Demand Response Participation in Renewable Energy Hubs

  • Mohammad Mohammadi
  • Younes Noorollahi
  • Behnam Mohammadi-Ivatloo
Chapter

Abstract

In traditional energy systems, supply side management was the main solution for responding to demand changes. However, the use of reserve capacity and large scale thermal systems to meet the power deficit in critical hours is not a logical solution. Another solution is to optimize consumption and adapt the pattern of consumption with existing resources, which is the basis of demand side management (DSM) and in particular demand response (DR) programs. DR includes approaches from DSM that are used to change customer consumption pattern due to price changes in the market or incentive payments. In this chapter research related to DSM programs in residential, commercial, agriculture, and industrial energy hubs is reviewed and discussed. Also a comprehensive operational optimization model for energy hub management in the presence of DR programs and renewable energy sources is proposed. In the proposed model, the DR program is formulated for a smart energy hub, which includes combined heat and power (CHP), boiler, wind turbine, electrical storage and the electricity and gas networks as energy resources. Simulation results show that in addition to load shifting, the customers in the smart energy hub can participate in DR program by switching between different energy carriers (e.g., from the electricity to the natural gas) during the peak hours.

Keywords

Energy hub Multi-energy systems Integrated management Sustainable energy system 

References

  1. 1.
    Mohammadi M, Noorollahi Y, Mohammadi-ivatloo B, Yousefi H, Jalilinasrabady S (2017) Optimal scheduling of energy hubs in the presence of uncertainty – a review. J Energy Manag Technol 1(1):1–17.  https://doi.org/10.22109/jemt.2017.49432 Google Scholar
  2. 2.
    Noorollahi Y, Itoi R, Yousefi H, Mohammadi M, Farhadi A (2017) Modeling for diversifying electricity supply by maximizing renewable energy use in Ebino City southern Japan. Sustain Cities Soc 34:371–384CrossRefGoogle Scholar
  3. 3.
    Boshell F, Veloza O (2008) Review of developed demand side management programs including different concepts and their results. In: Transmission and distribution conference and exposition: Latin America, 2008 IEEE/PES. IEEE, pp 1–7Google Scholar
  4. 4.
    Kazemi M, Mohammadi-Ivatloo B, Ehsan M (2014) Risk-based bidding of large electric utilities using information gap decision theory considering demand response. Electr Power Syst Res 114:86–92CrossRefGoogle Scholar
  5. 5.
    Nojavan S, Zare K, Mohammadi-Ivatloo B (2017) Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program. Appl Energy 187:449–464CrossRefGoogle Scholar
  6. 6.
    Rabiee A, Soroudi A, Mohammadi-ivatloo B, Parniani M (2014) Corrective voltage control scheme considering demand response and stochastic wind power. IEEE Trans Power Syst 29(6):2965–2973.  https://doi.org/10.1109/tpwrs.2014.2316018 CrossRefGoogle Scholar
  7. 7.
    Vahid-Pakdel MJ, Nojavan S, Mohammadi-ivatloo B, Zare K (2017) Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response. Energy Convers Manag 145:117–128CrossRefGoogle Scholar
  8. 8.
    U.S. Energy Information Administration (2015) http://www.eia.gov/forecasts/aeo/er/executive_summary. Accessed 02 Feb 2016
  9. 9.
    Beaudin M, Zareipour H (2015) Home energy management systems: a review of modelling and complexity. Renew Sust Energ Rev 45:318–335CrossRefGoogle Scholar
  10. 10.
    Rastegar M, Fotuhi-Firuzabad M, Lehtonen M (2015) Home load management in a residential energy hub. Electr Power Syst Res 119:322–328CrossRefGoogle Scholar
  11. 11.
    Jabari F, Nojavan S, Mohammadi-Ivatloo B, Sharifian MB (2016) Optimal short-term scheduling of a novel tri-generation system in the presence of demand response programs and battery storage system. Energy Convers Manag 122:95–108CrossRefGoogle Scholar
  12. 12.
    Rastegar M, Fotuhi-Firuzabad M (2015) Load management in a residential energy hub with renewable distributed energy resources. Energy Build 107:234–242CrossRefGoogle Scholar
  13. 13.
    Brahman F, Honarmand M, Jadid S (2015) Optimal electrical and thermal energy management of a residential energy hub, integrating demand response and energy storage system. Energy Build 90:65–75CrossRefGoogle Scholar
  14. 14.
