A Dynamic Peer-to-Peer Electricity Market Model for a Community Microgrid With Price-Based Demand Response

被引:45
作者
Alfaverh, Fayiz [1 ]
Denai, Mouloud [1 ]
Sun, Yichuang [1 ]
机构
[1] Univ Hertfordshire, Sch Phys Engn & Comp Sci, Hatfield AL10 9AB, Herts, England
关键词
Pricing; Batteries; Peer-to-peer computing; Microgrids; Costs; Vehicle dynamics; Demand response; P2P energy sharing; energy management; vehicle-to-grid; pricing mechanism; demand response; STRATEGY;
D O I
10.1109/TSG.2023.3246083
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Peer-to-Peer (P2P) energy sharing enables prosumers within a community microgrid to directly trade their local energy resources such as solar photovoltaic (PV) panels, small-scale wind turbines, electric vehicle battery storage among each other based on an agreed cost-sharing mechanism. This paper addresses the energy cost minimization problem associated with P2P energy sharing among smart homes which are connected in a residential community. The contribution of this paper is threefold. First, an effective Home Energy Management System (HEMS) is proposed for the smart homes equipped with local generation such as rooftop solar panels, storage and appliances to achieve the demand response (DR) objective. Second, this paper proposes a P2P pricing mechanism based on the dynamic supply-demand ratio and export-import retail prices ratio. This P2P model motivates individual customers to participate in energy trading and ensures that not a single household would be worse off. Finally, the performance of the proposed pricing mechanism, is compared with three popular P2P sharing models in the literature namely the Supply and Demand Ratio (SDR), Mid-Market Rate (MMR) and bill sharing (BS) considering different types of peers equipped with solar panels, electric vehicle, and domestic energy storage system. The proposed P2P framework has been applied to a community consisting of 100 households and the simulation results demonstrate fairness and substantial energy cost saving/revenue among peers. The P2P model has also been assessed under the physical constrains of the distribution network.
引用
收藏
页码:3976 / 3991
页数:16
相关论文
共 25 条
[1]   Electrical vehicle grid integration for demand response in distribution networks using reinforcement learning [J].
Alfaverh, Fayiz ;
Denai, Mouloud ;
Sun, Yichuang .
IET ELECTRICAL SYSTEMS IN TRANSPORTATION, 2021, 11 (04) :348-361
[2]  
Angaphiwatchawal Pikkanate, 2020, 2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), P37, DOI 10.1109/ECTI-CON49241.2020.9158275
[3]  
[Anonymous], 2013, ABOUT US
[4]  
[Anonymous], 2021, ABOUT US
[5]   Peer-to-Peer Operation Strategy of PV Equipped Office Buildings and Charging Stations Considering Electric Vehicle Energy Pricing [J].
Aznavi, Sima ;
Fajri, Poria ;
Shadmand, Mohammad B. ;
Khoshkbar-Sadigh, Arash .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2020, 56 (05) :5848-5857
[6]   Trading strategy optimization for a prosumer in continuous double auction based peer-to-peer market: A prediction-integration model [J].
Chen, Kaixuan ;
Lin, Jin ;
Song, Yonghua .
APPLIED ENERGY, 2019, 242 :1121-1133
[7]   Peer-to-Peer Energy Trading in Smart Grid Through Blockchain: A Double Auction-Based Game Theoretic Approach [J].
Doan, Hien Thanh ;
Cho, Jeongho ;
Kim, Daehee .
IEEE ACCESS, 2021, 9 :49206-49218
[8]   Which performs better under trader settings, double auction or uniform price auction? [J].
Kotani, Koji ;
Tanaka, Kenta ;
Managi, Shunsuke .
EXPERIMENTAL ECONOMICS, 2019, 22 (01) :247-267
[9]  
larc.nasa, Power data access viewer
[10]  
Li N, 2015, IEEE DECIS CONTR P, P2276, DOI 10.1109/CDC.2015.7402546