Binary glowworm swarm optimization for unit commitment

Journal of Modern Power Systems and Clean Energy

Xu Wang¹  Yu Gong¹  Yangyang Liu¹  Mingwei Li¹  Chuanwen Jiang¹ 

[1] Shanghai Jiao Tong University,Department of Electrical Engineering,Shanghai,China,200240;

关键词: Binary glowworm swarm optimization;    Correction method;    Priority list;    Unit commitment;   

DOI  :  10.1007/s40565-014-0084-9

来源: DOAJ

【 摘 要 】

This paper proposes a new algorithm-binary glowworm swarm optimization (BGSO) to solve the unit commitment (UC) problem. After a certain quantity of initial feasible solutions is obtained by using the priority list and the decommitment of redundant unit, BGSO is applied to optimize the on/off state of the unit, and the Lambda-iteration method is adopted to solve the economic dispatch problem. In the iterative process, the solutions that do not satisfy all the constraints are adjusted by the correction method. Furthermore, different adjustment techniques such as conversion from cold start to hot start, decommitment of redundant unit, are adopted to avoid falling into local optimal solution and to keep the diversity of the feasible solutions. The proposed BGSO is tested on the power system in the range of 10–140 generating units for a 24-h scheduling period and compared to quantum-inspired evolutionary algorithm (QEA), improved binary particle swarm optimization (IBPSO) and mixed integer programming (MIP). Simulated results distinctly show that BGSO is very competent in solving the UC problem in comparison to the previously reported algorithms.

【 授权许可】

Unknown