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Stochastic LMP (Locational marginal price) calculation method in distribution systems to minimize loss and emission based on Shapley value and two-point estimate method

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  • Azad-Farsani, Ehsan
  • Agah, S.M.M.
  • Askarian-Abyaneh, Hossein
  • Abedi, Mehrdad
  • Hosseinian, S.H.

Abstract

LMP (Locational marginal price) calculation is a serious impediment in distribution operation when private DG (distributed generation) units are connected to the network. A novel policy is developed in this study to guide distribution company (DISCO) to exert its control over the private units when power loss and green-house gases emissions are minimized. LMP at each DG bus is calculated according to the contribution of the DG to the reduced amount of loss and emission. An iterative algorithm which is based on the Shapley value method is proposed to allocate loss and emission reduction. The proposed algorithm will provide a robust state estimation tool for DISCOs in the next step of operation. The state estimation tool provides the decision maker with the ability to exert its control over private DG units when loss and emission are minimized. Also, a stochastic approach based on the PEM (point estimate method) is employed to capture uncertainty in the market price and load demand. The proposed methodology is applied to a realistic distribution network, and efficiency and accuracy of the method are verified.

Suggested Citation

  • Azad-Farsani, Ehsan & Agah, S.M.M. & Askarian-Abyaneh, Hossein & Abedi, Mehrdad & Hosseinian, S.H., 2016. "Stochastic LMP (Locational marginal price) calculation method in distribution systems to minimize loss and emission based on Shapley value and two-point estimate method," Energy, Elsevier, vol. 107(C), pages 396-408.
    • Handle: RePEc:eee:energy:v:107:y:2016:i:c:p:396-408
    DOI: 10.1016/j.energy.2016.04.036
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    References listed on IDEAS

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    Cited by:

    1. Azad-Farsani, Ehsan & Sardou, Iman Goroohi & Abedini, Saeed, 2021. "Distribution Network Reconfiguration based on LMP at DG connected busses using game theory and self-adaptive FWA," Energy, Elsevier, vol. 215(PB).
    2. Karhinen, Santtu & Huuki, Hannu, 2020. "How are the long distances between renewable energy sources and load centres reflected in locational marginal prices?," Energy, Elsevier, vol. 210(C).
    3. Farzaneh Pourahmadi & Payman Dehghanian, 2018. "A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations," Mathematics, MDPI, vol. 6(9), pages 1-14, September.
    4. Voswinkel, Simon & Höckner, Jonas & Khalid, Abuzar & Weber, Christoph, 2022. "Sharing congestion management costs among system operators using the Shapley value," Applied Energy, Elsevier, vol. 317(C).
    5. Cremers, Sho & Robu, Valentin & Zhang, Peter & Andoni, Merlinda & Norbu, Sonam & Flynn, David, 2023. "Efficient methods for approximating the Shapley value for asset sharing in energy communities," Applied Energy, Elsevier, vol. 331(C).

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