RENEWABLE ENERGY BASED POWER GENERATION FOR STAND-ALONE APPLICATIONS: A REVIEW Anurag Chauhan1
R.P.Saini Alternate Hydro Energy Centre, Indian Institute of Technology Roorkee, India Email:
[email protected]
Abstract - Small scale power generation near consumer’s premises has received greater attention in recent years for use in remote and rural communities due to the cost and complexity involved in the grid extension. It is therefore, suitable stand-alone systems using locally available renewable energy sources have become a preferred option. However, there are two approaches that are used to harness available renewable energy (RE) sources namely, integrated systems and hybrid systems. In the present paper, a suitable methodology and an extensive review on unit sizing, cost optimization, and energy flow management of renewable energy system have been discussed. Keywords - Small scale power generation, integrated, hybrid, unit sizing, cost optimization, energy flow management.
I. INTRODUCTION The scarcity of conventional energy resources, rise in the fuel prices and concern for the environment from the burning of fossil fuels has made power generation from conventional energy sources unsustainable and unviable. It is envisaged that supply-demand gap will continue to rise exponentially unless it is met by some other means of power generation. Inaccessibility of the grid power to the remote places and the lack of rural electrification have prompted for alternative sources of energy. The non-conventional energy resources, such as water, wind, sun, and biomass, have become better alternatives for conventional energy resources. From socioeconomic and environmental view points, exploitation of renewable energy enhances supply security, provides local solutions, lowers environmental impacts, offers sustainable energy development and provides job opportunities. In developing country like India, most of the population lives in isolated rural areas and electrification in decentralized mode by nearby available renewable energy resources will benefit the overall development of these areas. The locally available renewable energy resources in remote rural
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areas mainly include micro hydro power (MHP), biomass, wind and solar photo voltaic (SPV) [1]. II.
APPROACHES TO HARNESS RENEWABLE ENERGY SOURCES Basically there are two approaches that are used to harness available renewable energy sources. Two approaches namely, integrated renewable energy systems and hybrid systems [2]. A. Integrated Renewable Energy System: System utilizing two or more locally available renewable energy resources (such as small hydro, solar, wind, biomass etc.) in order to supply electricity in local villages is known as Integrated Renewable Energy System (IRES). Examples of IRES are integrated biomasspicohydel-solar-wind system, integrated biomasssolar-wind system etc. A typical example of wind/SPV/biomass/microhydro based IRES is shown in Figure 1. Control system is the heart of IRES which controls the flow of energy from resources to load with the help of energy storage devices. B. Hybrid Renewable Energy System: System combines two or more renewable energy resources with some conventional option (diesel or petrol powered generator, thermal plant) in order to fulfil the demand of local villages situated at remote site is termed as Hybrid Renewable Energy System (HRES). Most of the hybrid systems use diesel generator (DG) as conventional option [3]. Few examples of HRES are PV-wind-diesel generator HRES, wind-diesel generator HRES, PVwind-fuel cell HRES, biomass-wind-fuel cell system etc. A suitable schematic HRES is shown in Figure 2. The presented HRES includes diesel generator as conventional option with renewable energy resources to supply energy to load.
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• • • •
Fig 1. Schematic of wind/SPV/biomass/microhydro based IRES
Fig 2. Schematic of a SPV/wind/diesel generator based HRES
III. METHODOLOGY Following steps are taken for the IRES based power generation for the electrification of remote site villages [4, 5] 1) Demand Assessment: Find the load demand using accurate load forecasting of remote villages. Load assessment can be done by taking the interview of local bodies, school teachers etc. The following factors may be considered during the electrical load survey: • Demand for street lighting, • Number of schools, health centres, commercial establishment, and their energy demand, • Number of villages, houses, • Population • Number of small industries with energy requirement, • Miscellaneous demand. 2) Resource Assessment: Calculate potential available in solar, wind, MHP, Biomass and other renewable energy resources using meteorological data available. 3) Constraints/barriers: • Annual electricity demand,
Potential, Reliability, Emission, Employment.
