A two-stage robust low-carbon operation strategy for interconnected distributed energy systems considering source-load uncertainty

Interconnected distributed energy systems (DESs) can facilitate multi-energy consumption, improve energy efficiency, and advance decarbonization goals. In this context, this study proposes an energy sharing framework that considers multiple uncertainties to optimize the low-carbon robust economic operation of interconnected DESs. First, a low-carbon dispatch model for DESs that includes electricity and heat sharing, integrated demand response (IDR), and low-carbon policies is constructed. Then, a two-stage robust optimization model is developed considering the source-load uncertainty, and the Karush-Kuhn-Tucker (KKT) condition is introduced to transform the max-min problem in the second stage into a single-layer issue. In addition, an approach combining the alternating direction multiplier method (ADMM) with the column-and-constraint generation algorithm (CCG) is proposed for a distributed and hierarchical solving of the two-stage energy sharing problem. Finally, to address the issue of transactional payments for energy sharing, a profit allocation model based on multi-factor contributions is developed to ensure that the benefits generated by the sharing system are fairly distributed. Based on actual data simulation, the effectiveness of the two-stage robust sharing scheme presented in this study is demonstrated for economy and carbon reduction.