Seasonal Scheduling of Office Electricity Use via Adaptive Dynamic Programming
【摘要】：In this paper, an adaptive dynamic programming(ADP) based optimization method is proposed to schedule the electricity use of an office, where a battery is considered as the control variable, while solar and wind energies are included as additional energy supplies besides the grid. The electricity demand of an office generally contains socket, lighting and airconditioning demands. Based on the periodic models of electricity price, electricity demand, and solar and wind energies, the optimal control strategies of the battery are determined by the proposed ADP based optimization method, so that the electricity cost from the grid can be saved. Simulation analysis demonstrates that the proposed method can achieve optimal real-time scheduling of office electricity use in different seasons of a year.