Rule curves are fundamental guidelines for operating a reservoir system. The objective of this paper is to find a suitable objective function and to propose a smoothing function constraint for searching the optimal rule curves by using genetic algorithms connected simulation model. The results show that an average water shortage is the optimal objective function for searching the optimal rule curves. It can represent the situations of water deficit and excess release. The results also indicate that a moving average applied to be the constraint of searching can reduce the variation of the upper and lower rule curves. Further, the developed model has been applied to determine the optimal rule curves of the Bhumibol and Sirikit Reservoirs (the Chao Phraya River Basin, Thailand). It is shown that the model gives the rule curves which are more mitigate the situations of water deficit and excess release than the existing rule curves. It is also concluded that the genetic algorithms connected simulation with the smoothing constraint is more effective than the model without constraint.
Rule curves are monthly reservoir-operation guidelines for meeting the minimum of water shortage over the long run. This paper proposes a dynamic programming (DP) approach for finding the optimal rule curves of singleand multi-reservoir systems. The proposed DP approach uses a traditional DP technique conditionally and applies the principle of progressive optimality (PPO) to search its optimal solutions. The proposed DP-PPO approach is suitable because of the multi-stage, nonlinear, and continuous-type characteristics of the rule curve search. Its dimensionality is relatively small, as compared with that of the traditional one. Results of an illustrative application to a multi-reservoir system under two different initial feasible solutions (i.e., new or existing reservoirs) have demonstrated that the DP-PPO approach is generally fast and robust. Its convergence varies only slightly, according to the initial conditions.Key words: rule curves, principle of progressive optimality, dynamic programming (DP), monthly reservoir operation.
Résumé :Les courbes des niveaux optimaux sont des lignes directrices mensuelles de gestion de réservoir pour rencontrer le minimum de pénurie d'eau à long terme. Cet article propose une approche de programmation dynamique (« DP ») pour trouver les courbes des niveaux optimaux des systèmes à simple et à plusieurs réservoirs. L'approche « DP » proposée utilise la technique « DP » classique de manière conditionnelle et applique le principe d'optimalité progressive (« PPO ») pour rechercher ses solutions optimales. L'approche « DP-PPO » proposée est appropriée aux caractéristiques de plusieurs étages non linéaires et continus de la recherche de la courbe des niveaux optimaux. Sa dimensionnalité est relativement petite, si on la compare à celle de la technique classique. Les résultats d'une application typique à un système à plusieurs réservoirs sous deux solutions initiales faisables différentes (c.-à-d. nouveaux réser-voirs et réservoirs existants) démontrent que l'approche « DP-PPO » est généralement rapide et robuste. Sa convergence ne varie que légèrement selon les conditions initiales.Mots-clés : courbe des niveaux optimaux, principe d'optimalité progressive, programmation dynamique, gestion mensuelle du réservoir.[Traduit par la Rédaction] Chaleeraktrakoon and Kangrang 176
Effective reservoir operation is achieved using suitable rule curves to control the release of water following the release criteria. Conditional cuckoo search (CCS) algorithms and conditional particle swarm optimisation (CPSO) were linked with a reservoir simulation model to identify adaptive optimal reservoir rule curves. Three cases (normal, dry and wet years) were considered when producing the rule curves depending on the inflow pattern and inflow period. Lampao reservoir in Thailand was used to illustrate application of the method. The results showed that the new rule curve patterns produced by CCS algorithms and CPSO in a normal year were similar to the patterns obtained by conditional ant colony optimisation and current usage patterns. However, the obtained rule curves for wet and dry years were quite different from those for the normal year. Average water shortages using the normal-year inflow were less than using the dry-year inflow by 24·05% and 18·92% for CCS and CPSO models, respectively. Situations of water shortage when using the normal-year rule curves can best mitigate the water situation. In conclusion, the adaptive rule curves were suitable for reservoir operation under all inflow cases.
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