Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows

Abstract

Study region: The Shifeng Creek, situated within the Jiao River basin in East China. Study focus: To address complicated contradictory relationships in multi-reservoir scheduling system, this study develops a new two-layer hedging robust optimization model (TL-HRO) for multi-reservoir scheduling by combining the hedging strategy with robust optimization. The first hedging layer of the TL-HRO model integrates critical hedging relationship that exists between flood control and power generation benefits. The flood control benefits can be subdivided into upstream and downstream benefits, which also have a hedging relationship. The second layer mainly focuses on the interaction of the scheduling for the current period with the future period. Furthermore, considering the impact of uncertain inflows on scheduling, this study employed the vine copula function to extract the multivariate spatial-temporal relationships and perform stochastic simulations. For comparison, a multi-objective robust optimization model (MORO) is constructed where multiple objectives are optimized in parallel. New hydrological insights for the region: The TL-HRO model, through iterative optimization, yielded an optimal scheduling solution that improved total benefits by roughly 58.26 %, covering both flood control and power generation. The results further demonstrated that the TL-HRO model is closer to the optimal solution than the MORO model, particularly during flood seasons, under uncertain inflow conditions. This study serves as a valuable reference for decision-makers in formulating efficient scheduling schemes during flood seasons.