temporary removal of the failed components and consequently temporary modification of the station configuration. Creating such changes in the protection system configuration can make the system more vulnerable to the disturbances that may occur. Besides tripping of one circuit breaker may result in multiple switch functioning and consequently multiple line outages. Therefore, the relevant load centers

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will experience supply interruption at least for a certain time required for removing the failed breakers and re-closing the affected ones. This thesis work presents a research conducted on evaluating the system reliability as a result of a bulk power system performance. This research work was accomplished by using the university version of commercial software designated as NEPLAN. The quantitative analyses illustrated in this work provide information on how the contributions of sub systems impact the reliability of the overall system. Also, it indicates that, how the contribution of the station components may cause different results. One of the important aspects of this work is to illustrate the application of the computer software package, NEPLAN, in reliability analyses. Three different test systems have been taken under consideration in this work. Due to some restriction in using the university version of the software some simplifications have been applied for the two of the test systems. A simple distribution system has been implemented in NEPLAN, and the results have been validated by comparing the results to the ones obtained from another reliability solver known as RADPOW, developed in KTH, for reliability evaluation of distribution system.

ii

Acknowledgment This thesis work is a part of a long term research cooperation within EKC (Swedish Center of Excellence in Electric Power System) between KTH and ABB Corporate Research. This work has been performed within RCAM (Reliability Centered Asset Management) group in the School of Electrical Engineering, KTH and has been financed by EKC and ABB Corporate Research. The financial support is acknowledged. I would like to express my deep appreciation to Dr. Lina Bertling, my supervisor and examiner from KTH, for all her supports, advices and encouragements. Hereby, I also gratefully acknowledge Dr. Gabriel Olguin, my supervisor from ABB, for sharing his opinions with me, giving me valuable comments to improve my work and supporting me during the course of this work. Also I am really grateful to professor Math Bollen, from STRI, for allocating his valuable time to help me in my work and sharing his ideas with me to give me a deep insight over my work. It is also deserved to thank the people in the School of Electrical Engineering for providing me the opportunity to study and learn more. Besides, I would like to thank the persons in the BCP group for providing me an access to the NEPLAN tool. Appreciation also goes for friends and colleagues in RCAM group in the School of Electrical Engineering, KTH, and other friends inside and outside Sweden. And Finally I would like to express my sincere gratitude and deepest appreciation to my parents and my brothers for their consistent supports and encouragements. Shima Mousavi Gargari Stockholm, June, 2006

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Definitions Definition 1: Any events that cause a violation in system characteristics e.g. buses voltages, circuits currents, active and reactive power are defined as fault. Definition 2: Outage refers to any system state in which the component is not available to perform its intended function. Outages can be categorizes as Forced outages and Scheduled outage. Definition 3: Forced outage is the outage which results from emergency conditions [1] and requires the components disconnection either manually or automatically. Definition 4: Scheduled outages are usually performed foe construction, maintenance or repair purposes [1]. Definition 5: Failure refers to any outage events that prevent the system from supplying the load centers. Failures are divided to two main categories based on the restoration time. 1- Permanent failure 2- Temporary failure Definition 6: Credible events are defined as the failure mode which has the most significant impact on the system. Definition 7: Curtailable load refers to the load category which has not a significant importance in the system and they can be disconnected from the system during remedial action for a certain period. Definition 8: Firm load refers to the load that can not be remained unsupplied in the system. Thus not be disconnected during a remedial action. Definition 9: Availability is the probability of the component to be available or in service [2]. Definition 10: Unavailability is the probability of component being out of service [3]. Definition 11: Failure rate is the probability that the component will fail [3]. Definition 12: Repair rate is the probability that the out of service component will return in service mode [3].

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Table of Contents

Table of contents Abstract............................................................................................................................... i Acknowledgment.............................................................................................................. iii Definitions......................................................................................................................... iv Table of contents ............................................................................................................... v 1. Introduction................................................................................................................... 1 1.1. Background ............................................................................................................ 1 12. Power system reliability evaluation....................................................................... 2 1.3. Research objective ................................................................................................. 4 1.4. Thesis scope and outline ........................................................................................ 4 2. Composite system adequacy assessment by applying analytical approach............. 6 2.1. Introduction............................................................................................................ 6 2.2. Analytical approach............................................................................................... 7 3. Overview of NEPLAN software................................................................................. 17 3.1. Introduction.......................................................................................................... 17 3.2. Application study ................................................................................................. 21 3.3. Validation of the results....................................................................................... 26 4. System Studies............................................................................................................. 28 4.1. Background .......................................................................................................... 28 4.2. Overview of test systems RBTS, IEEE RTS and Birka system ....................... 29 4.3. RBTS Studies........................................................................................................ 32 4.4. IEEE-RTS test system ......................................................................................... 46 4.5. Birka system study............................................................................................... 51 5. Alternative Reliability Tools ...................................................................................... 54 5.1. Introduction.......................................................................................................... 54 5.2. Composite power reliability tools ....................................................................... 55 5.3. Transmission/distribution reliability tools ........................................................ 60 6. Closure ......................................................................................................................... 66 6.1. Conclusion ............................................................................................................ 66 6.2. Future work.......................................................................................................... 67 References........................................................................................................................ 68 Appendix........................................................................................................................... A A. Sample test system .................................................................................................. A B. IEEE-RTS .................................................................................................................B C. RBTS ......................................................................................................................... E D: Birka Nät .................................................................................................................. F

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Chapter 1. Introduction

1. Introduction

1.1. Background Electric power system is one of the most complexes and complicated man-made systems exist in this world. The basic function of the power system is to supply its customers with electrical energy as economically and reliably as possible. The power systems are subjected to many changes in order to fulfill this basic function. For instance, nowadays interconnecting the neighboring systems to enhance the efficiency of the overall system and support deficit power regions with the excessive power in surplus areas, is a common practice. Modifying the system does not necessarily imply that the system is capable of supporting the load centers with 100% reliable source. The blackout events happened in Europe and North America showed that the power systems are not as reliable as they are expected [4]. However, identifying the weak points of the system and reinforcing those areas in an appropriate way may result in achieving the higher reliability and lower probability of interruption.

1

Chapter 1. Introduction

Nowadays, due to increases in load demands, interconnecting the neighboring power systems is a common practice in order to increase the stability, reliability and cost efficiency. The role of transmission system which refers to transfer the bulk power from power station to load centers is highly significant in interconnected systems. Transmission lines outages may result a significant abnormality in system performance and may possibly result in supply interruptions in the load centers. Statistics indicates that transmission systems are less subjected to outages comparing to the distribution systems, however, their outages may result in longer interruptions in the load centers. Due to inherent stochastic characteristics of the power systems, not always the system can guarantee the continuous supply to the load centers i.e. facing supply interruptions in a practical system is unavoidable, however, the probability of its occurrence can be reduced by more investment during planning stage. It is evident that there is a confliction between reliability and economical constraints which in case may lead to difficult managerial decisions. Results for reliability studies may provide the planners an appropriate benchmark to decide if a certain part of the system deserves more preliminary investment during planning phase or not.

12. Power system reliability evaluation Generally, the term of reliability refers to the ability of a component or a system to perform its intended function. In field of power system, such evaluation can be defined as analyzing the ability of the system to satisfy the load demands. Therefore, power system reliability assessment is performed in two main domains; system adequacy and system security. The term of system adequacy relates to existence of sufficient facilities within a system to meet the consumers demand, whereas system security refers to the ability of the system to respond to disturbances arising within a system [5], [6]. Although these concepts are not independent of each other, the reliability evaluation is conducted only in one of the mentioned domains, either adequacy or security, and mostly in adequacy one. The research described in this work is focused on adequacy analysis.

System reliability

System adequacy

System security

Figure 1.1. Reliability evaluation domains [5], [6]

A power system can be divided into three main functional regions [1], [5], [6] designated as generation, transmission and distribution systems. Reliability evaluation of the power systems can be performed in either each individual functional zone or at the hierarchical levels obtained from combining the functional regions. 2

Chapter 1. Introduction

Generation System

HLI

HLII Transmission system

HLIII Distribution System

Figure 1.2. Hierarchical levels for reliability evaluation [5], [6]

HLI analyses refer to evaluating the generation systems and its ability to supply the load points. In this level, the transmission systems and their associated influences on the reliability of the overall system are disregarded. The adequacy indices in this level are loss of load expectation (LOLE), loss of energy expectation (LOEE), failure frequency and its relevant duration (FF and FD). HLII studies can be used to assess the adequacy of an existing or proposed system including the impact of various reinforcement alternatives at both the generation and transmission levels [6]. The adequacy evaluation in this level, results in achieving two different set of indices related to the system load points (individual bus) and the overall system. The most important indices in this level are failure frequency and its duration (FF and FD). Finally the level associated to the overall power system analysis including all the functional zones, starting from generation units and terminating at costumers load points [6] is known as HLIII evaluation. Generally, due to complexity of a practical power system, assessment in this level is not performed by considering all three functional zones; instead, the distribution system which receives its reliability data from the load point indices of HLII is evaluated. The common reliability indices in this level are system average interruption frequency index (SAIFI), the system average interruption duration index (SAIDI) and the customers average interruption duration index (CAIDI). The reliability evaluation of power system can be performed based on either deterministic or probabilistic techniques. Deterministic methods have been used considerably in practical applications. The main drawback of such techniques is their disability to respond to a stochastic behavior of the practical system, such as random failure 3

Chapter 1. Introduction

occurrence. Such impediments have led to utilizing the application of stochastic method for reliability evaluation which results in more accurate and precise prediction on the system reliability. The result of performing the reliability study is illustrated by reliability indices. The reliability indices, which are the numerical parameters, reflect the capability of the system to provide the customers by acceptable level of supply. Two fundamental methodologies are applied to calculate such indices. These methods can be categorized as an analytical approach and a simulation approach. In the analytical approach the system is represented by its mathematical equivalent model. The reliability indices are calculated by applying the direct numerical solution on the equivalent model. On the other hand, the simulation approach deals with analyzing random behaviors of the system in order to estimate the reliability indices. Even though the results of the analytical approach are not as precise as the one for simulation approach, applying this method consumes a comparatively shorter computational time which is an important factor in reliability studies. Reliability assessment in this thesis work has been conducted in adequacy domain with main focus on transmission system, by applying the analytical approach.

1.3. Research objective The main aim of this research work is to perform a reliability study of power system with main focus on the transmission system, by applying analytical approach and utilizing the NEPLAN tool. This research work is a part of a long term project in which the main goal is to develop the new techniques and their computer implementations suitable not only for reliability evaluation of a traditional power system (AC system), but also convenient for reliability assessment of a complex power systems where new technologies such as HVDC are employed in transmission systems in order to enhance the efficiency of the overall power system [7].

1.4. Thesis scope and outline This thesis work is organized in 6 chapters. Chapter 1 introduces the basic reliability concepts and different approaches available for assessing the reliability of power system. In Chapter 2, the main concern is with describing the reliability evaluation of composite power system by applying the analytical approach and introducing the relevant reliability indices. In Chapter 3, a detail explanation and description about NEPLAN software which is used as an analytical solver has been presented.

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Chapter 1. Introduction

Chapter 4 illustrates the application of the mentioned analytical solver for practical systems. In this chapter, three different test systems; modified RBTS test system, modified IEEE-RTS and Birka system have been presented and implemented in NEPLAN. The results of reliability evaluations have been introduced in this chapter. In Chapter 5, some commercial and non commercial tools used for reliability assessment of power systems convenient for evaluating comparatively large systems are introduced. In Chapter 6 very short conclusions and discussions on possible future work have been presented.

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Chapter 2. Composite system adequacy assessment by applying analytical approach

2. Composite system adequacy assessment by applying analytical approach

2.1. Introduction The basic function of a composite power system is to generate and deliver a required electrical energy to the load centers. From consumers’ point of view, the interruption in supply is not ideal, that is the customers prefer not to encounter any disconnection from network. Besides sometimes such interruptions are not desired from the supplier point of view, especially when the cost of compensation that should be paid to the customers of the network in case of interruption in supply is comparatively high. Therefore, in order to evaluate the system performance and reduce the probability of supply interruption and consequently reducing the possible social and economical disasters, it is an important task to study how often the system may encounter outages and how such outages influence the loads of the network,. Performing such studies require an appropriate knowledge over a system. That is, it is necessary to verify what kind of outages may occur in a practical system. 6

Chapter 2. Composite system adequacy assessment by applying analytical approach

Generally, inadequacy of the individual load points is caused by the distribution system [6], however, the outages in bulk power systems affect a larger section of the system. Considering the severity of the outages in the load centers caused by unreliability of the composite power systems, predicting the possible weaknesses within these regions is an important task in planning criteria. A considerable role of transmission system and its fundamental components in such studies is evident. The reliability assessment by focusing on the transmission system can be performed either on HLII level or on the transmission system individually. Due to the complexity of power system, its stochastic nature and its extremely large number of component, performing an adequacy assessment and analyzing the system performance for a practical system, is a very sophisticated work and requires a long computational time. Such analyses include many aspects such as load flow analysis, contingency assessment, generation rescheduling, transmission overload alleviation, load curtailment and etc [6]. In this thesis work it has been tried to cover all the procedures required in analytical approach. The load flow analyses have not been explained here, however, readers are referred to references on power systems analysis for detailed information regarding different load flow analyses. Application of load flow has been also explained in reference [8] and [9]. In following section analytical approach applied for reliability analysis of the bulk power system has been presented.

