Two‐stage glowworm swarm optimisation for economical operation of hydropower station

• DOI: 10.1049/iet-rpg.2017.0466
• Publication Date: 2018-04-10T02:23:29Z
• Authors: Xiaoyu Wang; Kan Yang; Xianghua Zhou
• Keywords: 0211 other engineering and technologies; 02 engineering and technology

This study proposes a two‐stage glowworm swarm optimisation (GSO) algorithm for the economical operation of inner plant hydropower station. Binary GSO and real‐coded (RCGSO) algorithms are applied with different types encodings to solve unit commitment sub‐problem economic load distribution (ELD) sub‐problem, respectively. Moreover, an improved dynamic patching mechanism is developed avoid invalid calculations enrich diversity solutions. A luciferin transfer helps escape local optimum research enhances solution space by selecting from among derived The RCGSO uses variable‐step missing optimal solution. In comparison genetic particle optimisation, significantly robust provides better solutions ELD sub‐problems. Numerical simulations exhibited superiority in terms stably quickly solving problem stations.