The　commercialization　process　of　energy　storage　patents　affects　the　development　of　the　energy　storage　industry.　Clarifying　the　relationships　between　the　characteristics　of　the　applicants　and　patent　transfer　can　facilitate　technology　transfer.　In　this　study,　China＇s　energy　storage　patent　data　from　2009　to　2021　were　divided　by　the　rolling　period.　Based　on　this,　the　patent　cooperation　network,　knowledge　network,　and　transfer　network　were　constructed　via　social　network　analysis.　The　analysis　reveals　the　following.　First,　the　number　of　industry　-university-research　institutions　that　jointly　apply　for　patents　is　increasing,　and　the　knowledge　field　is　also　expanding.　Cooperation　and　transfer　activities　are　more　frequent　in　the　eastern　developed　regions　of　China.　Second,　by　using　grey　relational　analysis　theory,　it　was　found　that　the　degree　centrality,　closeness　centrality,　and　clustering　coefficient　of　the　cooperation　network　are　closely　related　to　the　transfer　network.　Compared　with　the　cooperation　network,　the　energy　storage　knowledge　network　has　a　more　significant　relationship　with　the　transfer　network.　The　knowledge　elements　stock　of　patent　transferor　and　transferee　is　more　relevant　to　patent　transfer　activity　than　the　patent　stock.　This　also　proves　that　the　knowledge　and　cooperation　networks　are　decoupled.　Additionally,　patent　applicants　for　energy　storage　patents　should　focus　not　only　on　their　past　average　locations　to　maintain　the　competitive　advantage,　but　also　on　future　location　trends　to　seize　development　opportunities.　Finally,　the　proposed　recommendations　can　help　applicants　facilitate　patent　transfer　activities　in　the　energy　storage　industry　by　adjusting　the　location　of　the　network.