2.2. Analytical approach As explained in previous chapter, the analytical approach is one of the most common methods applied for reliability assessment of power systems. Results obtained from applying this approach provide an appropriate benchmark for evaluating the system performance and its reliability. In this section it has been tried to describe analytical approach briefly. In analytical approach the system is represented by its mathematical equivalent model. Direct numerical solutions are applied to provide the reliability indices. Generally, there are five main procedures in analytical approach. -

State space diagram generation System state enumeration System state analysis Remedial action Reliability indices

Each of the mentioned procedure has been explained in following parts.

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Chapter 2. Composite system adequacy assessment by applying analytical approach

2.1.1. State space diagram generation An important and basic stage in performing the reliability investigation is to generate the appropriate reliability model. In this level the physical system is transferred to the simple model which is convenient for reliability studies. The system model can be generated by applying the Markov process. Markov process is a stochastic and memory less process in which the present state of the system is independent of all former states except the immediately proceeding one [8], [10]. In Markov process the transition rates are assumed to be constant. Figure 2.1 shows the state space model for a single component which can have either in service or out of service modes. S1

μ1

Up

S2

λ1

Down

Figure 2.1. Markov model for one component

Practically, systems include more than a component. Generally, each component can be repaired in case of any outages and will be return back to the operating status after the certain time required for reparation. Figure 2.2 shows the Markov model for a system consists of two repairable independent components is shown in. S1 Up Up

λ1

λ2

μ1 S2

μ2

Down Up

Up Down

λ2

S3

λ1

μ2

μ1 Down Down

S i is a state of the system

S4 Figure 2.2. Markov model for 2-repair able-independent-component [5], [6]

where, λi and μ i are the failure rate and repair rate of component i respectively. The given model in Figure 2.2 is represented by IEEE committee for the independent events.

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Chapter 2. Composite system adequacy assessment by applying analytical approach

The transitional probability matrix for the model shown in Figure 2.2 is given in Eequation 2.1. 0 λ1 λ2 ⎡− (λ1 + λ 2 ) ⎤ ⎢ ⎥ − ( μ1 + λ 2 ) 0 μ1 λ2 ⎢ ⎥ α1 = ⎢ ⎥ 0 − ( μ 2 +λ 1 ) μ2 λ2 ⎢ ⎥ 0 − ( μ1 + μ 2 ) ⎦ μ2 μ1 ⎣

2.1

General approach in order to obtain the state probably is to solve the Equation set 2.2.a. This approach is applicable for the system consists of either independent or dependent component. More explanation can be found in [8], [10].

[PS −1

PS − 2

PS − 3

PS − 4 ] ⋅ [α1 ] = 0

2.2.a

PS −1 + PS − 2 + PS − 3 + PS − 4 = 1

For a system with “ n ” component the probability of each state can be calculated through Equation set 2.2.b.

[PS −1

PS − 2 . . . PS − n ] ⋅ [α ] = 0

2.2.b

PS −1 + PS − 2 + ... + PS − n = 1

where, [α ] is general transitional probability matrix for the model and PS −i is a probability of state i . Figure 2.3 shows the Markov model proposed for dependent outages. The probability of existence of each state can be calculated by applying the Equation set 2.2.b. Up Up

λ1

λ2

μ1 S2

Down Up

μ2

λC

Up Down

μC

λ2

S3

λ1

μ2

μ1 Down Down

S i is a state of the system

S4 Figure 2.3. Markov model for 2-repair able-dependent-outages [5], [6]

Practically, the number of possible system state in the composite power system evaluation is extremely large when both dependency and independency of outages 9

Chapter 2. Composite system adequacy assessment by applying analytical approach

considered in evaluation. Therefore, applying Equation set 2.2.b to calculate the system state probability is complicated. Generally, to simplify the calculation the assumption of independency may consider in reliability evaluation of the composite power system. By such assumption Equation set 2.2.b will be simplified to the one presented in Equation 2.3. Note that to calculate the state probability for dependent outages such as station originated outages equation 2.2.b should be used. The probability of encountering state i and its associated failure rate and repair rate for independent events can simply be obtained through Equation set 2.3. [5], [8], [11]. Ps − i = ∏ Pk ⋅ ∏ Qm k ∈U

μs −i = λs − i =

∑μ

m∈D

m∈D

2.3

m

∑λ

k ∈U

k

where Pk and λ k = Availability and failure rate of the component k respectively Qm and μ m = unavailability and repair rate of the component m respectively μ si and λ si = Repair rate and failure rate of the state i respectively U = Set of in-service components in state i D = Set of out of service components in state i

Pk =

μk

μk + λk λk Qki = μ k + λk

2.4

The result from Equation sets 2.2.b and 2.3 can be used to calculate the frequency of encountering each state. The frequency of each state is the probability of being in that specific state multiple by the departure rate from that state [5]. Such indices can be calculated by applying Equation 2.5.

f si = Psi ( μ si + λsi ) d si =

[8]

P si f si .8760

2.5

Applying the equations presented in 2.3 to 2.5, for the 2-component- repairable system shown in Figure 2.2 yields: Ps1 = P1 ⋅ P2 where;

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Chapter 2. Composite system adequacy assessment by applying analytical approach

P1 =

μ1

μ1 + λ1 μ2 P2 = μ 2 + λ2 μ si = ∑ μi = 0 System state repair rate

λsi = ∑ λi = λ1 + λ2

System state failure rate

f s1 = P1.P2 (λ1 + λ2 )

The same calculation can be done for the other states. Table 2.1 presents the results of this calculation. Table 2.1. System state data for 2-repairable-componet system

State S1

Probability P1.P2

S2

P1.Q2

S3

Q1.P2

S3

Q1.Q2

Repair rate 0

Failure rate λ1 + λ2

Frequency

μ1 μ2 μ1 + μ2

λ2 λ1

Q1.P2 (λ1 + μ 2 )

0

Q1.Q2 ( μ1 + μ 2 )

P1.P2 (λ1 + λ2 ) P1.Q2 ( μ1 + λ2 )

Now these results can be used to calculate the availability and unavailability of the both series and parallel systems. For a system with series components it is of necessity that all the components operate simultaneously in order to be in operating mode. For instance a system with two series components shown in Figure 2.4.a requires functioning of both components in order to be available. Com. 1 Com. 1

Comp.2

Com. 2

(a)

(b)

Figure2.4. System with 2 repairable components (a) Series system, (b) Parallel system

Considering the Markov process for this case yield that only the state 1 is the success mode and the other three states are the outages modes. Therefore, the availability of this system is equal to the probability of being in state 1 and the unavailability of this system is equal to the summation of the probability of being states 2, 3 and 4.

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Chapter 2. Composite system adequacy assessment by applying analytical approach

When the system is a parallel system, functioning of one of the components is enough to keep the system in operation or success mode. Figure 2.4.b shows a simple parallel system. Applying the Markov process for this system yield that only state 4 is the state in which the system encounters outage, and states 1, 2 and 3 are the states in which the system operates successfully. That is the availability of such system is equal to the summation of the probability of being in states 1, 2 and 3 and unavailability of the system is equal to probability of being in state 4.

2.1.2. System state enumeration One of the significant drawbacks of applying the Markov technique to achieve the reliability model is the extremely large number of generated states which assigns a large computational effort for reliability evaluation. Assume a system contains n components, by applying Markov process the total number of the states which should be evaluated for reliability studies will be 2 n .This leads to consume long computing time, which is not desired in reliability analysis. Therefore, some techniques should be applied in order to reduce the size of state space diagram. Several techniques such as enumerating the states in form of a tree graph, truncation of the states and contingency and ranking can be applied to reduce the number of the states for the system under study. The tree graph enumeration technique used in adequacy analysis is depth-first [8], in which the enumeration starts from level zero and continue from up to down and left to right direction. In Figure 2.3 it has been tried to illustrate this approach for system which consists of three components.

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Chapter 2. Composite system adequacy assessment by applying analytical approach

⎡U1 ⎤ ⎢U ⎥ ⎢ 2⎥ ⎢⎣U 3 ⎥⎦

⎡ D1 ⎤ ⎢U ⎥ ⎢ 2⎥ ⎣⎢U 3 ⎦⎥ ⎡ D1 ⎤ ⎢D ⎥ ⎢ 2⎥ ⎢⎣U 3 ⎥⎦

⎡ D1 ⎤ ⎢D ⎥ ⎢ 2⎥ ⎢⎣ D3 ⎥⎦

⎡U 1 ⎤ ⎢D ⎥ ⎢ 2⎥ ⎣⎢U 3 ⎦⎥ ⎡ D1 ⎤ ⎢U ⎥ ⎢ 2⎥ ⎢⎣ D3 ⎥⎦

⎡U 1 ⎤ ⎢U ⎥ ⎢ 2⎥ ⎣⎢ D3 ⎦⎥

⎡U 1 ⎤ ⎢D ⎥ ⎢ 2⎥ ⎢⎣ D3 ⎥⎦

U i : In service operation mode for component i Di : Out of service mode for component i

Figure 2.3. Depth-first enumeration techniques for 3-component system

In another method known as truncation of the state space, the size of the space can be reduced by eliminating the states which has the lower probability of occurrence. System state probability decrease when the system level increased [8]. This can be done by performing the analysis up to certain level of probability. Another method for reducing the number of states is contingency and ranking. In this approach only the credible events are considered. As defined previously the credible events are the failure events which have the most significant impact on the system performance. In order to choose the appropriate contingencies, it is necessary to obtain a deep understanding over the system under study and the factors that may cause a failure. Various solution techniques and their associated software packages depending upon the adequacy criteria employed and the intention behind the studies are developed and made available in order to analyze the adequacy of a power system [6]. Each software packages has a special predefined failure modes based on the intention behind its development. Such tools are mostly dealing with reliability assessment of either the transmission system or the composite power system and known as network based programs. Generally, in network-based programs failure is defined in terms of line overloads and unacceptable bus voltage level [12]. Network solution [8] which applied in network-based program can

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Chapter 2. Composite system adequacy assessment by applying analytical approach

be a network flow, AC load flow, fast decoupled load flow and DC load flow depends on the purpose of the study. AC load flow and fast decoupled one are the most popular programs while they provide the complete information on system characteristics. When the main concern is the reactive power balance then the DC load flow is the most appropriate program. Reader refers to [6] and [8] for detailed explanation. By applying the mentioned techniques a suitable model for reliability studies will be obtained. The next stage is to study how the possible outages influence the system performance.

2.1.3. System state analysis One of the main parts in reliability assessment is to analyze the impact of the possible failures that may occur in a practical system on the performance of the overall system. For instance how the overloaded transmission lines influence the overall power systems, is an important issue in reliability study of the bulk power systems. Network solutions can be applied to perform such analyses. In case of any violation in system characteristics the system state is defined as an abnormal state and requires the remedial action in form of corrective action or load curtailment to clear the abnormality.

2.1.4. Remedial action After identifying the violation in the system, remedial actions are applied. Remedial action is applied to alleviate the system abnormal conditions [8]. Therefore the main emphasis is on clearing the abnormality of the system due to the special contingency. This can be performed by applying corrective action such as removing the failed component or rescheduling the generation unit and re-supplying the loads. After performing the corrective action to re-supply the load if the violation still exists, then load curtailment will be required. The contingency which led to load curtailment contributes to provide the reliability indices.

2.1.5. Reliability indices Reliability indices are numerical parameters that reflect the capability of the system to provide its customers by an acceptable level of supply. They estimate the system reliability by providing the quantitative measures at each individual load point or for the whole system. In composite power evaluation, as described before, two sets of indices which indicate the performance of the whole system or the performance at each individual load buses within a system may obtain. The main reliability indices in the composite power system evaluation are frequency of interruption and the associated duration. These two indices are important as they indicate the expected frequency and duration of load supply interruption [11]. The load point indices are represented in Equations 2.6 to 2.11. [5], [8]. The main reliability indices in HLII are given in following:

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Chapter 2. Composite system adequacy assessment by applying analytical approach

-

Failure Probability ( FP ):

∑p

FP =

si∈F

-

Failure Frequency(FF) [occ yr ] : FF =

∑f

si∈F

-

2.7

si

Failure duration(FD) [hour distrubance] :

FD = -

2.6

si

FP ⋅ 8760 FF

Expected energy not supplied(EENS) [MWh yr ] : EENS =

∑p

si∈F

-

si

Lc.si 8760

2.9

Expected power not supplied(EPNS) [MW yr ] : EEPS =

∑p

si∈F

-

2.8

si

Lc.si

2.10

Expected load curtailed(ELC) [MW yr ] : ELC =

∑f

si∈F

si

Lc.si

2.11

F is a specific system failure state. p si and f si are the probability and frequency of each failure state respectively. Lc , si is a load curtailed at a specific bus or for overall system in system state si . For reliability evaluation with main focus on the transmission system or distribution system the overall system results obtained from HLII can be replaced by indices obtained from HLIII. The software employed for this thesis work has been developed for reliability evaluation of transmission and/or distribution systems and has the capability of providing indices results from HLIII. The indices obtained from HLIII are presented in the following. Reliability indices for HLIII [5], [13]: System Average Interruption Frequency Index (SAIFI) [int yr , cust ] :

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Chapter 2. Composite system adequacy assessment by applying analytical approach

Total Number of Customers Interruption = Total Number of Customers Served

SAIFI =

∑ λ ⋅N ∑N i

i

2.12

i

System Average Interruption Duration Index (SAIDI) [h yr , cust ] : Sum of Customers Duration Interruption = Total Number of Customer Service

SAIDI =

∑U ⋅ N ∑N i

i

2.13

i

Customers Average Interruption Index (CAIDI) [h int .] : CAIDI =

∑U ⋅ N ∑λ ⋅ N

Sum of Customers Duration Interruption = Total Number of Customer Interruption

i

i

i

i

2.14

Average Service Availability Index (ASAI) [%]: ASAI =

Customer hours of available Service = Customers hours service Demands.

