Multi-Objective Optimization Framework for Electricity and Natural Gas Energy Hubs Under Hydrogen Storage System and Demand Response Program

  • Majid Majidi
  • Sayyad NojavanEmail author
  • Kazem Zare


Energy hub is a new concept in the field of energy systems. Using multiple energy carriers as their inputs, these systems are capable of supplying various kinds of energy demands which seems to be interesting for system operators in the future. Different renewable and non-renewable generation units can be incorporated in gas and electricity energy hub systems to provide sufficient energy for supplying different types of loads. Primary fuel consumed by the units inside hub system is usually natural gas which is procured from gas network. In addition to distributed generation units in the hub system, upper network is also available to provide a reliable power to the electrical load. As expressed above, different energy carriers are involved in the hub energy systems. So, utilization of energy storage system seems to be vital. One of the energy storage systems that can be integrated in the future hub energy systems is hydrogen energy storage system (HSS). In this chapter, performance of hub energy system has been investigated from economic and environmental viewpoints in the presence of hydrogen energy storage system and demand response program (DRP). Four case studies have been evaluated in a sample hub energy system and the results are analyzed for comparison.


Multi-objective model Hydrogen storage system Demand response program 


  1. 1.
    Majidi M, Nojavan S, Zare K (2017) A cost-emission framework for hub energy system under demand response program. Energy 134:157CrossRefGoogle Scholar
  2. 2.
    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
  3. 3.
    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. CrossRefGoogle Scholar
  4. 4.
    Kamyab F, Bahrami S (2016) Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets. Energy 106:343–355. CrossRefGoogle Scholar
  5. 5.
    AlRafea K, Fowler M, Elkamel A, Hajimiragha A (2016) Integration of renewable energy sources into combined cycle power plants through electrolysis generated hydrogen in a new designed energy hub. Int J Hydrog Energy 41(38):16718–16728. CrossRefGoogle Scholar
  6. 6.
    Sheikhi A, Bahrami S, Ranjbar AM (2015) An autonomous demand response program for electricity and natural gas networks in smart energy hubs. Energy 89:490–499. CrossRefGoogle Scholar
  7. 7.
    Mukherjee U, Walker S, Maroufmashat A, Fowler M, Elkamel A (2017) Development of a pricing mechanism for valuing ancillary, transportation and environmental services offered by a power to gas energy system. Energy 128:447–462. CrossRefGoogle Scholar
  8. 8.
    Sheikhi A, Ranjbar AM, Oraee H (2012) Financial analysis and optimal size and operation for a multicarrier energy system. Energ Buildings 48:71–78. CrossRefGoogle Scholar
  9. 9.
    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. Energ Buildings 90:65–75. CrossRefGoogle Scholar
  10. 10.
    Peng DD, Fowler M, Elkamel A, Almansoori A, Walker SB (2016) Enabling utility-scale electrical energy storage by a power-to-gas energy hub and underground storage of hydrogen and natural gas. J Nat Gas Sci Eng 35:1180–1199. CrossRefGoogle Scholar
  11. 11.
    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. Energ Buildings 103:375–383. CrossRefGoogle Scholar
  12. 12.
    Koeppel G, Andersson G (2009) Reliability modeling of multi-carrier energy systems. Energy 34(3):235–244. CrossRefGoogle Scholar
  13. 13.
    Rastegar M, Fotuhi-Firuzabad M (2015) Load management in a residential energy hub with renewable distributed energy resources. Energ Buildings 107:234–242. CrossRefGoogle Scholar
  14. 14.
    Rastegar M, Fotuhi-Firuzabad M, Lehtonen M (2015) Home load management in a residential energy hub. Electr Power Syst Res 119:322–328. CrossRefGoogle Scholar
  15. 15.
    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. CrossRefGoogle Scholar
  16. 16.
    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. CrossRefGoogle Scholar
  17. 17.
    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. CrossRefGoogle Scholar
  18. 18.
    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. CrossRefGoogle Scholar
  19. 19.
    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. CrossRefGoogle Scholar
  20. 20.
    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. CrossRefGoogle Scholar
  21. 21.
    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. CrossRefGoogle Scholar
  22. 22.
    Orehounig K, Evins R, Dorer V (2015) Integration of decentralized energy systems in neighbourhoods using the energy hub approach. Appl Energy 154:277–289. CrossRefGoogle Scholar
  23. 23.
    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. CrossRefGoogle Scholar
  24. 24.
    Beigvand SD, Abdi H, La Scala M (2017) A general model for energy hub economic dispatch. Appl Energy 190:1090–1111. CrossRefGoogle Scholar
  25. 25.
    Mancarella P (2014) MES (multi-energy systems): An overview of concepts and evaluation models. Energy 65:1–17. CrossRefGoogle Scholar
  26. 26.
    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. CrossRefGoogle Scholar
  27. 27.
    Nojavan S, Zare K, Mohammadi-Ivatloo B (2017) Selling price determination by electricity retailer in the smart grid under demand side management in the presence of the electrolyser and fuel cell as hydrogen storage system. Int J Hydrog Energy 42(5):3294–3308CrossRefGoogle Scholar
  28. 28.
    Nojavan S, Zare K, Mohammadi-Ivatloo B (2017) Application of fuel cell and electrolyzer as hydrogen energy storage system in energy management of electricity energy retailer in the presence of the renewable energy sources and plug-in electric vehicles. Energy Convers Manag 136:404–417CrossRefGoogle 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 139:89CrossRefGoogle Scholar
  30. 30.
    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
  31. 31.
    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
  32. 32.
    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
  33. 33.
    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
  34. 34.
    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
  35. 35.
    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
  36. 36.
    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
  37. 37.
    The GAMS software website (2017). [Online].

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Electrical and Computer EngineeringUniversity of TabrizTabrizIran

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