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Article

Long-Term Hydropower Generation Scheduling of Large-Scale Cascade Reservoirs Using Chaotic Adaptive Multi-Objective Bat Algorithm

College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
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Water 2019, 11(11), 2373; https://doi.org/10.3390/w11112373
Received: 25 October 2019 / Revised: 10 November 2019 / Accepted: 11 November 2019 / Published: 13 November 2019
(This article belongs to the Section Water Resources Management, Policy and Governance)
With growing concerns over renewable energy, the cascade hydropower reservoirs operation (CHRO), which balances the development of economic benefits and power supply security, plays an increasingly important role in hydropower systems. Due to conflicting objectives and complicated operation constraints, the CHRO problem considering the requirements of maximizing power generation benefit and firm power output is determined as a multi-objective optimization problem (MOP). In this paper, a chaotic adaptive multi-objective bat algorithm (CAMOBA) is proposed to solve the CHRO problem, and the external archive set is added to preserve non-dominant solutions. Meanwhile, population initialization based on the improved logical mapping function is adopted to improve population diversity. Furthermore, the self-adaptive local search strategy and mutation operation are designed to escape local minima. The CAMOBA is applied to the CHRO problem of the Qingjiang cascade hydropower stations in southern China. The results show that CAMOBA outperforms the multi-objective bat algorithm (MOBA) and non-dominated sorting genetic algorithms-II (NSGA-II) in different hydrological years. The spacing (SP) and hypervolume (HV) metrics verify the excellent performance of CAMOBA in diversity and convergence. In summary, the CAMOBA is demonstrated to get better scheduling solutions, providing an effective approach for solving the cascade hydropower reservoirs operation (CHRO). View Full-Text
Keywords: cascade hydropower reservoirs operation; firm power output; multi-objective bat algorithm; Qingjiang cascade hydropower reservoirs operation; firm power output; multi-objective bat algorithm; Qingjiang
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MDPI and ACS Style

Su, L.; Yang, K.; Hu, H.; Yang, Z. Long-Term Hydropower Generation Scheduling of Large-Scale Cascade Reservoirs Using Chaotic Adaptive Multi-Objective Bat Algorithm. Water 2019, 11, 2373. https://doi.org/10.3390/w11112373

AMA Style

Su L, Yang K, Hu H, Yang Z. Long-Term Hydropower Generation Scheduling of Large-Scale Cascade Reservoirs Using Chaotic Adaptive Multi-Objective Bat Algorithm. Water. 2019; 11(11):2373. https://doi.org/10.3390/w11112373

Chicago/Turabian Style

Su, Lyuwen, Kan Yang, Hu Hu, and Zhe Yang. 2019. "Long-Term Hydropower Generation Scheduling of Large-Scale Cascade Reservoirs Using Chaotic Adaptive Multi-Objective Bat Algorithm" Water 11, no. 11: 2373. https://doi.org/10.3390/w11112373

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