A Distributed Optimization Approach for TSO-DSO Coordination under Electricity and Carbon Markets

Abstract

Recent efforts to decarbonize power systems have led to the development of carbon-aware optimal dispatch models. Existing approaches typically focus on modeling either the distribution or the transmission system, disregarding the effects of their operation decisions on each other. Nonetheless, there are a few attempts to combine the operational constraints of both transmission and distribution into a single model. However, existing formulations demand sensitive data sharing between transmission and distribution system operators (TSO and DSOs). This paper addresses the joint trade of energy and carbon allowances in a distributed fashion, thus avoiding excessive data sharing between TSO and DSOs. The optimization model is originally formulated as a centralized problem and then decomposed into subproblems, which are solved locally using the Alternating Direction Method of Multipliers (ADMM). Numerical simulations demonstrate that the distributed framework achieves near-optimal economic dispatch, maintaining total operational costs within 0.3% of the optimal solution. Computationally, the ADMM exhibits robust convergence for initial energy and carbon prices ranging from $0 to $60. Finally, the proposed model was tested in a multi-DSO environment, with computational times remaining within 300 seconds.