Application of Multi-objective Evolutionary Algorithm to Cascade Reservoirs Operation
In this paper, a multi-objective evolutionary algorithm, the non-dominated sorting genetic algorithm (NSGA-Ⅱ), is applied to examine the operations of four cascade reservoirs system in the upper Wujiang River, Guizhou Province of China. The Optimization model is established with two objects, which are the maximal generation of and the firm power in certain probability. The NSGA-Ⅱ is applied to simulate optimal operating strategies based on a 10 year data set Two representative algorithms, dynamic programming with successive approximation (SADP) and discrete differential dynamic programming, are also applied to evaluate simulation performance. The result demonstrates that both the annual generation and the firm power of cascade system, derived from NSGA-Ⅱ, are superior to the traditional strategy and the other two algorithms. It indicated that NSGA-Ⅱ exhibits obvious advantage on solution of complex multi-variable and multi-objective problems on comparison with other traditional optimization algorithms.
optimization model cascade reservoirs multiobjective evolutionary algorithm non-dominated sorting genetic algorithm wujiang river
Ma Kai Lu ShiBao Huang Qiang
Kay Lab of Northwest Water Resources an Environment Ecology of MOE, Xian University of Technology, P.R.China 710048 Xian, China
国际会议
太原
英文
484-487
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）