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Study on Nested-Structured Load Shedding Method of Thermal Power Stations Based on Output Fluctuations

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  • Liping Wang

    (Renewable Energy School, North China Electric Power University, Beijing 102206, China)

  • Minghao Liu

    (Renewable Energy School, North China Electric Power University, Beijing 102206, China)

  • Boquan Wang

    (Renewable Energy School, North China Electric Power University, Beijing 102206, China)

  • Jiajie Wu

    (Renewable Energy School, North China Electric Power University, Beijing 102206, China)

  • Chuangang Li

    (Renewable Energy School, North China Electric Power University, Beijing 102206, China)

Abstract

The balance of electric power and energy is important for designing power stations’ load distribution, capacity allocation, and future operation plans, and is thus of vital significance for power design and planning departments. In this paper, we analyzed the correlation between the output fluctuations of power stations and the load fluctuations of the power system in order to study the load change of the power system within a year/month/day, and the output variation amongst the power stations in operation. Reducing the output of hydropower stations or increasing the output of thermal power stations (TPS) could keep the monthly adjustment coefficient of the power system within a certain range, and thus balance the power system’s electric power and energy. The method for calculating the balance of electric power and energy of TPS is also improved. The nested-structured load shedding method (NSLSM), which is based on the calculation principle of the load shedding method, is put forward to iteratively calculate the peak shaving capacity and non-peak shaving capacity of every single thermal power station. In this way, the output process of each thermal power station can be obtained. According to the results and analysis of an example, the proposed methods of calculating monthly adjustment coefficients and the balance of electric power and energy of a thermal power station are validated in terms of correctness, feasibility, and effectiveness.

Suggested Citation

  • Liping Wang & Minghao Liu & Boquan Wang & Jiajie Wu & Chuangang Li, 2017. "Study on Nested-Structured Load Shedding Method of Thermal Power Stations Based on Output Fluctuations," Energies, MDPI, vol. 10(10), pages 1-16, September.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1472-:d:112987
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    References listed on IDEAS

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    1. Hyeon-Gon Park & Jae-Kun Lyu & YongCheol Kang & Jong-Keun Park, 2014. "Unit Commitment Considering Interruptible Load for Power System Operation with Wind Power," Energies, MDPI, vol. 7(7), pages 1-19, July.
    2. Blanco, J.M. & Vazquez, L. & Peña, F. & Diaz, D., 2013. "New investigation on diagnosing steam production systems from multivariate time series applied to thermal power plants," Applied Energy, Elsevier, vol. 101(C), pages 589-599.
    3. Cheng, Chun-Tian & Shen, Jian-Jian & Wu, Xin-Yu & Chau, Kwok-wing, 2012. "Operation challenges for fast-growing China's hydropower systems and respondence to energy saving and emission reduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2386-2393.
    4. Bin Xu & Ping-An Zhong & Xinyu Wan & Weiguo Zhang & Xuan Chen, 2012. "Dynamic Feasible Region Genetic Algorithm for Optimal Operation of a Multi-Reservoir System," Energies, MDPI, vol. 5(8), pages 1-17, August.
    5. Ming-Tse Kuo & Shiue-Der Lu, 2013. "Experimental Research and Control Strategy of Pumped Storage Units Dispatching in the Taiwan Power System Considering Transmission Line Limits," Energies, MDPI, vol. 6(7), pages 1-21, July.
    6. Li, Li & Tan, Zhongfu & Wang, Jianhui & Xu, Jun & Cai, Chengkai & Hou, Yong, 2011. "Energy conservation and emission reduction policies for the electric power industry in China," Energy Policy, Elsevier, vol. 39(6), pages 3669-3679, June.
    7. Shenglian Guo & Jionghong Chen & Yu Li & Pan Liu & Tianyuan Li, 2011. "Joint Operation of the Multi-Reservoir System of the Three Gorges and the Qingjiang Cascade Reservoirs," Energies, MDPI, vol. 4(7), pages 1-15, July.
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    1. Edwin Garcia & Alexander Águila & Leony Ortiz & Milton Ruiz, 2024. "Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids," Energies, MDPI, vol. 17(5), pages 1-16, February.

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