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Air Conditioning and Heating as Demand Response in Modern Power Systems

  • Yi DingEmail author
  • Yonghua Song
  • Hongxun Hui
  • Changzheng Shao
Chapter

Abstract

The utilization of renewable energy sources (RES) is burgeoning to deal with the rapidly increasing energy consumption and environment deterioration. The fluctuation brought by the growing share of RES will continuously increase, while the conventional operating reserve providers may not be able to satisfy the requirements of the system with burgeoning RES in the future. The development of information and communication technologies (ICT) and electricity market has made the remote control of flexible loads much easier. Thus it is possible for small end-customers to provide operating reserve to support the operation of the power systems. As one of the most popular and easily controlled flexible loads, air conditioners and heating equipment account for a large share in power consumption due to the mass application across the world. Facing the huge potential of air conditioning and heating loads, this book proposes the quantitative evaluation method of the regulation service, the capacity evaluation method of aggregated thermostatically controlled loads under dynamic price signals, the sequential-dispatch of operating reserve considering lead-lag rebound effect, and the frequency regulation control method, respectively. Moreover, the integration of flexible heating demand intro the integrated energy system and a three-level framework for utilizing the demand response to improve the operation of the integarated energy system are also proposed. The economical evaluation of the flexible resources for providng the operational flexibility in the power system is also analysed.

References

  1. 1.
    A. Ketsetzi, M.M. Capraro, Renewable Energy Sources. A Companion to Interdisciplinary STEM Project-Based Learning (2016), pp. 145–153CrossRefGoogle Scholar
  2. 2.
    H. Nosair, F. Bouffard, Reconstructing operating reserve: flexibility for sustainable power systems. IEEE Trans. Sustain. Energy 6(4), 1624–1637 (2015)CrossRefGoogle Scholar
  3. 3.
    Ž.B. Rejc, M. Čepin, Estimating the additional operating reserve in power systems with installed renewable energy sources. Int. J. Electr. Power Energy Syst. 30(62), 654–664 (2014)CrossRefGoogle Scholar
  4. 4.
    J. Wang, X. Wang, Y. Wu, Operating reserve model in the power market. IEEE Trans. Power Syst. 20(1), 223–229 (2005)CrossRefGoogle Scholar
  5. 5.
    K. Heussen, S. Koch, A. Ulbig, G. Andersson, Unified system-level modeling of intermittent renewable energy sources and energy storage for power system operation. IEEE Syst. J. 6(1), 140–151 (2012)CrossRefGoogle Scholar
  6. 6.
    I. Krad, E. Ibanez, W. Gao, A comprehensive comparison of current operating reserve methodologies, in 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D) (IEEE, 2016)Google Scholar
  7. 7.
    P. Siano, D. Sarno, Assessing the benefits of residential demand response in a real time distribution energy market. Appl. Energy 1(161), 533–551 (2016)CrossRefGoogle Scholar
  8. 8.
    C.L. Su, D. Kirschen, Quantifying the effect of demand response on electricity markets. IEEE Trans. Power Syst. 24(3), 1199–1207 (2009)CrossRefGoogle Scholar
  9. 9.
    P. Palensky, D. Dietrich, Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans. Ind. Inform. 7(3), 381–388 (2011)CrossRefGoogle Scholar
  10. 10.
    Y. Ding, P Nyeng, J. Østergaard, M.D. Trong, S. Pineda, K. Kok, G.B. Huitema, O.S. Grande, Ecogrid EU-a large scale smart grids demonstration of real time market-based integration of numerous small DER and DR, in 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), vol. 14 (2012), pp. 1–7Google Scholar
  11. 11.
    J.M. Lujano-Rojas, C. Monteiro, R. Dufo-Lopez, J.L. Bernal-Agustín, Optimum residential load management strategy for real time pricing (RTP) demand response programs. Energy Policy 30(45), 671–679 (2012)CrossRefGoogle Scholar
  12. 12.
    Energy Institute at Hass, Air conditioning and global energy demand (2015). https://energyathaas.wordpress.com/2015/04/27/air-conditioning-and-global-energy-demand/
  13. 13.
    Science Daily, Air conditioning consumes one third of peak electric consumption in the summer (2012). https://www.sciencedaily.com/releases/2012/10/121022080408.htm
  14. 14.
    P. Nyeng, J. Ostergaard, Information and communications systems for control-by-price of distributed energy resources and flexible demand. IEEE Trans. Smart Grid 2(2), 334–341 (2011)CrossRefGoogle Scholar
  15. 15.
    G. Bianchini, M. Casini, A. Vicino, D. Zarrilli, Demand-response in building heating systems: a model predictive control approach. Appl. Energy 15(168), 159–170 (2016)CrossRefGoogle Scholar
  16. 16.
    N. Lu, An evaluation of the HVAC load potential for providing load balancing service. IEEE Trans. Smart Grid 3(3), 1263–1270 (2012)CrossRefGoogle Scholar
  17. 17.
    K. Bhattacharyya, M.L. Crow, A fuzzy logic based approach to direct load control. IEEE Trans. Power Syst. 11(2), 708–714 (1996)CrossRefGoogle Scholar
  18. 18.
    H.T. Yang, K.Y. Huang, Direct load control using fuzzy dynamic programming. IEE Proc. Gener. Transm. Distrib. 146(3), 294–300 (1999)CrossRefGoogle Scholar
  19. 19.
    H. Salehfar, P.J. Noll, B.J. LaMeres, M.H. Nehrir, V. Gerez, Fuzzy logic-based direct load control of residential electric water heaters and air conditioners recognizing customer preferences in a deregulated environment, in Power Engineering Society Summer Meeting, IEEE 1999, vol. 2 (1999), pp. 1055–1060Google Scholar
  20. 20.
    W.C. Chu, B.K. Chen, C.K. Fu, Scheduling of direct load control to minimize load reduction for a utility suffering from generation shortage. IEEE Trans. Power Syst. 8(4), 1525–1530 (1993)CrossRefGoogle Scholar
  21. 21.
    J.C. Laurent, G. Desaulniers, R.P. Malhamé, F. Soumis, A column generation method for optimal load management via control of electric water heaters. IEEE Trans. Power Syst. 10(3), 1389–1400 (1995)CrossRefGoogle Scholar
  22. 22.
    D.P. Chassin, D. Rondeau, Aggregate modeling of fast-acting demand response and control under real-time pricing. Appl. Energy 1(181), 288–298 (2016)CrossRefGoogle Scholar
  23. 23.
    W. Wang, S. Katipamula, H. Ngo, R. Underhill, D. Taasevigen, R. Lutes, Field evaluation of advanced controls for the retrofit of packaged air conditioners and heat pumps. Appl. Energy 15(154), 344–351 (2015)CrossRefGoogle Scholar
  24. 24.
    N. Alibabaei, A.S. Fung, K. Raahemifar, A. Moghimi, Effects of intelligent strategy planning models on residential HVAC system energy demand and cost during the heating and cooling seasons. Appl. Energy 185, 29–43 (2016)CrossRefGoogle Scholar
  25. 25.
    ConEdison, Control your cool with smart ACs (2016). http://www.coned.com
  26. 26.
    L. Sugden, Smart Grids create new opportunities for heat pumps. REHVA J., 20–22 (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yi Ding
    • 1
    Email author
  • Yonghua Song
    • 1
    • 2
  • Hongxun Hui
    • 1
  • Changzheng Shao
    • 1
  1. 1.Zhejiang UniversityHangzhouChina
  2. 2.University of MacauMacauChina

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