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Towards Optimal Planning and Scheduling in Smart Homes

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Document pages: 24 pages

Abstract: This research addresses the planningand scheduling problem in and among thesmart homes in a community microgrid. We develop a bi-linear algorithm, namedECO-Trade to generate the near-optimal schedules of the households’ loads, storage andenergy sources. The algorithm also facilitates Peer-to-Peer (P2P) energytrading among the smart homes in a community microgrid. However, P2P tradingpotentially results in an unfair cost distribution among the participatinghouseholds. To the best of our knowledge, the ECO-Trade algorithm is the firstnear-optimal cost optimization algorithm which considers the unfair costdistribution problem for a Demand Side Management (DSM) system coordinated withP2P energy trading. It also solves the time complexity problem of ourpreviously proposed optimal model. Our results show that the solution time ofthe ECO-Trade algorithm is mostly less than a minute. It also shows that 97 ofthe solutions generated by the ECO-Trade algorithm are optimal solutions.Furthermore, we analyze the solutions and identify that the algorithm sometimesgets trapped at a local minimum because it alternately sets the microgrid priceand quantity as constants. Finally, we describe the reasons of the costincrease by a local minimum and analyze its impact on cost optimization.

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