Home energy management in a residential smart micro grid under stochastic penetration of solar panels and electric vehicles

Implementing demand side management programs in a residential area causes to increase the role of consumers in managing the total power network. Moreover, the owner of the smart home can reduce energy dependence on the power network and also his electricity bill by using optimal managing the operational schedule of home appliances and available generated power of renewable distributed generation and electric vehicle. In this paper, a new multi-objective scheduling method based on intelligent algorithms is utilized for energy managing in smart homes of a residential micro grid. Home appliances, rooftop photovoltaic panel and plug-in hybrid electric vehicle are schedulable devices of each smart home. Photovoltaic and electric vehicle uncertainties are also considered. The combination algorithm of the multi-objective dragonfly algorithm and analytical hierarchy process method is used for optimizing the techno-economic objective function and finding the best schedule of devices. Real-time pricing tariff is considered as the price-based demand response program. For evaluating the efficiency of the proposed method, it is applied to a smart micro grid with 20-smart home. The numerical result demonstrates the appropriate performance of the proposed home energy management method in reducing the electricity bill of smart homes and peak demand of the residential smart micro grid.