Extracting Optimal Operation Rule Curves of Multi-Reservoir System Using Atom Search Optimization, Genetic Programming and Wind Driven Optimization

This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 2017. These included Huai Nam Bo Reservoir, the Upper Huai Sai-1 Reservoir, the Upper Huai Sai-2 Reservoir, the Upper Huai Sai-3 Reservoir, and the Huai Sai Khamin Reservoir. In this study, the monthly reservoir rule curves, the average monthly inflow to the reservoirs during 2005–2020, the water demand of the reservoirs, hydrological data, and physical data of the reservoirs were considered. In addition, the performance of the newly obtained rule curves was evaluated by comparing the operation with a single reservoir and the operation with a multi-reservoir network. The results showed situations of water shortage and water in terms of frequency, duration, average water, and maximum water. The newly obtained rule curves from the multi-reservoir system case showed an average water excess of 43.722 MCM/year, which was less than the optimal curves from the single reservoir case, where the average water excess was 45.562 MCM/year. An analysis of the downstream reservoir of the multi-reservoir system, which diverts water from the upstream reservoirs, was performed. The results showed that the new optimal rule curves of ASO, GP, and WDO operated as a multi-reservoir system performed better than when operated as a single reservoir. Therefore, this research is suitable for sustainable water management without construction.