Heat market for interconnected multi-energy microgrids: A distributed optimization approach

被引:0
|
作者
Gonzalez-Castellanos, Alvaro [1 ]
Bischi, Aldo [2 ]
机构
[1] Corp Red Solvers, Barranquilla, Atlantico, Colombia
[2] Univ Pisa, Dept Energy Syst Terr & Construct Engn, Largo Lucio Lazzarino 1, I-56122 Pisa, Italy
来源
ENERGY NEXUS | 2024年 / 14卷
关键词
Interconnected microgrids; Multi-energy microgrids; Heat market; Combined heat and power; Distributed optimization; SYSTEMS; NETWORK; ADMM;
D O I
10.1016/j.nexus.2024.100292
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Thermal networks, part of heat -and -power multi -energy microgrids, may face capacity issues, generation and distribution ones, either due to the increase in the requested demand or capacity underused, which is sized for peak hours. Under -capacity issues may be addressed with generation and pipeline capacity expansion, resulting in considerable capital costs and extra maintenance costs. In the case of over -capacity, better usage of the existing assets may bring further revenues and increase the multi -energy microgrid's overall energy efficiency. In the electricity sector, it is being considered the interconnection of microgrids via the distribution system network, since microgrids can operate in both islanded and network -connected modes. In this work, in a similar fashion, we propose the interconnection of adjacent thermal networks enabling direct heat trading among them to increase the micro -grids' supply flexibility, help meeting demand peaks, and reduce operational costs. Examples of integrated heat -and -power microgrids that could benefit from thermal interconnections are industrial parks, university campuses, hospitals, and even residential complexes with a shared heat generator. This paper presents a market model for the optimal heat transfer between thermally interconnected heat -and -power microgrids. The resulting model is a convex quadratic programming model that enables the derivation of heat transfer prices that guarantee a competitive equilibrium. Furthermore, we performed numerical tests to explore the impact of connection topology, thermal power transfer capacity, and interconnection efficiency on transferred energy and prices.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Peer-to-peer multi-energy distributed trading for interconnected microgrids: A general Nash bargaining approach
    Shuai Xuanyue
    Wang, Xiuli
    Wu, Xiong
    Wang, Yifei
    Song, Zhenzi
    Wang, Bangyan
    Ma, Zhicheng
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2022, 138
  • [2] Joint Optimization of Renewable Energy Utilization and Multi-Energy Sharing for Interconnected Microgrids with Carbon Trading
    Rong, Jieqi
    Liu, Weirong
    Tang, Nvzhi
    Jiang, Fu
    Zhang, Rui
    Li, Heng
    ELECTRONICS, 2024, 13 (24):
  • [3] A robust model of local energy market under a security constraint-based approach for distribution system operator and multi-energy microgrids
    Sahebi, Ali
    Jadid, Shahram
    ELECTRIC POWER SYSTEMS RESEARCH, 2023, 217
  • [4] Distributed peer-to-peer energy sharing framework in multi-energy microgrids: A two-stage robust optimization approach with multi-interval uncertainty
    Cai, Pengcheng
    Mi, Yang
    Li, Dongdong
    Wang, Peng
    ELECTRIC POWER SYSTEMS RESEARCH, 2025, 241
  • [5] Peer-to-peer energy trading with energy trading consistency in interconnected multi-energy microgrids: A multi-agent deep reinforcement learning approach
    Cui, Yang
    Xu, Yang
    Wang, Yijian
    Zhao, Yuting
    Zhu, Han
    Cheng, Dingran
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 156
  • [6] Peer-to-Peer Energy Trading and Energy Conversion in Interconnected Multi-Energy Microgrids Using Multi-Agent Deep Reinforcement Learning
    Chen, Tianyi
    Bu, Shengrong
    Liu, Xue
    Kang, Jikun
    Yu, F. Richard
    Han, Zhu
    IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (01) : 715 - 727
  • [7] A scenario-based two-stage stochastic optimization approach for multi-energy microgrids
    Li, Ke
    Yang, Fan
    Wang, Lupan
    Yan, Yi
    Wang, Haiyang
    Zhang, Chenghui
    APPLIED ENERGY, 2022, 322
  • [8] Distributed Optimization for Generation Scheduling of Interconnected Microgrids
    Li, Yansong
    Liu, Nian
    Wu, Chenshuo
    Zhang, Jianhua
    2015 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2015,
  • [9] Multi-agent Stackelberg game trading strategy of electricity-gas multi-energy market considering participation of multi-energy microgrids
    Li X.
    Yang M.
    Zhang R.
    Jiang T.
    Fu L.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2023, 43 (05): : 145 - 153
  • [10] Distributed energy management for interconnected operation of combined heat and power-based microgrids with demand response
    Liu, Nian
    Wang, Jie
    Wang, Lingfeng
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2017, 5 (03) : 478 - 488