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A new three-part tariff pricing scheme for the electricity microgrid considering consumer regret

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  • Tsao, Yu-Chung
  • Linh, Vu-Thuy

Abstract

This study considers a pricing scheme problem involving a power company and an electricity consumer. The power company determines the time-varying price for nonrenewable energy and the buy-back price for renewable energy, while maximizing its profit. A three-part tariff price schedule was applied to nonrenewable energy and, based on the pricing policy, the electricity consumer decides whether they want to become a prosumer. If the electricity consumer decides to become a prosumer, they also determine the price of renewable energy for other consumers to maximize their utility. The regret value is included in the consumer model to help them make the decisions. A nonlinear method was used to solve the proposed problems and obtain theoretical results in two cases: with and without the consideration of peer-to-peer trading. Several examples are presented to illustrate the proposed model and solution approach. The results show that considering the regret value increases the electricity price. Thus, the regret parameter has a positive influence on electricity price. This also demonstrates that the case with consideration for peer-to-peer trading is more beneficial for the prosumer than the case without it.

Suggested Citation

  • Tsao, Yu-Chung & Linh, Vu-Thuy, 2022. "A new three-part tariff pricing scheme for the electricity microgrid considering consumer regret," Energy, Elsevier, vol. 254(PC).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pc:s0360544222012907
    DOI: 10.1016/j.energy.2022.124387
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    Citations

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    Cited by:

    1. Gjorgievski, Vladimir Z. & Velkovski, Bodan & Francesco Demetrio, Minuto & Cundeva, Snezana & Markovska, Natasa, 2023. "Energy sharing in European renewable energy communities: Impact of regulated charges," Energy, Elsevier, vol. 281(C).
    2. Carvalho, Diego B. & Bortoni, Edson da C., 2024. "Proposed model with weighted parameters for microgrid management: Incorporating diverse load profiles, assorted tariff policies, and energy storage devices," Energy, Elsevier, vol. 296(C).

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