∑ N ⋅ 8760 −U ⋅N ∑ N ⋅ 8760 i

i

i

2.15

i

where, N i represents the number of customers at load point i , λi [1 yr ] is a expected failure rate per year at load point i , U i is the unavailability of load point i

16

Chapter 3. Overview of NEPLAN software

3. Overview of NEPLAN software

3.1. Introduction NEPLAN is an electric power analyzer which has been developed by the BCP group in Switzerland. This software package is used mainly for transmission and distribution systems analyses. It includes optimal power flow, transient stability and reliability analyses [14]. NEPLAN reliability software can be used to provide not only the reliability indices for both the individual load points and the overall power system, but also it can be used to provide the cost of unreliability. NEPLAN is based on Markov process and enumeration techniques. This implies that the approach in NEPLAN follows the same procedure that has been explained in the pervious chapter. Figure 3.1 shows the evaluation approach taken in NEPLAN to achieve the reliability indices for both load point ant the overall system.

17

Chapter 3. Overview of NEPLAN software

Processing of network data

Creating possible outage events combination

First order outage events

Single stochastic outage

Second order outage events

Single deterministic outage

Two stochastic outages

Single stochastic and deterministic outages

Effect analysis of each outages mode on system performance

Normal

System performance

Abnormal Alleviating the abnormality of the system

Normal

System performance

Abnormal Load curtailment



Registering the failure rate

Load point indices, failure frequency, duration, etc.

Overall system indices

Figure.3.1. Flowchart for reliability evaluation in NEPLAN

18

Chapter 3. Overview of NEPLAN software

The first step is to analyze all the input data required for load flow analysis and data required for reliability evaluation. After processing the data and solving the load flow program for the system in order to obtain the system characteristics in normal condition, the system will be modeled by applying the Markov process. The achieved model will be reduced to the reasonably small model by applying the contingency and ranking or the truncation of states techniques. But as noted before, applying such techniques require a deep understanding over practical systems i.e. it is necessary to know what kind of outages may occur in practical system. In NEPLAN the predefined outages events in are categorized in two groups i.e. first order contingencies and second order contingencies. The second step is to create a first order and second order outage combinations. First order contingencies deal with single stochastic outages and single deterministic outages. Generally the single deterministic group does not contribute in interruption frequency while it causes no supply interruption to the loads of the system. Single stochastic outages group includes several modes such as independent single outage, common mode outage, ground fault and unintended switch opening. The reliability input data for these categories are failure rate and repair time and the output data are failure frequency and its relevant duration. Second order contingencies can be considered either as two stochastic outages or stochastic and deterministic outages. In the case of overlapping of two stochastic outages the failure frequency is calculated by applying equation 3.1 or 3.2. The failure frequency for overlapping of stochastic and deterministic outages is obtained through equation 3.3. For independent outages [15], FF = λ A ⋅ λB (rA + rB )

3.1.

where λ A and λ B are the failure rate and ri is their relevant repair time. For dependent outages where the second outage may occur with the probability of Pr as a consequent of the first outage, like a second short circuit due to delay in clearing the first short circuit in network, the failure frequency is calculated by applying 3.2 [15]. FF = λ A ⋅ PrB

3.2.

As cited previously the deterministic outage itself may not cause supply interruption in load, but simultaneous occurrence of deterministic and stochastic outages may result in forced outage, which leads to load failure. In such case the failure frequency at load points obtained by applying 3.3 [15]. FF = λ A ⋅ λB ⋅ rB

3.3.

where λ A and λ B are the failure rate for stochastic and deterministic outages respectively and ri is the relevant repair time for maintenance (deterministic outage).

19

Chapter 3. Overview of NEPLAN software

After reaching the appropriate reliability model, all the possible outages combinations which have been contributed to provide the reliability model will be analyzed individually to verify their impacts on the system performance. If the created outages result in any variation in system characteristic such as fluctuation in bus voltages, the corrective action such as disconnecting the faulty line and supplying the load in an appropriate way is performed. After performing the corrective action, if the abnormality still exists, the remedial action i.e. load curtailment will be required. The failure frequency of that specific state which results in load curtailment will be calculated. For second order combinations the failure frequency in NEPLAN is calculated by applying Equations 3.1 to 3.3. The calculated failure frequency will be registered in order to contribute for final reliability calculation. This procedure will be continued to analyze all the possible outage events that may occur within a practical system. The last step after studying all the possible outage events is to sum up the registered failure frequency relevant to a specific load bus and calculated the relevant indices at each individual load point and overall system. Table 3.1 and 3.2 shows the indices for each individual load points and overall power system provided by NEPLAN. Table 3.1. Load point indices [15], [16]

Index Interruption Frequency

Unit

[1 yr ]

Interruption Duration

[min yr ] [hrs yr ]

Mean Time of interruption

min, hrs [kW yr ] [MW yr ] [kWh yr ] [MWh yr ] [ $ yr ]

Power not supplied Energy not supplied Interrupted cost

Description Expected frequency of supply interruption per year Expected probability of interruption in minute or hours per year Average duration of customer interruption Product of interrupted power and its interruption frequency Product of interrupted power and its interruption probability Cost of supply interruption

Table 3.2. Overall system indices [15], [16]

Index

Unit

N SAIFI

-

[1 yr ]

SAIDI

[min

CAIDI ASAI F

h

T Pr P W C

yr ]

%

[1 yr ] h [min yr ] [MW yr ] [MWh yr ] [CU yr ]

Description Total number of customers not served System average interruption frequency index System average interruption index Customer average interruption duration index System average availability System load interruption frequency System load interruption frequency System load interruption probability Total interrupted load power Total load energy not supplied Total load interruption cost

20

Chapter 3. Overview of NEPLAN software

3.2. Application study Figure 3.2 shows a small test system implemented in NEPLAN in three different modes in order to clarify a reliability calculation approach. The hand calculation for southern part of the system has been illustrated in the following part, to demonstrate how the software calculates the indices.

LP-5

CB

TR

DISC

LP-6

Figure 3.2. Test system [13]

Mode 1: In this mode there is no connection between bus 5 and 6. Therefore neither disconnect switch nor connection link exist. The model has been shown in Figure 3.3. LP-5

LP-6

CB

TR

DISC

Figure 3.3. Test system without disconnect switches [13]

21

Chapter 3. Overview of NEPLAN software

Hand calculation of Load point indices for LP6: As noted previously in this part reliability indices for southern part of the sample system which supplies the load point 6 will be calculates by hand. Equations 3.4 and 3.5 can be applied to calculate the failure frequency and associated duration for the series and parallel components. For series components: λS = ∑i λi RS =

∑ λ ⋅r i

i

i

[13]

3.4

[13]

3.5

λS

For parallel components or second order failure combination: λ ⋅ λ ⋅ (r + r ) λ12 = 1 2 1 2 1 + λ1 ⋅ r1 + λ2 ⋅ r2 r ⋅r r12 = 1 2 r1 + r2 Figure 3.4 shows the southern part of the sample test system. BB4

CB6

BB5

CB7

TB3

CB8

BB6

LP-6

Figure 3.4. The circuit which feeds load point 6

FF = λBB 4 + λCB 6 + λBB 5 + λCB 7 + λTR 3 + λCB 8 + λBB 6 FF = 0.001 + 0.02 + 0.001 + 0.02 + 0.015 + 0.02 + 0.001 FF = 0.078 1

yr

Failure duration calculation for load point 6: ∑ λi ri RS =

λs

0.001 ∗ 2 + 0.02 ∗ 24 + 0.001 ∗ 2 + 0.02 ∗ 24 + 0.015 ∗ 15 + 0.02 ∗ 24 + 0.001 ∗ 2 0.078 RS = 21.42 [h yr ] RS =

22

Chapter 3. Overview of NEPLAN software

System Indices: System indices can be calculated by applying equations 2.12-2.15 Applying equation these equations yield:

SAIFI =

0.103 ∗ 80 + 0.078 ∗ 100 = 0.09 80 + 100

SAIDI =

0.103 ∗ 21.42 ∗ 60 ∗ 100 + 0.078 ∗ 23.362 ∗ 60 ∗ 80 = 124.78 [min yr.cust ] 100 + 80

CAIDI =

0.103 ∗ 23.362 ∗ 100 + 0.078 ∗ 21.42 ∗ 80 = 22.63 [h] 0.103 ∗ 100 + 0.078 ∗ 80

ASAI =

[int

yr.cust ]

(100 + 80) ∗ 8760 − (0.103 ∗ 23.362 ∗ 100 + 0.078 ∗ 21.42 ∗ 80) ∗ 10 = 99.976 [%] 180 ∗ 8760

Results obtained from NEPLAN:

Load point indices: Table.3.3. Load point indices for system illustrated in 3.2 obtained from NEPLAN

Load Point L-5 L-6

Failure Frequency [1 yr ] 0.103 0.078

Failure Duration [h ] 5.362 21.425

Overall system indices: Table 3.4. Overall system indices for system illustrated in figure 3.2

Index N SAIFI

Unit -

[1 yr ]

180 0.092 124.748

CAIDI

[min yr ] [h]

ASAI

%

99.976

SAIDI

23

22.631

Chapter 3. Overview of NEPLAN software

Mode 2: In this mode the disconnect switch has been incorporated for reliability calculation. It is worth to note that, this switch has been considered to be in open mode at the begining. The single line diagram of the circuit is illustrated in Figure 3.5. LP-5

LP-6

Figure 3.5. Single line diagram of the test system, open disconnect switch [13]

Load point indices: Table.3.5. Load point indices for test system when DICS switch is open

Load Point L-5 L-6

Failure Frequency [1 yr ] 0.103 0.078

Failure Duration [h ] 1.011 1.014

Overall system indices: Table 3.6. Overall system indices for test system, DISC switch is open

Index N SAIFI

Unit -

[1 yr ]

180 0.091

CAIDI

[min yr ] [h]

1.012

ASIA

%

99.999

SAIDI

5.501

In this part, the failure frequency is the same while the disconnect switch is open and it has no influence on the interruption frequency in the load points. However, the duration has been influenced. That means, whenever there is any interruption occurred in each part of the system, the disconnect switch can be closed and the affected load point has the possibility to partially supply from the other part of the system. That is, re-supplying at least a part of the interrupted load in the shorter period is possible by closing this switch.

24

Chapter 3. Overview of NEPLAN software

Mode 3: Disconnect switch is closed in this evaluation: LP-5

LP-6

Figure 3.7. Single line diagram of the test system, Closed disconnect switch [13]

Load point indices: Table.3.7. Load point indices for test when DICS switch is close.

Load Point L-5 L-6

Failure Frequency [1 yr ] 0.063 0.063

Failure Duration [h ] 1.049 1.049

Overall system indices: Table 3.8. Overall system indices for test system, DISC switch is close.

Index N SAIFI

Unit -

[1 yr ]

180 0.063

CAIDI

[min yr ] [h]

1.049

ASIA

%

99.991

SAIDI

3.966

In this mode, since the disconnect switch was closed from the beginning it has been contributed in reliability calculation. The results show that the failure frequencies in both load points have been decreased.

25

Chapter 3. Overview of NEPLAN software

3.3. Validation of the results A comparison has been made between the results from NEPLAN and another reliability tool known as RADPOW to validate the obtained results. RADPOW is a reliability tool developed in KTH School of Electrical Engineering for reliability assessment of distribution system. This tool was developed based on analytical approach [13]. A new version of RADPOW which has been recently developed, includes simulation approach [25]. This software package has been explained more in detail in Chapter 5. It is worth mentioning that in this work the term of RADPOW refers to analytical approach of this solver, and term of Simulation refers to Simulation approach of RADPOW. Comparisons of the results obtained from NEPLAN and RADPOW for the test system in three different modes have been shown in following tables. Mode 1: Table.3.9. Failure frequency index obtained from different software for Mode 1.

Failure Frequency LP-5 LP-6

Neplan [1 yr ] 0.103 0.078

RADPOW [1 yr ] 0.103 0.078

Simulation [1 yr ] 0.103 0.078

Δ( NEP − RAD)

Δ( NEP − Sim)

0.000 0.000

0.000 0.000

Table.3.10. Unavailability index obtained from different software for Mode 1.

