Optimal reactive power dispatch by improved GSA-based algorithm with the novel strategies to handle constraints |
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| Affiliation: | 1. Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;2. Research Center on Complex Power System Analysis and Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;3. Key Laboratory of Communication Network and Testing Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;1. Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;2. Research Center on Complex Power System Analysis and Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;3. Dept. of Electrical Engineering, Hubei Minzu University, Enshi 445000, China;4. Hubei Energy Group Qiyueshan Wind Power Co., Ltd., Lichuan 445400, China;1. Young Researcher and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran;2. Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran;3. Department of Electrical Engineering, Bilesavar Branch, Islamic Azad University, Bilesavar, Iran;1. Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran;2. Islamic Azad University, Kazerun Branch, Kazerun, Iran;3. Department of Electrical Engineering, Semnan University, Semnan, Iran |
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| Abstract: | Optimal reactive power dispatch (ORPD) is well known as a complex mixed integer nonlinear optimization problem where many constraints are required to handle. In the last decades, many artificial intelligence-based optimization methods have been used to solve ORPD problem. But, these optimization methods lack an effective means to handle constraints on state variables. Thus, in this paper, the novel and feasible conditional selection strategies (CSS) are devised to handle constraints efficiently in the proposed improved gravitational search algorithm (GSA-CSS). In addition, considering the weakness of GSA itself, the improved GSA-CSS (IGSA-CSS) is presented which employs the memory property of particle swarm optimization (PSO) to enhance global searching ability and utilizes the concept of opposition-based learning (OBL) for optimizing initial population. The presented GSA-CSS and IGSA-CSS methods are applied to ORPD problem on IEEE14-bus, IEEE30-bus and IEEE57-bus test systems for minimization of power transmission losses (Ploss) and voltage deviation (Vd), respectively. The comparisons of simulation results reveal that IGSA-CSS provides better results and the improvements of algorithm in this work are feasible and effective. |
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| Keywords: | Optimal reactive power dispatch (ORPD) Conditional selection strategies (CSS) Gravitational search algorithm (GSA) Improved GSA (GSA-CSS) Improved GSA-CSS (IGSA-CSS) |
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