Two-stage stochastic decentralized low-carbon economic dispatch of integrated electricity-gas networks

Abstract

To achieve low-carbon operation optimization of integrated electricity gas network (IEGN) system with uncertainty, a two-stage stochastic decentralized low-carbon economic scheduling model and its solution method for multi-region interconnection is proposed. Firstly, an IEGN operation cost model considering the stepped carbon emission cost and the benefits of P2G's participation in carbon market transactions is constructed, considering demand-side management (DSM) with user satisfaction and degree of regulation. Secondly, multi-region interconnection is served to overcome single-region space-time limitations with the multi-energy flow, regional decoupling is realized by copying multi-region IEGN boundary nodes, and the scenario method is used to quantify the output uncertainty of IEGN. Hence, a two-stage stochastic optimal scheduling model of multi-region IEGN is established. Then, an improved successive linearization method is proposed for the non-convex transformation. Considering the decentralized autonomy and information privacy of different decision-makers, a decentralized optimization model is established, and the synchronous alternating direction multiplier method (synchronous-ADMM) based on nested improved successive linearization is introduced for the iterative solution. Finally, the feasibility and superiority of the proposed model and algorithm are verified by comparing and analyzing the simulation results of multi-region IEGN under different scenarios and scheduling strategies.