A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems

被引:95
作者
Ghasemi, Mojtaba [1 ]
Aghaei, Jamshid [1 ]
Akbari, Ebrahim [2 ]
Ghavidel, Sahand [3 ]
Li, Li [3 ]
机构
[1] Shiraz Univ Technol, Dept Elect & Elect Engn, Shiraz, Iran
[2] Univ Isfahan, Esfahan, Iran
[3] Univ Technol Sydney, Fac Engn & Informat Technol, POB 123, Broadway, NSW 2007, Australia
关键词
MAED (Multi-area economic dispatch); RCMAED (reserve constrained multi-area economic dispatch); RCMAEED (reserve constrained environmental/economic dispatch); DEPSO (differential evolution particle swarm optimization); OPTIMAL POWER-FLOW; IMPERIALIST COMPETITIVE ALGORITHM; LOAD DISPATCH; WIND POWER; EMISSION DISPATCH; SEARCH METHOD; COMBINED HEAT; GENERATION; METHODOLOGY; CONSTRAINTS;
D O I
10.1016/j.energy.2016.04.002
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper proposes a new, efficient and powerful heuristic-hybrid algorithm using hybrid DE (differential evolution) and PSO (particle swarm optimization) techniques DEPSO (differential evolution particle swarm optimization) designed to solve eight optimization problems with benchmark functions and the MAED (multi-area economic dispatch), RCMAED (reserve constrained MAED) and RCMAEED (reserve constrained multi area environmental/economic dispatch) problems with reserve sharing in power system operations. The proposed hybridizing sum-local search optimizer, entitled HSLSO, is a relatively simple but powerful technique. The HSLSO algorithm is used in this study for solving different MAED problems with non-smooth cost function. The effectiveness and efficiency of the HSLSO algorithm is first tested on a number of benchmark test functions. Experimental results showe the HSLSO has a better quality solution with the ability to converge for most of the tested functions. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:182 / 195
页数:14
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