Transactive energy framework in multi-carrier energy hubs: A fully decentralized model

被引:91
作者
Javadi, Mohammad Sadegh [1 ]
Nezhad, Ali Esmaeel [2 ]
Jordehi, Ahmad Rezaee [3 ]
Gough, Matthew [4 ,5 ]
Santos, Sergio F. [4 ,6 ]
Catalao, Joao P. S. [4 ,5 ]
机构
[1] Islamic Azad Univ, Shiraz Branch, Dept Elect Engn, Shiraz, Iran
[2] LUT Univ, Sch Energy Syst, Dept Elect Engn, Lappeenranta 53850, Finland
[3] Islamic Azad Univ, Rasht Branch, Dept Elect Engn, Rasht, Iran
[4] Inst Syst & Comp Engn, Technol & Sci INESC TEC, Porto, Portugal
[5] Univ Porto, Fac Engn, FEUP, Porto, Portugal
[6] Portucalense Univ Infante D Henr UPT, R Dr Antonio Bernardino de Almeida 541, Porto, Portugal
关键词
Alternating direction method of multipliers; Peer-to-Peer; Transactive energy; Multi-carrier energy hubs; MANAGEMENT; ALGORITHM;
D O I
10.1016/j.energy.2021.121717
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper investigates a fully decentralized model for electricity trading within a transactive energy market. The proposed model presents a peer-to-peer (P2P) trading framework between the clients. The model is incorporated for industrial, commercial, and residential energy hubs to serve their associated demands in a least-cost paradigm. The alternating direction method of multipliers (ADMM) is implemented to address the decentralized power flow in this study. The optimal operation of the energy hubs is modeled as a standard mixed-integer linear programming (MILP) optimization problem. The corresponding decision variables of the energy hubs operation are transferred to the peer-to-peer (P2P) market, and ADMM is applied to ensure the minimum data exchange and address the data privacy issue. Two different scenarios have been studied in this paper to show the effectiveness of the electricity trading model between peers, called integrated and coordinated operation modes. In the integration mode, there is no P2P energy trading while in the coordinated framework, the P2P transactive energy market is taken into account. The proposed model is simulated on the modified IEEE 33-bus distribution network. The obtained results confirm that the coordinated model can efficiently handle the P2P transactive energy trading for different energy hubs, addressing the minimum data exchange issue, and achieving the least-cost operation of the energy hubs in the system. The obtained results show that the total operating cost of the hubs in the coordinated model is lower than that of the integrated model by $590.319, i.e. 11.75 % saving in the costs. In this regard, the contributions of the industrial, commercial, and residential hubs in the total cost using the integrated model are $3441.895, $596.600, and $988.789, respectively. On the other hand, these energy hubs contribute to the total operating cost in the coordinated model by $2932.645, $590.155, and $914.165 respectively. The highest decrease relates to the industrial hub by 14.8 % while the smallest decrease relates to the residential hub by 1 %. Furthermore, the load demand in the integrated and coordinated models is mitigated by 13 % and 17 %, respectively. These results indicate that the presented framework could effectively and significantly reduce the total load demand which in turn leads to reducing the total cost and power losses. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:15
相关论文
共 37 条
  • [1] Towards transactive energy systems: An analysis on current trends
    Abrishambaf, Omid
    Lezama, Fernando
    Faria, Pedro
    Vale, Zita
    [J]. ENERGY STRATEGY REVIEWS, 2019, 26
  • [2] Cooperative energy management of multi-energy hub systems considering demand response programs and ice storage
    Bahmani, Ramin
    Karimi, Hamid
    Jadid, Shahram
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 130 (130)
  • [3] East S, 2018, IEEE DECIS CONTR P, P2641, DOI 10.1109/CDC.2018.8619731
  • [4] Hybrid probabilistic- harmony search algorithm methodology in generation scheduling problem
    Estahbanati, M. J.
    [J]. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2014, 26 (02) : 283 - 296
  • [5] A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism
    Ghalelou, Afshin Najafi
    Fakhri, Alireza Pashaei
    Nojavan, Sayyad
    Majidi, Majid
    Hatami, Hojat
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2016, 120 : 388 - 396
  • [6] Gough M, 2019, IEEE INT C ENV EL EN, P1, DOI [10.1109/EEEIC.2019.8783696.2019, DOI 10.1109/EEEIC.2019.8783696.2019]
  • [7] Optimal Management of a Distribution Feeder During Contingency and Overload Conditions by Harnessing the Flexibility of Smart Loads
    Haider, Zunaib Maqsood
    Mehmood, Khawaja Khalid
    Khan, Saad Ullah
    Khan, Muhammad Omer
    Wadood, Abdul
    Rhee, Sang-Bong
    [J]. IEEE ACCESS, 2021, 9 : 40124 - 40139
  • [8] Javadi MS, 2009, INT REV ELECTR ENG-I, V4, P199
  • [9] Optimal Operation of Energy Hubs Considering Uncertainties and Different Time Resolutions
    Javadi, Mohammad Sadegh
    Lotfi, Mohamed
    Nezhad, Ali Esmaeel
    Anvari-Moghaddam, Amjad
    Guerrero, Josep M.
    Catalao, Joao P. S.
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2020, 56 (05) : 5543 - 5552
  • [10] Javadi MS, 2019, IEEE IND ELEC, P4157, DOI 10.1109/IECON.2019.8927263