  In this paper, we investigate the problem of coordination between economic
dispatch (ED) and demand response (DR) in multi-energy systems (MESs), aiming
to improve the economic utility and reduce the waste of energy in MESs. Since
multiple energy sources are coupled through energy hubs (EHs), the
supply-demand constraints are nonconvex. To deal with this issue, we propose a
linearization method to transform the coordination problem to a convex social
welfare optimization one. Then a decentralized algorithm based on parallel
Alternating Direction Method of Multipliers (ADMM) and dynamic average tracking
protocol is developed, where each agent could only make decisions based on
information from their neighbors. Moreover, by using variational inequality and
Lyapunov-based techniques, we show that our algorithm could always converge to
the global optimal solution. Finally, a case study on the modified IEEE 14-bus
network verifies the feasibility and effectiveness of our algorithm.
