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Optimal day-ahead scheduling for a system-centric community energy managementsystem (CEMS) is proposed to provide economic benefits and user comfort ofenergy management at the community level. Our proposed community includesdifferent types of homes and allows prosumers to trade energy locally usingmid-market rate pricing. A mathematical model of the community is constructedand the optimization problem of this model is transformed into an MILP problemthat can be solved in a short time. By solving this MILP problem, theoptimization of the overall energy cost of the community and satisfaction ofthe thermal comfort at every home are achieved. For comparison, we alsoestablish two different scenarios for the same community: a prosumer-centricCEMS and no CEMS. The simulation results demonstrate that the overall energycost of the community with the system-centric CEMS is the smallest among thethree scenarios and is only half that of the community with theprosumer-centric CEMS. Moreover, by using linear transformation, thecomputational time of the optimization problem of the proposed system-centricCEMS is only 118.2 s for a 500-home community, which is a short time forday-ahead scheduling of a community.

MILP-based optimal day-ahead scheduling for system-centric CEMS supporting different types of homes and energy trading