Based　on　the　intermittent　output　and　inverse　peak　regulation　characteristics　of　wind　power,　a　multisource　peak　regulation　transaction　optimization　model　that　considers　the　feasibility　of　combining　thermal　power,　energy　storage,　and　demand　response　for　both　power　generation　and　consumption　is　proposed　in　this　paper.　First,　a　multisource　peak　regulation　transaction　cost　model　is　established　by　considering　flexible　load　participation　in　peak　regulation　and　price-　and　incentive-based　demand　responses.　Subsequently,　with　the　objective　of　minimizing　both　the　peak　regulation　cost　and　wind　curtailment　rate,　a　reduced　half　gradient　membership　function　is　selected　to　transform　the　multiobjective　model.　Finally,　by　analyzing　the　roles　of　the　different　subjects　in　multisource　peak　regulation　transactions,　a　compensation　mechanism　based　on　the　Shapley　method　is　designed,　and　a　local　power　grid　in　northeast　China　is　chosen　as　the　simulation　object.　The　results　show　the　following:　(1)　When　the　thermal　power　generators　(TPGs)　transit　from　regular　peak　regulation　to　deep　peak　regulation,　the　wind　curtailment　rate　decreases　by　5.10%,　and　the　peak　regulation　cost　increases　by　$　0.793　x　10(6).　This　indicates　that　the　peak　regulation　cost　of　the　TPGs　and　the　income　of　the　on-grid　wind　power　need　to　be　balanced.　(2)　When　the　energy　storage　and　the　demand　response　are　combined　for　peak　regulation,　both　the　peak　load　regulation　cost　and　wind　curtailment　rate　reach　the　optimal　values,　decreasing　by　$　0.642　x　10(6)　and　5.72%,　respectively,　showing　cooperative　optimization.　However,　the　TPGs　require　a　higher　regulation　cost,　whereas　the　other　subjects　achieve　incremental　benefits.　(3)　The　compensation　mechanism　assists　each　subject　in　obtaining　incremental　benefits　depending　on　the　contribution　rate.　With　the　strengthening　of　the　peak　regulation　of　the　TPGs,　more　energy　storage　and　demand　response　output　are　introduced　to　meet　the　urgent　peak　regulation　requirement,　which　leads　to　increased　regulation　revenue　and　optimal　dispatching.　In　summary,　the　proposed　transaction　and　compensation　mechanism　of　multisource　peak　regulation　can　be　used　to　balance　the　peak　regulation　ability　and　contributions　of　different　subjects　and　establish　the　optimal　peak　regulation　scheme.　(C)　2022　The　Author(s).　Published　by　Elsevier　Ltd.