Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties

Aiming at the problems that the uncertainty modeling process of price-based demand response is oversimplified, inconsistent for change pattern of error, and the reliability in user's comprehensive satisfaction is neglected in the optimal scheduling for power system under multiple uncertainties, integrated factors of economy, environment and society, a multi-objective robust fuzzy optimal scheduling model considering power demand response and user's comprehensive satisfaction with electricity under multiple uncertainties is proposed. On the basis of analyzing the operation mechanism of the multi-source system and the characteristics of multiple uncertainty sources, the robust theory is used to construct power output model of wind and photovoltaic (PV), and the fuzzy theory is used to construct power demand response model. Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO₂ and atmospheric pollutants as environmental objective and the largest user's comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. Based on the improved IEEE-39 node system to verify the validity and superiority of the price-based demand response uncertainty modelling method and multiple uncertainty modelling method in this paper, as well as the reasonableness and necessity for considering the reliability in the user's comprehensive satisfaction with electricity and the multiple uncertainties in power system optimal scheduling.