个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:水利工程系
学科:水文学及水资源. 水利水电工程
联系方式:wuxinyu@dlut.edu.cn
电子邮箱:wuxinyu@dlut.edu.cn
Stochastic dynamic programming for hydropower reservoir operations with multiple local optima
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论文类型:期刊论文
发表时间:2018-09-01
发表刊物:JOURNAL OF HYDROLOGY
收录刊物:SCIE、EI
卷号:564
页面范围:712-722
ISSN号:0022-1694
关键字:Cascaded reservoir; Operating rule; SDP; Global optimization
摘要:Multiple optima seriously confine the solution accuracy of stochastic dynamic programming (SDP) for non-concave maximization models of reservoir operation. To address the problem, a two-stage optimization algorithm combining traversing and search is proposed to obtain an optimal decision at each state combination. Single or multiple promising regions where a local optimal solution may exist are identified through coarse traversing in the whole feasible region, and a local search algorithm is used to local optimization in each promising region. Energy maximization model is used to analyze the multiple optima problem and test the method. In the model, quadratic and concave penalty functions are used to address the total power constraint for smaller shortages and fewer shortage periods respectively. The total power constraint increases the probability of multiple local optima existence and intensifies the difficulty in finding optimal decisions. The proposed model and method are applied to the cascaded reservoir system on middle-lower Lancang River in China. Numerical results show that the total power constraint is well addressed, the computing time can be reduced by more than 50% using the two-stage algorithm in getting operating rules with similar performance comparing to only traversing, and the multi-point search algorithm is superior to traversing and single point search in solving the proposed model.