With the widespread application of combined heat and power (CHP) units

the economic dispatch of integrated electric and district heating systems (IEHSs) has drawn increasing attention. Because the electric power system (EPS) and district heating system (DHS) are generally managed separately

the decentralized dispatch pattern is preferable for the IEHS dispatch problem. However

many common decentralized methods suffer from the drawbacks of slow and local convergence. Moreover

the uncertainties of renewable generation cannot be ignored in a decentralized pattern. Additionally

the most commonly used individual chance constraints in distributionally robust optimization cannot consider safety constraints simultaneously

so the safe operation of an IEHS cannot be guaranteed. Thus

distributionally robust joint chance constraints and robust constraints are jointly introduced into the IEHS dispatch problem in this paper to obtain a stronger safety guarantee

and a method combined with Bonferroni and conditional value at risk (CVaR) approximation is presented to transform the original model into a quadratic program. Additionally

a dynamic boundary response (DBR)-based distributed algorithm based on multiparametric programming is proposed for a fast solution. Case studies showcase the necessity of using mixed distributionally robust joint chance constraints and robust constraints

as well as the effectiveness of the DBR algorithm.