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Feng, Yu; Zhou, Jianzhong; Mo, Li; Wang, Chao; Yuan, Zhe; Wu, Jiang

A gradient-based cuckoo search algorithm for a reservoir-generation scheduling problem. (English) Zbl 1461.90046

Algorithms (Basel) 11, No. 4, Paper No. 36, 21 p. (2018).
Summary: 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.

MSC:

90B35 Deterministic scheduling theory in operations research
90C59 Approximation methods and heuristics in mathematical programming

Keywords:

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

Software:

GSA
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References:

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