Unavailability NEPLAN [h yr ] LP-5 0.0964 LP-6 0.470

RADPOW [h yr ] 0.097 0.471

Simulation [h yr ]

Δ( NEP − RAD) Δ( NEP − Sim) 0.0006 0.001

Mode 2: Table.3.11. Failure frequency index obtained from different software for Mode 2.

Failure Frequency LP-5 LP-6

NEPLAN [1 yr ] 0.103 0.078

RADPOW [1 yr ] 0.103 0.078

Simulation [1 yr ] 0.103 0.078

Δ( NEP − RAD)

Δ( NEP − Sim)

0.000 0.000

0.000 0.000

Table.3.12. Unavailability index obtained from different software for Mode 2.

Unavailability NEPLAN [h yr ] LP-5 0.104 LP-6 0.079

RADPOW [h yr ] 0.104 0.079

Simulation [h yr ] 0.104 0.079

26

Δ( NEP − RAD) Δ( NEP − Sim)

0.000 0.000

0.000 0.000

Chapter 3. Overview of NEPLAN software

Mode 3: Table.3.13. Failure frequency index obtained from different software for Mode 3.

Failure Frequency LP-5 LP-6

NEPLAN [1 yr ] 0.063 0.063

RADPOW [1 yr ] 0.064 0.064

Simulation [1 yr ] 0.064 0.064

Δ( NEP − RAD)

Δ( NEP − Sim)

0.001 0.001

0.001 0.001

Table.3.14. Unavailability index obtained from different software for Mode 3.

Unavailability

LP-5 LP-6

NEPLAN [h yr ] 0.066 0.066

RADPOW [h yr ] 0.065 0.065

Simulation [h yr ] 0.065 0.065

Δ( NEP − RAD) Δ( NEP − Sim) 0.001 0.001

0.001 0.001

The small differences between the results obtained from these tools can be justified by considering the possible different assumption defined for each tool. However, these differences are small enough to be neglected.

27

Chapter 4. System studies

4. System Studies

4.1. Background Three test systems, two composite power systems and one distribution system are utilized in this thesis work. Roy Billinton reliability test system designated as RBTS [17] and IEEE-RTS [18] have been used in wide range in reliability studies. These test systems have been developed for educational purposes and are used enormously for composite power reliability evaluations. These test systems as well as a small part of the distribution system in Stockholm city, so-called as Birka system, have been implemented in the NEPLAN the results have been presented in the following sections.

28

Chapter 4. System studies

4.2. Overview of test systems RBTS, IEEE RTS and Birka system The reliability test system designated as RBTS was developed in university of Saskatchewan for educational and research purposes. The small size of this test system makes it a suitable test system to conduct large number of reliability studies in reasonable time. The RBTS comprises of 6 buses; 2 generator buses and 5 load buses. The 2 generator buses consist of 11 generators. The buses are connected via 9 transmission lines. The total installed capacity is 240 MW and the system peak load is 185MW . The voltage level on transmission line is 230kV . The second test system designated as IEEE-RTS was developed by the Subcommittee on the Application Methods in the IEEE Power Engineering Society to provide a common test system for reliability studies. This test system is a 24-bus system comprises 10 generator buses, 10 load buses and 4 intermediate buses. The total number of generation units available in generator buses is 32 units. The buses are connected through 33 transmission lines. The system has divided two Northern and Southern part. In northern part the voltage level is 230kV and in southern part is 138kV . The total installed capacity in generation units is 3405MW and the total peak load is 2850 MW . The southern part is power deficit area while the northern part is surplus power area. Birka system is a practical distribution system in Stockholm city. Figures 4.1, 4.2 and 4.3 show the single line diagram of these test systems respectively. The data for the systems required for load flow and reliability studies, including generation units’ data, transmission lines and load model data are given in Appendix A.

29

Chapter 4. System studies

G

2 × 40 MW 1 × 20 MW

G

1 × 10 MW

3

1 × 40 MW 4 × 20 MW 2 × 5MW

Bus 2

Bus 1

20 MW

1

2

6

7

4 Bus 4

Bus 3

85MW

5

8

Bus 5

20 MW

9 Bus 6

20 MW

Figure 4.1. Single line diagram of the RBTS [17]

30

40 MW

Chapter 4. System studies

G G

B.18

G

B.21

B.22

B.17

B.23 G G

B.16

B.19

B.20

B.14 G

B.15 B.13

G

B.24

B.11

B.12

B.9

B.3

B.10

B.6

B.4 B.5

B.8

B.1

B.2 G

B.7 G

Figure 4.2. Single Line diagram of the IEEE-RTS [18]

31

G

Chapter 4. System studies



220 kV

c1 c2

c8

c3

c9 c4

c10

110 kV

bus

c5

transformer

cable c6 c7

c15

c49 c50

c53

c52

c19 c20

c23

c27

c40

c43

c24

c21

c17

load point

c36

c38

c55

c58

supply point

c37 c16

c57

fuse

c13

c54

c51

c56

c12

33 kV

c14

breaker

c11

c39

c25

c18

c22

11 kV

c28

c11

c26

c46

c41 c42

c44 c45

c47 c48

SL

HD c29 c30

c31

c32 c33 c34 c35 LH11

Figure4.3. Single line diagram for Birka system [13]

4.3. RBTS Studies 4.3.1. The base case studies for the Modified RBTS test system Base case studies provide appropriate information in reliability study to obtain the affects of the system modifications. In the base case studies the sub stations’ elements are considered to be ideal and also the common mode failures are disregarded. It is noteworthy to mention that in this work the substations for RBTS and IEEE-RTS systems have been simplified due to limited number of nodes in university version of the tool. That is the implemented test systems in NEPLAN are the modified ones and are not the same as the practical ones. Figure 4.4 shows the modified RBTS test system. The substation in generation sides has been simplified due to restriction in number of possible nodes. For IEEE-RTS, the station configuration is simplified to only 1 circuit breaker. 32

Chapter 4. System studies

G

G

G

G

N23

N22 G G

N11

N14

1

LINE3

N23

G 5

2

2

N21

1

3

N24

4

Bus 1

N25

N12

3

20 MW

Bus 2

G

4

G

LINE2

N13

LINE1

LINE7

LINE6

N33 N36 N32 3

N43

LINE4

N35 2

1

3

2

Bus 3 4

4

N51 N31

1

20 MW

40 MW

4

N62

LINE9 1

N41 N52

3

Bus 6

5

2

85MW Bus 5

1

Bus 4

LINE8

5

N42

N44

N45

LINE5

2

N61

i

: is Circiut breakers

G

: is generator

N

: is node

LIN

: is transmission Line

20 MW Figure 4.4. Schematic of the implemented model

The load point indices can be calculated by assuming either a constant load level (a peak load) or a load duration curve. The results obtained from the former one is called as the 33

G

Chapter 4. System studies

annualized indices and the ones for latter one called as annual indices. Since in the second calculation the load variation versus time is considered, the calculated indices are more accurate and close to reality compared to the ones obtained from the first calculation. However, the first approach consumes less computational time. In NEPLAN it is possible to define the load duration curve up to 4 steps. In this evaluation the reliability of the power system has been studied under the peak load of the system. Therefore the obtained results are the annualized indices. The curtailment of the load at the appropriate system buses in the event of capacity deficiency [6] is an important consideration in reliability evaluation. Normally, load can be assumed as firm load and curtailable load [6], [8]. This implies that practically it is not possible to curtail more than a specific part of the load in case of deficit power. In this study 20% of the load is allowed to be curtailed. Besides, it is necessary to mention the load priority to assign a load curtailment order in case of deficit power in network. There are several issues which are used in order to classify the load and to determine the load curtailment philosophy. Some features such as economic priority can be used to assign a load curtailment sequence. Basically, some loads are more important than the other load within a system. Therefore each load buses could be classified regarding its importance within a system. NEPLAN has the capability of performing the load shedding regarding the defined priority of load buses. The priority order can be arranged based on economic factor. The cost of energy not supplied can be an appropriate index to allocate the priority of load curtailment for each load buses. The cost of energy not supplied and the priority of load curtailment for RBTS are given in Tables 4.1 and 4.2 respectively. Table 4.1. Cost of energy not supplied for RBTS [2]

Bus

Cost of energy not supplied [$ kWh] 7.41 2.69 6.78 4.87 3.63

2 3 4 5 6

Table 4.2. Priority of load for RBTS [2]

Priority order 1 2 3 4 5

Bus 2 4 5 6 3

34

Chapter 4. System studies

For the base case study as mentioned previously the station originated outages and common mode outage have not been considered. The evaluation has been performed by considering the peak load values. The results are presented in following tables. Table 4.3. Load point annualized indices for RBTS for base case study.

L-2 L-3 L-4 L-5 L-6

Failure Frequency [1 yr ] 0.01 0.038 0.123 0.002 0.002

Duration [h]

1.000 1.000 2.849 5.000 5.000

Probability [min yr ]

0.600 2.280 21.107 0.685 0.685

Power not supplied [MW yr ] 0.200 3.229 4.939 0.046 0.046

Energy not supplied [MWh yr ] 0.200 3.229 14.071 0.228 0.228

Figure 4.5. Load point annualized indices for RBTS for base case study.

Results shown in Table 4.3 and Figure 4.5 imply that the load point 4 is the weakest point in the system for the base case study. The failure frequency and the interruption duration at this load point is higher than the ones for other load points. Since the dependent outages (station originated and common mode outages) have been disregarded in this study, the provided indices are not an appropriate benchmark to evaluate the adequacy of the system or each load point. But as mentioned before, they can be used to compare the contribution of the different kind of dependent outages on the adequacy. Table 4.4 shows the annualized indices for the overall power system. Although these indices are mainly used for distribution system, they can be used to indicate the reliability of the overall system when the focus is on transmission system. As it is already evident

35

Chapter 4. System studies

from the results, the system performance is considerably high and the probability of encountering load interruption is quite low. Table 4.4.Overall system annualized indices for RBTS

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.035 5.071 2.401 99.99 0.174 2.367 24.671 8.46 17.957

One of the interesting features of NEPLAN is its ability to register the different outage combinations and demonstrate their relevant effect analysis. Such kind of information may help the planners to identify that how the mal operation of the components may lead to unreliability of the system. Table 4.5 indicates one of the created outage combinations for the presented system under given assumption. For the base case study under the peak load, 138 outage combinations have been created in NEPLAN. In this section only two of the possible failures are shown. Table 4.5. Sample outage combination for RBTS under peak load and base case study

Outage Combination Outage Combination 1 Failed Element Protection tripping

Type of Element

Element name

Generator Circuit Breaker Circuit breaker Generation unit

GEN11 CB-11* CB-13* GEN11

Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit *CB-11 is the circuit breaker number 1 in bus 1. *CB-13 is the circuit breaker number 3 in bus 1.

GEN12 GEN13 GEN14 GEN22 GEN23 GEN26 GEN21 GEN27 GEN25 GEN24

Influenced feeders/generation units

36

Chapter 4. System studies

As shown in Table 4.5, when generator 1 in bus section 1 encounters any failures, the circuit breakers 1 and 3 in bus section 1 are tripping in order to isolate the fault. As a result of circuit breakers operation, the mentioned generation unit will be disconnected from the system. Consequently, the available generated power with in a system will be less than the normal operation mode. As a result of deficit power within the system, due to loss of the generation unit, the other generation units should increase their production in order to compensate for the lack of power in the area. In case if the other generation unit hit their maximum capacity before compensating for the deficiency, the load curtailment which is assigned by load curtailment philosophy should be applied. In this case the available capacity of the generation units have the possibility to cover the deficiency. That is, there is no need to curtail the load when this outage occurs. Table 4.7 shows another sample of the evaluation which results in load curtailment. Table 4.6. Sample outage combination for RBTS under peak load and base case study

Outage Combination Outage Combination 5 Failed Element Protection tripping Influenced feeders/generation units

Opening switch after an hour 01:00:00 Involved elements Closing switch after an hour 01:00:00 Involved elements Influenced load Influenced generation unit

Type of Element

Element name

Generator Circuit Breaker Circuit breaker Generation unit

GEN22 CB-21* CB-22* GEN11

Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit

GEN12 GEN13 GEN14 GEN22 GEN23 GEN26 GEN21 GEN27 GEN25 GEN24

Disconnect switch

GEN22

Circuit breaker Circuit breaker Load Generation Unit Generation Unit Generation Unit Generation Unit Generation Unit Generation Unit Generation Unit Generation Unit Generation Unit

CB-22 CB-21 L-2 GEN11 GEN13 GEN14 GEN23 GEN26 GEN27 GEN21 GEN25 GEN24

37

Chapter 4. System studies

As a result of failure in generator 2 in bus section 2, the circuit breakers 1 and 2 in bus section 2 are tripping to isolate the fault. But by their tripping operation not only the fault is isolated but also the load which is connected at the mid point of these breakers will be isolated from the rest of the system and will face interruption for a certain period. It will take an hour to remove the failed generator and re-closed the circuit breakers. Therefore, in such case re-supplying the interrupted load will take 1 hour. Besides, due to failure of the generation unit other generators in the system have been affected too. That is they should increase their capacity in order to compensate for the lost generation unit.

