Abstract: Few traditional demand response strategies consider an environment using renewable energy generation and storage systems, and such traditional strategies are not able to accommodate developmental trends and new challenges. For example, the randomness of power generation via renewable energy introduces cost risks for a demand response strategy, and the buffering effect of the storage system increases the complexity of the demand response model. This paper focuses on such issues and investigates a residential demand side response strategy that considers energy storage and renewable-energy-sourced generators. By considering the randomness of renewable energy and the buffering effect of the battery system, a two-stage stochastic programming model is constructed for a residential demand side response to reduce the cost risks due to forecast errors. Furthermore, a compromise between accuracy and the computation complexity of the model is determined that solves the model quickly without requiring a complex heuristics algorithm. Finally, the effectiveness of the proposed demand response strategy is verified using a comparison with the deterministic approach.