Electrical energy consumption is steadily growing worldwide, while renewable energy sources are gaining market share. In parallel, energy systems are undergoing a profound transformation, moving from a top-down hierarchical structure to a more decentralized model focused on the consumer, who will also produce, store and sell their own energy.
This paper proposes a decision algorithm designed to help with the energy management task, in the context of a grid-connected household, with renewable energy production and electric vehicles (EVs). The algorithm makes use of several inputs such as energy consumption prediction, energy production output, EV battery state, and grid energy price in order to perform the optimal charge and discharge actions.
The proposed algorithm was validated in a simulated environment attaining an average decrease of 18.9% in the energy cost of the household.