Fuzzy Optimal Dispatching of Low-Carbon Regional Integrated Energy System Considering Source-Load Uncertainty

Abstract

The optimal dispatching of the regional integrated energy system (RIES) is of great significance to realizing the multi-energy complementarity and economic operation of the system. However, the intermittence of renewable energy and the uncertainty of load demand in the RIES cause the random fluctuations of both supply and demand sides in the system. To solve this problem, a low-carbon economic dispatching model considering fuzzy opportunity constraints is proposed in this paper, taking into account the influence of the uncertainty on both sides of the source and load on the low-carbon dispatching of the RIES. Fuzzy membership parameters are used to characterize the uncertainty of renewable energy and load demand. A credibility fuzzy chance constraint model considering the uncertainty of wind power, photovoltaic and load demand is constructed. After the clear equivalence class transformation, GUROBI is used to solve the fuzzy dispatching problem. Finally, a study case shows that the proposed model can effectively improve the reliability and economy of the optimal dispatching scheme and reduce carbon emissions.