Wuhan University Journal of Natural Sciences

, Volume 23, Issue 1, pp 31–42 | Cite as

Integrated heat and power dispatch model for wind-CHP system with solid heat storage device based on robust stochastic theory

  • Huanhuan Li
  • Zhongfu Tan
  • Hongtao Chen
  • Hongwu Guo
Complex Science Management


This paper built a combined heat and power (CHP) dispatch model for wind-CHP system with solid heat storage device (SHS) aiming at minimizing system coal consumption, and set system demand-supply balance and units’ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.


wind power abandoned wind solid electric heat storage device combined heat and power (CHP) heat storage robust stochastic optimization theory 

CLC number

TM 614 


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  1. [1]
    He G, Zhang H L, Xu Y, et al. China’s clean power transition: Current status and future prospect[J]. Resources Conservation and Recycling, 2017, 121: 3–10.CrossRefGoogle Scholar
  2. [2]
    Ju L W, Li H H, Zhao J W, et al. Multi-objective stochastic scheduling optimization model for connecting a virtual power plant to wind-photovoltaic-electric vehicles considering uncertainties and demand response[J]. Energy Conversion and Management, 2016, 128: 160–177.CrossRefGoogle Scholar
  3. [3]
    Ju L W, Tan Z F, Yuan J Y, et al. A bi-level stochastic dispatch optimization model for a virtual power plant connected to a wind-photovoltaic-energy storage system considering the uncertainty and demand response[J]. Applies Energy, 2016, 171(6): 184–199.CrossRefGoogle Scholar
  4. [4]
    Lam L T, Branstetter L, Azevedo I M L. China’s wind industry: Leading in deployment, lagging in innovation[J]. Energy Policy, 2017, 106: 588–599.CrossRefGoogle Scholar
  5. [5]
    Du J C, Chi Y N, Zhao L, et al. Study on grid capability to accommodate wind energy based on power balance[J]. Energy Education Science and Technology Part A—Energy Science and Research, 2011, 28(1): 117–124.Google Scholar
  6. [6]
    Ye J, Yuan R X. Integrated natural gas, heat, and power dispatch considering wind power and power-to-gas[J]. Sustainability, 2017, 9(4): 602.CrossRefGoogle Scholar
  7. [7]
    Tan Z F, Ju L W, Li H H, et al. A two-stage scheduling optimization model and solution algorithm for wind power and energy storage system considering uncertainty and demand response[J]. International Journal of Electrical Power and Energy Systems, 2014, 63: 1057–1069.CrossRefGoogle Scholar
  8. [8]
    Ju L W, Tan Z F, Yuan J Y, et al. A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind-photovoltaic-energy storage system considering the uncertainty and demand response[J]. Applied Energy, 2016, 171: 184–199.CrossRefGoogle Scholar
  9. [9]
    Tan Z F, Ju L W, Reed B, et al. The optimization model for multi-type customers assisting wind power consumptive considering uncertainty and demand response based on robust stochastic theory[J]. Energy Conversion and Management, 2015, 105: 1070–1081.CrossRefGoogle Scholar
  10. [10]
    Yan H G, Chen S S, Li S H, et al. Research on the current situation and development trend of demand response[J]. Distribution & Utilization, 2017, 34(03): 2–8.Google Scholar
  11. [11]
    Zhang N, Lu X, McElroy M B. Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage[J]. Applied Energy, 2016, 184(12): 987–994.CrossRefGoogle Scholar
  12. [12]
    Lü Q, Jiang G H, Chen T Y, et al. Wind power accommodation by combined heat and power plant with electric boiler and its national economic evaluation[J]. Autom Electr Power Syst, 2014, 38 (1): 6–12(Ch).Google Scholar
  13. [13]
    Meibom P, Kiviluoma J, Barth R, et al. Value of electric heat boilers and heat pumps for wind power integration[J]. Wind Energy, 2007, 10(4): 321–337.CrossRefGoogle Scholar
  14. [14]
    Papaefthymiou G, Hasche B, Nabe C. Potential of heat pumps for demand side management and wind power integration in the German electricity market[J]. IEEE Trans Sustain Energy, 2012, 3(4): 636–642.CrossRefGoogle Scholar
