Enhanced harmony search algorithm for sustainable ecological operation of cascade hydropower reservoirs in river ecosystem

被引:8
作者
Niu, Wen-jing [1 ]
Feng, Zhong-kai [2 ]
Jiang, Zhi-qiang [3 ]
Wang, Sen [4 ]
Liu, Shuai [5 ]
Guo, Wei [1 ]
Song, Zhen-guo [6 ]
机构
[1] Changjiang Water Resources Commiss, Bur Hydrol, Wuhan 430010, Peoples R China
[2] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
[4] Minist Water Resources, Key Lab Pearl River Estuarine Dynam & Associated, Guangzhou 510611, Peoples R China
[5] China Water Resources Beifang Invest Design & Res, Tianjin 300222, Peoples R China
[6] China Ship Dev & Design Ctr, Wuhan 430064, Peoples R China
基金
中国国家自然科学基金;
关键词
cascade hydropower reservoirs; ecological operation; water management; enhanced harmony search algorithm; engineering optimization; metaheuristic algorithm; TERM OPTIMAL OPERATION; GENETIC ALGORITHM; OPTIMIZATION; RULES; SYSTEM; DECOMPOSITION; INTELLIGENCE; STRATEGIES; MANAGEMENT; NETWORKS;
D O I
10.1088/1748-9326/abf60c
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the merits of superior performance and easy implementation, the harmony search (HS), a famous population-based evolutionary method, has been widely adopted to resolve global optimization problems in practice. However, the standard HS method still suffers from the defects of premature convergence and local stagnation in the complex multireservoir operation problem. Thus, this study develops an enhanced harmony search (EHS) method to improve the HS's search ability and convergence rate, where adaptive parameter adjustment strategy is used to enhance the global search performance of the swarm, while the elite-learning evolutionary mode is used to improve the converge trajectory of the population. To verify its practicability, EHS is applied to solve numerical optimization and multireservoir operation problems. The results show that EHS can produce better results than several existing methods in different cases. For instance, the mean objective of EHS is improved by about 23.9%, 28.7% and 26.8% compared with particle swarm optimization, differential evolution and gravitational search algorithm in 1998-1999 typical runoff case. Hence, an effective optimizer is developed for sustainable ecological operation of cascade hydropower reservoirs in river ecosystem.
引用
收藏
页数:16
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