Optimal reservoir operation using the improved multi-step-ahead time-varying hedging rule under climate and land-use changes

ABSTRACT This study aims to optimize Yeywa Hydropower Reservoir (YHR) operation using the multi-step-ahead time-varying hedging (TVH) rule under climate change (CC) and land-use change (LUC) to improve summer power generation. The performance of three multi-objective algorithms – the Multi-objective Salp Swarm Algorithm (MOSSA), the Multi-objective Antlion Optimizer (MOALO) and the Non-dominated Sorting Whale Optimization Algorithm (NSOWA) – are compared. MOSSA provides the best solutions with a higher mean hypervolume in a shorter computation time, and it is utilized to optimize the TVH rules for four periods: monthly (TVH-1), quarterly (TVH-3), half-yearly (TVH-6) and yearly (TVH-12). The six-month-ahead TVH-6 rule and the five-month-ahead TVH-6 rule generate the highest summer power for the historical period (2011–2020) and the future period (2020–2059), respectively. The future decadal power generation is expected to be higher than the historical power generation. The future TVH-6 rule is more reliable and it has lower water deficits than the historical YHR operation rule.