A Grid-friendly Neighborhood Energy Trading Mechanism

被引:9
作者
Abeygunawardana, Anula [1 ]
Liu, Aaron [1 ]
Ledwich, Gerard [1 ]
机构
[1] Queensland Univ Technol, Brisbane, Qld, Australia
基金
澳大利亚研究理事会;
关键词
Peer-to-peer computing; Pricing; Voltage control; Tariffs; Costs; Reactive power; Investment; Direct power flow; directional adjacency; local energy market; peer-to-peer; prosumer; solar community; sustainable building; transdisciplinary research; PEER-TO-PEER; MARKETS; SOLAR;
D O I
10.35833/MPCE.2020.000925
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
More customers are tending to install batteries with photovoltaic (PV), so they can better control their electricity bills. In this context, customers may be tempted to go off-grid at a substantial up-front cost, leading electricity companies into a death spiral, thereby raising electricity price further on those remaining on grid. Neighborhood energy markets can promote the sharing of locally generated renewable energy and encourage prosumers to stay on grid with financial incentives. A novel neighborhood energy trading (NET) mechanism is developed using the topology of existing radial distribution network to encourage sustainable energy sharing in neighborhood and encourage prosumers to stay on grid. This mechanism considers loss, congestion management, and voltage regulation, and it is scalable with low computation and communication overhead. An IEEE test system is used to validate the NET mechanism. The simulation shows that the price and flow results are obtained with fast computation speed (within 10 iterations) and with loss reflected, flow limit reinforced, and voltage regulated. This study proves that the economic demand-supply-based pricing mechanism can be applied effectively in distribution networks to help encourage more renewable energy sharing in sustainable neighborhood and avoid energy network death spiral.
引用
收藏
页码:1349 / 1357
页数:9
相关论文
共 27 条
[1]   A New Risk-Managed Planning of Electric Distribution Network Incorporating Customer Engagement and Temporary Solutions [J].
Arefi, Ali ;
Abeygunawardana, Anula ;
Ledwich, Gerard .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (04) :1646-1661
[2]  
Australian Competition and Consumer Commission, 2017, RET EL PRIC INQ PREL
[3]   An Excessive Tap Operation Evaluation Approach for Unbalanced Distribution Networks With High PV Penetration [J].
Bai, Feifei ;
Yan, Ruifeng ;
Saha, Tapan Kumar ;
Eghbal, Daniel .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2021, 12 (01) :169-178
[4]   Exogenous Cost Allocation in Peer-to-Peer Electricity Markets [J].
Baroche, Thomas ;
Pinson, Pierre ;
Latimier, Roman Le Goff ;
Ben Ahmed, Hamid .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (04) :2553-2564
[5]  
Brenna Morris, 2010, Journal of Electromagnetic Analysis and Applications, V2, P467, DOI 10.4236/jemaa.2010.28062
[6]   Constrained Broadcast With Minimized Latency in Neighborhood Area Networks of Smart Grid [J].
Ding, Yuemin ;
Tian, Yu-Chu ;
Li, Xiaohui ;
Mishra, Yateendra ;
Ledwich, Gerard ;
Zhou, Chunjie .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (01) :309-318
[7]  
Energex, 2016, EN DEM SID ENG STRAT
[8]   Electrical-distance driven peer-to-peer energy trading in a low-voltage network [J].
Guerrero, Jaysson ;
Sok, Bunyim ;
Chapman, Archie C. ;
Verbic, Gregor .
APPLIED ENERGY, 2021, 287
[9]   Decentralized P2P Energy Trading Under Network Constraints in a Low-Voltage Network [J].
Guerrero, Jaysson ;
Chapman, Archie C. ;
Verbic, Gregor .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (05) :5163-5173
[10]   Comparative Analysis of P2P Architectures for Energy Trading and Sharing [J].
Jogunola, Olamide ;
Ikpehai, Augustine ;
Anoh, Kelvin ;
Adebisi, Bamidele ;
Hammoudeh, Mohammad ;
Gacanin, Haris ;
Harris, Georgina .
ENERGIES, 2018, 11 (01)