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Optimum placement and sizing of DGs considering average hourly variations of load
Affiliation:1. Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. UM Power Energy Dedicated Advanced Centre (UMPEDAC) Level 4, Wisma R&D, University of Malaya, Jalan Pantai Baharu, 59990 Kuala Lumpur, Malaysia;1. Power Distribution Research Department, China Electric Power Research Institute, Beijing 100192, China;2. China North Vehicle Research Institute, Beijing 100072, China;1. Zanjan Electric Distribution Company, Zanjan, Iran;2. Department of Electrical Engineering, University of Zanjan, Zanjan, Iran;1. Young Researchers and Elites Club, Borujerd Branch, Islamic Azad University, Borujerd, Iran;2. Faculty of Engineering, Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran
Abstract:This paper presents a multiobjective technique for obtaining optimal sizing of Distributed Generation (DG) units considering both technical and economical factors of the distribution system. The technical factors include real power loss reduction, line load reduction and voltage profile improvement and the economical factors consider optimal DG investment cost. Three different Distributed Generation systems solar photovoltaic, biomass and wind system are considered for integration with the existing distribution system. Since solar photovoltaic system is not available at night time, only biomass and wind systems are operated and for day time operation all the three distribution generation systems are considered. A new sensitivity index based on voltage sensitivity and apparent load power is proposed for identification of optimal locations for DG placement. The optimum sizing of DG units operating at unity power factor and lagging power factor is obtained using GA for different load levels considering daily average hourly loading aiming at improving the technical performance of the distribution system with optimum investment on DG units. Simulation results are presented to show the advantage of the proposed methodology in terms of technical performance and annual economical savings of the distribution system.
Keywords:Distributed generation  Genetic algorithm  Solar photovoltaic  Biomass  Wind system  Real power loss reduction
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