Skip to main content

2022 | OriginalPaper | Buchkapitel

7. Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems

verfasst von : Behzad Motallebi Azar, Amir Mirzapour-Kamanaj, Rasool Kazemzadeh, Behnam Mohammadi-Ivatloo, Kazem Zare

Erschienen in: Whole Energy Systems

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In the recent decade, due to the increasing dependency of communities on energy, the issues related to optimal operation and energy management have been increasingly considered by researchers and beneficiaries in this field. In this regard, the subject of energy can be regarded as the critical challenge of humankind in the present century, including economic, environmental, and security contexts. The proposed solution to address these challenges is to move toward smart energy systems and utilizing renewable energy resources and energy storage systems, which have been introduced and discussed in various aspects in recent years. The power-to-X (P2X) facilities are a new framework for energy conversion technologies to improve energy systems’ optimal operation. Interconnected hybrid energy systems (IHESs) along with P2X facilities containing power-to-heat (P2H), power-to-cool (P2C), and power-to-hydrogen (P2Hy) technologies can supply disparate demands of energy systems locally. Also, IHESs can trade energy with each other, in addition to meeting individual demands. This approach improves systems’ efficiency, flexibility, and performance and reduces greenhouse gas emissions. In this chapter, the optimal coalition operation of IHESs using renewable and nonrenewable energy resources to mitigate operation and emission costs has been investigated. For more comparison, two case studies are considered. In the first case study, the individual optimal operation of each hybrid energy system (HES) is taken into account. In the second one, the optimal coalition operation of IHESs is modeled. The mixed-integer linear programming (MILP) optimization problem is solved in GAMS software under the CPLEX solver. The obtained results indicate that the interconnected operation of the HESs improves system performance and reduces system operating costs.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Mohammadi, M., Noorollahi, Y., Mohammadi-Ivatloo, B., & Yousefi, H. (2017). Energy hub: From a model to a concept–a review. Renewable and Sustainable Energy Reviews, 80, 1512–1527.CrossRef Mohammadi, M., Noorollahi, Y., Mohammadi-Ivatloo, B., & Yousefi, H. (2017). Energy hub: From a model to a concept–a review. Renewable and Sustainable Energy Reviews, 80, 1512–1527.CrossRef
2.
Zurück zum Zitat Berjawi, A., Walker, S., Patsios, C., & Hosseini, S. (2021). An evaluation framework for future integrated energy systems: A whole energy systems approach. Renewable and Sustainable Energy Reviews, 145, 111163.CrossRef Berjawi, A., Walker, S., Patsios, C., & Hosseini, S. (2021). An evaluation framework for future integrated energy systems: A whole energy systems approach. Renewable and Sustainable Energy Reviews, 145, 111163.CrossRef
3.
Zurück zum Zitat Favre-Perrod, P. (2005). A vision of future energy networks. In 2005 IEEE power engineering society inaugural conference and exposition in Africa, IEEE, pp. 13–17. Favre-Perrod, P. (2005). A vision of future energy networks. In 2005 IEEE power engineering society inaugural conference and exposition in Africa, IEEE, pp. 13–17.
4.
Zurück zum Zitat Geidl, M., Koeppel, G., Favre-Perrod, P., Klockl, B., Andersson, G., & Frohlich, K. (2006). Energy hubs for the future. IEEE Power and Energy Magazine, 5(1), 24–30.CrossRef Geidl, M., Koeppel, G., Favre-Perrod, P., Klockl, B., Andersson, G., & Frohlich, K. (2006). Energy hubs for the future. IEEE Power and Energy Magazine, 5(1), 24–30.CrossRef
5.
Zurück zum Zitat Geidl, M. (2007). Integrated modeling and optimization of multi-carrier energy systems. ETH Zurich. Geidl, M. (2007). Integrated modeling and optimization of multi-carrier energy systems. ETH Zurich.
6.
Zurück zum Zitat Sheikhi, A., Rayati, M., Bahrami, S., Ranjbar, A. M., & Sattari, S. (2015). A cloud computing framework on demand side management game in smart energy hubs. International Journal of Electrical Power & Energy Systems, 64, 1007–1016.CrossRef Sheikhi, A., Rayati, M., Bahrami, S., Ranjbar, A. M., & Sattari, S. (2015). A cloud computing framework on demand side management game in smart energy hubs. International Journal of Electrical Power & Energy Systems, 64, 1007–1016.CrossRef
7.
