Intelligent energy management system for buildings with renewables and vehicle-to-grid charging

• Autor(a) principal: Silva, João Nuno Pereira
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/35771
• topic: Smart home; Energy; EV; Household; Load demand; Consumption forecast; Decision algorithm; Energy management system; HEMS; ML

Renewable energies have recently seen a strong development. The awareness of the masses regarding the pollution due to fossil fuels is rising and with it, the use of electric vehicles (EVs). Hence, there is an increasing effort to keep energy distribution sustainable and to find ways of reducing its price. The aim of this study is to build a decision algorithm that will help minimize the electrical bill of a household, making use of V2H (Vehicle-to- Home) chargers. In this approach EVs can be used to store energy, which can then be supplied to the household during periods of high demand. One of the inputs that the designed algorithm requires is the household’s energy consumption forecast. Therefore, a energy consumption predictor was developed in this work altogether with a version that does not require past information of the specific household. This predictor is useful while there is not enough past data to train a more reliable model. The decision algorithm was tested in a simulated environment against a baseline decision algorithm. In the several scenarios and test houses, the proposed approach attained an average of 19.29% decrease in the energy expenses of the household.