Evolutionary programming based security constrained optimal power flow |
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| Affiliation: | 1. Department of Chemistry and Chemical Biology, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4M1, Canada;2. Department of Chemistry, Moscow State University, Leninskie Gory, House 1, Building 3, GSP-2, Moscow 119992, Russia;1. Guizhou Key Laboratory of Intelligent Technology in Power System, College of Electrical Engineering, Guizhou University, Guiyang, 550025, China;2. State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China;1. Department of Electrical Engineering, Faculty of Engineering, Unesp Univ Estadual Paulista, 17033-360 Bauru, SP, Brazil;2. Department of Mathematics, Faculty of Sciences FC, Unesp Univ Estadual Paulista, 17033-360 Bauru, SP, Brazil |
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| Abstract: | This paper presents an algorithm for solving security constrained optimal power flow problem through the application of evolutionary programming (EP). The controllable system quantities in the base-case state are optimised to minimize some defined objective function subject to the base-case operating constraints as well as the contingency-case security constraints. An IEEE 30-bus system is taken for investigation. The security constrained optimal power flow results obtained using EP are compared with those obtained using conventional security constrained optimal power flow. The investigations reveal that the proposed algorithm is relatively simple, reliable and efficient and suitable for on-line applications. |
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