Prevision and planning for residential agents in a transactive energy environment

被引:16
作者
Toquica, David [1 ,2 ]
Agbossou, Kodjo [1 ,2 ]
Henao, Nilson [1 ,2 ]
Malhame, Roland [3 ]
Kelouwani, Sousso [2 ,4 ]
Amara, Fatima [5 ]
机构
[1] Univ Quebec Trois Rivieres, Dept Elect & Comp Engn, 3351 Boul Forges, Quebec City, PQ G8Z 4M3, Canada
[2] Smart Energy Res & Innovat Lab, LIREI, Trois Rivieres, PQ, Canada
[3] Polytech Montreal, Dept Elect Engn, CP 6079,Succ Ctr Ville, Montreal, PQ H3C 3A7, Canada
[4] Univ Quebec Trois Rivieres, Dept Mech Engn, 3351 Loul Forges, Trois Rivieres, PQ G8Z 4M3, Canada
[5] Inst Rech Hydroquebec IREQ LTE, Varennes, PQ, Canada
来源
SMART ENERGY | 2021年 / 2卷
基金
加拿大自然科学与工程研究理事会;
关键词
Agents interaction; Forward market; Multi-agent system; Price-elasticity; Prosumer; Smart energy markets; Stackelberg game; Transactive energy; Utility function; MANAGEMENT; FRAMEWORK; MARKETS; MICROGRIDS; AUCTION; SYSTEMS;
D O I
10.1016/j.segy.2021.100019
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
Transactive Energy (TE) has brought exciting opportunities for all stakeholders in energy markets by enabling management decentralization. This new paradigm empowers demand-side agents to play a more active role through coordinating, cooperating, and negotiating with other agents. Nevertheless, most of these agents are not used to process market signals and develop optimal strategies, especially in the residential sector. Accordingly, it is indispensable to create tools that automate and facilitate demand-side participation in TE systems. This paper presents a new methodology for residential automated agents to perform two key tasks: prevision and planning. Specifically, the proposed method is applied to a forward market where agents' planning is a fundamental step to maintain the dynamic balance between demand and generation. Since planning depends on future demand, agents' prevision of consumption is an inevitable part of this step. The procedures for automating the targeted tasks are developed in a general way for residential prosumers and consumers, interacting at the distribution level. These players are managed by a demand aggregator as the leader by means of the Stackelberg game. The suggested process results in a TE setup for multi-stage single-side auctions, useful to manage future Smart Energy Markets. Through simulated transactions, this paper examines the market clearing mechanism and the convenience of agents' planning. The results show that customers with higher price elasticity leverage lower costs periods. However, they make it harder to reduce the peak-to-average ratio of the aggregated demand profile since a unique price signal can create prisoner's dilemma conditions. & COPY; 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:12
相关论文
共 74 条
  • [41] A Generalized Nash Equilibrium Approach for Autonomous Energy Management of Residential Energy Hubs
    Liang, Yile
    Wei, Wei
    Wang, Cheng
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (11) : 5892 - 5905
  • [42] COMPARISON OF SEVERAL ALGORITHMS FOR COMPUTING SAMPLE MEANS AND VARIANCES
    LING, RF
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1974, 69 (348) : 859 - 866
  • [43] Two-Stage Optimal Scheduling of Electric Vehicle Charging Based on Transactive Control
    Liu, Zhaoxi
    Wu, Qiuwei
    Ma, Kang
    Shahidehpour, Mohammad
    Xue, Yusheng
    Huang, Shaojun
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (03) : 2948 - 2958
  • [44] Smart energy and smart energy systems
    Lund, Henrik
    Ostergaard, Poul Alberg
    Connolly, David
    Mathiesen, Brian Vad
    [J]. ENERGY, 2017, 137 : 556 - 565
  • [45] 4th Generation District Heating (4GDH) Integrating smart thermal grids into future sustainable energy systems
    Lund, Henrik
    Werner, Sven
    Wiltshire, Robin
    Svendsen, Svend
    Thorsen, Jan Eric
    Hvelplund, Frede
    Mathiesen, Brian Vad
    [J]. ENERGY, 2014, 68 : 1 - 11
  • [46] Economic Dispatch of a Hybrid Microgrid With Distributed Energy Storage
    Mahmoodi, Mishel
    Shamsi, Pourya
    Fahimi, Babak
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (06) : 2607 - 2614
  • [47] Malkiel B., 1973, A Random Walk Down Wall Street, V13th
  • [48] Framework for smart transactive energy in home-microgrids considering coalition formation and demand side management
    Marzband, Mousa
    Fouladfar, Mohammad Hossein
    Akorede, Mudathir Funsho
    Lightbody, Gordon
    Pouresmaeil, Edris
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2018, 40 : 136 - 154
  • [49] Residential Load Modeling of Price-Based Demand Response for Network Impact Studies
    McKenna, Killian
    Keane, Andrew
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2016, 7 (05) : 2285 - 2294
  • [50] Melton R, 2016, TRANSACTIVE ENERGY A