4.3.2 System studies incorporating station originated and common cause outages In previous section the station configurations and its fundamental components’ outage were not incorporated in the reliability evaluation. Practically, station related outages can have considerable impact on the reliability of a composite generation and transmission system [19]. When one of the breakers encounters failure, the other breakers might be switching. As a result of breakers tripping, the relevant lines will be disconnected and consequently the loads fed through these lines will be interrupted. The probabilities associated with station originated and multiple common-cause outages can be quite high compared to the corresponding event probabilities associated with independent outages [6]. Therefore, it is not practical to disregard the impact of these outages. 4.3.2.1. Reliability assessment incorporating station originated outages.

The representation of stations as a simple node [20] or disregarding the station originated outages which could cause a significant impact on the reliability of the system is one of the simplifications applied in reliability evaluation. As the station originated outages have a large influence on the reliability of the overall power system, it is not a right assumption to disregard the stations configurations and their associated outages. The failure of station component may result in multiple outages of generators and/or transmission lines [6] and consequently supply interruption to the load points. In previous case study, it has been assumed that the stations’ elements are fully reliable, whilst in this section the unreliable stations’ elements have been incorporated. Tables 4.7, 4.8 and Figure 4.6 indicate the result for the implemented RBTS test system in NEPLAN. Table 4.7. Load point annualized indices incorporating station originated outages.

L-2 L-3 L-4 L-5 L-6

Failure Frequency [1 yr ] 0.243 0.372 0.478 0.283 0.735

Duration [h]

12.996 8.859 7.959 11.736 11.783

Probability [min yr ]

189.607 197.871 228.131 198.949 519.794

38

Power not supplied [MW yr ] 4.863 31.643 19.110 5.650 14.705

Energy not supplied [MWh yr ] 63.202 280.317 152.087 66.316 173.265

Chapter 4. System studies

Figure 4.6. Load point annualized indices incorporating station originated outages.

As it is evident from the obtained results, when the dependent outages are incorporated, the scenario of adequacy and inadequacy of the load is changed. In this case, the load point 6 which was the most adequate load in the system is happened to be an inadequate one. As it is obvious from the single line diagram of RBTS shown in Figure 4.1, this load bus is connected to the rest of the system through the single transmission line. Therefore, any outage combination in which the transmission line 6 is contributed will result in isolating this bus from the rest of the system. As there is no individual generation unit available in this bus section, the outage of transmission line results in overall load interruption connected to this bus. Therefore, it can be concluded that this load bus is the one which requires more concern during planning phase. Since in such analyses the dependent outage events have been regarded, the achieved results can provide a sufficient data regarding the supply adequacy and inadequacy. But note that in this case study only one kind of dependent outages has been considered. Common mode outages will be dealt with in next section. Table 4.8 indicates the annualized indices for the overall power system. As the results show, the availability of the system when the station components outages are contributed in evaluation is 99.94. The total load curtailment for the system is 75.972 [MW yr ] and consequently energy not supplied is 735.88 [MWh yr ] . Such results imply that, even though there are multiple outages happened in load point, but the supply availability in the overall system is quite high.

39

Chapter 4. System studies Table 4.8. Overall system annualized indices incorporating station originated outages

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.422 266.870 10.535 99.94 2.055 10.735 1323.755 75.972 735.88

Table 4.9 indicates one of the outage combinations has for the implemented system. Table 4.9. Sample outage combination under peak load + Station relevant outages

Outage Combination Event1: Outage Combination 60 Failed Element Protection tripping

Influenced load Influenced feeders/generation units

Event 2: Opening switch After 01:00:00 hour

Type of Element

Element name

Circuit Breaker Circuit Breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Load point 2 Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Disconnect switch

CB21 CB-35 CB-31 CB-14 CB-31 CB-44 CB-43 CB-25 CB-22 CB-31 L-2 GEN11 GEN12 GEN13 GEN14 GEN26 GEN23 GEN22 GEN21 GEN27 GEN25 GEN24 Disc-LIN3

Disconnect switch Disconnect switch Disconnect switch

Disc-LIN2 Disc-GEN 22 Disc-GEN 21

40

Chapter 4. System studies

Event 3: closing switch after 01:00:00

Circuit breaker

CB-14

Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker

CB-35 CB-11 CB-31 CB-44 CB-43

As mentioned previously, the outage of the circuit breakers may result in multiple outages. In this case as a result of a fault occurrence in circuit breaker 21 (circuit breaker 1 in bus 2), the other breakers given in Table 4.9 have been influenced. Load point 2 which is connected to the mid point of the two tripped breakers (circuit breakers 1 and 2 in bus 2) has been disconnected from the rest of the system. Besides, as a result of the operation of the mentioned breakers in Table 4.9, some of the generators will be disconnected from the system and consequently the amount of power within a network has been decreased while the load demand is still the same as before, therefore, the other available generation unit should increase their generating capacity till the disconnected generators returned back to the system. If the available generators can not produce a required energy for satisfying the load demands, load curtailment according to the load priority should be applied. The affected generation units due to the fault in breaker 21 are also introduced in Table 4.9. Note that the affected components will be return back to their operation mode, after removal of the breaker 21, and re-closing the influenced breakers. This process will take one hour in this case study. A duration which the failed component requires to return back to the operating mode is its relevant repair time plus the switching time. In this outage event the load center 2, is the load point which encounters interruption. This load will be re-supplied after removal of the failed breakers and re-closing the other switches. That is re-supplying the load requires an hour which is the switching time of the breakers. Although the load point 2, is the most adequate one, when it encounters outages, its relevant duration is longer than the other load point indices. The reason is due to interruption duration of the components contributing in the outages combination. 4.3.2.2 Incorporating common mode outages.

In previous case the dependent outages in form of station originated ones, has been studied. Another kind of dependent outages can be presented in form of common mode outages. In RBTS reliability test system the transmission lines which are vulnerable to common mode outages are the lines in common right of way. These circuits are the lines 1, 6, 2 and 7. As shown in single line diagram of RBTS, two transmission lines leave bus 1 and go to busbar 3, and also two lines leave bus 2 and go to busbar 4. There is a possibility that simultaneous outages occur due to outages in common right of way e.g. fault in the tower which carries these lines. Table 4.10, 4.11 and Figure 4.7 show the reliability indices when common mode outages are incorporated.

41

Chapter 4. System studies Table 4.10. Load point annualized indices incorporating common mode outages.

L-2 L-3 L-4 L-5 L-6

Failure Frequency [1 yr ] 0.010 0.190 0.656 0.009 0.009

Duration [h]

Probability [min yr ]

1.000 1.010 13.022 2.219 2.219

0.600 11.533 512.888 1.207 1.207

Power not supplied [MW yr ] 0.200 16.176 26.258 0.181 0.181

Energy not supplied [MWh yr ] 0.200 16.339 341.925 0.402 0.402

Figure 4.7. Load point annualized indices incorporating common mode outages. Table 4.11. Overall system annualized indices incorporating common mode outages

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.175 105.487 10.048 99.98 0.854 10.250 525.298 42.997 359.269

42

Chapter 4. System studies

Comparing the obtained results to the ones when station outages are incorporated, it is evident that the effect of station components and its configuration on the reliability of power system is more pronounced [6]. As it is clear from the results, the weakest point in this system is the load center 4 due to its higher failure frequency and higher unavailability duration. Note that due to load curtailment philosophy assigned by load priority and the permitted percentage of load curtailment, the load 3 and 4 are happened to be affected more than the other loads in the system. The worst case is when lines 1, 6, 2 and 7 are disconnected simultaneously, which result in isolating the bus sections 3, 4, 5 and 6. Anyhow this case does not occur in NEPLAN due to restriction in number of simultaneous outages (2 simultaneous outages). The results show that the load not supplied in bus 4 is higher than the other buses due to higher number of failure frequency in this bus. Definitely, this case is not desirable, due to the cost of compensation given in Table 4.1 for energy not supplied. Therefore, this load bus is the weakest point in the system, not only from frequency of interruption point of view but also from cost of energy not supplied standpoint i.e. this bus section is weak both from customers and suppliers stand points and required more investment during planning and operating phases. 4.3.2.3 Incorporating the station originated and common mode failures.

In this study case both the station originated and common mode failure are considered in the assessment. The results are introduced in Tables 4.12, 4.13 and Figure 4.8. Table 4.12. Load point annualized indices for RBTS incorporating the station originated + common mode outages.

L-2 L-3 L-4 L-5 L-6

Failure Frequency [1 yr ] 0.243 0.537 1.020 0.291 0.744

Duration [h]

12.996 6.449 11.826 11.422 11.659

Probability [min yr ]

189.607 207.903 723.418 199.620 520.465

43

Power not supplied [MW yr ] 4.863 45.673 40.782 5.825 14.880

Energy not supplied [MWh yr ] 63.202 294.530 482.278 66.540 173.488

Chapter 4. System studies

Figure 4.8.

Load point annualized indices for RBTS incorporating the station originated + common mode outages.

Table 4.13. Overall system annualized indices for RBTS incorporating the station originated + common mode outage

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.567 368.208 10.822 99.93 2.753 11.063 1827.608 112.025 1080.057

As stated before, comparison of the results presented in Tables 4.7 and 4.10 shows that the station elements reliability effects are more dominant compare to the common mode outages of the transmission lines, therefore, the results when both outages are considered must not vary that much from the case when only the station originated outages are considered. Results in Table 4.12 confirm that idea, while the given results do not differ that much from the results in Table 4.7. In the case when only the station originated outages has been considered, the inadequate load bus was the load connected to bus 6, while in this case the most inadequate load is 44

Chapter 4. System studies

the one connected to bus 4. As it has been mentioned previously, due to contribution of dependent outages the reliability results may varied extremely from the base case results. This is even valid for contribution of different kind of dependent outages. Comparing the results of common mode outages and the one for station originated, one can say that depend on the focus of the study different judgment over a system adequacy can be performed. So it is important to know what kind of analyses one prefers to run. Thus mentioning a priority for the contribution of the different outages is an important issue in reliability studies which may result in different judgments. In this case 762 failure combinations have been created and contributed in calculation of reliability indices. Table 4.14 presents a sample of the outage combination for this case study. Table 4.14. Sample outage combination for RBTS under peak load + Station outages

Outage Combination Event1: Outage Combination 60 Failed Element Protection tripping

Influenced load Influenced feeders/generation units

Event 2: Opening switch After 01:00:00 hour

Type of Element

Element name

Busbar Circuit Breaker Circuit Breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Load point 3 Load point 4 Generation unit

N36 CB-44 CB-13 CB-12 CB-33 CB-34 CB-35 CB-31 CB-14 CB-11 CB-25 CB-21 CB-43 CB-45 CB-25 L-3 L-4 GEN11

Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Disconnect switch

GEN13 GEN12 GEN14 GEN26 GEN23 GEN22 GEN27 GEN21 GEN25 GEN24 Disc-LIN2

Disconnect switch

Disc-LIN6

45

Chapter 4. System studies

Event 3: closing switch after 01:00:00 Involved elements

Disconnect switch Disconnect switch Circuit breaker

Disc-GEN 22 Disc-GEN 21 CB-14

Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Circuit breaker Load point 3 Generation unit

CB-25 CB-35 CB-11 CB-31 CB-21 CB-13 CB-12 L-3 GEN 11

Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit Generation unit

GEN 13 GEN 22 GEN 23 GEN 26 GEN 27 GEN 25 GEN 24

Influenced loads Influenced feeders/generation units

In case of simultaneous outage in node 36 and circuit breaker 4 in bus section 4, the mentioned circuit breaker in Table 4.14 are operating. Consequently the load points 3 and 4 and the mentioned generation units are affected. After these failures the corrective action is applied in order to alleviate the abnormality of the system. After an hour of delay in switching time, some of the components influenced by occurred faults will be restored. Load point 4, is the load center which is restored after the switching time, while load point 3, is the load which is restored after the repairing time of the failed component. Also, some of the generation units which have been influenced due to these faults can be return back to their normal operation just after the repairing time of the failed node and bus bar.

4.4. IEEE-RTS test system In this part, the simplified IEEE-RTS test system has been taken under consideration. The station configuration of this test system has been simplified to only one circuit breaker. Such simplification is not correct, while, as mentioned before, the station configuration are one of the most dominant contributor in reliability assessment of the power system. However, this test system was implemented in NEPLAN by considering the mentioned simplification i.e. the bus configuration has been disregarded and only one circuit breaker was considered. The results obtained from evaluation are shown in following sections. The priority order is arranged based on economical issues. The costs of energy not supplied are presented in Table 4.15 and the corresponding load priority is given in 4.16.

