Distributed Conditional-Distributionally robust coordination for an electrical power and flexibility-enhanced district heating system

Abstract

In an integrated electricity and heating system (IEHS), building flexibility-enhanced district heating systems (DHSs) that use advanced flexibility-enhanced technologies are effective for promoting renewable energy accommodation. However, it is challenging to comprehensively utilize these flexibility-enhanced technologies in IEHS dispatch. This paper proposes a distributed conditional-distributionally robust coordination method for an electrical power and flexibility-enhanced DHS. The DHS is retrofitted with bypass compensation technology and uses a variable mass flow operation strategy to enhance its flexibility and promote renewable energy accommodation. Moreover, conditional-distributionally robust optimization is used to consider the inherent dependency between the forecasting error of a wind farm and the forecast output information, which goes beyond the state-of-the-art models. Additionally, a novel reformulation method is adopted to transform the problem with random variables and bilinear constraints into a more tractable programming problem, yielding a conservative approximative model of the original model that guarantees feasibility. Finally, to protect the privacy of electrical power system and DHS operators, this paper proposes a double-layer distributed algorithm to solve the problem in a distributed fashion while guaranteeing feasibility. Case studies demonstrate that the proposed model with flexibility-enhanced DHSs significantly promotes renewable energy accommodation and reduces dispatch costs, and the proposed double-layer distributed algorithm effectively solves the dispatch problem in a distributed fashion and guarantees the feasibility of dispatch results.