Improvement of Optimal Reservoir Rule Curve by Atom Search Technique: A Case Study of Huai Luang Reservoir
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Abstract
The objective of this study was to investigate the best optimization of the reservoir rule curve by applying the atomic search optimization technique together with the simulation of the Huai Luang reservoir system, Udon Thani Province. In three cases, objective functions are utilized in the search for the optimal solution: the mean of the least water shortages, the least frequency of water shortages, and the smallest maximal shortage. The monthly data for the reservoir rule curve were considered. The data used in this study consisted of monthly average runoff into the reservoir from 1984-2022, hydrologic data, water demand information, and reservoir physical data. The results show that the new rule curve obtained using the Atom Search Optimization technique has a similar shape to the existing rule curve. When the new rule curve was tested and compared to the existing rule curve under identical conditions, the new rule curve was found to be more accurate. It was determined that the new rule curve mitigates water shortage and excess conditions more effectively than the existing rule curve. In addition, 1,000 sets of monthly runoff events were synthesized for the reservoir to evaluate the efficiency of the new rule curve. It was found to perform slightly better than the existing rule curve.
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