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Wind Power Consumption Research Based on Green Economic Indicators

Author

Listed:
  • Xiuyun Wang

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Yibing Zhou

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Junyu Tian

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Jian Wang

    (State Grid Sanmenxia Power Supply Company, Sanmenxia 472000, China)

  • Yang Cui

    (School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

Abstract

As a representative form of new energy generation, wind power has effectively alleviated environmental pollution and energy shortages. This paper constructs a green economic indicator to measure the degree of coordinated development of environmental and social benefits. To increase the amount of wind power consumption, an economic dispatch model based on the coordinated operation of cogeneration units and electric boilers was established; we also introduced the green certificate transaction cost, which effectively meets the strategic needs of China’s energy low-carbon transformation top-level system design. Wind power output has instability and volatility, so it puts higher requirements on the stable operation of thermal power units. To solve the stability problem, this paper introduces the output index of the thermal power unit and rationally plans the unit combination strategy, as well as introducing the concept of chance-constrained programming due to the uncertainty of load and wind power in the model. Uncertainty factors are transformed into load forecasting errors and wind power prediction errors for processing. Based on the normal distribution theory, the uncertainty model is transformed into a certain equivalence class model, and the improved disturbance mutated particle swarm optimization algorithm is used to solve the problem. Finally, the validity and feasibility of the proposed model are verified based on the IEEE30 node system.

Suggested Citation

  • Xiuyun Wang & Yibing Zhou & Junyu Tian & Jian Wang & Yang Cui, 2018. "Wind Power Consumption Research Based on Green Economic Indicators," Energies, MDPI, vol. 11(10), pages 1-24, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2829-:d:176974
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    References listed on IDEAS

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    1. Can Ding & Yiyuan Zhou & Qingchang Ding & Kaiming Li, 2022. "Integrated Carbon-Capture-Based Low-Carbon Economic Dispatch of Power Systems Based on EEMD-LSTM-SVR Wind Power Forecasting," Energies, MDPI, vol. 15(5), pages 1-27, February.

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