Day-ahead electricity consumption optimization algorithms for smart homes

Abstract The electricity consumption optimization and the advanced tariff schemes are some of the key factors in the demand response programs, which target several aspects such as the minimization of the consumption peak, a reduced electricity bill, the reduction of the consumption, etc. By various incentives, the electricity consumers become more and more active, thus being able to change their consumption behavior as a consequence of the tremendous progress of IT&C and sensor technologies. In this paper, we propose four novel algorithms that are able to minimize the consumption peak for eleven complex smart homes with over three hundred appliances and eight roof-PhotoVoltaic (PV) systems connected to the Internet and smart meters which allow different resolutions for the consumption records. The four algorithms are executed in parallel and the best option is chosen for the day-ahead electricity consumption optimization, while the electricity generated by the PV systems is shared at the community level, further improving the results of the optimization algorithms. In addition, several Time-of-Use (ToU) tariffs are implemented to assess the electricity payment and verify the efficiency of the proposed algorithms.

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