An Improved Optimization Method of Regional Integrated Energy System Based on Information Gap Decision Theory Considering Time-Varying Uncertainties of Wind Generation

Information Gap Decision Theory (IGDT) delivers a structured and systematic methodological strategy for addressing uncertainty-related problems. The risk-seeking (RS) strategy embedded within IGDT prioritizes the maximization of economic efficiency to construct optimization model. But the above model does not consider the time-varying characteristics with uncertain variables. This article according to the error with wind turbine output prediction proposes a time-varying uncertainty radius within IGDT to address optimization problem of RIES. Firstly, a data-driven IGDT model is proposed, this work constructs a box set of time-varying uncertainty radius based on historical data, where the uncertainty radius is dynamically adjusted through the box set. Secondly, this article takes the deviation factor of the objective function as one of the optimization variables, ultimately obtain a suitable objective deviation factor. This approach overcomes the inherent subjectivity constraints of conventional approaches, thereby enhancing solution adaptability across optimization problems considering uncertainty of new energy system. The numerical results verify the superiority on economic performance compared traditional IGDT in dealing with uncertainty.