Investigation of the Peer-to-Peer energy trading performances in a local community under the future climate change scenario in Sweden

Pei Huang*, Marco Lovati, Jingchun Shen, Jiale Chai, Xingxing Zhang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Peer-to-peer (P2P) energy sharing among neighboring households is a promising solution to mitigating the difficulties of renewable power (such as solar Photovoltaics (PV)) penetration on the power grid. Until now, there is still a lack of study on the impacts of future climate change on the P2P energy trading performances. The future climate change will cause variances in the renewable energy production and further lead to changes in the economic performances of households with various energy uses and affect the decision making in PV ownership and pricing strategies. Being unaware of these impacts could potentially hinder the P2P energy sharing application in practice. To bridge such knowledge gap, this paper conducts a systematic investigation of the climate change impacts on the energy sharing performance in solar PV power shared communities. The future weather data is generated using the Morphine method, and an agent-based modeling method is used for simulating the energy trading behaviors of households. Four comparative scenarios of different PV ownerships and pricing strategies are designed. The detailed energy trading performances (including the PV power self-sufficiency, cost saving, revenues, and compound annual growth rate) for the four comparative scenarios are analyzed under both the present and future climates and compared. The study results of a building community located in Sweden show that the future climate change is more beneficial to large energy use households while less beneficial to small households. High price of energy trading can improve the fairness of the economic performances in the community, especially when some of the households do not have any PV ownership. This study can help understand the future climate impacts on the energy sharing performances of building communities, which can in turn guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications.

Original languageEnglish
Pages (from-to)989-1001
Number of pages13
JournalEnergy Reports
Volume8
DOIs
Publication statusE-pub ahead of print - 27 Dec 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • Agent-based modeling
  • Building community
  • Energy sharing
  • Future climate change
  • Peer-to-peer (P2P)
  • Photovoltaics (PV)

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