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Optimal Scheduling of a Regional Power System Aiming at Accommodating Clean Energy

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  • Xing Chen

    (China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China
    State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Suhua Lou

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yanjie Liang

    (Power Dispatch and Control Center of China Southern Power Grid, Guangzhou 510623, China)

  • Yaowu Wu

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Xianglu He

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The regional power system is an essential mechanism to solve the unbalanced distribution of resources and achieve more efficient resource allocation. In this paper, an optimal scheduling model of the regional power system is developed, to maximize social welfare and minimize clean energy electricity curtailment. This model can realize the optimal allocation of power generation resources and the maximum accommodation of multiple types of clean energy, by minimizing the sum of the electricity purchase cost and the dynamic penalty cost of clean energy. Meanwhile, it considers the modeling of the key AC/DC hybrid tie-line in the regional power grid. To this end, the modeling methods of power transmitted by AC/DC tie-line, the net loss of the tie-line, the stair-like operation of the DC tie-line power, the operation constraints of the DC tie-line are proposed. Then a simulation example study is conducted to verify the effectiveness of the model, which proves that the regional power system can stimulate the resource optimization potential better than the provincial power system.

Suggested Citation

  • Xing Chen & Suhua Lou & Yanjie Liang & Yaowu Wu & Xianglu He, 2021. "Optimal Scheduling of a Regional Power System Aiming at Accommodating Clean Energy," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2169-:d:501155
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    References listed on IDEAS

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    1. Zhang, Heng & Hu, Xiao & Cheng, Haozhong & Zhang, Shenxi & Hong, Shaoyun & Gu, Qingfa, 2021. "Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty," Energy, Elsevier, vol. 222(C).
    2. Quan, Hao & Srinivasan, Dipti & Khosravi, Abbas, 2016. "Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study," Energy, Elsevier, vol. 103(C), pages 735-745.
    3. Pang, Rui-Zhi & Deng, Zhong-Qi & Hu, Jin-li, 2015. "Clean energy use and total-factor efficiencies: An international comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1158-1171.
    4. Geng, Zhaowei & Conejo, Antonio J. & Chen, Qixin & Xia, Qing & Kang, Chongqing, 2017. "Electricity production scheduling under uncertainty: Max social welfare vs. min emission vs. max renewable production," Applied Energy, Elsevier, vol. 193(C), pages 540-549.
    5. Göransson, Lisa & Johnsson, Filip, 2009. "Dispatch modeling of a regional power generation system – Integrating wind power," Renewable Energy, Elsevier, vol. 34(4), pages 1040-1049.
    6. Shunjiang Lin & Guansheng Fan & Yuan Lu & Mingbo Liu & Yi Lu & Qifeng Li, 2019. "A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units," Energies, MDPI, vol. 12(19), pages 1-24, September.
    7. Kaldellis, J.K. & Zafirakis, D., 2020. "Prospects and challenges for clean energy in European Islands.The TILOS paradigm," Renewable Energy, Elsevier, vol. 145(C), pages 2489-2502.
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    Cited by:

    1. Yi Luo & Yin Zhang & Muyi Tang & Youbin Zhou & Ying Wang & Defu Cai & Haiguang Liu, 2021. "A Novel Receiving End Grid Planning Method with Mutually Exclusive Constraints in Alternating Current/Direct Current Lines," Sustainability, MDPI, vol. 13(13), pages 1-16, June.

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