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Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units

Author

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  • Shan Deng

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Qinghua Wu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Zhaoxia Jing

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Lilan Wu

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Feng Wei

    (School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China)

  • Xiaoxin Zhou

    (China Electric Power Research Institute, State Grid Corporation of China, Qinghe, Beijing 100192, China)

Abstract

The simulation model is one of the key points affecting the optimal planning and operation of energy hubs (EHs). Since treating the efficiencies of generation units as constants would significantly simplify the calculation, only a simplified model is investigated in most research works. In this paper, aiming at optimizing the capacity configuration of an EH, we present a part-load characteristics-based (PLCB) model, in which the efficiencies of generation units will change with the fluctuating load. Based on the PLCB model, the accuracy of the EH model can be improved. Furthermore, a two-stage planning method is proposed to solve the optimal capacity configuration problem of the EH. Group Search Optimizer (GSO) is used to determine the optimal size in the first stage, and a mathematical programming method is applied to obtain the optimal operation of the EH in the second stage. Comparative studies using the PLCB model and the simplified model are performed to examine the impacts of equipment part-load characteristics on the sizing results. Simulation results indicate that the proposed model appears to have a better economic performance than the simplified model.

Suggested Citation

  • Shan Deng & Qinghua Wu & Zhaoxia Jing & Lilan Wu & Feng Wei & Xiaoxin Zhou, 2017. "Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units," Energies, MDPI, vol. 10(12), pages 1-19, November.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:1966-:d:120382
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    References listed on IDEAS

    as
    1. Ying-Yi Hong & Yuan-Ming Lai & Yung-Ruei Chang & Yih-Der Lee & Pang-Wei Liu, 2015. "Optimizing Capacities of Distributed Generation and Energy Storage in a Small Autonomous Power System Considering Uncertainty in Renewables," Energies, MDPI, vol. 8(4), pages 1-20, March.
    2. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    3. Jing, Z.X. & Jiang, X.S. & Wu, Q.H. & Tang, W.H. & Hua, B., 2014. "Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system," Energy, Elsevier, vol. 73(C), pages 399-415.
    4. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim & Yong-Hoon Im & Jae-Yong Lee, 2017. "Optimal Energy Management of Combined Cooling, Heat and Power in Different Demand Type Buildings Considering Seasonal Demand Variations," Energies, MDPI, vol. 10(6), pages 1-21, June.
    5. Rong, Aiying & Lahdelma, Risto, 2005. "An efficient linear programming model and optimization algorithm for trigeneration," Applied Energy, Elsevier, vol. 82(1), pages 40-63, September.
    6. Kamyab, Farhad & Bahrami, Shahab, 2016. "Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets," Energy, Elsevier, vol. 106(C), pages 343-355.
    7. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    8. Kaabeche, A. & Belhamel, M. & Ibtiouen, R., 2011. "Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system," Energy, Elsevier, vol. 36(2), pages 1214-1222.
    9. Rongxiang Yuan & Timing Li & Xiangtian Deng & Jun Ye, 2016. "Optimal Day-Ahead Scheduling of a Smart Distribution Grid Considering Reactive Power Capability of Distributed Generation," Energies, MDPI, vol. 9(5), pages 1-17, April.
    10. Wei, F. & Wu, Q.H. & Jing, Z.X. & Chen, J.J. & Zhou, X.X., 2016. "Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach," Energy, Elsevier, vol. 111(C), pages 933-946.
    11. Liu, Bo-Tau & Chien, Kuo-Hsiang & Wang, Chi-Chuan, 2004. "Effect of working fluids on organic Rankine cycle for waste heat recovery," Energy, Elsevier, vol. 29(8), pages 1207-1217.
    12. Zheng, J.H. & Chen, J.J. & Wu, Q.H. & Jing, Z.X., 2015. "Multi-objective optimization and decision making for power dispatch of a large-scale integrated energy system with distributed DHCs embedded," Applied Energy, Elsevier, vol. 154(C), pages 369-379.
    13. Lozano, M.A. & Carvalho, M. & Serra, L.M., 2009. "Operational strategy and marginal costs in simple trigeneration systems," Energy, Elsevier, vol. 34(11), pages 2001-2008.
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    Cited by:

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    3. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "Combined heating and cooling networks with part-load efficiency curves: Optimization based on energy hub concept," Applied Energy, Elsevier, vol. 307(C).

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