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.

Highlights

  • The latest report from International Energy Agency (IEA) (2021) on Roadmap to Net Zero by 2050 calls for scaling up solar and wind rapidly this decade, reaching annual additions of 630 gigawatts of solar photovoltaics (PV) and 390 GW of wind by 2030, four times the record levels set in 2020

  • This study reveals the impacts of future climate change on solar powered building community energy sharing performances, which can help guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications

  • Pself,Ts is the power self-consumed by a household in the specific time-step, which is calculated as the smaller one of the hourly electricity demand and hourly PV power production. dgrid,Ts (SEK/(kW h)) is the cost of electricity offered by the external grid in the specific time-step, i.e., the grid electricity price

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Summary

Introduction

The latest report from International Energy Agency (IEA) (2021) on Roadmap to Net Zero by 2050 calls for scaling up solar and wind rapidly this decade, reaching annual additions of 630 gigawatts of solar photovoltaics (PV) and 390 GW of wind by 2030, four times the record levels set in 2020. 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 unknown about these impacts could potentially hinder the P2P energy sharing application in communities. The impacts of future climate change on the P2P energy sharing performances of solar power shared building community, including the self-sufficiency, cost savings, revenues and compound annual growth rate (CAGR), are investigated and analyzed. This study reveals the impacts of future climate change on solar powered building community energy sharing performances, which can help guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications. An ensemble approach is generally preferred to a one-model response (Knutti et al, 2010)

Prediction of the future climate using the Morphine method
Agent-based modeling of the P2P energy sharing under different scenarios
Performance indicators for analysis
Building modeling
Renewable energy system modeling
Case studies and results analysis
Comparison of the present and future climates
Comparison P2P energy sharing performances
Findings
Discussion of the study results
Conclusion
Full Text
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