A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Algorithms

Zhe Yuan¹  Jiang Wu¹  Chao Wang²  Li Mo³  Yu Feng³  Jianzhong Zhou³ 

[1] Changjiang River Scientific Research Institute, Changjiang Water Resources Commission of the Ministry of Water Resources of China, Wuhan 430010, China;China Institute of Water Resources and Hydropower Research, Beijing 100038, China;School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;

关键词: long-term hydropower generation scheduling;    cascade reservoirs;    gradient-based cuckoo search algorithm;    Jinsha River;   

DOI  :  10.3390/a11040036

来源: DOAJ

【 摘 要 】

In this paper, a gradient-based cuckoo search algorithm (GCS) is proposed to solve a reservoir-scheduling problem. The classical cuckoo search (CS) is first improved by a self-adaptive solution-generation technique, together with a differential strategy for Lévy flight. This improved CS is then employed to solve the reservoir-scheduling problem, and a two-way solution-correction strategy is introduced to handle variants’ constraints. Moreover, a gradient-based search strategy is developed to improve the search speed and accuracy. Finally, the proposed GCS is used to obtain optimal schemes for cascade reservoirs in the Jinsha River, China. Results show that the mean and standard deviation of power generation obtained by GCS are much better than other methods. The converging speed of GCS is also faster. In the optimal results, the fluctuation of the water level obtained by GCS is small, indicating the proposed GCS’s effectiveness in dealing with reservoir-scheduling problems.

【 授权许可】

Unknown