For residential loads with photovoltaic(PV) system and energy storage system, in view of the characteristics that the forecast accuracy of PV systems decreases gradually with the growing time-scale, also the consumption behavior of residential consumers has the characteristics of uncertainty, the models for distributed energy sources, residential loads and the uncertainty of residential consumers’ behavior are built in the paper. Based on that, a stochastic adjustable robust optimization hybrid co-scheduling strategy for smart residential electricity consumption is proposed, taking advantages of both optimization methods. It is aimed at minimizing the operating cost of the system and increasing the PV local consumption, meeting the requirements of comfort level and consumption freedom. With the engineering game theory and Improved Particle Swarm Optimization, the optimization model is transformed to Mixed Integer Linear Programming. Through the simulation results of the test system the effectiveness of the strategy is proved.
