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Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China

Author

Listed:
  • Peng Wang

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Chunsheng Wang

    (School of Information Science and Engineering, Central South University, Changsha 410083, China)

  • Yukun Hu

    (School of Management, Cranfield University, Bedford MK43 0AL, UK)

  • Liz Varga

    (School of Management, Cranfield University, Bedford MK43 0AL, UK)

  • Wei Wang

    (College of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost.

Suggested Citation

  • Peng Wang & Chunsheng Wang & Yukun Hu & Liz Varga & Wei Wang, 2018. "Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China," Energies, MDPI, vol. 11(6), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1498-:d:151393
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    References listed on IDEAS

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    Cited by:

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    2. Yanyue Wang & Guohua Fang, 2022. "Joint Operation Modes and Economic Analysis of Nuclear Power and Pumped Storage Plants under Different Power Market Environments," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    3. Wu, C.B. & Guan, P.B. & Zhong, L.N. & Lv, J. & Hu, X.F. & Huang, G.H. & Li, C.C., 2020. "An optimized low-carbon production planning model for power industry in coal-dependent regions - A case study of Shandong, China," Energy, Elsevier, vol. 192(C).
    4. Xiangyu Kong & Jingtao Yao & Zhijun E & Xin Wang, 2019. "Generation Expansion Planning Based on Dynamic Bayesian Network Considering the Uncertainty of Renewable Energy Resources," Energies, MDPI, vol. 12(13), pages 1-20, June.
    5. Majid Dehghani & Mohammad Taghipour & Saleh Sadeghi Gougheri & Amirhossein Nikoofard & Gevork B. Gharehpetian & Mahdi Khosravy, 2021. "A Deep Learning-Based Approach for Generation Expansion Planning Considering Power Plants Lifetime," Energies, MDPI, vol. 14(23), pages 1-21, December.
    6. Qingtao Li & Jianxue Wang & Yao Zhang & Yue Fan & Guojun Bao & Xuebin Wang, 2020. "Multi-Period Generation Expansion Planning for Sustainable Power Systems to Maximize the Utilization of Renewable Energy Sources," Sustainability, MDPI, vol. 12(3), pages 1-18, February.

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