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Decarbonizing the grid: Utilizing demand-side flexibility for carbon emission reduction through locational marginal emissions in distribution networks

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  • Park, Byungkwon
  • Dong, Jin
  • Liu, Boming
  • Kuruganti, Teja

Abstract

Decarbonization of the electric grid has become an important world-wide priority and is actively happening in many ways by introducing innovations and new technologies from the generation sectors to the demand sectors. In particular, one promising pathway toward such net-zero carbon emissions is to utilize the demand-side flexibility with the increasing number of flexible loads in distribution networks. In this paper, we explore a load shifting strategy with the emerging concept of location marginal emissions (LMEs) to reduce carbon emissions. LMEs measure the impact of carbon emissions including the locational aspect in more granular way and thus provide a novel mechanism for the system operator and load aggregators to design the LME-based load shifting strategy, which can efficiently guide consumers and thus adjust their consumption behaviors. Simulation case studies on the IEEE test networks are performed to validate the capability of the proposed load shifting method to reduce carbon emissions. We also compare this with other relevant strategies to discuss multiple scenarios and corresponding results. While each provides a different level of flexibility, all the explored strategies tested have led to solutions that have lower carbon emissions, indicating the great potential of demand-side flexibility in reducing carbon emissions for future distribution networks.

Suggested Citation

  • Park, Byungkwon & Dong, Jin & Liu, Boming & Kuruganti, Teja, 2023. "Decarbonizing the grid: Utilizing demand-side flexibility for carbon emission reduction through locational marginal emissions in distribution networks," Applied Energy, Elsevier, vol. 330(PA).
  • Handle: RePEc:eee:appene:v:330:y:2023:i:pa:s0306261922015604
    DOI: 10.1016/j.apenergy.2022.120303
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    References listed on IDEAS

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    1. Wang, Y. & Wang, C. & Miller, C.J. & McElmurry, S.P. & Miller, S.S. & Rogers, M.M., 2014. "Locational marginal emissions: Analysis of pollutant emission reduction through spatial management of load distribution," Applied Energy, Elsevier, vol. 119(C), pages 141-150.
    2. Strachan, Neil & Farrell, Alexander, 2006. "Emissions from distributed vs. centralized generation: The importance of system performance," Energy Policy, Elsevier, vol. 34(17), pages 2677-2689, November.
    3. Na (Nora) Wang, 2018. "Transactive control for connected homes and neighbourhoods," Nature Energy, Nature, vol. 3(11), pages 907-909, November.
    4. Dong, Jin & Olama, Mohammed M. & Kuruganti, Teja & Melin, Alexander M. & Djouadi, Seddik M. & Zhang, Yichen & Xue, Yaosuo, 2020. "Novel stochastic methods to predict short-term solar radiation and photovoltaic power," Renewable Energy, Elsevier, vol. 145(C), pages 333-346.
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    Cited by:

    1. Zhao, Xudong & Wang, Yibo & Liu, Chuang & Cai, Guowei & Ge, Weichun & Zhou, Jianing & Wang, Dongzhe, 2024. "Low carbon scheduling method of electric power system considering energy-intensive load regulation of electrofused magnesium and wind powerfluctuation stabilization," Applied Energy, Elsevier, vol. 357(C).
    2. Förster, Robert & Harding, Sebastian & Buhl, Hans Ulrich, 2024. "Unleashing the economic and ecological potential of energy flexibility: Attractiveness of real-time electricity tariffs in energy crises," Energy Policy, Elsevier, vol. 185(C).

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