Due　to　the　large　number　and　strong　randomness　of　EVs　(electric　vehicles),　their　participation　in　the　peak　adjustment　demand　response　of　the　grid　through　V2G　aggregators　is　highly　uncertain,　which　not　only　affects　the　operation　quality　of　the　grid,　but　also　cannot　guarantee　the　economic　benefits　of　aggregators　and　users.　Therefore,　an　effective　response　mechanism　is　urgently　needed　to　guide　EV　to　reasonably　participate　in　the　grid　service.　In　consideration　of　the　profitability　requirements　and　development　prospects　for　V2G　aggregation　businesses,　we　propose　a　multi-temporal　optimization　scheduling　strategy　that　takes　into　account　the　reliability　of　EV　peak　demand　response.Firstly,　the　day-ahead　pre-scheduling　of　EV　demand　response　is　carried　out　with　the　goal　of　optimal　integrity-capacity　comprehensive　index　of　EV　cluster.　Secondly,　in　order　to　cope　with　the　adverse　impact　of　intra-day　EV　default　uncertainty　on　peak　demand　response,　the　V2G　aggregator　uses　the　intra-day　default　emergency　mechanism　to　conduct　emergency　response　invitation　for　the　whole　range　of　EVs,　and　then　optimizes　EV　scheduling　with　the　dynamic　evaluation　model　with　the　optimal　response　reliability　index.　Then,　the　benefits　related　to　peak　regulation　demand　response　are　evaluated　by　V2G　aggregators　and　on　EVs　sides,　including　the　demand　response　benefits　and　default　costs　of　the　power　grid　and　aggregators,　as　well　as　aggregators　and　EVs.　In　addition,　the　surplus　of　the　default　capital　pool　of　V2G　aggregators　is　issued　to　EV　with　good　credit　in　the　form　of　credit　incentives　to　encourage　EV　to　keep　its　promise.　Finally,　a　simulation　example　is　used　to　verify　that　the　proposed　optimal　scheduling　strategy　for　peak　demand　response　can　effectively　improve　the　reliability　of　EV　cluster　response　and　increase　the　effectiveness　of　economic　benefits　for　EV　and　V2G　aggregators.　©　2025　Science　Press.　All　rights　reserved.