Quantifying the robustness of optimal reservoir operation for the Xinanjiang-Fuchunjiang reservoir cascade

“In this research we investigate the robustness of the common implicit stochastic optimization (ISO)
method for dam reoperation. As a case study, we focus on the Xinanjiang-Fuchunjiang reservoir
cascade in eastern China, for which adapted operating rules were proposed as a means to reduce
the impact of climate change and socio-economic developments. The optimizations were based on
five different water supply and demand scenarios for the future period from 2011 to 2040. Main
uncertainties in the optimization can be traced back to correctness of the assumed supply and
demand scenarios and the quality and tuning of the applied optimization algorithm. To investigate
the robustness of proposed operation rules, we (1) compare cross-scenario performance of all
obtained Pareto-optimal rulesets and (2) investigate whether different metaheuristic optimization
algorithms lead to the same results. For the latter we compare the originally used genetic algorithm
(Nondominated Sorting Genetic Algorithm II, NSGA-II) with a particle swarm optimization algorithm
(MOPSO). Reservoir performance was measured using the shortage index (SI) and mean annual
energy production (MAEP) as main indicators. It is found that optimal operating rules, tailored to a
specific scenario, deliver at most 2.4% less hydropower when applied to a different scenario, while
the SI increases at most with 0.28. NSGA-II and MOPSO are shown to yield approximately the same
Pareto-front for all scenarios, even though small differences can be observed.”
© IWA Publishing 2015
(Citaat: Vonk, E., Xu, Y.P., Booij, M.J., Augustijn, D.C.M. – Quantifying the robustness of optimal reservoir operation for the Xinanjiang-Fuchunjiang reservoir cascade – Water Science & Technology Water Supply 16(2016)1, p.79-85)