大规模电网分层分区解耦的最优潮流
[Abstract]:With the expansion of power system scale and the promotion of regional power network interconnection project, the traditional centralized optimal power flow becomes more and more difficult to meet the requirements of on-line analysis and real-time control. At the same time, there are some problems such as high risk of data leakage, large amount of data transmission, calculation of "dimension disaster" and so on. Fast, efficient and stable partition decoupling distributed algorithm has become the key to solve large scale OPF. In order to realize the divisional decoupling computation, a large power system should be divided into several regional systems by using the partition method, and then the distributed decoupling computing of the multi-area system is carried out by using the decomposition and coordination algorithm. Therefore, this paper mainly involves two main contents, one is partition method, the other is decomposition and coordination algorithm. In the area of power grid partition, this paper proposes a voltage partition method. 500kV / 220kV electromagnetic ring network, which is suitable for the hierarchical partition structure, will bring a lot of adverse effects to the power system operation. It will be the development direction of the power network to open the electromagnetic ring network to form a layered and partitioned grid structure. Based on the characteristics of hierarchical partition structure, a partition method based on 220kV voltage grade is proposed. The large power grid is divided into transmission networks with 500kV and above voltage levels and high voltage distribution networks with multiple 220kV and voltage levels below. In this way, several subnets with moderate scale and weak coupling between regions can be obtained, which are also suitable for power dispatching based on voltage level in reality. In the realization of classifying the whole network data by region, the nodal injection current method is proposed. In order to solve the optimal power flow problem for multi-region systems, two efficient decomposition and coordination algorithms, the decomposition coordinated interior point method, are used to improve the approximate Newton direction method. By dividing the boundary nodes into two and adding the coupling constraints, the decomposition and coordination interior point method realizes the equivalent transformation of the multi-region model, and uses the robust modern interior point method to solve the problem. The internal variables of each region are kept independent of each other, only the information of boundary variables is transferred and coordinated, thus the distributed optimal power flow calculation after partition decoupling is realized, and the improved approximate Newton direction method is based on the approximate Newton direction method. The gradient part of the power flow equation is preserved in the reduced correction equation, which makes the obtained approximate Newton direction approach to the pure Newton direction better, and it can also achieve complete decoupling for the strongly coupled system. Both of the proposed decomposition and coordination algorithms have a remarkable characteristic, and the modified equations have diagonal edge structure. The diagonal triangulation structure can be used to reduce the order decoupling of the modified equation, which greatly reduces the dimension of the modified equation, improves the computing speed and reduces the computer memory consumption, and also realizes the partition decoupling calculation. Firstly, the proposed node injection current method is used to realize the fast partitioning of power system. Then, two decomposition and coordination algorithms are used to verify the optimal power flow of the multi-area system formed after partitioning. The results show that the two decoupling algorithms can improve the efficiency of calculation and realize the partition decoupling calculation of large grid. This decoupling method also has a wide application prospect for other large-scale optimization problems.
【学位授予单位】:广西大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TM744
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