基于拓扑连通性约束遗传算法的主动解列断面搜索

随着大规模新能源互联电网的发展，电力系统发生连锁故障的风险越来越高，适当的主动解列可以阻止故障的传播。为解决主动解列断面求解过程中的系统拓扑连通性和计算复杂度高的问题，提出了一种含拓扑连通性约束遗传算法的主动解列断面搜索方法。该方法首先构建了解列断面搜索的数学模型，然后基于图论知识提出了一种系统拓扑连通性约束，并加入到遗传算法中。同时提出了一种系统拓扑简化和预处理方法。最后将简化后的系统拓扑和数据输入到含拓扑连通性约束的遗传算法中进行主动解列断面的求解。IEEE 118节点系统算例表明，所提算法能够保证求解出的主动解列断面具有拓扑连通性且有功功率基本平衡，系统拓扑简化和预处理方法能够有效提高算法的运行效率。

Intentional islanding section searching based on a genetic algorithm with a topological connectivity constraint

With the development of large-scale renewable energy power grids, the risk of cascading failures is becoming increasingly higher. Appropriate intentional islanding can prevent the spread of faults. To solve the problems of topological connectivity of power systems and high computational complexity in the process of intentional islanding sections, this paper proposes an intentional islanding section search method with a topological connectivity constraint genetic algorithm. The method first constructs a mathematical model for intentional islanding section searching, and then proposes a system topology connectivity constraint based on the knowledge of graph theory. This is added to the genetic algorithm. At the same time, a system topology simplification and preprocessing method is proposed. Finally, the simplified system topology and data is input into the genetic algorithm with topological connectivity constraint to solve the intentional islanding sections. The calculation example on the IEEE 118 node system shows that the proposed algorithm can ensure that the solved intentional islanding sections has topological connectivity and basically achieves active power balance, and the system topology simplification and preprocessing methods can effectively improve the efficiency of the algorithm. This work is supported by the Science and Technology Project of the Headquarters of State Grid Corporation of China (No. 5211DS21N013).