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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

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  • Feng, Zhong-kai
  • Niu, Wen-jing
  • Wang, Wen-chuan
  • Zhou, Jian-zhong
  • Cheng, Chun-tian

Abstract

Recently, the booming electricity demand and intermittent energy has sharply increased the peak shaving pressure in China. However, for a majority of regional power grids in China, the installed capacity of flexible energy (like hydropower and pumped-storage) is small and the thermal plants are asked to respond the sudden load change at peak periods. The existing method based on specialist experience and historical information may generate inferior solutions and fail to reduce the peak pressure. Thus, a practical mixed integer linear programming (MILP) model is developed for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy, where the goal is chosen to minimize the peak-valley difference of the residual load series obtained by subtracting all the thermal generation from the original load curve while satisfying the necessary physical constraints. The MILP model is used to the thermal system in the China’s largest regional power grid, East China Power Grid. The simulations show that the MILP model can effectively smooth the residual load curve by gathering power generation of thermal plants at peak periods. Therefore, an alternative tool is provided to alleviate the peak pressure of thermal-dominant regional power grid in China.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:175:y:2019:i:c:p:618-629
    DOI: 10.1016/j.energy.2019.03.117
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    1. 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.
    2. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm," Energy, Elsevier, vol. 153(C), pages 706-718.
    3. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Liao, Sheng-li, 2017. "Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design," Energy, Elsevier, vol. 126(C), pages 720-732.
    4. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Zhou, Jian-zhong, 2017. "Peak shaving operation of hydro-thermal-nuclear plants serving multiple power grids by linear programming," Energy, Elsevier, vol. 135(C), pages 210-219.
    5. Song, Chunhe & Jing, Wei & Zeng, Peng & Yu, Haibin & Rosenberg, Catherine, 2018. "Energy consumption analysis of residential swimming pools for peak load shaving," Applied Energy, Elsevier, vol. 220(C), pages 176-191.
    6. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
    7. Zhang, Huifeng & Zhou, Jianzhong & Fang, Na & Zhang, Rui & Zhang, Yongchuan, 2013. "Daily hydrothermal scheduling with economic emission using simulated annealing technique based multi-objective cultural differential evolution approach," Energy, Elsevier, vol. 50(C), pages 24-37.
    8. Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
    9. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2019. "China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities," Renewable Energy, Elsevier, vol. 136(C), pages 805-818.
    10. Zhang, Huifeng & Yue, Dong & Xie, Xiangpeng & Dou, Chunxia & Sun, Feng, 2017. "Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power," Energy, Elsevier, vol. 122(C), pages 748-766.
    11. Ming, Bo & Liu, Pan & Guo, Shenglian & Zhang, Xiaoqi & Feng, Maoyuan & Wang, Xianxun, 2017. "Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions," Applied Energy, Elsevier, vol. 204(C), pages 432-445.
    12. Feng, Zhong-kai & Niu, Wen-jing & Wang, Sen & Cheng, Chun-tian & Jiang, Zhi-qiang & Qin, Hui & Liu, Yi, 2018. "Developing a successive linear programming model for head-sensitive hydropower system operation considering power shortage aspect," Energy, Elsevier, vol. 155(C), pages 252-261.
    13. Catalão, J.P.S. & Pousinho, H.M.I. & Contreras, J., 2012. "Optimal hydro scheduling and offering strategies considering price uncertainty and risk management," Energy, Elsevier, vol. 37(1), pages 237-244.
    14. Deepti Rani & Maria Moreira, 2010. "Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1107-1138, April.
    15. Catalão, J.P.S. & Pousinho, H.M.I. & Mendes, V.M.F., 2011. "Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approach," Energy, Elsevier, vol. 36(1), pages 500-507.
    16. Yi-min Wang & Jian-xia Chang & Qiang Huang, 2010. "Simulation with RBF Neural Network Model for Reservoir Operation Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2597-2610, September.
    17. Gu, Yujiong & Xu, Jing & Chen, Dongchao & Wang, Zhong & Li, Qianqian, 2016. "Overall review of peak shaving for coal-fired power units in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 723-731.
    18. Niu, Wen-jing & Feng, Zhong-kai & Cheng, Chun-tian, 2018. "Optimization of variable-head hydropower system operation considering power shortage aspect with quadratic programming and successive approximation," Energy, Elsevier, vol. 143(C), pages 1020-1028.
    19. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhou, Yanlai & Gao, Shida & Li, He, 2018. "Robust hydroelectric unit commitment considering integration of large-scale photovoltaic power: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1341-1352.
    20. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Wu, Xin-yu, 2017. "Optimization of hydropower system operation by uniform dynamic programming for dimensionality reduction," Energy, Elsevier, vol. 134(C), pages 718-730.
    21. Chen, Diyi & Liu, Si & Ma, Xiaoyi, 2013. "Modeling, nonlinear dynamical analysis of a novel power system with random wind power and it's control," Energy, Elsevier, vol. 53(C), pages 139-146.
    22. Shen, Jianjian & Cheng, Chuntian & Wu, Xinyu & Cheng, Xiong & Li, Weidong & Lu, Jianyu, 2014. "Optimization of peak loads among multiple provincial power grids under a central dispatching authority," Energy, Elsevier, vol. 74(C), pages 494-505.
    23. Wang, Xuebin & Chang, Jianxia & Meng, Xuejiao & Wang, Yimin, 2018. "Short-term hydro-thermal-wind-photovoltaic complementary operation of interconnected power systems," Applied Energy, Elsevier, vol. 229(C), pages 945-962.
    24. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
    Full references (including those not matched with items on IDEAS)

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