46

Chapter 4. System studies

Table 4.15. Cost of energy not supplied for IEEE-RTS [2]

Bus

Cost of energy not supplied

$ 1 2 3 4 5 6 7 8 9 10 13 14 15 16 18 19 20

kWh

6.20 4.89 5.30 5.62 6.11 5.50 5.41 5.40 2.30 4.14 5.39 3.41 3.01 3.54 3.75 2.29 3.60

Table 4.16. Priority of load curtailment for IEEE-RTS [2]

Priority order 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Bus 1 5 4 6 7 8 13 3 2 10 18 20 16 14 15 9 19

In NEPLAN it is possible to mention the priority up to level 10. Therefore, another simplification, regarding the priority of load curtailment is required. Load buses 10 to 17 mentioned in Table 4.16 are assumed to have the same priority in this analysis.

47

Chapter 4. System studies

For this system, the bus configurations have been disregarded. Therefore, it has been preferred to not go for the base case analysis and analyze the system for two modes. These modes are explained in following sections.

4.4.1. System studies incorporating station originated and common cause outages 4.4.1.1. Incorporating station originated and common mode outages.

In this study case both the station originated and common mode failure are considered in the assessment. The results are introduced in Tables 4.17 and 4.18. Table 4.17. Load point annualized indices for Modified-IEEE RTS incorporating the station originated + common mode outages.

L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8 L-9 L-10 L-13 L-14 L-15 L-16 L-18 L-19 L-20

Failure Frequency [1 yr ] 0.000 0.000 0.000 0.000321 0.000256 0.000814 0.000 0.000082 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000081 0.000039

Duration [h]

0.000 0.000 0.000 5.000 5.000 7.78 0.000 1.38 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3.1181 3.3143

Probability [min yr ]

0.000 0.000 0.000 0.09616 0.07684 0.3797 0.000 0.0068 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.015216 0.007788

48

Power not supplied [MW yr ] 0.000 0.000 0.000 0.026093 0.020006 0.1217 0.000 0.015 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.016193 0.0055

Energy not supplied [MWh yr ] 0.000 0.000 0.000 0.1304 0.100032 0.9468 0.000 0.02125 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.05049 0.01827

Chapter 4. System studies Table 4.18. Overall system annualized indices for Modified-IEEE RTS

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.000094 0.034266 6.096221 99.9993 0.001558 6.154671 0.575339 0.204889 1.267304

As it can be seen from the results presented in Table 4.17 the weakest points of the system are the load points 4, 5, 6, 8, 19 and 20. Load point 4, 5, 6 and 8 are the innermost bus sections, which are located in the southern region of the test system where there is a problem of deficit power. Also, there is no local generation unit available in these buses. Therefore, due to any outages in which the connections of these buses to the generation units are affected, the supply of the mentioned loads will be interrupted. Somehow, these bus sections are the most delicate buses within a system under study. On the other hand, there are two more weak load buses, which are located in the northern part of the system. Load buses 19 and 20 which are the innermost buses in the northern part are also exposed to interruptions. The main reason that these loads might be encountered any interruption can be described as a result of common mode outages of the transmission lines. These buses are connected to the generation buses via a transmission line on common right of way. 4.4.1.2.

Incorporating station originated outages.

In this study case only station originated outages are considered i.e. the circuit breakers assumed to be not reliable. Tables 4.19 and 4.20 show the results for this case study. Table 4.19. Load point annualized indices for Modified-IEEE RTS incorporating the station originated outages.

L-1 L-2 L-3 L-4 L-5 L-6 L-7 L-8

Failure Frequency [1 yr ] 0.000 0.000 0.000 0.000321 0.000256 0.000814 0.000 0.000

Duration [h]

Probability [min yr ]

0.000 0.000 0.000 5.000 5.000 7.78 0.000 0.000

0.000 0.000 0.000 0.09616 0.07684 0.3797 0.000 0.000 49

Power not supplied [MW yr ] 0.000 0.000 0.000 0.026093 0.020006 0.1217 0.000 0.000

Energy not supplied [MWh yr ] 0.000 0.000 0.000 0.1304 0.100032 0.9468 0.000 0.000

Chapter 4. System studies

L-9 L-10 L-13 L-14 L-15 L-16 L-18 L-19 L-20

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Table 4.20. Overall system annualized indices for Modified IEEE-RTS+ station originated outages

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.000082 0.032514 6.6256 99.99994 0.001390 6.6256 0.5527 0.1678 1.1772

As the results shown in Table 4.19 imply, when the common mode outages are disregarded in analysis, the load interruptions in buses 8, 19 and 20 are eliminated. These results confirm the explanation given in previous part for outages in buses 19 and 20. This also works for load bus 8. This bus is connected to the rest of the system through a single transmission lines and 2 transmission lines on common right of way. A comparatively large number of the components in this system disabled us to perform a right analysis over this system. However, there are several program, commercial and noncommercial, available which has the capability of evaluating such a large system. Some of these programs are introduced in Chapter 5. Consider that the commercial version of NEPLAN has the ability to perform assessment of such a large system. Due to several simplification applied to the presented composite power systems, validation of the approach was impossible, since the obtained results are completely different from the results presented in others research works by applying the same test systems. Therefore, a small test system, known as Birka system has been implemented in NEPLAN and the results has been compared to the results from RADPOW, in order to validate the approach. This test system is presented in up coming section.

50

Chapter 4. System studies

4.5. Birka system study Another test system which has been considered in this thesis work is a part of the Stockholm city distribution system, so-called as Birka system. In this work a part of the system has been chosen and implemented in NEPLAN. The result of the implementation has been validated by the results available from RADPOW.

4.5.1. Case study Birka system: Figure 4.6 shows the single line diagram of this system. Three main load points are fed from this system. Two 33-kV load points referred to Högalid station (HD) and Statens Järnvägar railway (SJ) and the station referred to Liljeholmen station (LHII). The more data regarding the system can be found in Appendix. Table 4.21. Load point annualized indices for Birka system.

L-SJ L-LH L-HD

Failure Frequency [1 yr ] 0.056 0.278 0.057

Duration [h]

1.727 1.691 1.704

Probability [min yr ]

5.762 28.207 5.867

Power not supplied [MW yr ] 0.044 0.214 0.044

Energy not supplied [MWh yr ] 0.200 0.362 0.077

Figure.4.9. Load point indices for Birka system.

As the results in Table 4.21 and Figure 4.7 show, the weakest point in the system is the load point belongs to Liljeholmen station. This is apparently logical. Considering the single line diagram of the system, it is obvious that the number of components which connect the Bredäng station to this station is more than the ones for other stations. Consequently the relevant failure rate will be increased. The unavailability of this load

51

Chapter 4. System studies

point is 28.207 [min yr ] which is not a large value, however, comparing to the unavailability of the other two stations within the system it is. Table 4.22. Overall system annualized indices for Birka system

System indices SAIFI [1 yr ] SAIDI [min yr ] CAIDI [h] ASAI (%) F [1 yr ] T (h) Pr [min yr ] P [MW yr ] W [MWh yr ]

0.062 6.286 1.703 99.999 0.308 1.757 32.463 1.578 2.687

Table 4.22 shows the indices for the overall system. As the results show the availability of the system is high and almost near to 100% (ASAI= 99.999%). This implies that the system is almost fully reliable. The system average interruption duration index is 6.286 [min yr ] which itself demonstrate the high reliability of the system. The comparison of the results to the one obtained from RADPOW has been made in order to be validated. Note that in this comparison, the term of “RADPOW” refers to analytical approach of this software and the term of “Simulation” refers to Simulation approach of this software. Anyhow, the results obtained from the mentioned programs, NEPLAN and RADPOW have been compared, and as the following table show, the results are almost the same. The differences are almost negligible. Table.4.23. Failure frequency index obtained from different approach.

Failure Frequency L-SJ L-LH L-HD

NEPLAN [1 yr ] 0.056 0.278 0.057

RADPOW [1 yr ] 0.057 0.279 0.058

Simulation [1 yr ] 0.057 0.279 0.058

Δ( NEP − RAD)

Δ( NEP − Sim)

0.001 0.001 0.001

0.001 0.001 0.001

Table.4.24. Unavailability index obtained from different approach

Unavailability L-SJ L-LH L-HD

NEPLAN [h yr ] 0.0964 0.470 0.0977

RADPOW [h yr ] 0.097 0.471 0.098

52

Simulation [h yr ] 0.097 0.471 0.098

Δ( NEP − RAD) Δ ( NEP − Sim) 0.0006 0.001 0.0003

0.0006 0.001 0.0003

Chapter 4. System studies

Obtaining almost the same results from different approaches shows the correctness of the approach and consequently the validity of the results. Even though, the implementation of the composite power systems have not been performed completely and the results obtained from the analyses were extremely different from the reality, but the approach has been validated by implementing the comparatively small system. And this is a valuable result to know that the approach is correct and it can be used to provide the precise results regardless of various assumptions that have been assigned for its development.

53

Chapter 5. Alternative reliability tools

5. Alternative Reliability Tools

5.1. Introduction Various software packages applied for composite power systems and/or transmission systems reliability evaluation are available. These programs have the capability of evaluating the system either from adequacy point of view or security standpoint. The software used for reliability evaluation of generation unit often developed as production models using Monte Carlo techniques, whilst transmission software developed mainly using Markov process [18]. In this section it has been tried to introduce and describe some of these software tools.

54

Chapter 5. Alternative reliability tools

5.2. Composite power reliability tools 5.2.1. MECORE The MECORE software is the Monte Carlo based program used for composite power system reliability evaluation developed by power research group in university of Saskatchewan and enhanced at BC hydro. The result of the evaluation is presented in form of reliability indices both for individual load point and the overall system. This software also has the capability of providing the unreliability cost. MECORE is base on a combination of state sampling (Monte Carlo simulation) and enumeration techniques (analytical approach). The state sampling techniques is used to simulate system component states and to calculate annualized indices at the system peak load level. A hybrid method utilizing an enumeration approach for aggregated load studies is used to calculate annual indices using an annual load curve [4], [21], [22], [23]. This software has the capability to handle up to 1000 buses and 2000 branches. Brief description of the system capabilities are given in this section. 1) Failure modes: - Independent failures of generators, lines and transformers - Common cause outages of transmission lines - Generating unit derating states 2) Failure criteria: - capacity deficiency - Line overload - System separation- load loss - Bus isolation- load loss 3) Load model: - Annual, seasonal and monthly load curve - Multi-step models - Bus load proportional scaling and flat level model 4) Probability indices: - System and bus indices - Annualized and monthly/ seasonal/ annual indices - Basic and IEEE proposed indices Basic indices: ¾ Probability of load curtailment (PLC):

PLC = ∑ Pi i∈s

55

Chapter 5. Alternative reliability tools

where Pi is the probability of the system state i and S is the set of all system states associated with load curtailment. ¾ Expected number of load curtailment (ENLC) [ occ. / yr ]:

ENLC = ∑ Fi i∈S

where Fi is the system state frequency. ¾ Expected duration of load curtailment (EDLC) [ hrs / yr ]: EDLC = PLC ∗ 8760 ¾ Average duration of load curtailment (ADLC) [ hrs / disturbance ]: ADLC = EDLC EFLC

¾ Expected load curtailment (ELC) [ MW / yr ]:

ELC = ∑ C i Fi i∈S

where Ci is the load curtailment of system state i . ¾ Expected demand not supplied (EDNS) [ MW ]:

EDNS = ∑ C i Pi i∈S

¾ Expected energy not supplied (EENS) [ MWh / yr ]:

EENS = ∑ C i Fi Di i∈S

where Di is the duration of system state i . ¾ Expected damage cost (EDC) [ k $ / yr ]:

EDCL = ∑ C i Fi DiW i∈S

IEEE proposed indices: ¾ Bulk power interruption index (BPII)[ MW MW − yr ]:

BPII =

∑ C ⋅F i

i

i

L

where L is the system peak load in MW.

56

Chapter 5. Alternative reliability tools

¾ Bulk power/energy curtailment index (BPECI)[ MWh MW − yr ]:

EENS L ¾ Bulk power supply average MW curtailment index (BPACI) [ MW Disturbance ]:

EPECI =

BPACI =

ELC EFLC

where EFLC is expected frequency of load curtailment and can be obtained from equation : EFLC = ∑ ( Fi − f i )

[occ

yr ]

i∈S

¾ Modified bulk power curtailment (MBECI) [ MW MW − yr ]:

EDNS L ¾ Severity index (SI) [ system. min yr ]:

MBECI =

SI = BPECI × 60

5) Linear programming optimization model. MECORE program utilizes a linear programming Optimal Power Flow model to reschedule generation, alleviate line overloads and avoid load curtailment if possible or minimize total load curtailments if unavoidable

5.2.2. COMREL As it has been mentioned previously, two different approaches, Enumeration approach (Analytical) and State sampling (Monte Carlo simulation), are applied for reliability evaluation and consequently development of relevant computer software packages. A computer program, COMREL which is the abbreviation of Composite system Reliability, is the analytical based techniques propagated by power system research group in university of Saskatchewan. This program uses the contingency enumeration techniques for the evaluation of composite systems. This program has the capability of evaluating the system considering independent outages, common mode outages and station originated outages. As it has been cited before network solutions are important feature in reliability evaluation. COMREL is equipped with network solution technique such as AC load flow, DC load flow.

57

Chapter 5. Alternative reliability tools

Figure 5.1 shows the basic structure of COMREL program.