    Bozchalui MC, Hashmi SA, Hassen H, Cañizares CA, Bhattacharya K (2012) Optimal operation of residential energy hubs in smart grids. IEEE Trans Smart Grid 3(4):1755–1766CrossRefGoogle Scholar
  15. 15.
    Mohammadi M, Noorollahi Y, Mohammadi-ivatloo B, Yousefi H (2017) Energy hub: from a model to a concept – a review. Renew Sustain Energy Rev 80:1512–1527CrossRefGoogle Scholar
  16. 16.
    United Nations Environment Programme (2016) http://www.unep.org/sbci/AboutSBCI/Background.asp. Accessed 02 Apr 2016
  17. 17.
    Steinfeld J, Bruce A, Watt M (2011) Peak load characteristics of Sydney office buildings and policy recommendations for peak load reduction. Energy Build 43(9):2179–2187CrossRefGoogle Scholar
  18. 18.
    Bozchalui MC, Sharma R (2012) Optimal operation of commercial building microgrids using multi-objective optimization to achieve emissions and efficiency targets. In: Power and energy society general meeting, 2012 IEEE. IEEE, pp 1–8Google Scholar
  19. 19.
    U.S. Energy Information Administration (2014) http://www.eia.gov/forecasts/ieo/. Accessed 02 Jan 2016
  20. 20.
    Finn P, Fitzpatrick C (2014) Demand side management of industrial electricity consumption: promoting the use of renewable energy through real-time pricing. Appl Energy 113:11–21CrossRefGoogle Scholar
  21. 21.
    Alipour M, Zare K, Mohammadi-Ivatloo B (2014) Short-term scheduling of combined heat and power generation units in the presence of demand response programs. Energy 71:289–301CrossRefGoogle Scholar
  22. 22.
    Alipour M, Mohammadi-Ivatloo B, Zare K (2014) Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs. Appl Energy 136:393–404CrossRefGoogle Scholar
  23. 23.
    Alipour M, Zare K, Mohammadi-Ivatloo B (2016) Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets. Renew Sust Energ Rev 60:421–432CrossRefGoogle Scholar
  24. 24.
    Alipour M, Mohammadi-Ivatloo B, Zare K (2015) Stochastic scheduling of renewable and CHP-based microgrids. IEEE Trans Ind Inf 11(5):1049–1058CrossRefGoogle Scholar
  25. 25.
    Ding YM, Hong SH, Li XH (2014) A demand response energy management scheme for industrial facilities in smart grid. IEEE Trans Ind Inf 10(4):2257–2269CrossRefGoogle Scholar
  26. 26.
    Xu FY, Lai LL (2015) Novel active time-based demand response for industrial consumers in smart grid. IEEE Trans Ind Inf 11(6):1564–1573CrossRefGoogle Scholar
  27. 27.
    Ball VE, Färe R, Grosskopf S, Margaritis D (2015) The role of energy productivity in US agriculture. Energy Econ 49:460–471CrossRefGoogle Scholar
  28. 28.
    Abbasi AZ, Islam N, Shaikh ZA (2014) A review of wireless sensors and networks’ applications in agriculture. Comput Stand Interfaces 36(2):263–270CrossRefGoogle Scholar
  29. 29.
    Gelogo YE, Park J, Kim H-K (2015) A study on U-agriculture for smart grid systems deployment. Adv Sci Tech Lett 97:64--70 http://dx.doi.org/10.14257/astl.205.97.11
  30. 30.
    Odara S, Khan Z (2015) Ustun TS integration of precision agriculture and smartgrid technologies for sustainable development. In: Technological innovation in ICT for agriculture and rural development (TIAR), 2015 IEEE. IEEE, pp 84–89Google Scholar
  31. 31.
    Kaviani AK, Riahy G, Kouhsari SM (2009) Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages. Renew Energy 34(11):2380–2390CrossRefGoogle Scholar
  32. 32.
    Haghifam MR, Manbachi M (2011) Reliability and availability modelling of combined heat and power (CHP) systems. Int J Electr Power Energy Syst 33(3):385–393.  https://doi.org/10.1016/j.ijepes.2010.08.035 CrossRefGoogle Scholar
  33. 33.
    Parisio A, Del Vecchio C, Vaccaro A (2012) A robust optimization approach to energy hub management. Int J Electr Power Energy Syst 42(1):98–104CrossRefGoogle Scholar
  34. 34.
    Dietrich K, Latorre JM, Olmos L, Ramos A (2012) Demand response in an isolated system with high wind integration. IEEE Trans Power Syst 27(1):20–29CrossRefGoogle Scholar
  35. 35.
    Gen B (2005) Reliability and cost/worth evaluation of generating systems utilizing wind and solar energy (Ph.D. Thesis). Department of Electrical Engineering, University of Saskatchewan, SaskatoonGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mohammad Mohammadi
    • 1
  • Younes Noorollahi
    • 1
  • Behnam Mohammadi-Ivatloo
    • 2
  1. 1.Department of Renewable Energy and Environment, Faculty of New Sciences and TechnologiesUniversity of TehranTehranIran
  2. 2.Department of Electrical and Computer EngineeringUniversity of TabrizTabrizIran

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