Complementary Evaluation of Regional Integrated Energy System Considering Uncertainties in Source and Load

The growing demand for multi-energy facilitates the expansion planning for integrated energy systems. In this paper, we propose a complementary evaluation method to quantify how uncertainties affect the regional integrated energy system (RIES). To solve the complicated nonlinear problem, we apply second-order cone programming and big-M algorithm. Targeted on economic, reliable and flexible significance, complementary indicators are selected for evaluation. A case study is applied to validate effectiveness of the proposed approach.