4.7 Article

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

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 11, Issue 4, Pages 2457-2469

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2019.2961432

Keywords

Resistance heating; Natural gas; Pipelines; Indexes; Cogeneration; Heat engines; Couplings; Energy hub; multi-carrier energy system; multi-energy couplings; wind energy; alternating direction method of multipliers (ADMM)

Funding

  1. National Natural Science Foundation of China [51877072]
  2. Huxiang Young Talents programme of Hunan Province [2019RS2018]
  3. Hunan Provincial Innovation Foundation for Postgraduate [CX2018B166]
  4. China Scholarship Council [201806130197]

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This article 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.

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