论文名称：耦合KL理论与调度特征的大规模水电站群优化调度降维方法
发表刊物：Shuili Xuebao/Journal of Hydraulic Engineering
卷号：52
期号：2
页面范围：169-181
ISSN号：0559-9350
摘要：The computing efficiency of the optimal operation of large-scale hydropower plants is one of the toughest problems in the operation of hydropower and power systems, which is a theoretical and technical barrier to solve the complex system with more than 100 hydropower plants. This study presents a dimension reduction method for optimal operation of large-scale hydropower plants with Karhunen-Loève (KL) theory and dispatching features. Based on a long series of historical operation records, the principal component analysis is used to identify characteristic value of water level change in the front of the dam and corresponding characteristic function. The KL expansion method is then introduced to represent random variables of the water level at any period as a linear function of characteristic terms of reservoir level change. Thus, the operation decision of a specified reservoir inflow process can be determined by a combination of random coefficients of all characteristic terms. A framework of iterative optimization is constructed, where a solution procedure for searching random coefficients of characteristic terms is given to efficiently solve optimal operations of large-scale hydropower plants. The presented method is verified by long-term operations of a provincial hydropower system with more than 100 plants in Yunnan. The validity, efficiency, and sensitivity of this method are respectively demonstrated by several case studies. A comparison with conventional dynamic programming and its modifications shows that the method contributes a substantial improvement of computational efficiency while ensuring basically the same solution accuracy. © 2021, China Water Power Press. All right reserved.
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发表时间：2021-01-01