Research On Restoration Algrithms In Power System After Wide Area Blackout

The interconnection of power grids meets the growing demand for electricity in modern society, also leads to more complex network structure which brings lots of potential threat to the power system operation. The effects of wide area outages in such huge power system may be quite more severe too. Therefore, as an important defense measure, the research on the restoration of the power supply safely, promptly and orderly after wide area outage which caused by faults is of great theoretical and practical significance. It will help to speed up the system restoration and reduce the loss. It's also an important part in the construction of the smart power network.The problem of restoration after wide area service interruption is a complex decision-making and control problem. It can be described as a multi-objective, multiple-participant, multi-stage, combinatorial, nonlinear optimization problem with constraints. Using appropriate optimization algorithms to make decision in the restoration process after wide area outage is quite essential. According to the three stages of a general restoration process, this thesis focuses on the following issues:1. A method to predict the over-voltage that may appear during the process of energizing the no-load long transmission lines by using the Support Vector Machine theory is presented. The comparison with the Neural Network's prediction results and EMTP calculation results shows that the method to predict over-voltage with the Support Vector Machine theory works well, and can meet the prediction requirement for speed and accuracy.2. A method to evaluate the node importance in power system grid is proposed. Describe the power grid in a weighted complex first, and then an improved node contraction and node importance evaluation method in weighted complex network is adopted to evaluate the node importance in weighted power system network. Determine the important nodes to reconstruct in current stage after appropriate adjustments based on the nodes actual importance and the importance assessment results above. Then by using the Kruskal algorithm to construct the minimum spanning tree of the power network, through the appropriate branches cut , a local minimum spanning tree that covering all the selected important nodes can be constructed as the skeleton- network.3. An Ant Colony algorithm combining with the Shortest Path algorithm is adopted to optimize the skeleton- network structure, give the path and node restoration sequence too. The combined algorithm consists of two layers. The outer calculation solves the nodes sequence by Ant Colony algorithm. The shortest path algorithm in the inner calculation provides the distance and path between each important node and the equivalent power supply area. The distance is also the basis for updating Pheromone in Ant Colony algorithm. Examples show the effectiveness of the method.4. An improved Ant Colony algorithm is used for the network optimization in the load restoration phase. The maximum amount of recovery load in current step can be calculated by an extended power flow method on the basis of system reserve capacity. Then an improved Ant Colony algorithm which combined with a random topology search strategy is used to optimize the network for load recovery. Improved pheromone update strategy expand the searching scope of the proposed algorithm, ensure a greater opportunity for the global optimal solution. By memorize some better recovery modes searched, the time used to verify the recovery schema by time-consuming power flow calculation can be greatly reduced. Several examples show the effectiveness of the proposed algorithm for load recovery optimization. The proposed algorithm is suitable for all stages in load recovery optimization.