摘要：In recent years, power grid accidents have occurred frequently and higher requirements have been placed on their safety operation. In current safety management in the world, there is an effective practice that uses a unified standard for structuring an accident case database and based on that database, conducts quantitative analysis to cope with accident risks. However, that is not the case for power safety management. Case-based reasoning (CBR) is such a process that solves new problems based on the solutions to similar past problems. It works by matching a current problem with historical cases and solutions in a database, in order to obtain similar case solutions or inspirations. In the matching process, if necessary, such past solutions may be modified in order to better adapt to the current actual problems. Based on the CBR method, this paper proposes how to construct a case database of power grid operational accidents, provide data support for management of power grid risks and provide knowledge services for accurate grasping of grid accident development dynamics and making quick decisions to rapidly response to the emergencies. First, it designs an operational accident case database after considering the following three aspects: case features, power grid features and accident features based on safety management theory. Secondly, in terms of how to use the power grid operational accident case database, it proposed a two-level search strategy, as well as the corresponding similarity calculation methods for different feature attributes of the case. Finally, it carried out a demonstration to verify the model by selecting four typical grid accidents. The grid database and CBR strategy proposed in this article could help China’s power grids practice intelligent analysis of grid operational accidents and improve digitalization in safety management.
关键词：power grid operational accident; case-based reasoning; case database; case collection; similarity calculation power grid operational accident ; case-based reasoning ; case database ; case collection ; similarity calculation
