Optimal energy management in smart buildings with electric vehicles based on economic and risk aspects using developed whale optimization algorithm

Abstract

With the development of smart electricity consumption technology, consumers can benefit from an economically optimized home energy management system, considering their well-being and utilizing electrical appliances. The multi-objective modelling of energy management in smart buildings with the presence of electric vehicles is the main topic of this paper, which also takes risk and economic considerations into account. To make the problem more realistic, various practical and nonlinear constraints are taken into account, such as production limits, flexible loads, and cost-risk limitations and indicators. Since solving this problem with classical methods is challenging and prone to suboptimal solutions, a developed whale optimization algorithm is suggested. In the proposed developed approach, efforts are made to enhance its capabilities and prevent it from converging to local points using local search. Finally, the proposed method and model are discussed and examined under different scenarios. The results demonstrate that when consumers have a positive attitude towards energy consumption, the net cost significantly decreases compared to a conservative attitude. The battery is used during times of favourable prices when users perceive more solar energy availability. Moreover, when users adopt different price risk indicators, these indicators have varying effects on the electricity purchasing strategy of the user.