A novel fuzzy adaptive configuration of particle swarm optimization to solve large-scale optimal reactive power dispatch |
| |
| Affiliation: | 1. Faculty of Engineering and Technology, Razi University, Eslam Abad Gharb, Kermanshah, Iran;2. Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran;3. Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, USA;1. Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Iran;2. Systems Engineering Group, Department of Engineering & Technology, University of Huddersfield, UK;1. Electrical Engineering Department, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt;2. Elec. Power and Machines Eng. Depart., Faculty of Eng., Tanta University, Tanta, Egypt;1. Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran;2. Department of Electrical Engineering, University of Birjand, Birjand, Iran;3. Department of Electrical Engineering, University of Technology Sydney, Sydney, Australia;4. Faculty of Engineering and Technology, Razi University, Eslam Abad Gharb, Kermanshah, Iran;5. Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, USA |
| |
| Abstract: | Management and scheduling of reactive power resources is one of the important and prominent problems in power system operation and control. It deals with stable and secure operation of power systems from voltage stability and voltage profile improvement point of views. To this end, a novel Fuzzy Adaptive Heterogeneous Comprehensive-Learning Particle Swarm Optimization (FAHCLPSO) algorithm with enhanced exploration and exploitation processes is proposed to solve the Optimal Reactive Power Dispatch (ORPD) problem. Two different objective functions including active power transmission losses and voltage deviation, which play important roles in power system operation and control, are considered in this paper. In order to authenticate the accuracy and performance of the proposed FAHCLPSO, it applied on three different standard test systems including IEEE 30-bus, IEEE 118-bus and IEEE 354-bus test systems with six, fifty-four and one-hundred-sixty-two generation units, respectively. Finally, outcomes of the proposed algorithm are compared with the results of the original PSO and those in other literatures. The comparison proves the supremacy of the proposed algorithm in solving the complex optimization problem. |
| |
| Keywords: | Comprehensive-learning (CL) strategy Fuzzy adaptive heterogeneous comprehensive-learning particle swarm optimization (FAHCLPSO) Optimal reactive power dispatch (ORPD) Voltage deviation index (VDI) |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
