Single and Multi-Objective Optimization Algorithms | ||||
International Journal of Applied Energy Systems | ||||
Article 5, Volume 1, Issue 2, July 2019, Page 77-84 PDF (1.93 MB) | ||||
Document Type: Original papers | ||||
DOI: 10.21608/ijaes.2019.169954 | ||||
View on SCiNiTO | ||||
Authors | ||||
R. M. Kotb1; A. M. Ewais2; A. M. Hemeida2 | ||||
1Electrical Engineering Department Faculty of Energy Engineering, Aswan University, Aswan, Egypt | ||||
2Electrical Engineering Department Faculty of Energy Engineering, Aswan University Aswan, Egypt | ||||
Abstract | ||||
Hybrid and multi optimization techniques are used extensively for solving optimal power flow problems. In this paper, particle swarm optimization (PSO), is incorporated with grey wolf optimization, (GWO) to form a hybrid algorithm called HPSOGWO and using the multi-objective optimization of this algorithm, which called MO-HPSOGWO, and comparing them. The HPSOGWO and MO-HP SOGWO are implemented to enhance the optimal power flow solution of the ieee-30 bus system. Five objective functions (OPF) optimizing separately by HPSOGWO and simultaneously in a single run by MO-HPSOGWO. Matlab software is used to solve the system. | ||||
Keywords | ||||
Hybrid and multi optimization techniques; Multi optimization techniques; Single objective functions (OPF) | ||||
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