发电机组并行恢复动态决策的熵权方法

Dynamic strategy based on entropy weight theory for parallel restoration of generators

采用并行恢复策略可以加快电力系统大停电后的恢复进程,减少停电损失和社会影响。到目前为止,电力系统并行恢复研究主要集中在分区策略和恢复方案评估与决策方面,从全局层面研究并行恢复动态决策方法则鲜有报道。在此背景下,研究了从整个发电机组恢复过程的角度制定最优恢复策略问题。首先,根据各台发电机组的状态信息,确定每个恢复供电方案中已恢复机组的出力能力和启动待恢复机组所需投入及其恢复对系统全局恢复的效益。然后,建立基于熵权法的机组并行恢复动态优化决策的混合整数线性规划模型,寻求互不冲突的恢复供电方案最优组合。所提出的模型考虑了各台发电机组的状态信息,并能够协调恢复过程中不同机组间的需求冲突。新英格兰10机39节点系统验证了所提方法的可行性与有效性。

The parallel restoration can accelerate the restoration from serious blackout and reduce the outage loss and social impact. The researches of parallel restoration are normally focused on the sectionalizing strategies and restoration scheme evaluation while the study of dynamic parallel restoration strategy at a global level is not found. The optimal restoration strategy is developed with the consideration of whole generator sets. The output power of restored units,the input power needed for restoring the candidate unit and its contribution to the global system restoration are analyzed first according to the status information of generators for each restoration scheme. A mixed integer linear programming model is then built based on the entropy weight theory for the dynamic optimization and decision-making of parallel generators restoration and the optimal combination of restoration schemes without conflicts is obtained. The proposed model fully considers the status information of every generator and appropriately coordinates the power demands among generators. The feasibility and effectiveness of the proposed method is verified by New England 10-unit 39-bus power system.