Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization |
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Affiliation: | 1. Department of Electrical and Electronics Engineering, S.A. Engineering College, Chennai 600077, India;2. School of Electrical Engineering, VIT University, Chennai Campus, Chennai 600127, India;1. Department of Electronics and Electrical Engineering, Shiraz University of Technology, Shiraz, Iran;2. University of Isfahan, Isfahan, Iran;1. Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia;2. Technical Institute Shatra, Southern Technical University, Ministry of Higher Education & Scientific Research, Thi-qar, Iraq;3. Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia;1. Electrical Engineering Department, Faculty of Engineering, Aswan University, Egypt;2. Electrical Engineering Department, Faculty of Engineering, El-Minia University, Egypt;3. Electrical Engineering Department, Faculty of Energy Engineering, Aswan University, Egypt |
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Abstract: | The optimization is an important role in the wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. Using adaptive real coded biogeography-based optimization (ARCBBO), we present the optimization of various objective functions of an optimal power flow (OPF) problem in a power system. We aimed to determine the optimal settings of control variables for an OPF problem. The proposed approach was tested on a standard IEEE 30-bus system and an IEEE 57-bus system with different objective functions. Simulation results reveal that the proposed ARCBBO approach is effective, robust and more accurate than current methods of power flow optimization in literature. |
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Keywords: | Adaptive mutation Biogeography-based optimization Optimal power flow Fuel cost minimization Voltage profile improvement Voltage stability enhancement |
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