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Load frequency control of an autonomous hybrid power system by quasi-oppositional harmony search algorithm
Affiliation:1. Department of Electrical and Electronics Engineering, Anna University – University College of Engineering Dindigul, India;2. Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, India;1. Electric Power and Machine Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt;2. Electric Power and Machine Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt;3. Currently, Electrical Department, Faculty of Engineering, Jazan University, KSA;1. Department of Electrical Engineering, Shiraz University of Technology, Shiraz, Iran;2. Department of Energy Technology, Aalborg University, Aalborg DK-9220, Denmark
Abstract:This paper deals with a novel quasi-oppositional harmony search algorithm (QOHSA) based design of load frequency controller for an autonomous hybrid power system model (HPSM) consisting of multiple power generating units and energy storage units. QOHSA is a novel improved version of music inspired harmony search algorithm for obtaining the best solution vectors and faster convergence rate. In this paper, the efficacy of the proposed QOHSA is adjudged for optimized load frequency control (LFC) of an autonomous HPSM. The studied HPSM consists of renewable/non-renewable energy based generating units such as wind turbine generator, solar photovoltaic, solar thermal power generator, diesel engine generator, fuel cell with aqua-electrolyzer while energy storage units consists of battery energy storage system, flywheel energy storage system and ultra-capacitor. Gains of the conventional controllers such as integral (I) controller, proportional–integral (PI) controller and proportional–integral–derivative (PID) controller (installed as frequency controller one at a time in the proposed HPSM) is optimized using QOHSA to mitigate any frequency deviation owing to sudden generation/load change. In order to corroborate the efficacy of QOHSA, performance of QOHSA to design optimal LFC is compared with that of other well-established technique such as teaching learning based optimization algorithm (TLBOA). The comparative performances of the HPSM under the action of QOHSA/TLBOA based optimized conventional controllers (I or PI or PID) are investigated and compared in the present work. It is found that the QOHSA tuned frequency controllers improves the overall dynamic response in terms of settling time, overshoot and undershoot in the profile of frequency deviation and power deviation of the studied HPSM.
Keywords:Hybrid power system model  Load frequency control  Quasi-oppositional harmony search algorithm  Renewable energy sources  Teaching learning based optimization algorithm
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