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Supply Side Management in Renewable Energy Hubs

  • Sayyad Nojavan
  • Majid Majidi
  • Afshin Najafi-Ghalelou
  • Kazem Zare
Chapter

Abstract

Crises over energy resources has challenged system operators to look for new energy resources with higher efficiency and less pollutants. One of the new technologies that has been focused much more recently is hub energy system. These systems usually include local renewable and non-renewable energy resources to supply energy demands with different types. In detail, these systems benefit from combined heat and power systems that guarantee efficient utilization of heat and electricity. Furthermore, renewable energy resources can be integrated with other resources to help hub system generate clean energy but with considering severe uncertainty of renewable generation, supply side management becomes important. One of the available options for supply side management is energy storage system. In this chapter, compressed air energy storage system (CAES) has been employed to handle fluctuating generation of local renewable units in the hub energy system. Also, electrical load has been capable of participating in demand response programs (DRP) to gain economic and environmental benefits. A sample renewable-based hub energy system has been evaluated in this chapter and the results obtained from related simulations are presented for comparison.

Keywords

Compressed air energy storage system Energy hub Demand response programs 

References

  1. 1.
    Tazvinga H, Zhu B, Xia X (2015) Optimal power flow management for distributed energy resources with batteries. Energy Convers Manag 102:104–110.  https://doi.org/10.1016/j.enconman.2015.01.015 CrossRefGoogle Scholar
  2. 2.
    Majidi M, Nojavan S, Esfetanaj NN, Najafi-Ghalelou A, Zare K (2017) A multi-objective model for optimal operation of a battery/PV/fuel cell/grid hybrid energy system using weighted sum technique and fuzzy satisfying approach considering responsible load management. Sol Energy 144:79–89CrossRefGoogle Scholar
  3. 3.
    Karami H, Sanjari MJ, Gooi HB, Gharehpetian GB, Guerrero JM (2017) Stochastic analysis of residential micro combined heat and power system. Energy Convers Manag 138:190–198.  https://doi.org/10.1016/j.enconman.2017.01.073 CrossRefGoogle Scholar
  4. 4.
    Li C, Gillum C, Toupin K, Park YH, Donaldson B (2016) Environmental performance assessment of utility boiler energy conversion systems. Energy Convers Manag 120:135–143.  https://doi.org/10.1016/j.enconman.2016.04.099 CrossRefGoogle Scholar
  5. 5.
    Nojavan S, Majidi M, Zare K (2017) Performance improvement of a battery/PV/fuel cell/grid hybrid energy system considering load uncertainty modeling using IGDT. Energy Convers Manag 147:29–39CrossRefGoogle Scholar
  6. 6.
    Majidi M, Nojavan S, Zare K (2017) A cost-emission framework for hub energy system under demand response program. Energy 134:157–166CrossRefGoogle Scholar
  7. 7.
    Majidi M, Nojavan S, Zare K (2017) Optimal stochastic short-term thermal and electrical operation of fuel cell/photovoltaic/battery/grid hybrid energy system in the presence of demand response program. Energy Convers Manag 144:132–142CrossRefGoogle Scholar
  8. 8.
    Al-Sharafi A, Yilbas BS, Sahin AZ, Ayar T (2017) Performance assessment of hybrid power generation systems: Economic and environmental impacts. Energy Convers Manag 132:418–431.  https://doi.org/10.1016/j.enconman.2016.11.047 CrossRefGoogle Scholar
  9. 9.
    Derafshi Beigvand S, Abdi H, La Scala M (2016) Optimal operation of multicarrier energy systems using time varying acceleration coefficient gravitational search algorithm. Energy 114:253–265.  https://doi.org/10.1016/j.energy.2016.07.155 CrossRefGoogle Scholar
  10. 10.
    Parisio A, Del Vecchio C, Vaccaro A (2012) A robust optimization approach to energy hub management. Int J Electr Power Energy Syst 42(1):98–104.  https://doi.org/10.1016/j.ijepes.2012.03.015 CrossRefGoogle Scholar
  11. 11.
    Wasilewski J (2015) Integrated modeling of microgrid for steady-state analysis using modified concept of multi-carrier energy hub. Int J Electr Power Energy Syst 73:891–898.  https://doi.org/10.1016/j.ijepes.2015.06.022 CrossRefGoogle Scholar
  12. 12.
    Pazouki S, Haghifam M-R (2016) Optimal planning and scheduling of energy hub in presence of wind, storage and demand response under uncertainty. Int J Electr Power Energy Syst 80:219–239.  https://doi.org/10.1016/j.ijepes.2016.01.044 CrossRefGoogle Scholar
  13. 13.
    Orehounig K, Evins R, Dorer V, Carmeliet J (2014) Assessment of renewable energy integration for a village using the energy hub concept. Energy Procedia 57:940–949.  https://doi.org/10.1016/j.egypro.2014.10.076 CrossRefGoogle Scholar
  14. 14.
