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Optimal Scheduling of Power System Incorporating the Flexibility of Thermal Units

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  • Tong Guo

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Yajing Gao

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Xiaojie Zhou

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China)

  • Yonggang Li

    (Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China)

  • Jiaomin Liu

    (Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

Due to the randomness, volatility and intermittent nature of wind power, power systems with significant wind penetration face serious “curtailment” problems. The flexibility of a power system is an important factor that affects the large-scale consumption of wind power. Based on this fact, this paper takes into account the economics and flexibility of the system, and proposes an optimal scheduling method that takes the flexibility of each thermal power unit into account. Firstly, a comprehensive evaluation index system of thermal power unit flexibility is designed by an analytic hierarchy process and entropy method. The system covers the technical indexes and economic characteristics of thermal power units and is able to quantitatively evaluate the different types of thermal power units in the system. Secondly, a multi-objective optimization scheduling model involving the overall flexibility of the unit and the total power generation cost is established. Finally, the correctness and effectiveness of the proposed indicators and models are verified by a case study.

Suggested Citation

  • Tong Guo & Yajing Gao & Xiaojie Zhou & Yonggang Li & Jiaomin Liu, 2018. "Optimal Scheduling of Power System Incorporating the Flexibility of Thermal Units," Energies, MDPI, vol. 11(9), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2195-:d:165148
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    References listed on IDEAS

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    1. Oree, Vishwamitra & Sayed Hassen, Sayed Z., 2016. "A composite metric for assessing flexibility available in conventional generators of power systems," Applied Energy, Elsevier, vol. 177(C), pages 683-691.
    2. Zhiwei Li & Tianran Jin & Shuqiang Zhao & Jinshan Liu, 2018. "Power System Day-Ahead Unit Commitment Based on Chance-Constrained Dependent Chance Goal Programming," Energies, MDPI, vol. 11(7), pages 1-20, July.
    3. Eser, Patrick & Singh, Antriksh & Chokani, Ndaona & Abhari, Reza S., 2016. "Effect of increased renewables generation on operation of thermal power plants," Applied Energy, Elsevier, vol. 164(C), pages 723-732.
    4. Mengyue Hu & Zhijian Hu, 2018. "Optimization Scheduling Method for Power Systems Considering Optimal Wind Power Intervals," Energies, MDPI, vol. 11(7), pages 1-19, July.
    5. Tuohy, Aidan & Meibom, Peter & Denny, Eleanor & O'Malley, Mark, 2009. "Unit commitment for systems with significant wind penetration," MPRA Paper 34849, University Library of Munich, Germany.
    6. Michal Wydra, 2018. "Performance and Accuracy Investigation of the Two-Step Algorithm for Power System State and Line Temperature Estimation," Energies, MDPI, vol. 11(4), pages 1-20, April.
    7. Kubik, M.L. & Coker, P.J. & Barlow, J.F., 2015. "Increasing thermal plant flexibility in a high renewables power system," Applied Energy, Elsevier, vol. 154(C), pages 102-111.
    8. Shi, Rui-jing & Fan, Xiao-chao & He, Ying, 2017. "Comprehensive evaluation index system for wind power utilization levels in wind farms in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 461-471.
    9. Wenlei Bai & Duehee Lee & Kwang Y. Lee, 2017. "Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model," Energies, MDPI, vol. 10(12), pages 1-19, December.
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    Cited by:

    1. Jianjun Wang & Jikun Huo & Shuo Zhang & Yun Teng & Li Li & Taoya Han, 2021. "Flexibility Transformation Decision-Making Evaluation of Coal-Fired Thermal Power Units Deep Peak Shaving in China," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
    2. Xiaoye Jin & Meiying Li & Fansheng Meng, 2019. "Comprehensive Evaluation of the New Energy Power Generation Development at the Regional Level: An Empirical Analysis from China," Energies, MDPI, vol. 12(23), pages 1-15, December.

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