Distributed Multi-Energy Operation of Coupled Electricity, Heating, and Natural Gas Networks

TLDR

The multi‑period multi‑energy scheduling problem is challenging due to strong couplings and inherent nonconvexities within the coupled electrical, heating, and natural gas networks. This paper proposes a distributed multi‑period multi‑energy operational model for a multi‑carrier energy system. The model uses energy hubs as distributed decision‑makers, reformulates the problem as a MISOCP solved via sequential SOCP, and employs a fully‑distributed consensus‑based ADMM that exchanges only neighboring information to optimize multi‑energy flows, benchmarked on a four‑hub urban system over 24 hours. Simulations show the scheme improves operational economy and renewable energy use, confirming the effectiveness of the distributed approach.

Abstract

This paper proposes a distributed multi-period multi-energy operational model for the multi-carrier energy system. In this model, energy hubs function as distributed decision-makers and feature the synergistic interactions of generation, delivery, and consumption of coupled electrical, heating, and natural gas energy networks. The multi-period multi-energy scheduling is a challenging optimization problem due to its strong couplings and inherent nonconvexities within the multi-energy networks. The original problem is thus reformulated as a mixed integer second-order cone programming (MISOCP) and subsequently solved with a sequential second-order cone programming (SOCP) approach to guarantee a satisfactory convergence performance. Furthermore, a fully-distributed consensus-based alternating direction method of multipliers (ADMM) approach with only neighboring information exchange required is developed to optimize the multi-energy flows while considering the local energy-autonomy of heterogeneous energy hubs. The proposed methodology is performed and benchmarked on a four-hub urban multi-energy system over a 24 hourly scheduling periods. Simulation results demonstrated the superiority of the proposed scheme in system operational economy and renewable energy utilization, and also verify the effectiveness of the proposed distributed approach.