Bidirectional EV integration in home load energy management using swarm intelligence

A swarm-based meta-heuristic search approach has been adopted in this study for Home Load Energy Management set-up (HLEMs) to schedule smart appliances with minimum energy bills utilising the bidirectional energy flow of Electric Vehicles (EV). The Instant state of charge (IOC) level of EV is utilised to achieve the proper scheduling of home loads by considering the energy threshold with a cost-effective user opulence. The problem objective is formulated with a meta-heuristic population-based elephant herding optimisation technique to schedule the home loads along with the EV to incur a minimum bill of daily energy expenditure and also to enhance the utilisation of daily average power by minimising the peak to average ratio of a typical smart home. The analysis has been compared with the Grey Wolf Optimisation scheduling technique to prove the proficiency of the proposed method.