Economic Dispatching for Cyber-Physical Integrated Energy System Based on GP-WGAN and Improved Distributionally Robust Optimization

Although renewable energy, especially wind power, enables environmentally friendly power generation, its uncertainty remarkably influences the economy of the integrated energy system (IES) dispatching. Together with the naturally existing load uncertainty issue, the economy of IES could severely deteriorate. However, in recent years the cyber-physical system has been deeply coupled with IES to form the cyber-physical integrated energy system (CPIES). Therefore, driven by the comprehensive data flows, it is possible to model and analyze the uncertainties in energy flows using data-driven approaches. To analyze and solve the wind power generation (WPG) uncertainty and the load uncertainty issues in CPIES dispatching, this paper develops and introduces a distributionally robust optimization approach to realize the optimized economic dispatching for CPIES. First, the ambiguity set based on the imprecise Dirichlet theory is adopted. Further, aiming at solving the potential issue arising from the insufficiency of the WPG data samples utilized for constructing the ambiguity set, a gradient penalty-based Wasserstein generative adversarial network is presented to generate additional samples to enhance the uncertainty depicting the ability of the ambiguity set. Moreover, to improve the processing efficiency, deep-embedded clustering is also adopted to carry out the sample clustering to obtain the typical WPG scenarios. On the basis of the clustering results, ambiguity sets describing the uncertainties of different WPG scenarios and the uncertainty of the load are finally constructed, which are ultimately involved in implementing the optimized economic dispatching model for CPIES. At last, the model is solved using the duality theory, the column and constraint generation algorithm, and the Big-M method. The case studies demonstrate that the work presented in this paper can effectively improve the dispatching economy of CPIES.