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Does P2P trading favor investments in PV–Battery Systems?

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  • Andreolli, Francesca
  • D’Alpaos, Chiara
  • Kort, Peter

Abstract

In a conducive regulatory framework, thanks to the advancements in communication technologies and the digitalization of the energy power system (e.g., smart meters, control devices), Peer-to-Peer (P2P) trading can effectively empower prosumers and consumers and favor the penetration of renewable energy. In this paper, we investigate households’ decision to invest in domestic PV plants coupled with battery storage, namely PV–battery systems (PVBs), participate in a local energy community (EC), and exchange energy among EC members via P2P trading. Thanks to storage and P2P trading, households can strategically decide their optimal energy production/consumption patterns and offer services to other EC participants. We investigate whether P2P trading affect the investment value and the households’ decision on the optimal investment timing and size. In detail, we develop a stochastic optimization model based on the real options approach. Our results show that, ceteris paribus, thanks to P2P trading, households accelerate investments and invest in larger plants compared to scenarios in which P2P trading in not permitted. According to our findings, it is never optimal to invest immediately. Consequently, the households’ optimal strategy is to defer investment. Nonetheless, as soon as the share of P2P trading increases, households accelerate investments, though the optimal size of plants reduces.

Suggested Citation

  • Andreolli, Francesca & D’Alpaos, Chiara & Kort, Peter, 2025. "Does P2P trading favor investments in PV–Battery Systems?," Energy Economics, Elsevier, vol. 145(C).
    • Handle: RePEc:eee:eneeco:v:145:y:2025:i:c:s0140988325002427
    DOI: 10.1016/j.eneco.2025.108418
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    Keywords

    PV plants; Battery storage; P2P trading; Real options; Dynamic stochastic optimization;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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