ABSTRACT This paper presents a novel bi‐level optimisation framework to coordinate the operations of transmission system operators (TSOs) and distribution system operators (DSOs) under wind power uncertainty. At the upper level, the TSO minimises system‐wide generation costs while managing wind forecast errors through chance constraints. At the lower level, the DSO responds to locational marginal price and nodal carbon intensity signals issued by the TSO and minimises total operational costs, including electricity procurement, local generation and carbon costs. By incorporating the carbon emission flow theory, the framework accurately quantifies carbon intensity at each transmission node, providing essential signals that enable the DSO to jointly optimise economic performance and carbon reduction. To solve the complicated bi‐level optimisation problem, we reformulate it as a single‐level mixed‐integer programme to ensure computational tractability. Numerical simulations demonstrate that the proposed framework effectively enhances system‐wide economic efficiency and reduces carbon emissions. The results further reveal that the selected confidence level under uncertainty has a pronounced impact on the optimal economic dispatch outcomes.
Wei et al. (Thu,) studied this question.