Base Case system Analysis Select contingency State Evaluate Contingency Problem NO

Yes Remedial Action

Problem NO

Yes Accumulate adequecy indices

Figure 5.1.Structure of COMREL program

Brief description of the program capabilities are given in this section: 1) Failure modes: - Independent failures - Common cause outages - Station originated failures 2) Failure criteria: - Lack of sufficient generation in the system to meet load demands - Interruption of continuity of power supply to a load point - Overload of transmission facilities - Violation of bus voltage - Generating unit MVAR violation 3) Network analysis - Network flow - AC load flow - DC load flow

58

Chapter 5. Alternative reliability tools

4) Contingency and ranking - Predetermined contingency level (4 simultaneous generation outages, 3 simultaneous transmission, and 3 transmission and generation outages) - Ranking (Credible events) - Frequency cut off (Neglecting the contingency with frequency of occurrence) 5) Remedial action - Generation rescheduling - Handling the bus isolation - Line overload alleviation - Correction generation unit MVAR unit - Correction of bus voltage limit - Load curtailment 6) Load curtailment policies - Firm load - Curtailable load 7) Load model: - Annual, seasonal and monthly load curve - Multi-step models 8) Reliability indices: - Load point indices - System indices Load point indices: ¾ ¾ ¾ ¾ ¾ ¾

Probability of failure Frequency of failure Expected number of load curtailment Expected load curtailed Expected energy not supplied Expected duration of load curtailment

Overall system indices: ¾ ¾ ¾ ¾

Bulk power supply average MW curtailment index (BPSACI) Bulk power interruption index (BPII) Bulk power energy curtailment index (BPECI) Modified bulk power energy curtailment index (MBPECI)

The calculations of these indices are indicated in [24].

59

Chapter 5. Alternative reliability tools

5.3. Transmission/distribution reliability tools 5.3.1. RADPOW [13], [25] RADPOW which is the abbreviation of Reliability Assessment of Distribution Power System has been developed at the school of electrical engineering, KTH for reliability evaluation of distribution systems. The first version of this tool developed based on analytical approach. Recently the module based on simulation approach has been added to this software package. Figure 5.2 illustrates the overall methodology used in this tool.

System data

Network model

Assign each LPs the events that lead to failure for that LP Analytical method

Simulation method

Calculate the reliability indices for each LP based on predefined formulas

Make a large number of random experiments to see how these affect the load point

Calculate the reliability for the system Figure.5.2. Flowchart for the analytical and simulation methods used in RADPOW [25]

Figure 5.3 shows the algorithm used in analytical approach of this software.

60

Chapter 5. Alternative reliability tools

Intput data

For each load point

For each failure mode

Evaluate basic reliability indices

λi , U i , ri , LOEi

Evaluate load point indices

λLP = ∑ λi , U LP = ∑U i ,

rLP = U LP λLP , LOE LP = ∑ LOEi

Evaluating the systme indices

∑λ ⋅ N ∑N ∑U ⋅ N CAIDI = ∑λ ⋅ N SAIFI =

LP

LP

∑U ⋅ N ∑N ∑ LOE , AENS = ∑N

, SAIDI =

LP

LP

LP

LP

LP

LP

LP

LP

LP

LP

Output data Figure. 5.3. Algorithm for the evaluation of the reliability indices in RADPOW [13]

Note that λ [occ yr ] represents the expected failure rate, r [h f ] represents the average outage duration, U [h yr ] illustrates annual expected outage time and LOE [kWh yr ] shows the average loss of energy. Detailed explanation on simulation approach of this tool can be found in [25].

61

Chapter 5. Alternative reliability tools

5.3.2. VERA and PROCOSE VERA (Value-Based Evaluation and System Reliability Assessment) and PROCOSE (Probabilistic Composite System Evaluation) programs are used in Ontario hydro. VERA was designed to calculate customer interruption costs and delivery point reliability indices. PROCOSE was developed to examine the impact of other generating resources that are available on a system, in mitigating any load cuts required when transmission elements are out –of-service. But it does not consider the impact of transmission grid configuration, nor does it examine every possible contingency condition [21].

5.3.3. PSS/TPLAN PSS/TPLAN is a commercial software package designed for reliability evaluation of transmission system which has been developed by SIEMENS PTI (power transmission and distribution). The reliability evaluation criteria in this program is completely different from the ones introduces previously. The previous software packages provide the adequacy indices, while PSS/TPLAN is analyzing the system from security point of view, in which the capability of the system to respond to the disturbances is assessed. Figure 5.4 shows the algorithm of this tool. Base Case System Analysis Select Contingency State Evaluate Contingency Classifying the Results NO

Problem Yes

Local Trouble

System Trouble

Remedial Action

NO

Problem

Yes Reliability Indices Figure 5.4.Structure of PSS/TPLAN program [26]

62

Chapter 5. Alternative reliability tools

Brief description of the program capabilities are given in this section: 1) Failure criteria: -

Local trouble ¾ ¾ ¾ ¾ ¾

-

Overload Low voltage High voltage Islanding Load shed

System trouble ¾ Voltage collapse ¾ Cascading outages

2) Network analysis - AC load flow - DC load flow 3) Contingency ranking -

Overload ranking Voltage trouble ranking Voltage collapse ranking

4) Remedial action - Preventive action for base case ¾ Adjusting the generators’ real power ¾ Phase shifter angle ¾ Load shedding

-

Security constrained preventive action ¾ Adjusting the generators’ real power ¾ Phase shifter angle ¾ Load shedding

5) Load curtailment policies - Firm load - Curtailable load 6) Load model: - Peak load - Multi-step models

63

Chapter 5. Alternative reliability tools

7) Reliability indices: - Probabilistic system trouble indices ¾ Frequency and duration of load shed, overload, low and high voltage and voltage collapse ¾ Bulk power interruption index, [occ yr ] BPII =

∑F ⋅L i

i

Lt

Where Fi is event frequency , Li is load lost and Lt is total load of the system ¾ Bulk energy curtailment index [h yr ] BECI = -

Energy Curtailed No min al Load

Costumer impact indices ¾ Un-served energy

8) Cost of unreliability for individual buses [$ yr ] : N

Cost = ∑ Fi ⋅ i

$ ⋅ Li ⋅ 8760 MWh

Where, Fi is the frequency of loss of load caused by i th contingency. [$ MWh] is the cost point corresponding to the duration of the loss of load Li is the load curtailed on special bus due to i th contingency

5.3.4. CREAM The program CREAM is the abbreviation of Composite Reliability Assessment by Monte Carlo. This program has been developed by Electric power research institute (EPRI). The program utilizes Monte Carlo sampling methodology to randomly select system conditions from the conditions probability distribution [27].

5.4. Tools applied for HVDC system evaluation Nowadays, due deregulation of the power systems by employing new techniques such as FACTS and HVDC system, many software tools which has the capability of evaluating such systems are developed. Some of these programs which are used in BC hydro in Canada for HVDC evaluation are presented in this section. This part is taken from [21].

64

Chapter 5. Alternative reliability tools

1) SPARE: This program has the capability of not only calculating the common reliability indices but also unavailability due to aging failures for each component. Input data for this case is the mean life and deviation of each component. The aging failures can be modeled using Weibull or Normal distribution. 2) NETREL: This tool was developed to calculate availability/unavailability of a network consisting of components in parallel and/or series. This program also provides the average capacity for a given HVDC configuration. The results from NETREL take into account both aging related and repairable failure modes producing a comprehensive reliability picture of HVDC poles that are in the endof-life stage. 3) MCGSR: which is the abbreviation of Monte Carlo Generation System Reliability is used by means of generating unit reliability evaluation tools. The presented software packages are not the commercial one and they are patented by British Columbia Hydro (BC Hydro), therefore the detailed information about the structure of the programs is not available.

65

6.Closure

6. Closure

6.1. Conclusion The results obtained from reliability studies, provide an appropriate benchmark for assessing the system performance and identifying the weak point of the system. Verifying the weak point of the system may make the planners to increase the investment at a certain load point during the planning phase and consequently reduce the further costs due to supply interruption in operation stage. The results illustrated in chapter 4, not only showed the weak points of the system, but also indicated that depends on the assumptions of the studies the adequacy of the system at each individual load points may vary. An important result from evaluating the system in different modes is that the station configuration and its components have a significant impact on the final results. Therefore, it is not rational to ignore them in reliability

66

6.Closure

evaluation and simplify the stations to the single bus bars which are generally used in the conventional load flow analysis. The principal aim of this work was to study the reliability evaluation of the power system with the main focus on the transmission system and utilization of the NEPLAN tool for such evaluation. The university version of NEPLAN is not proper software for studying a comparatively large transmission system including many nodes such as IEEE-RTS. However, it can be more appropriate tool for distribution systems. The commercial version of this software as well as the other tools introduced in Chapter 5 could be proper software for assessing a comparatively large system.

6.2. Future work As mentioned before, the main focus in the long term research work is to investigate the transmission system reliability, where new technologies such as HVDC and FACTS are employed in the system to enhance the efficiency of the overall power system. In this work the traditional (AC) power system has been taken under consideration in order to build up knowledge over the reliability of such system. Now as a next stage in this work, it is of interest to modify the test systems and include the complementary link e.g. a HVDC link and examine the reliability of a DC system. Comparison of the results for the modified system to the one illustrated in this assessment can provide a basic knowledge over the performances of these special AC and DC systems, but still can not provide a general idea for general power systems i.e. results of such comparison may not work for all kind of AC and DC systems. In this work the failure rates and repair time have been considered to be constant during the evaluation, but this is not a right assumption while an environmental impact has been disregarded. Environmental conditions have significant impacts on the reliability of a transmission system; especially overhead lines are more exposed to be damaged due to fluctuation in weather condition. Therefore, such evaluation can come as a follow up work of this thesis. So, developing new techniques in which the realistic environmental conditions can be modeled are required. One of the basic ideas in this work was to study the possible approaches that can be applied for reliability assessment of the power systems. In Chapters 2 and 3 the analytical approach and the applicable commercial software which is based on enumeration techniques (Analytical approach) were explained. Although the analytical approach is a fast and an appropriate technique in reliability evaluation, yet the simulation approach can provide more accurate results. However, such evaluation requires a comparatively longer computational time. Therefore, as a continuation of this thesis it might be of interest to study the approach based on simulation and state sampling (Monte Carlo simulation).

67

References

References 1. Electric power transmission engineering, Turan Gönen, Wiley-Interscience

Publication, 1988. 2. Xiaosu Tang, Consideration in bulk system reliability assessment, Master thesis,

University of Saskatchewan, 2000. 3. Efficient operation and planning of Power systems, Lenart Söder, Mikael Amelin,

Royal institute of Technology, Stockholm, Sweden, 2006. 4. Ran Mo, Deterministic/Probabilistic evaluation in composite systems, Master 5. 6. 7.

8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

18. 19.

20. 21.

22.

thesis, University of Saskatchewan, October 2003. Reliability Evaluation of Power system, Roy Billinton, Ronald N. Allan. Reliability Assessment of Large Electric Power System, Roy Billinton, Ronald N. Allan, Kluwer Academic Publishers, 1988. Lina Bertling, Pre-study on reliability modeling and assessment for complex power system with special focus on HVDC, KTH School of Electrical Engineering, 2005. Wei Zhang, Reliability Evaluation of Bulk Power Systems using analytical and equivalent approaches, Doctoral Dissertation, University of Saskatchewan, 1998. Fang Yang, Sun Wook Kang, George Stefopoulos, Comprehensive power system reliability assessment, Final project, Georgia Institute of Technology, April 2005. Reliability evaluation of engineering system, Roy Billinton, Ronald N. Allan Roy Billinton, W. Zhang, Algorithm for failure frequency and duration assessment of composite power systems, March 1998. R. Billinton, N.D.Reppen, M.P. Phavaraju, Requirements for composite system reliability evaluation models, IEEE. 1998. Lina Bertling, Reliability Centered Maintenance for Electric Power Distribution Systems, Doctoral Dissertation, Royal Institute of Technology, 2002. www.neplan.ch Neplan reliability, Math Bollen, STRI AB, Ludvika, Sweden, March, 2006. Neplan User’s guide. A reliability test system for educational purposes- Basic data, Power system research group in university of Saskatchewan, IEEE transactions on power systems, Vol. 4, No 3, August 1989. The IEEE reliability test system-1996, IEEE transactions on power systems, Vol. 14, No 3, August 1999. R. Nighot, R. Billinton, Reliability evaluation of the IEEE-RTS incorporating station related outages, Power system research group, University of Saskatchewan. D.S. Arentz, M.Th. Schilling, M. B. Coutto Folho, J.C.Souza, Nodal Reliability, June 2002. Michael Emmerton, Don Somatilake, Probabilistic Transmission Planning, Document reference: p:\pba\150251, prepared for Electricity Commission, August 2004. Yi Gao, Adequacy assessment of electric power systems incorporating wind and solar energy, Master Thesis, University of Saskatchewan, January 2006.

68

References

23. Yifeng Li, Bulk system reliability evaluation in a deregulated power industry,

Master thesis, university of Saskatchewan, December 2003. 24. Steve Kwaku Adzanu, Reliability assessment of non-utility generation and

25.

26. 27.

28.

29.

30.