    Ma T, Wu J, Hao L (2017) Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub. Energy Convers Manag 133:292–306.  https://doi.org/10.1016/j.enconman.2016.12.011 CrossRefGoogle Scholar
  15. 15.
    Orehounig K, Evins R, Dorer V (2015) Integration of decentralized energy systems in neighbourhoods using the energy hub approach. Appl Energy 154:277–289.  https://doi.org/10.1016/j.apenergy.2015.04.114 CrossRefGoogle Scholar
  16. 16.
    Najafi A, Falaghi H, Contreras J, Ramezani M (2016) Medium-term energy hub management subject to electricity price and wind uncertainty. Appl Energy 168:418–433.  https://doi.org/10.1016/j.apenergy.2016.01.074 CrossRefGoogle Scholar
  17. 17.
    Beigvand SD, Abdi H, La Scala M (2017) A general model for energy hub economic dispatch. Appl Energy 190:1090–1111.  https://doi.org/10.1016/j.apenergy.2016.12.126 CrossRefGoogle Scholar
  18. 18.
    Koeppel G, Andersson G (2009) Reliability modeling of multi-carrier energy systems. Energy 34(3):235–244.  https://doi.org/10.1016/j.energy.2008.04.012 CrossRefGoogle Scholar
  19. 19.
    Shariatkhah M-H, Haghifam M-R, Parsa-Moghaddam M, Siano P (2015) Modeling the reliability of multi-carrier energy systems considering dynamic behavior of thermal loads. Energy Build 103:375–383.  https://doi.org/10.1016/j.enbuild.2015.06.001 CrossRefGoogle Scholar
  20. 20.
    Mancarella P (2014) MES (multi-energy systems): An overview of concepts and evaluation models. Energy 65:1–17.  https://doi.org/10.1016/j.energy.2013.10.041 CrossRefGoogle Scholar
  21. 21.
    Moghaddam IG, Saniei M, Mashhour E (2016) A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building. Energy 94:157–170.  https://doi.org/10.1016/j.energy.2015.10.137 CrossRefGoogle Scholar
  22. 22.
    Kamyab F, Bahrami S (2016) Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets. Energy 106:343–355.  https://doi.org/10.1016/j.energy.2016.03.074 CrossRefGoogle Scholar
  23. 23.
    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 90:65–75.  https://doi.org/10.1016/j.enbuild.2014.12.039 CrossRefGoogle Scholar
  24. 24.
    Rastegar M, Fotuhi-Firuzabad M (2015) Load management in a residential energy hub with renewable distributed energy resources. Energy Build 107:234–242.  https://doi.org/10.1016/j.enbuild.2015.07.028 CrossRefGoogle Scholar
  25. 25.
    Rastegar M, Fotuhi-Firuzabad M, Lehtonen M (2015) Home load management in a residential energy hub. Electr Power Syst Res 119:322–328.  https://doi.org/10.1016/j.epsr.2014.10.011 CrossRefGoogle Scholar
  26. 26.
    Shabanpour-Haghighi A, Seifi AR (2016) Effects of district heating networks on optimal energy flow of multi-carrier systems. Renew Sust Energ Rev 59:379–387.  https://doi.org/10.1016/j.rser.2015.12.349 CrossRefGoogle Scholar
  27. 27.
    Ghalelou AN, Fakhri AP, Nojavan S, Majidi M, Hatami H (2016) A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism. Energy Convers Manag 120:388–396.  https://doi.org/10.1016/j.enconman.2016.04.082 CrossRefGoogle Scholar
  28. 28.
    Shafiee S, Zareipour H, Knight AM, Amjady N, Mohammadi-Ivatloo B (2017) Risk-constrained bidding and offering strategy for a merchant compressed air energy storage plant. IEEE Trans Power Syst 32(2):946–957Google Scholar
  29. 29.
    Nojavan S, Majidi M, Esfetanaj NN (2017) An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management. Energy 139:89–97CrossRefGoogle Scholar
  30. 30.
    Nojavan S, Majidi M, Najafi-Ghalelou A, Ghahramani M, Zare K (2017) A cost-emission model for fuel cell/PV/battery hybrid energy system in the presence of demand response program: ε-constraint method and fuzzy satisfying approach. Energy Convers Manag 138: 383–392CrossRefGoogle Scholar
  31. 31.
    Nojavan S, Majidi M, Zare K (2017) Risk-based optimal performance of a PV/fuel cell/battery/grid hybrid energy system using information gap decision theory in the presence of demand response program. Int J Hydrog Energy 42(16):11857–11867CrossRefGoogle Scholar
  32. 32.
    Pazouki S, Haghifam M-R, Moser A (2014) Uncertainty modeling in optimal operation of energy hub in presence of wind, storage and demand response. Int J Electr Power Energy Syst 61:335–345CrossRefGoogle Scholar
  33. 33.
    Elsied M, Oukaour A, Gualous H, Hassan R (2015) Energy management and optimization in microgrid system based on green energy. Energy 84:139–151CrossRefGoogle Scholar
  34. 34.
    Elsied M, Oukaour A, Gualous H, Brutto OAL (2016) Optimal economic and environment operation of micro-grid power systems. Energy Convers Manag 122:182–194CrossRefGoogle Scholar
  35. 35.
    The GAMS Software Website (2017) [Online]. Available: http://www.gams.com/dd/docs/solvers/cplex.pdf

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Sayyad Nojavan
    • 1
  • Majid Majidi
    • 1
  • Afshin Najafi-Ghalelou
    • 1
  • Kazem Zare
    • 1
  1. 1.Faculty of Electrical and Computer EngineeringUniversity of TabrizTabrizIran

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