A new approach for unit commitment problem via binary gravitational search algorithm

被引:83
|
作者
Yuan, Xiaohui [1 ]
Jia, Bin [1 ]
Zhang, Shuangquan [2 ]
Tian, Hao [1 ]
Hou, Yanhong [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Energy & Power Engn, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Binary gravitational search algorithm; Unit commitment; Economic load dispatch; Heuristic strategy; Local mutation; GENETIC ALGORITHM; OPTIMIZATION; DISPATCH; GSA;
D O I
10.1016/j.asoc.2014.05.029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a new gravitational search algorithm to solve the unit commitment (UC) problem, which is integrated binary gravitational search algorithm (BGSA) with the Lambda-iteration method. The proposed method is enhanced by priority list based on the unit characteristics and heuristic search strategies to repair the spinning reserve and minimum up/down time constraints. Furthermore, local mutation strategies are applied to improve the performance of BGSA. The implementation of the proposed method for UC problem consists of three stages. Firstly, the BGSA based on priority list is applied for solution unit scheduling when neglecting minimum up/down time constraints. Secondly, heuristic search strategies are used to handle minimum up/down time constraints and decommit excess spinning reserve units. Thirdly, local mutation strategies are raised to avoid premature convergence of the algorithm and prevent it from trapping into local optima. Finally, Lambda-iteration method is adopted to solve economic load dispatch based on the obtained unit schedule. The feasibility and effectiveness of the proposed method is verified by the systems with the number of units in the range of 10-100 and the results are compared with those of other methods reported in literatures. The results clearly show that the proposed method gives better quality solutions than other methods. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:249 / 260
页数:12
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