期刊
ENERGY
卷 193, 期 -, 页码 1084-1101出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2019.116817
关键词
Optimal power flow; Pareto front multi-objective optimization; Techno-economic benefits in power systems; Emission minimization; Enhancing voltage profile
资金
- King Fahd University of Petroleum & Minerals through Power Research Group [RG171002]
- King Abdullah City for Atomic and Renewable Energy (K.A.CARE)
- Egypt-France Cooperation Program (STDF - IFE) Call 5 [31161]
Optimal Power Flow (OPF) problem is one of the most widely nonlinear optimization problems in power systems. This paper proposes a novel hybrid optimization algorithm that combines the merits of salp swarm optimization (SSO) algorithm with particle swarm optimization (PSO) algorithm for solving the OPF problem. The proposed hybrid method is considered to accomplish economic, environmental and technical benefits. The proposed method is applied to single and multi-objective optimization problems with different objective functions such as generation cost minimization, emission reduction, transmission power loss minimization, voltage profile improvement, and voltage stability enhancement. To prove the capability of the proposed hybrid optimization algorithm, 18 case studies are employed and tested on three standard test systems. The proposed PSO-SSO algorithm achieves significantly the effectiveness and robustness of the OPF results for the cases considered. The simulation results demonstrate that the proposed method leads to superior levels of techno-economic-environmental benefits compared with those reported in the literature. In addition, the sensitivity analysis study confirms that the proposed hybrid method produces robust results against parameter variations. (C) 2019 Elsevier Ltd. All rights reserved.
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