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作 者:肖胜贤 伍永刚[1] 章国勇[1] 胡斌奇[2] 成涛[2]
机构地区:[1]华中科技大学水电与数字化工程学院,湖北省武汉市430074 [2]湖南省电力公司电力调度通信局,湖南省长沙市410007
出 处:《电网技术》2015年第7期1900-1906,共7页Power System Technology
基 金:国家自然科学基金(51379081);国家电网公司科技项目(DKJS-13-00220)~~
摘 要:针对水库群优化调度这一典型的多维非线性规划问题,基于逐步优化算法(progressive optimality algorithm,POA)和逐步逼近策略(dynamic programming successive approximation,DPSA)的时间和空间降维优势,同时考虑到POA-DPSA方法输出伪最优解的可能性,引入广义时间和广义空间状态概念,对陷入伪最优解下的状态变量进行变阶段联合调整,提高了算法的全局寻优性能。同时,为保证算法的高效求解,在保持广义状态内部一致性的前提下,提出一种等约束滑行策略对各子阶段状态量进行调整。经典4库和10座水库群及湖南沅水流域优化调度结果表明,改进算法能有效提高水电站群联合发电效益,且寻优效率高,为水电站群优化调度工程应用提供新的方法。An advanced progressive optimality algorithm-dynamic programming successive approximation(POA-DPSA) is proposed to optimize the operation of multi-reservoir plants, which is a typical highly nonlinear, multi-dimensional programming problem. In view of the advantage of POA and DPSA in reducing the dimensions of stages and the cardinal number of multi-reservoir system, the POA-DPSA method is firstly constructed. However, it is found out that conventional POA-DPSA suffers from the disadvantage of pseudo optimization solution. This paper proposes a novel POA-DPSA method with generalized time and space state analysis, in which a combined multi-stage adjustment strategy is applied to provide new search space for the iterative loop when it falls into the pseudo optimization solution. For the above adjustment strategy, the variables of each stage in generalized state move along the boundary constraints under the condition of the same relationship among them, hence ensuring high efficiency. The validity of the proposed approach is demonstrated by applying it to two test systems consisting of 4 and 10 reservoirs respectively and Yushui River in Hunan. Compared to the existing methods, the proposed method is found more effective for multi-reservoir optimal operation with higher accuracy and less computational cost.
分 类 号:TM721[电气工程—电力系统及自动化]
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