Robust Optimal Scheduling of Power-Gas Interconnected Integrated Energy System with Double Uncertainty of Source and Load

Aiming at the risk of uncertainties to operation and scheduling of the electric-gas interconnected integrated energy system, a robust optimal scheduling model for this system is proposed by considering double uncertainties of new energy and load. A stochastic programming model for the integrated energy system with Electricity-Gas interconnection is established with the total minimal operating cost as the objective function. The moment uncertainty distributed robust optimization method (DRO-MU) is used to construct the uncertainty set of wind power output and load. Under the source-load double uncertainty set, the stochastic programming model is transformed into a moment-indeterminate distributed robust optimization model, which is transformed into a deterministic semi-definite programming model by Lagrangian duality principle. The simulation results show that the operating cost obtained by using the DRO-MU model considering the dual uncertainty of source and load is increased compared without considering new energy or load uncertainty. However, the new scheme reduces the operation risk brought by uncertainties, and is more realistic. Compared with the stochastic optimization method and the traditional robust method, the DRO-MU method not only ensures the robustness of the scheduling strategy, but also overcomes its overly conservative problem. As the range of source-load moment uncertainties increases, the system operation cost increases. By setting the range of source-load moment uncertainties reasonably, the system economy and robustness can be balanced.