1.College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.Shanghai Keliang Information Technology Co., Ltd., Shanghai 200030, China

Aiming at the issue that the existing price-based demand response models are difficult to accurately reflect the randomness and fuzziness of response behaviors of users at the same time, and the modeling of demand response based on symmetric cloud model has the problems such as high fitting error and weak solution stability, an uncertainty modeling method for price-based demand response based on multi-step backward cloud generator and semi-cloud model is proposed. The return rate is defined as the unified evaluation standard for the cognition of the return amount by different users, and the mapping relationship model between the return rate and the response behaviors of users based on the semi-cloud model is established. The multi-step backward cloud generator is used to obtain the digital characteristics of the semi-cloud model, and the forward cloud generator is used to generate the distribution cloud map reflecting the response behaviors of users. The simulation examples show that the semi- cloud model has higher fitting accuracy compared with the symmetric cloud model and the traditional price-based demand response modeling method; the multi-step backward cloud generator has better stability compared with the single-step backward cloud generator.