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This study proposes a decentralized optimization approach for peer-to-peer trading among multi-energy networked microgrids (MENMGs) in transactive energy markets (TEMs) and local electricity markets (LEMs), incorporating photovoltaic (PV) generation. In this study, MENMGs utilizing PVs and combined heat and power (CHP) units share their offer/bid in peer-to-peer transactive energy markets with the aim of minimizing operating costs. The fast alternating direction method of multipliers (ADMM) algorithm has been used to achieve the equilibrium point of microgrids in peer-to-peer transactive energy markets. MENMGs are developed considering the AC power flow constraints and bus voltage variations. A 14-bus test system is used to model the physical behavior of multi-energy carrier microgrids. The proposed problem is modeled by a second-order conic programming (SOCP) that guarantees a global optimal solution to the problem. The obtained results strongly confirm the effectiveness of the proposed model.

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Multi-Energy Networked Microgrid Scheduling in Smart Cities Under Transactive Energy Concept

  • 章节

  • 发表日期：

    2025年

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  • Nima Nasiri,
  • Asma Nasiri,
  • Sajad Najafi Ravadanegh,
  • Behnam Mohammadi-ivatloo,
  • Mehdi Abapour

摘要

This study proposes a decentralized optimization approach for peer-to-peer trading among multi-energy networked microgrids (MENMGs) in transactive energy markets (TEMs) and local electricity markets (LEMs), incorporating photovoltaic (PV) generation. In this study, MENMGs utilizing PVs and combined heat and power (CHP) units share their offer/bid in peer-to-peer transactive energy markets with the aim of minimizing operating costs. The fast alternating direction method of multipliers (ADMM) algorithm has been used to achieve the equilibrium point of microgrids in peer-to-peer transactive energy markets. MENMGs are developed considering the AC power flow constraints and bus voltage variations. A 14-bus test system is used to model the physical behavior of multi-energy carrier microgrids. The proposed problem is modeled by a second-order conic programming (SOCP) that guarantees a global optimal solution to the problem. The obtained results strongly confirm the effectiveness of the proposed model.