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A Two-Stage Algorithm of Locational Marginal Price Calculation Subject to Carbon Emission Allowance

Author

Listed:
  • Mingxing Wu

    (Guangdong Power Exchange Center Co., Guangzhou 510080, China)

  • Zhilin Lu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Qing Chen

    (Guangdong Power Exchange Center Co., Guangzhou 510080, China)

  • Tao Zhu

    (Guangdong Power Exchange Center Co., Guangzhou 510080, China)

  • En Lu

    (Guangdong Power Exchange Center Co., Guangzhou 510080, China)

  • Wentian Lu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Mingbo Liu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

Abstract

To analyze the effect of carbon emission quota allocation on the locational marginal price (LMP) of day-ahead electricity markets, this paper proposes a two-stage algorithm. For the first stage of the algorithm, a multi-objective optimization model is established to simultaneously minimize the total costs and carbon emission costs of power systems. Hence, an evenly distributed Pareto optimal solution can be solved effectively by means of the normalized normal constraint method. For the second stage, a tracing model is built with the goal of minimizing the total costs of power systems and satisfying the constraints generated based on the Pareto optimal solution obtained from the first stage. Furthermore, the influence of carbon emission quota allocation on the LMP of electricity markets is analyzed, and different schemes to allocate carbon emission quotas are evaluated on a real 1560-bus and 52-unit system.

Suggested Citation

  • Mingxing Wu & Zhilin Lu & Qing Chen & Tao Zhu & En Lu & Wentian Lu & Mingbo Liu, 2020. "A Two-Stage Algorithm of Locational Marginal Price Calculation Subject to Carbon Emission Allowance," Energies, MDPI, vol. 13(10), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2510-:d:358839
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    References listed on IDEAS

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    1. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
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    3. Lin, Boqiang & Jia, Zhijie, 2020. "Is emission trading scheme an opportunity for renewable energy in China? A perspective of ETS revenue redistributions," Applied Energy, Elsevier, vol. 263(C).
    4. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
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    Cited by:

    1. Ning Ren & Xiufan Zhang & Decheng Fan, 2022. "Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019," IJERPH, MDPI, vol. 19(23), pages 1-24, November.
    2. Wei Li & Tengfei Zhu & Xiaoyu Li & Jianzhang Dong & Jun Liu, 2022. "Recommending Advanced Deep Learning Models for Efficient Insect Pest Detection," Agriculture, MDPI, vol. 12(7), pages 1-17, July.
    3. Sergio Cantillo-Luna & Ricardo Moreno-Chuquen & Harold R. Chamorro & Jose Miguel Riquelme-Dominguez & Francisco Gonzalez-Longatt, 2022. "Locational Marginal Price Forecasting Using SVR-Based Multi-Output Regression in Electricity Markets," Energies, MDPI, vol. 15(1), pages 1-14, January.
    4. Yixin Huang & Xinyi Liu & Zhi Zhang & Li Yang & Zhenzhi Lin & Yangqing Dan & Ke Sun & Zhou Lan & Keping Zhu, 2020. "Multi-Stage Transmission Network Planning Considering Transmission Congestion in the Power Market," Energies, MDPI, vol. 13(18), pages 1-22, September.

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