Improving reservoir operation efficiency using electric EEL foraging optimization and transit search algorithms with standard operating policy: Nong Han-Kumphawapi case study

This study proposes a new optimization method to improve the operational efficiency of reservoir systems by applying the Electric Eel Foraging Optimization (EEFO) and Transit Search Optimization (TSO) techniques. The optimization was conducted in the Nong Han-Kumphawapi reservoir system, located in the Udon Thani province of Thailand. The objective was to determine optimal rule curves for the reservoir's operation, specifically focusing on mitigating both water shortage and excess water release situations. The proposed model was evaluated using historic inflow data from 2006 to 2021 and synthetic data for 500 samples. The findings revealed that the EEFO technique could minimize average annual water shortages to 4.349 MCM/year, while the frequency of water shortage events was reduced to 0.496 times per year. For excess water management, the EEFO-derived rule curves limited the average annual excess water release to 132.056 MCM/year. Comparatively, the TSO model produced similar performance, demonstrating a high degree of consistency in reducing both water shortage and excess water release risks. The results suggest that these optimization techniques can effectively enhance the reliability and performance of reservoir operations, providing valuable insights for sustainable water resource management in the region.