The Application of Particle Swarm Optimization for Searching Optimal Rule Curve of Lampao Reservoir

บทคัดย่อ

This research aims to apply particle swarm optimization connected with a simulation model in order to improve the rule curves of a reservoir. The minimum average water shortage was used as the objective function for the searching procedure. Monthly rule curves of Lampao reservoir located in Kalasin province were considered in this study. The curves include average monthly infl ows into the reservoir from years 1968 to 2011, net demand from the reservoir, hydrologic data and physical data of the Lampao reservoir. In addition, 100 samples of generated infl ow data were used to evaluate the performance of the new rule curves. The results present situation of water shortage and overfl owin term of frequency and duration, amount of average and maximum water. The results found that the pattern of the obtained rule curves from particle swarm optimization connected to a simulation model is similar to the existing rule curves. The new lower rule curve is higher than the existing rule curve during the dry season from December to May. Hence, water is stored to meet the demand. The new upper rule curve is lower than the existing rule curves during June to August. Hence, the stored water is released in order to geta free volume for reducing fl ood risk in the rainy season as well as maintaining fl ood volume. The results of the evaluation of the new rule curve found that the situation of water shortage and overfl ow decreased slightly. In a simulated case where increasing the irrigation area by 8,000 hectares, the new rule curve can be used as a basis for releasing water from the reservoir. Water shortage average amount 161 MCM in 44 years.