  15. [15]
    Mehdi M, Ali R S, Taher N. Multi-objective energy management of CHP(combined heat and power)-based micro-grid[J]. Energy, 2013, 51: 123–136.CrossRefGoogle Scholar
  16. [16]
    Lü Q, Chen T Y, Wang H X, et al. Analysis on peak-load regulation ability of cogeneration unit with heat accumulator[J]. Autom Electr Power Syst, 2014, 38(11): 34–41(Ch).Google Scholar
  17. [17]
    Lü Q, Li L, Zhu Q S, et al. Comparison of coal saving effect and national economic indices of three feasible curtailed wind power accommodating strategies[J]. Autom Electr Power Syst, 2015, 39(7): 75–83(Ch).Google Scholar
  18. [18]
    Lü Q, Chen T Y, Wang H X, et al. Combined heat and power dispatch model for power system with heat accumulator[J]. Electric Power Automation Equipment, 2014, 34 (5): 79–85(Ch).Google Scholar
  19. [19]
    Jin H Y, Sun H B, Guo Q L, et al. Multi-day self-dispatch method for combined system of CSP plants and wind power with large-scale thermal energy storage contained[J]. Autom Electr Power Syst, 2016, 40(11): 17–23(Ch).Google Scholar
  20. [20]
    Chen X. Increasing the flexibility of combined heat and power for wind power integration in China: Modeling and implications[J]. IEEE Trans Power Syst, 2015, 30(4): 1848–1857.CrossRefGoogle Scholar
  21. [21]
    Deepesh S, Soni S L, Dilip S. Micro-trigeneration for energy sustainability: Technologies, tools and trends[J]. Applied Thermal Engineering, 2014, 71(2): 790–796.CrossRefGoogle Scholar
  22. [22]
    Yuan R X, Ye J, Lei J Z, et al. Integrated combined heat and power system dispatch considering electrical and thermal energy storage[J]. Energies, 2016, 9(6): 474.CrossRefGoogle Scholar
  23. [23]
    Li G Q, Zhang R F, Jiang T, et al. Optimal dispatch strategy for integrated energy systems with CCHP and wind power[J]. Applied Energy, 2017, 192(4): 408–419.CrossRefGoogle Scholar
  24. [24]
    Wu C Y, Jiang P, Sun Y, et al. Economic dispatch with CHP and wind power using probabilistic sequence theory and hybrid heuristic algorithm[J]. Journal of Renewable and Sustainable Energy, 2017, 9(1): 013303.CrossRefGoogle Scholar
  25. [25]
    Guo Y H, Hu B, Wan L Y, et al. Optimal economic short-term dispatch of CHP microgrid incorporating heat pump[J]. Autom Electr Power Syst, 2015, 39(14): 16-22 (Ch).Google Scholar
  26. [26]
    Bai S X, Zhao G B, Dong F. Solid electric heat-storage equipment and its economic analysis[J]. Electric Power, 2002, (6): 83–84(Ch).Google Scholar
  27. [27]
    Ge Y F, Li X F, Ge Y Y, et al. Technical plan for electric heat storage and heating by wind energy curtailment based on joint dispatching of heat and electricity[J]. Smart Grid, 2015, (10): 901–905.Google Scholar
  28. [28]
    Nanaeda K, Mueller F, Brouwer J. Dynamic modeling and evaluation of solid oxide fuel cell-combined heat and power system operating strategies[J]. Journal of Power Sources, 2010, 195(10): 3176–3185.CrossRefGoogle Scholar
  29. [29]
    Xu F, Yao J, Gen J, et al. Modeling and analysis of unit I/O characteristics based on mixed-integer programming[J]. Autom Electr Power Syst, 2010, 34: 45–50(Ch).Google Scholar
  30. [30]
    Hu K, Chen L, Chen Q, et al. Phase-change heat storage installation in combined heat and power plants for integration of renewable energy sources into power system[J]. Energy, 2017, 124: 640–651.CrossRefGoogle Scholar

Copyright information

© Wuhan University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Huanhuan Li
    • 1
  • Zhongfu Tan
    • 1
    • 2
  • Hongtao Chen
    • 3
  • Hongwu Guo
    • 1
  1. 1.School of Economics and ManagementNorth China Electric Power UniversityBeijingChina
  2. 2.School of Economics and ManagementYan’an UniversityShaanxiChina
  3. 3.East China Electric Power Test and Research InstituteShanghaiChina

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