Decentralized Chance-Constrained Economic Dispatch for Integrated Transmission-District Energy Systems

The rapid development of distributed renewable energy sources (RES) stimulates the coordination of the transmission system (TS) and several district energy systems (DESs). In this paper, a novel decentralized chance-constrained ED model for TS and DESs is proposed, wherein, economic model predictive control (EMPC) is adopted to take future uncertainties into account, and over each receding horizon, the TS and DES subproblems are solved in a decentralized manner to protect privacy. Such a decentralized solution has a solid practical implication: the TS works as a source supplying power and reserves to DESs at the optimal energy prices, while the DESs specify the corresponding requirements of boundary power and spinning reserves. Moreover, in each DES, the chance-constrained programming based on the versatile probability distribution (VPD) has been applied to address the random power outputs from RES. The case studies have validated the advantages of the proposed dispatch method.