Zurück zum Zitat Sheikhi, A., Mozafari, B., & Ranjbar, A. M. (2011). CHP optimized selection methodology for a multi-carrier energy system. In 2011 IEEE Trondheim PowerTech, IEEE, pp. 1–7. Sheikhi, A., Mozafari, B., & Ranjbar, A. M. (2011). CHP optimized selection methodology for a multi-carrier energy system. In 2011 IEEE Trondheim PowerTech, IEEE, pp. 1–7.
8.
Zurück zum Zitat Parisio, A., Del Vecchio, C., & Vaccaro, A. (2012). A robust optimization approach to energy hub management. International Journal of Electrical Power & Energy Systems, 42(1), 98–104.CrossRef Parisio, A., Del Vecchio, C., & Vaccaro, A. (2012). A robust optimization approach to energy hub management. International Journal of Electrical Power & Energy Systems, 42(1), 98–104.CrossRef
9.
Zurück zum Zitat Moeini-Aghtaie, M., Dehghanian, P., Fotuhi-Firuzabad, M., & Abbaspour, A. (2013). Multi-agent genetic algorithm: an online probabilistic view on economic dispatch of energy hubs constrained by wind availability. IEEE Transactions on Sustainable Energy, 5(2), 699–708.CrossRef Moeini-Aghtaie, M., Dehghanian, P., Fotuhi-Firuzabad, M., & Abbaspour, A. (2013). Multi-agent genetic algorithm: an online probabilistic view on economic dispatch of energy hubs constrained by wind availability. IEEE Transactions on Sustainable Energy, 5(2), 699–708.CrossRef
10.
Zurück zum Zitat Schulze, M., & Del Granado, P. C. (2009). Multi-period optimization of cogeneration systems: Considering biomass energy for district heating. In 2nd Power systems modeling conference (vol. 126). Schulze, M., & Del Granado, P. C. (2009). Multi-period optimization of cogeneration systems: Considering biomass energy for district heating. In 2nd Power systems modeling conference (vol. 126).
11.
Zurück zum Zitat Maroufmashat, A., et al. (2015). Modeling and optimization of a network of energy hubs to improve economic and emission considerations. Energy, 93, 2546–2558.CrossRef Maroufmashat, A., et al. (2015). Modeling and optimization of a network of energy hubs to improve economic and emission considerations. Energy, 93, 2546–2558.CrossRef
12.
Zurück zum Zitat Tian, M.-W., et al. (2019). Risk-based stochastic scheduling of energy hub system in the presence of heating network and thermal energy management. Applied Thermal Engineering, 159, 113825.CrossRef Tian, M.-W., et al. (2019). Risk-based stochastic scheduling of energy hub system in the presence of heating network and thermal energy management. Applied Thermal Engineering, 159, 113825.CrossRef
13.
Zurück zum Zitat Liu, T., Zhang, D., Dai, H., & Wu, T. (2019). Intelligent modeling and optimization for smart energy hub. IEEE Transactions on Industrial Electronics, 66(12), 9898–9908.CrossRef Liu, T., Zhang, D., Dai, H., & Wu, T. (2019). Intelligent modeling and optimization for smart energy hub. IEEE Transactions on Industrial Electronics, 66(12), 9898–9908.CrossRef
14.
Zurück zum Zitat Mirzaei, M. A., et al. (2020). Integrated energy hub system based on power-to-gas and compressed air energy storage technologies in the presence of multiple shiftable loads. IET Generation, Transmission & Distribution, 14(13), 2510–2519.CrossRef Mirzaei, M. A., et al. (2020). Integrated energy hub system based on power-to-gas and compressed air energy storage technologies in the presence of multiple shiftable loads. IET Generation, Transmission & Distribution, 14(13), 2510–2519.CrossRef
15.
Zurück zum Zitat Ebadi, R., Yazdankhah, A. S., Mohammadi-Ivatloo, B., & Kazemzadeh, R. (2020). Coordinated power and train transportation system with transportable battery-based energy storage and demand response: A multi-objective stochastic approach. Journal of Cleaner Production, 275, 123923.CrossRef Ebadi, R., Yazdankhah, A. S., Mohammadi-Ivatloo, B., & Kazemzadeh, R. (2020). Coordinated power and train transportation system with transportable battery-based energy storage and demand response: A multi-objective stochastic approach. Journal of Cleaner Production, 275, 123923.CrossRef
16.
Zurück zum Zitat Chamandoust, H., Derakhshan, G., Hakimi, S. M., & Bahramara, S. (2019). Tri-objective optimal scheduling of smart energy hub system with schedulable loads. Journal of Cleaner Production, 236, 117584.CrossRef Chamandoust, H., Derakhshan, G., Hakimi, S. M., & Bahramara, S. (2019). Tri-objective optimal scheduling of smart energy hub system with schedulable loads. Journal of Cleaner Production, 236, 117584.CrossRef
17.