31.

demand-side management in composite power system, PhD Thesis, University of Saskatchewan, Fall 1998. Johan Setréus, Development of a simulation module for the reliability computer program RADPOW, Master thesis, KTH School of Electrical Engineering, Stockholm, Sweden, 2006. www.pti-us.net M. J. Bashir, T. C. Cheng, A.S. A. Farag, Comparison of Monte Carlo Simulation and State Enumeration Bases Adequacy Programs: CREAM and COMREL, IEEE transaction, 1996. Janak Raj Acharya, Weather effect considerations in reliability evaluation of electrical transmission and distribution systems, Master thesis, University of Saskatchewan, August 2005. R. Billinton, A. Sankarakrishnan, Adequacy assessment of composite power systems with HVDC link using Monte Carlo simulation, IEEE transactions on power systems, August 1994 Hua Yang, Incorporating station related maintenance and aging outages in composite system reliability evaluation, Master thesis, University of Saskatchewan, September 2005. Sastry Kuruganty, HVDC transmission system models for power system reliability evaluation, IEEE CAT, 1995.

69

Appendix

Appendix A. Sample test system Load data:

Load point no. System 5 6 Load point no.

Total no. of customers 180 100 80

Industrial 0.0 0.0

4.00 5.00

Load point no.

Total reactive power per customer 2.00 2.50

Commercial 0.2 0.2

Residential 0.8 0.8

Customers

Total active power per customer

5 6

5 6

Customers

Industrial 0.0 0.0

Commercial 0.3 0.3

Residential 0.7 0.7

Customers Industrial 0.0 0.0

Commercial 0.3 0.3

Residential 0.7 0.7

Elements reliability data:

Element Busbar Cir.Breaker Transformer Disc.Switch

Failure rate Permanent Active 0.001 0.001 0.02 0.02 0.015 0.015 0.002 0.002

Permanent 2.0 24 15 4.0

A

Duration Maintenance 1.0 1.0 1.0 1.0

Switching 0.0 0.0 0.0 0.0

Appendix

B. IEEE-RTS Bus Number

101 102 103 104 105 106 107 108 109 110 113 114 115 116 118 119 120

Bus no Bus type Bus no Bus type

Bus load data Load MW MVar

Bus Load % of system load 3.8 3.4 6.3 2.6 2.5 4.8 4.4 6.0 6.1 6.8 9.3 6.8 11.1 3.5 11.7 6.4 4.5 Total: 100,0

108 97 180 74 71 136 125 171 175 195 265 194 317 100 333 181 128 2850

If Peak load 10% higher MW MVar

22 20 37 15 14 28 25 35 36 40 54 39 64 20 68 37 26 580

118.8 106.7 198 81.4 78.1 149.6 137.5 188.1 192.5 214.5 291.5 213.4 348.7 110 366.3 199.1 140.8 3135

24.2 22 40.7 16.5 15.4 30.8 27.5 38.5 39.6 44 59.4 42.9 70.4 22 74.8 40.7 28.6 638

101

102

103

IEEE-RTS-96 Bus data, area A 104 105 106 107 108 109

PU

PU

PQ

PQ

PQ

PQ

PU

PQ

PQ

PQ

PQ

PQ

113

114

115

116

117

118

119

120

121

122

123

124

Slack PU

PU

PU

PQ

PU

PQ

PQ

PU

PU

PU

PQ

B

110

111

112

Appendix

Bus ID 101 101 101 101 102 102 102 102 107 107 107 113 113 113 114 115 115 115 115 115 115 116 118 121 122 122 122 122 122 122 123 123 123

Data for generators at each bus PG QG Unit type MW MVAR U20 10 0 U20 10 0 U76 76 14.1 U76 76 14.1 U20 10 0 U20 10 0 U76 76 14.1 U76 76 14.1 U100 80 17.2 U100 80 17.2 U100 80 17.2 U197 95.1 40.7 U197 95.1 40.7 U197 95.1 40.7 Sync Cond 0 13.7 U12 12 0 U12 12 0 U12 12 0 U12 12 0 U12 12 0 U155 155 0.05 U155 155 0.05 U400 400 137.4 U400 400 137.4 U50 50 -4.96 U50 50 -4.96 U50 50 -4.96 U50 50 -4.96 U50 50 -4.96 U50 50 -4.96 U155 155 31.79 U155 155 31.79 U350 350 71.78

C

Q max MVAR 10 10 30 30 10 10 30 30 60 60 60 80 80 80 200 6 6 6 6 6 80 80 200 200 16 16 16 16 16 16 80 80 150

Q min MVAR 0 0 -25 -25 0 0 -25 -25 0 0 0 0 0 0 -50 0 0 0 0 0 -50 -50 -50 -50 -10 -10 -10 -10 -10 -10 -50 -50 -25

Appendix

From

To

L

BUS

BUS

km

1 101 101 102 102 103 103 104 105 106 107 107 108 108 109 109 110 110 111 111 112 112 113 113 114 115 115 115 115 116 116 117 117 118 118 119 119 120 120 121

102 103 105 104 106 109 124 109 110 110 108 203 109 110 111 112 111 112 113 114 113 123 123 215 116 116 121 121 124 117 119 118 122 121 121 120 120 123 123 122

4.827 88.495 35.4 53.097 80.45 49.879 0.0 43.443 37.007 25.744 25.744 67.578 69.187 69.187 0.0 0.0 0.0 0.0 53.097 46.661 53.097 107.803 96.54 83.668 43.443 19.308 54.706 54.706 57.924 28.962 25.744 16.09 117.457 28.962 28.962 44.2475 44.2475 24.13 24.13 75.623

Data for Transmission system Per outage Tran R X rate outage rate Dur. PU λP λt Dur. PU

0.24 0.51 0.33 0.39 0.48 0.38 0.02 0.36 0.34 0.33 0.03 0.44 0.44 0.44 0.02 0.02 0.02 0.02 0.40 0.39 0.4 0.52 0.49 0.47 0.38 0.33 0.41 0.41 0.41 0.35 0.34 0.32 0.54 0.35 0.35 0.38 0.38 0.34 0.34 0.45

16 10 10 10 10 10 768 10 10 35 10 10 10 10 768 768 768 768 11 11 11 11 11 11 11 11 11 11 111 11 11 11 11 11 11 11 11 11 11 11

0.0 2.9 1.2 1.7 2.6 1.6 0.0 1.4 1.2 0.0 0.8 202 2.3 2.3 0.0 0.0 0.0 0.0 0.8 0.7 0.8 1.6 1.5 1.3 0.7 0.3 0.8 0.8 0.9 0.4 0.4 0.2 1.8 0.4 0.4 0.7 0.7 0.4 0.4 1.2

0.003 0.055 0.022 0.033 0.050 0.031 0.002 0.027 0.023 0.014 0.016 0.042 0.043 0.043 0.002 0.002 0.002 0.002 0.006 0.005 0.006 0.012 0.011 0.010 0.005 0.002 0.006 0.006 0.007 0.003 0.003 0.002 0.014 0.003 0.003 0.005 0.005 0.003 0.003 0.009

D

B PU

0.014 0.461 0.211 0.057 0.085 0.023 0.127 0.034 0.192 0.052 0.119 0.032 0.084 0.0 0.104 0.028 0.088 0.024 0.061 2.459 0.061 20.017 0.161 1.044 0.165 0.045 0.165 0.045 0.084 0.0 0.084 0.0 0.084 0.0 0.084 0.0 0.048 0.100 0.042 0.088 0.048 0.100 0.097 0.203 0.087 0.182 0.075 0.158 0.059 0.02 0.017 0.036 0.049 0.103 0.049 0.103 0.052 0.109 0.026 0.055 0.023 0.049 0.014 0.030 0.105 0.221 0.026 0.055 0.026 0.055 0.040 0.083 0.040 0.083 0.022 0.046 0.022 0.046 0.068 0.142

Continuous rating MVA 175 175 175 175 175 175 400 175 175 175 175 175 175 175 400 400 400 400 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500

Appendix

Unit group

Unit size

Generator Data Unit type Forced MTTF Outage (Hour)

MTTR (Hour)

Scheduled Maintenance ( wks ) year

U12 U20 U50 U76 U100 U155 U197 U350 U400

12 20 50 76 100 155 197 350 400

Oil/Steam Oil/CT Hydro Coal/Steam Oil/Steam Coal/Steam Oil/Steam Coal/Steam Nuclear

0.02 0.10 0.01 0.02 0.04 0.04 0.05 0.08 0.12

2940 450 1960 1960 1200 960 950 1150 1100

60 50 20 40 50 40 50 100 150

2 2 2 3 3 4 4 5 6

C. RBTS Bus no. 1 2 3 4 5 6

Load Active Reactive 0.00 0.020 0.85 0.40 0.20 0.020

From Bus

To bus

1 2 1 3 3 1 2 4 5

3 4 2 4 5 3 4 5 6

0.00 0.00 0.00 0.00 0.00 0.00

Bus data for RBTS PG Q

Qmax 0.50 0.75 0.00 0.00 0.00 0.00

1.00 1.20 0.00 0.00 0.00 0.00

V

Qmin -0.40 -0.40 0.00 0.00 0.00 0.00

Line data for RBTS R X Current rating 0.0342 0.18 0.85 0.1140 0.60 0.71 0.0912 0.48 0.71 0.0228 0.12 0.71 0.0228 0.12 0.71 0.0342 0.18 0.85 0.1140 0.60 0.71 0.0228 0.12 0.71 0.0228 0.12 0.71

E

Vmax 1.05 1.05 1.05 1.05 1.05 1.05

Vmin 0.97 0.97 0.97 0.97 0.97 0.97

Failure per year 1.50 5.00 4.00 1.00 1.00 1.50 5.00 1.00 1.00

Repair time 10.0 10.0 10.0 10.0 10.0 10.0 10.0 10.0 10.0

Appendix

Generator data for RBTS Rating (MW) Failure per year 40.0 6.00 40.0 6.00 10.0 4.00 20.0 5.00 5.00 2.00 5.00 2.00 40.0 3.00 20.0 2.40 20.0 2.40 20.0 2.40 20.0 2.40

Bus no. 1 1 1 1 2 2 2 2 2 2 2

Repair time (hours) 45.0 45.0 45.0 45.0 45.0 45.0 60.0 55.0 55.0 55.0 55.0

D: Birka Nät Load data:

Load point no. System LHII (35) HD (48) SJ (35) Load point no.

Total no. of customers 180 447 23400 1

Industrial 0.25 0.1 0

1.7203.00 0.9829 0.8

Load point no.

Total reactive power per customer 0.00 0.00 0.00

Commercial 0.25 0.1 1

Residential 0.5 0.8 0

Customers

Total active power per customer

LHII (35) HD (48) SJ (35)

LHII (35) HD (48) SJ (35)

Customers

Industrial 0.4 0.2 0

Commercial 0.2 0.1 1

Residential 0.4 0.7 0

Customers Industrial 0.00 0.00 0.00

F

Commercial 0.00 0.00 0.00

Residential 0.00 0.00 0.00

Appendix

Elements’ ID number and Type:

ID no Type

ID no Type ID no Type

1

2

3

4

5

6

7

8

9

10

BU 220

BR 110

TR 220

BR 110

CA 110a

TR 110

BR 33

BR 110

TR 220

BR 110

11

12

13

14

15

16

17

18

19

20

CA 110b 21

TR 110 22

BR 33 23

BU 220 24

BR 33 25

CALH 33 26

TR 33 27

BR 11 28

BR 33 29

CALH 33 30

TR 33

BR 11

BR 33

CALH 33

TR 33

BR 11

BU 11

BR 11

BUS D

CALH 11

32

33

34

35

36

37

38

39

40

BUS D 42

TR 11 43

FUSE

BUS D 46

BR 33 47

CAHDa

44

BU 04 45

BR 33 49

BR 33 50

BR 33 52

BR 33 53

CAHD c 54

BR 33 55

BUS D 56

BR 33 57

BU 220 58

BUS D

BR 33

BR 33

BR 33

CA SJb

BR 33

BUS D

BR 33

BU 220

ID 31 no Type CALH 11 ID 41 no Type CAHD b ID 51 no Type CA Sja

48

Elements reliability data:

Element Bus D BU220 BU11 BU04 BR110 BR33 BR11 CA110a CA110b CALH33

Failure rate Permanent Active 0.000 0.000 0.00964 0.00964 0.00867 0.00867 0.000 0.000 0.00870 0.00870 0.00089 0.00089 0.00243 0.00243 0.07012 0.07012 0.07031 0.07031 0.00028 0.00028

Permanent 0.0 1.0 1.0 0.0 24 24 24 168 168 48

G

Duration Maintenance 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Switching 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

Appendix

CAHDa CAHDb CAHDc CASJa CASJb CALH11 FUSE TR220 TR110 TR33 TR11

0.02291 0.02285 0.02265 0.00863 0.00837 0.10069 0.01340 0.02610 0.02050 0.01989 0.00331

0.02291 0.02285 0.02265 0.00863 0.00837 0.10069 0.01340 0.02610 0.02050 0.01989 0.00331

48 48 48 48 48 6 4 24 24 24 24

H

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0