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In this paper, we investigate the management of energy storage control andload scheduling in scenarios considering a grid-connected photovoltaic (PV)system using packetized energy management. The aim is to reduce an averageaggregated system cost through the proposed \textit{packetized energymanagement controller} considering household energy consumption, procurementprice, load scheduling delays, PV self-sufficiency via generated renewableenergy and battery degradation. The proposed approach solves the jointoptimization problem using established heuristics, namely genetic algorithm(GA), binary particle swarm optimization (BPSO), and differential evolution(DE). Additionally, the performances of heuristic algorithms are also comparedin terms of the effectiveness of load scheduling with delay constraints,packetized energy transactions, and battery degradation cost. Case studies havebeen provided to demonstrate and extensively evaluate the algorithms. Thenumerical results show that the proposed packetized energy managementcontroller can considerably reduce the aggregated average system cost up to4.7\%, 5.14\%, and 1.35\% by GA, BPSO, and DE, respectively while meeting thepacketized energy demand and scheduling delays requirements.

Packetized Energy Management Controller for Residential Consumers