To　contribute　to　the　intelligence　and　knowledge　of　power　grid　regulation　and　control　operations,　this　paper　presents　a　method　of　power　grid　regulation　knowledge　modeling　based　on　ELG　(Event　Logic　Graph),　which　includes　an　event　word　extraction　based　on　a　predicate-argument　model,　an　event　chain　extraction　and　fusion　based　on　event　similarity　theory,　an　event　generalization　based　on　a　soft-pattern　algorithm,　and　an　event　relationship　recognition　based　on　rule　pattern　matching　method　and　joint　constraints.　Finally,　this　paper　uses　events　as　nodes　and　event　relationships　as　directed　edges　to　construct　an　affair　graph　stipulated　by　the　power　grid　regulation　and　control　regulations.　The　ELG　is　also　called　the　new　generation　knowledge　graph.　But　the　knowledge　graph　can　only　describe　the　existence　of　entities　and　the　upper　and　lower　associations　between　entities.　ELG　can　explain　the　inheritance,　causality　between　entities　and　the　logic　of　affair　evolution,　and　the　probability　of　transition　between　legacy　and　causality.　Therefore,　knowledge　modeling　based　on　ELG　has　intelligent　advantages.　Also,　compared　with　ontology-based　knowledge　modeling　methods,　the　method　proposed　in　this　paper　can　realize　the　dynamic　representation　of　control　operation　knowledge,　can　express　the　logic　of　behavior　and　logic　of　operation,　and　also　has　higher　retrieval　accuracy.　©　2021　Institute　of　Physics　Publishing.　All　rights　reserved.