A Study of Fuzzy Programming with Optimization Algorithms for Reservoir Operation

• Main Authors: Yu-Chen Chiu, 邱昱禎
• Other Authors: Fi-John Chang
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/13693454733414758731

碩士 === 國立臺灣大學 === 生物環境系統工程學系暨研究所 === 91 === Recently optimization approach can be easily carried out to build a reservoir operation model because of the rapid progress in computer. Many kinds of intelligent optimization approaches have been proposed and widely used to solve a great number of complex optimization problems. Among these methods, the genetic algorithm (GA) and simulated annealing (SA) are two well-known and popularly used methods. The main purpose of this research is to build a mathematical model for reservoir operation. In this study, GA and SA are applied to search the best storage histogram in a reservoir, and a new hybrid model, annealing genetic algorithm (AG) is also implemented and investigated it advantages for reservoir operation. The framework of this study includes a fuzzy programming and the optimization processes. The fuzzy programming theorem is adopted to construct a suitable set of objective function and for reservoir operation, while the optimization methods are used for gaining long-term operation histograms. The Shi-Man reservoir, Taiwan, is used as a case study. The observed monthly inflow data in different hydrological conditions are implemented to simulate the model performances with different optimization approaches. The Generalized Shortage Index (GSI) and total shortage amounts are the criteria for evaluating the model’s performance. The results demonstrate that the annealing genetic algorithm does have great ability to optimize the fuzzy programming model in long-term reservoir operation.