Uncertainty-Based System Flexibility Evaluation and Multi-Objective Collaborative Optimization of Integrated Energy System

With the advancement of integrated energy systems (IES) and the increasing penetration of variable renewable energy, IES confronts complex uncertainties that necessitate enhanced flexibility. Therefore, this study focuses on improving IES flexibility. To this end, multi-dimensional flexibility evaluation indexes for the “Source–Structure–Demand” dimensions were established, and a multi-objective optimization model considering flexibility and source–demand side uncertainties was developed. The flexibility evaluation indexes include the Grid Dependency Level (GDL) for the source side, Insufficient Flexible Resource Probability (IFRP) for the structure side, and Loss of Load Probability (LOLP) for the demand side. Moreover, considering the distinct adjustment response times and inertia of different energy flows during IES operation, thermal and electrical energy are optimized on separate time scales. Thus, the multi-objective optimization constitutes a multi-time scale, high-dimensional, non-convex nonlinear model targeting economy, flexibility, security, and low carbon emissions. This paper employs single-economy objective, single-flexibility objective, and multi-objective optimization to analyze IES configuration, operation, risk, carbon emissions, and flexibility. The results indicate that poor flexibility leads to high operational risk, while excessive pursuit of flexibility incurs high costs and destabilizes operations. By implementing this multi-objective optimization, IES flexibility is enhanced while ensuring system economic performance. It also addresses the flexibility deficiency in traditional single-economy objective optimizations. Additionally, the system increases the renewable energy absorption rate by approximately 10%.