TY - JOUR
T1 - Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration
AU - Zhou, Yuekuan
AU - Lund, Peter D.
N1 - Funding Information:
This work is supported by The Hong Kong University of Science and Technology . All copyright licenses have been successfully applied for all cited graphics, images, tables and/or figures. This work was supported by the Hong Kong University of Science and Technology (Guangzhou) startup grant ( G0101000059 ). This work was supported by Regional joint fund youth fund project ( P00038-1002 ) and HKUST(GZ)-enterprise cooperation project ( R00017-2001 ). This work was also supported in part by the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone ( HZQB-KCZYB-2020083 ).
PY - 2023/5
Y1 - 2023/5
N2 - Peer-to-peer (P2P) energy sharing can complement other energy management strategies needed in the energy transition to clean energy such as renewables. The recent advances in artificial intelligence, machine learning and internet of things can provide cutting-edge solutions to dynamic information interaction and power exchange, enabling efficient P2P energy sharing and trading schemes. However, the current electricity market fails to comprehensively consider devices degradation costs and transmission losses, fairness distribution and allocation on cost-benefit model, synergistic collaborations and operations for different stakeholders. Here, a comprehensive review on P2P energy sharing and trading is presented covering novel system configurations, energy sharing and marginal/trading price mechanisms, and decision-making in dynamic P2P energy trading combined with synergistic collaboration and operation among key stakeholders. Significances of this review include comprehensive consideration on internal trading pricing, fairness distribution and allocation with active participation in P2P energy sharing, synergistic collaborations and operations with mutual economic benefits. Modelling tools for P2P energy trading platforms for real applications are also reviewed. The review shows that P2P when optimally designed can provide win-win economic benefits to all related stakeholders such as prosumers, consumers, retailers, and aggregators with fair access to distributed energy resources. The P2P energy sharing can improve the system efficiency, reduce energy storage capacity and primary energy consumption, improve renewable penetration, avoid energy quality devaluation and mitigate stressed grid power together with voltage support and congestion management for the local power grid. Employing blockchain technology improves the automation level in P2P thus decreasing human interactions improving the security with transparent, tamper-proof and secure systems, and accelerating real-time settlements with smart contracts. Synergistic collaboration and operation among stakeholders can ensure economic benefits for each participant, fair energy distribution and cost allocation, and decrease reliance on retailers or aggregators. The results presented provide cutting-edge guidelines for increasing the use and acceptance of smart and fair P2P energy sharing and trading frameworks.
AB - Peer-to-peer (P2P) energy sharing can complement other energy management strategies needed in the energy transition to clean energy such as renewables. The recent advances in artificial intelligence, machine learning and internet of things can provide cutting-edge solutions to dynamic information interaction and power exchange, enabling efficient P2P energy sharing and trading schemes. However, the current electricity market fails to comprehensively consider devices degradation costs and transmission losses, fairness distribution and allocation on cost-benefit model, synergistic collaborations and operations for different stakeholders. Here, a comprehensive review on P2P energy sharing and trading is presented covering novel system configurations, energy sharing and marginal/trading price mechanisms, and decision-making in dynamic P2P energy trading combined with synergistic collaboration and operation among key stakeholders. Significances of this review include comprehensive consideration on internal trading pricing, fairness distribution and allocation with active participation in P2P energy sharing, synergistic collaborations and operations with mutual economic benefits. Modelling tools for P2P energy trading platforms for real applications are also reviewed. The review shows that P2P when optimally designed can provide win-win economic benefits to all related stakeholders such as prosumers, consumers, retailers, and aggregators with fair access to distributed energy resources. The P2P energy sharing can improve the system efficiency, reduce energy storage capacity and primary energy consumption, improve renewable penetration, avoid energy quality devaluation and mitigate stressed grid power together with voltage support and congestion management for the local power grid. Employing blockchain technology improves the automation level in P2P thus decreasing human interactions improving the security with transparent, tamper-proof and secure systems, and accelerating real-time settlements with smart contracts. Synergistic collaboration and operation among stakeholders can ensure economic benefits for each participant, fair energy distribution and cost allocation, and decrease reliance on retailers or aggregators. The results presented provide cutting-edge guidelines for increasing the use and acceptance of smart and fair P2P energy sharing and trading frameworks.
KW - Blockchain
KW - Decision-making
KW - Machine learning
KW - Multi-stakeholders
KW - Peer-to-peer (P2P) energy sharing and trading
KW - Trading pricing
UR - http://www.scopus.com/inward/record.url?scp=85149740650&partnerID=8YFLogxK
U2 - 10.1016/j.renene.2023.02.125
DO - 10.1016/j.renene.2023.02.125
M3 - Review Article
AN - SCOPUS:85149740650
SN - 0960-1481
VL - 207
SP - 177
EP - 193
JO - Renewable Energy
JF - Renewable Energy
ER -