4) After doing this, one approach is adopted out of following two approaches: a) Approach I (Integrated Approach): In the first approach, demand is fulfilled by one or combination of more than one renewable energy resources. • Stand alone SPV with battery storage, • Stand alone Wind with battery storage, • SPV-Wind with battery storage, • SPV-Wind-MHP with battery storage, • SPV-Wind-MHP-Biomass with battery storage, b) Approach II (Hybrid Approach): In this approach, Demand is fulfilled by hybrid approach. Demand can be met by combination of renewable energy resources with conventional sources (diesel generator set, thermal plant). • PV/wind/diesel generator HRES, • wind/diesel generator HRES, • PV/wind/fuel cell HRES, • Biomass/wind/fuel cell HRES 5) Optimize the selected system configuration with suitable technique. IV. UNIT SIZING & COST OPTIMIZATION Unit sizing and cost optimization is basically a method of determining the size of the integrated/hybrid system components by minimizing the system cost while maintaining system reliability. Optimum resource management is necessary to achieve acceptable cost and reliability level in the integrated/hybrid generation system. Over sizing the system components will enhance the system cost whereas under sizing can lead to failure of power supply. In consequence, sufficient care should be taken to design a reliable system at minimum cost. Sizing techniques can be classified into conventional and artificial techniques and shown in the Figure 3.
Fig 3. Classification of conventional techniques
A. Conventional Technique: These techniques uses availability of weather data irradiance, clearness index and wind speed. This technique is classified on the basis of concept of
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energy balance and reliability of supply [6] and shown in Figure 3. Conventional sizing methods give accurate results when actual weather data is available. Li et al. [7] developed an algorithm to determine the cost effective system configuration using an iterative technique based on energy balance. Zhou K et al. determined optimal sizes of the system components for a hybrid PV/FC/Battery system producing onsite hydrogen [8]. S. Kumaravel [9] et al. optimized a stand-alone Biomass/SolarPV/Pico-hydel energy system and suggested the rating of solar PV, pico-hydel generator, biomass gassifier and battery based on the energy balance. They also compared the cost of energy of the proposed system with the diesel-based hybrid energy system (HES). P. Balamurugan et al. [10] calculated the optimal sizing of an integrated wind-biomass gasifier based hybrid energy system. They compared the cost of energy (COE) of integrated wind-biomass system with the wind-diesel system. Some of the sizing procedures in the literature consider the reliability parameters like Loss of power probability (LOPP), Loss of power supply probability (LPSP), Load coverage rate (LCR), equivalent loss factor (ELF), Energy index ratio (EIR), Expected energy not supplied (EENS). Ardakani et. al. [11] used equivalent loss factor (ELF) for optimizing the size of the components in an integrated wind/ PV/Battery system. Xu et.al. [12] proposed a strategy to minimize the total system cost subject to the constraint of LPSP using GA. Nelson et.al. [13] evaluated LPSP less than or equal to 0.0003 that meant loss of power of 1 day in 10 years for sizing the system components in a wind/PV/FC system. Yu Fu et.al. [14] developed the optimal design models of an integrated wind-hydrosolar power generation system with battery bank. They minimized the annualized cost of the proposed systems under the constrained of loss of power supply probability (LPSP). B. Artificial Intelligence Techniques (AI): These techniques are used in case of nonavailability of weather data in remote sites. The main algorithms under AI techniques are Artificial Neural Networks (ANN), Fuzzy Logic (FL), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) or a hybrid of such techniques and shown in Figure 5. Andrew Arnette et al. [15] analysed cost and emission under different scenarios like minimize cost, minimize emission, Minimax-equal weight, Minimax-cost weighted, Minimax-emissions weighted. Rajesh Kumar et al. [16] developed a Biogeography Based Optimization (BBO) algorithm for the prediction of the optimal sizing coefficient of wind/PV/diesel generator/battery hybrid energy system. A. Arabali et.al. [17] minimized cost and increased efficiency of an integrated SPV-wind
Fig 4. Classification of AI techiniques
system with battery storage using Genetic algorithm (GA) based optimization approach together with a two-point estimate method. Jeroen Tant et al. [18] proposed a optimization method in SPV with battery energy storage systems and envisaged the trade-offs among objective functions: voltage regulation, Peak power reduction, Annual cost. Abdelhamid Kaabeche et.al. [19] proposed an optimization model of an integrated SPV/wind energy system with battery bank using iterative optimization technique. Abd ElShafy A. Nafeh [20] compared the cost of integrated PV-wind-battery systems to the PV-alone and wind-alone systems. Component sizing is generally accompanied by optimizing the system components or other parameters, such as investment cost, output energy cost or consumption of fuel [21]. Optimization is generally carried with the objective of minimizing the Net Present Cost (NPC) or by minimizing the Levelized Cost of Energy (LCE) [22]. Wang and Singh [23] proposed a constrained mixed-integer multi objective particle swarm optimization (PSO) method to minimize the system cost and simultaneously maximize the system reliability. The unit sizing and optimization by minimizing the NPC using HOMER for a hybrid PV-Wind-Diesel-Battery system and hybrid PVDiesel-Battery system has been carried out in [24] and [25], respectively. V.
