期刊
APPLIED SOFT COMPUTING
卷 59, 期 -, 页码 229-242出版社
ELSEVIER
DOI: 10.1016/j.asoc.2017.05.034
关键词
Economic load dispatch; Multi-area economic load dispatch; Orthogonal design; Particle swarm optimization; Valve-point effects
资金
- National Natural Science Foundation of China [71402103, 61273367, 61672334, 71501132]
- Natural Science Foundation of Guang-dong Province [2015A030313556, 52012040006834, 2016A030310067]
- MOE Youth Foundation Project of Humanities and Social Sciences at Universities in China [13YJC630123]
- China Postdoctoral Science Foundation Funded Project [2015M580053, 2016T90042]
- Fundamental Research Funds for the Central Universities [GK201703062]
Economic load dispatch (ELD) problems have been an important issue in optimal operation and planning of power system. Characterized by non-convex/non-smooth properties and various practical constraints, the ELD problems are difficult to solve using conventional optimization techniques. In this paper, an improved orthogonal design particle swarm optimization (IODPSO) algorithm is presented for solving the single-area and multi-area ELD problems with nonlinear characteristics of the generators, such as valve point effects, prohibited operating zones, ramp rate limits and multiple fuels. In the IODPSO algorithm, an orthogonal designed method is used to construct a promising exemplar. Multiple auxiliary vector generating strategies are proposed to enhance the efficiency and effectiveness of orthogonal design operations. A tent chaotic map is employed for the adaptation of the acceleration coefficients, thus improving the proposed algorithm's robustness and global search capabilities. In addition, we designed a repair method to handle the practical constraints. Six cases of ELD problems with different characteristics are utilized to benchmark the proposed algorithm. Experimental results demonstrate that IODPSO algorithm is a promising approach for solving the non-convex/non-smooth ELD problems. (C) 2017 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据