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Investigating peer-to-peer power transactions for reducing EV induced network congestion

Author

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  • Haider, Sajjad
  • Rizvi, Rida e Zahra
  • Walewski, John
  • Schegner, Peter

Abstract

Current electricity pricing models take into account costs of generation, transmission, emissions and a fixed cost of distribution based on time of day and type of primary source. However, the authors postulate that increasing fast charging for EVs will lead to increased overloading and voltage drops observed in networks at the low voltage level. To this end, the authors propose a novel method that encourages reactive power injection to minimize voltage drops and active power injection to minimize cable loading by using a centralized, double-sided optimized algorithm. This model allows for peer-to-peer power delivery, incentivized using pricing factors, encouraging local optimization-based solutions to network overloading as well as increased islanding in the network as a means of improving grid resilience and allowing optimal EV charging and discharging. Incentivized peer-to-peer transactions are then recorded in a centralized blockchain, with instantaneous power serving as the transactional commodity for both fixed consumers and generators (houses) and mobile consumers and generators (EVs). The mathematical model, as well as the impact of such a decentralized network compared to a business-as-usual network shows the potential of decongestion of 5–10% in terms of a reduction in voltage drops and cable loading with even a low EV penetration level (<5% of available transportation) by using existing resources as V2G and voltage stability resources.

Suggested Citation

  • Haider, Sajjad & Rizvi, Rida e Zahra & Walewski, John & Schegner, Peter, 2022. "Investigating peer-to-peer power transactions for reducing EV induced network congestion," Energy, Elsevier, vol. 254(PB).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s0360544222012208
    DOI: 10.1016/j.energy.2022.124317
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    5. Hussain, Sadam & Azim, M. Imran & Lai, Chunyan & Eicker, Ursula, 2023. "New coordination framework for smart home peer-to-peer trading to reduce impact on distribution transformer," Energy, Elsevier, vol. 284(C).

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