简介：一个热电源系统的效率能被电产生和电消费的操作的工艺的前进改进，这广泛地被认出了。聪明的米启用在顾客和电产生系统之间的双向通讯。电产生系统使用价格刺激(即在高峰时期的更高的价格和在离峰的时期的更低的价格)在聪明的格子环境下面从山峰转移要求的部分到离峰的时期。给在每个时期的那燃料消费是严格地增加的事实电源输出的凸的功能，我们求婚二时期并且多时期定价策略，和研究减少燃料消费上的不同定价策略的效果。

简介：Inthispaper,wefocusonthereal-timeinteractionsamongmultipleutilitycompaniesandmultipleusersandformulatereal-timepricing(RTP)asatwo-stageoptimizationproblem.Atthefirststage,basedoncostfunction,weproposeacontinuoussupplyfunctionbiddingmechanismtomodeltheutilitycompanies’profitmaximizationproblem,bywhichtheanalyticexpressionofelectricitypriceisfurtherderived.Atthesecondstage,consideringthatindividuallyoptimalsolutionmaynotbesociallyoptimal,weemployconvexoptimizationwithlinearconstraintstomodelthepriceanticipatingusers’dailypayoffmaximum.Substitutetheanalyticexpressionofelectricitypriceobtainedatthefirststageintotheoptimizationproblematthesecondstage.Usingcustomizedproximalpointalgorithm(C-PPA),theoptimizationproblematthesecondstageissolvedandelectricitypriceisobtainedaccordingly.WealsoprovetheexistenceanduniquenessoftheNashequilibriuminthementionedtwostageoptimizationandtheconvergenceofC-PPA.Inaddition,inordertomakethealgorithmmorepractical,astatisticalapproachisusedtoobtainthefunctionofpriceonlythroughonlineinformationexchange,insteadofsolvingitdirectly.TheproposedapproachoffersRTP,powerproductionandloadschedulingformultipleutilitycompaniesandmultipleusersinsmartgrid.Statisticalapproachhelpstoprotectthecompany’sprivacyandavoidtheinterferenceofrandomfactors,andC-PPAhasanadvantageoverLagrangianalgorithmbecausetheformerneednotobtaintheobjectionfunctionofthedualoptimizationproblembysolvinganoptimizationproblemwithparameters.Simulationresultsshowthattheproposedframeworkcansignificantlyreducepeaktimeloadingandefficientlybalancesystemenergydistribution.