Decentralized Coordination Between Economic Dispatch and Demand Response in Multi-Energy Systems

TL;DR

This paper presents a decentralized algorithm for coordinating economic dispatch and demand response in multi-energy systems, improving efficiency and energy utilization through convex optimization and convergence guarantees.

Contribution

It introduces a novel linearization method and a decentralized ADMM-based algorithm with proven convergence for multi-energy system coordination.

Findings

Algorithm converges to the global optimal solution.

Case study verifies effectiveness on IEEE 14-bus network.

Improves energy efficiency and reduces waste in MESs.

Abstract

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.