Natural disasters such as earthquake, tsunami, storm etc. can cause power outages and limitations on the grid. Moreover, power limitations or outages up to 24 h can be applied to the disaster area as a precaution, even if there is no damage in the buildings and power system components. The reflection of the power limitations or outages can be vital for sufferers in post-disaster conditions. However, their impacts can be prevented by using electric vehicles as a mobile source in home energy systems. Electric vehicles are offering a promising technology as mobile emergency power source which ensure energy availability for critical demands in disaster conditions. Therefore, in this study a dynamic home energy management system (HEMS) algorithm that classifies all the appliances according to their importance in post-disaster conditions is proposed to enhance grid resiliency via preventing energy interruption of residential buildings. The algorithm utilizes efficient usage of local renewable energy sources (RESs) and electric vehicles (EVs). Load curtailment methods are applied considering the worst load consumption for the next 24 h according to the prospective remaining energy (PRE) of the EV battery (EVB). The main objective of the proposed algorithm is to arrange the permitted loads dynamically according to their importance levels in order to prevent energy interruption of a home. The proposed algorithm is verified with case based scenarios in MATLAB®/Simulink® environment by using experimentally gathered load and weather condition data. The energized time of the critical loads are prolonged up to %241 with the proposed algorithm.
Elsevier, Sustainable Energy, Grids and Networks, Volume 34, June 2023, 101015
