Group Intelligent Decision Support System for Power System Skeleton Restoration

Power system skeleton restoration is a typical semi-structured problem and difficult to establish accurate mathematical model. Constrains such as transient overvoltages, sustained power frequency overvoltages, self-excitation, and restoration duration are comprehensively considered in this paper. A model of group intelligent decision support system for power system skeleton restoration is constructed, three parts of which are comprehensive data platform, intelligent control sub-system and group decision support sub-system. The multi-attribute utility theory is employed to dynamically determine next restoration target. This system can not only generate feasible cases for case-based reasoning, but also provide online supports in actual process of restoration.