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Modeling and Optimization of the Medium-Term Units Commitment of Thermal Power

Author

Listed:
  • Shengli Liao

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Zhifu Li

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Gang Li

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Jiayang Wang

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Xinyu Wu

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

Abstract

Coal-fired thermal power plants, which represent the largest proportion of China’s electric power system, are very sluggish in responding to power system load demands. Thus, a reasonable and feasible scheme for the medium-term optimal commitment of thermal units (MOCTU) can ensure that the generation process runs smoothly and minimizes the start-up and shut-down times of thermal units. In this paper, based on the real-world and practical demands of power dispatch centers in China, a flexible mathematical model for MOCTU that uses equal utilization hours for the installed capacity of all thermal power plants as the optimization goal and that considers the award hours for MOCTU is developed. MOCTU is a unit commitment (UC) problem with characteristics of large-scale, high dimensions and nonlinearity. For optimization, an improved progressive optimality algorithm (IPOA) offering the advantages of POA is adopted to overcome the drawback of POA of easily falling into the local optima. In the optimization process, strategies of system operating capacity equalization and single station operating peak combination are introduced to move the target solution from the boundary constraints along the target isopleths into the feasible solution’s interior to guarantee the global optima. The results of a case study consisting of nine thermal power plants with 27 units show that the presented algorithm can obtain an optimal solution and is competent in solving the MOCTU with high efficiency and accuracy as well as that the developed simulation model can be applied to practical engineering needs.

Suggested Citation

  • Shengli Liao & Zhifu Li & Gang Li & Jiayang Wang & Xinyu Wu, 2015. "Modeling and Optimization of the Medium-Term Units Commitment of Thermal Power," Energies, MDPI, vol. 8(11), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:11:p:12345-12864:d:58715
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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. Dang, Chuangyin & Li, Minqiang, 2007. "A floating-point genetic algorithm for solving the unit commitment problem," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1370-1395, September.
    3. Niknam, Taher & Khodaei, Amin & Fallahi, Farhad, 2009. "A new decomposition approach for the thermal unit commitment problem," Applied Energy, Elsevier, vol. 86(9), pages 1667-1674, September.
    4. Liu, Liwei & Zong, Haijing & Zhao, Erdong & Chen, Chuxiang & Wang, Jianzhou, 2014. "Can China realize its carbon emission reduction goal in 2020: From the perspective of thermal power development," Applied Energy, Elsevier, vol. 124(C), pages 199-212.
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    Cited by:

    1. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    2. Shengli Liao & Hongye Zhao & Gang Li & Benxi Liu, 2019. "Short-Term Load Dispatching Method for a Diversion Hydropower Plant with Multiple Turbines in One Tunnel Using a Two-Stage Model," Energies, MDPI, vol. 12(8), pages 1-18, April.
    3. Gang Wang & Daihai You & Suhua Lou & Zhe Zhang & Li Dai, 2017. "Economic Valuation of Low-Load Operation with Auxiliary Firing of Coal-Fired Units," Energies, MDPI, vol. 10(9), pages 1-20, September.
    4. Alok K. Tripathi, 2021. "Crisis of Survival of Thermal Power Plants in India due to Consistently Falling Capacity Utilization Factors Responsible and Future Outlook," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 328-337.
    5. Ying-Yi Hong, 2016. "Electric Power Systems Research," Energies, MDPI, vol. 9(10), pages 1-4, October.

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