ENERGY FLOW MANAGEMENT
An energy flow management (EFM) among the various energy sources in integrated/hybrid energy system is essential as the power output from renewable sources is intermittent in nature and dependent on several uncontrolled conditions. The energy flow management ensures high system efficiency and high reliability with least cost. The main objective of the technique should be supply peak load demand at all times.
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Generation Renewable energy resources
Storage devices Batteries, ultracapacitors, flywheels, pumped-hydro
Coventional power plant
Energy Management Optimized storage scheduling
Best scheduling of Energatic, Ecological and Economical Constrsints
Loads Primary loads
Deferrable loads
Fig 5. Intelligent Energy Flow Management System
An optimal EFM is generally a dispatch strategy which is a set of rules used to control the operation of the generator(s) and the battery bank whenever there is insufficient renewable energy to supply the load [26, 27]. Figure 5 shows an intelligent flow energy management system which directly controls generation, storage devices, and loads [28]. After forecasting, an EFM optimizes generation and demand with proper scheduling of storage devices. Majid Nayeripou et.al. [29] proposed a control strategy for frequency control in stand-alone PV/wind/Fuel cell /double layer capacitor by coordination control of fuel cells (FCs) and doublelayer capacitor (DLC) bank. Dulal Ch. Das et al. [30] proposed a frequency controller for solar thermaldiesel-wind hybrid energy system with storage (fuel cells, battery, flywheel, ultra capacitor and aqua electrolyzer) to regulate the output power from the sources in order to eliminate the mismatch in supply and demand. Thounthong et.al. [31] proposed an intelligent model-based control of a standalone photovoltaic-fuel cell power plant with super capacitor (SC) energy storage. They used SC as an auxiliary source and a short-term storage system for supplying the deficiency power (transient and steadystate) from the PV and the FC. Three stand-alone hybrid PV systems (PV/Battery, PV/FC, PV/FC/Battery) using different energy storage technologies are discussed, analyzed and compared in [30] Ipsakis et al. [32] proposed three power management strategies for a hybrid PV-Wind-FCBattery system with hydrogen production using electrolyzers. They compared the strategies based on a sensitivity analysis by considering parameters such as state of charge (SOC) of batteries and output power from FC, the power delivered by the renewable energy sources. Kang and Won [33] suggested a PMS for a PV/FC/Battery hybrid system
based on the cost of battery and FC. The aimed at reducing the number of change over between FC and battery by introduction of measuring and time delay elements to the conventional strategy. Jiang [34] presented an effective energy management strategy and simulated in virtual test bed (VTB) environment for a PV/FC/Battery system connected to the dc bus through appropriate dc–dc power converters and controls. VI. SCOPE AND FUTURE TRENDS Renewable energy sources have come a long way in terms of research and development. However, there are still certain scope in terms of their efficiency and optimal use. The following scope is being observed during literature survey: • The renewable energy sources, such as solar PV and FCs, need break-through technology to exploit more amount of useful power from them. The poor efficiency of solar PV is a major obstruction in encouraging its use. • The manufacturing cost of renewable energy sources needs a significant drop because the high capital cost leads to an increased payback time. • The losses involved in power electronic converters have been reduced to a satisfactory level; however, it should be ensured that there is minimal amount of power loss in these converters. In future, following work has been proposed: 1) New Battery technologies deserve more research attention and efforts to improve their durability and performance, and lower their cost. 2) These standalone systems are less adaptable to load fluctuations. Large variation in load might even lead to entire system collapse. 3) With the development of efficient equipment and household appliances that use dc voltage, several researchers have explored the merit of DC Micro grid for localized loads [35, 36]. VII. CONCLUSION This paper provides a summary of available approaches and methodology for harnessing renewable energy resources in stand-alone applications for rural electrification. Detailed literature survey has been presented on integrated/hybrid systems based power generation covering unit sizing, cost optimization, and energy flow management. The presented literature review facilitate interested researchers in the design and power management of integrated/hybrid RE energy systems with focus on energy sustainability.
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