The residential sector is gaining a more active role in the management of energy resources with the deployment of microgeneration based on renewables, the development of bidirectional communication infrastructures, and the new technologies of the power grid systems including smart metering. The consumer becomes an active agent and should be able to make decisions about the usage of his loads, while keeping the quality of the energy services provided. We propose an integrated energy management approach using Markovian processes that, based on weather conditions, local storage of renewable energy, time based tariffs, and grid/technical constraints, optimally allocates the available resources to fulfill the energy requirements. The goal is to reduce the energy bill, while maintaining the consumer's satisfaction. The results show that a significant bill reduction can be obtained depending on the tariff structure and technology used. A comparison with a genetic algorithm used for the same purpose is also provided.
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Nistor et al. (2016) studied this question.
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