Multi‐objective unit and load commitment in smart homes considering uncertainties

Although smart homes play an important role in implementing demand-side management programs, the concept is currently faced with challenges in hourly scheduling of devices, because it is difficult for consumers to manually control appliances based on time-varying prices and the power produced by local energy sources. Thus, the operating schedule of home appliances, renewable energy sources, and electric vehicles is optimized using a home energy management system in this paper. A price-based demand response program is utilized for operational scheduling. Renewable energy resources and electric vehicle uncertainties as well as the hourly variation of solar irradiance and wind power are also taken into account. To achieve the best plan of devices operation, a technical-economic formulation is developed for HEM problem, and the multi-objective dragonfly algorithm is used for its optimization. The decision-aid approach is adopted for choosing the best compromise solution, that is, selecting the best operational schedule of home appliances from the Pareto front. Numerical simulations illustrated the proper performance of the proposed method in finding the best schedule of home devices and improving the operation indices of the smart home.