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A Spinning Reserve Allocation Method for Power Generation Dispatch Accommodating Large-Scale Wind Power Integration

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  • Jianhua Chen

    (Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

  • Wenchuan Wu

    (Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

  • Boming Zhang

    (Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

  • Bin Wang

    (Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

  • Qinglai Guo

    (Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

Abstract

Spinning reserve allocation is a critical problem for active power dispatch with large-scale wind power penetration. A risk-based reserve allocation method that accounts multiple control sub-area coordination is given in this paper. And a multi-objective optimization model is constructed to schedule the spinning generation reserve for online active power dispatch. A fuzzy optimization method is used to transform the multi-objective optimization problem into a single-objective optimization one. The relationship between loss of load expectation and spinning reserve is also derived. And a particle swarm optimization (PSO) method is employed to provide a numerical solution to the problem. Numerical tests on IEEE RTS system are also given to validate the proposed method.

Suggested Citation

  • Jianhua Chen & Wenchuan Wu & Boming Zhang & Bin Wang & Qinglai Guo, 2013. "A Spinning Reserve Allocation Method for Power Generation Dispatch Accommodating Large-Scale Wind Power Integration," Energies, MDPI, vol. 6(10), pages 1-25, October.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:10:p:5357-5381:d:29671
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    References listed on IDEAS

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    1. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
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    Cited by:

    1. Hong, Ying-Yi & Apolinario, Gerard Francesco DG. & Chung, Chen-Nien & Lu, Tai-Ken & Chu, Chia-Chi, 2020. "Effect of Taiwan's energy policy on unit commitment in 2025," Applied Energy, Elsevier, vol. 277(C).
    2. Kyung-bin Kwon & Hyeongon Park & Jae-Kun Lyu & Jong-Keun Park, 2016. "Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand," Energies, MDPI, vol. 9(10), pages 1-16, October.
    3. Dai Cui & Fei Xu & Weichun Ge & Pengxiang Huang & Yunhai Zhou, 2020. "A Coordinated Dispatching Model Considering Generation and Operation Reserve in Wind Power-Photovoltaic-Pumped Storage System," Energies, MDPI, vol. 13(18), pages 1-24, September.
    4. Hong Zhang & Hao Sun & Qian Zhang & Guanxun Kong, 2018. "Microgrid Spinning Reserve Optimization with Improved Information Gap Decision Theory," Energies, MDPI, vol. 11(9), pages 1-17, September.

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