Zurück zum Zitat Ma, T., Wu, J., & Hao, L. (2017). Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub. Energy Conversion and Management, 133, 292–306.CrossRef Ma, T., Wu, J., & Hao, L. (2017). Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub. Energy Conversion and Management, 133, 292–306.CrossRef
18.
Zurück zum Zitat Liu, T., Zhang, D., Wang, S., & Wu, T. (2019). Standardized modelling and economic optimization of multi-carrier energy systems considering energy storage and demand response. Energy Conversion and Management, 182, 126–142.CrossRef Liu, T., Zhang, D., Wang, S., & Wu, T. (2019). Standardized modelling and economic optimization of multi-carrier energy systems considering energy storage and demand response. Energy Conversion and Management, 182, 126–142.CrossRef
19.
Zurück zum Zitat Mirzapour-Kamanaj, A., Majidi, M., Zare, K., & Kazemzadeh, R. (2020). Optimal strategic coordination of distribution networks and interconnected energy hubs: A linear multi-follower bi-level optimization model. International Journal of Electrical Power & Energy Systems, 119, 105925.CrossRef Mirzapour-Kamanaj, A., Majidi, M., Zare, K., & Kazemzadeh, R. (2020). Optimal strategic coordination of distribution networks and interconnected energy hubs: A linear multi-follower bi-level optimization model. International Journal of Electrical Power & Energy Systems, 119, 105925.CrossRef
20.
Zurück zum Zitat Fasihi, M., & Breyer, C. (2020). Baseload electricity and hydrogen supply based on hybrid PV-wind power plants. Journal of Cleaner Production, 243, 118466.CrossRef Fasihi, M., & Breyer, C. (2020). Baseload electricity and hydrogen supply based on hybrid PV-wind power plants. Journal of Cleaner Production, 243, 118466.CrossRef
21.
Zurück zum Zitat Bianchini, C., & Barbaro, P. (2009). Catalysis for sustainable energy production. Wiley. Bianchini, C., & Barbaro, P. (2009). Catalysis for sustainable energy production. Wiley.
22.
Zurück zum Zitat Deng, Z., & Jiang, Y. (2020). Optimal sizing of wind-hydrogen system considering hydrogen demand and trading modes. International Journal of Hydrogen Energy, 45(20), 11527–11537.CrossRef Deng, Z., & Jiang, Y. (2020). Optimal sizing of wind-hydrogen system considering hydrogen demand and trading modes. International Journal of Hydrogen Energy, 45(20), 11527–11537.CrossRef
23.
Zurück zum Zitat Troncoso, E., & Newborough, M. (2011). Electrolyzers for mitigating wind curtailment and producing ‘green’ merchant hydrogen. International Journal of Hydrogen Energy, 36(1), 120–134.CrossRef Troncoso, E., & Newborough, M. (2011). Electrolyzers for mitigating wind curtailment and producing ‘green’ merchant hydrogen. International Journal of Hydrogen Energy, 36(1), 120–134.CrossRef
24.
Zurück zum Zitat Mansour-Saatloo, A., Agabalaye-Rahvar, M., Mirzaei, M. A., Mohammadi-Ivatloo, B., Abapour, M., & Zare, K. (2020). Robust scheduling of hydrogen based smart micro energy hub with integrated demand response. Journal of Cleaner Production, 267, 122041.CrossRef Mansour-Saatloo, A., Agabalaye-Rahvar, M., Mirzaei, M. A., Mohammadi-Ivatloo, B., Abapour, M., & Zare, K. (2020). Robust scheduling of hydrogen based smart micro energy hub with integrated demand response. Journal of Cleaner Production, 267, 122041.CrossRef
25.
Zurück zum Zitat Syed, F. (2011). Analysis of a clean energy hub interfaced with a fleet of plug-in fuel cell vehicles. University of Waterloo. Syed, F. (2011). Analysis of a clean energy hub interfaced with a fleet of plug-in fuel cell vehicles. University of Waterloo.
26.
Zurück zum Zitat Kholardi, F., Assili, M., Lasemi, M. A., & Hajizadeh, A. (2018). Optimal management of energy hub with considering hydrogen network. In 2018 International conference on Smart Energy Systems and Technologies (SEST), IEEE, pp. 1–6. Kholardi, F., Assili, M., Lasemi, M. A., & Hajizadeh, A. (2018). Optimal management of energy hub with considering hydrogen network. In 2018 International conference on Smart Energy Systems and Technologies (SEST), IEEE, pp. 1–6.
27.
Zurück zum Zitat Dagdougui, H., Ouammi, A., & Sacile, R. (2012). Modelling and control of hydrogen and energy flows in a network of green hydrogen refuelling stations powered by mixed renewable energy systems. International Journal of Hydrogen Energy, 37(6), 5360–5371.CrossRef Dagdougui, H., Ouammi, A., & Sacile, R. (2012). Modelling and control of hydrogen and energy flows in a network of green hydrogen refuelling stations powered by mixed renewable energy systems. International Journal of Hydrogen Energy, 37(6), 5360–5371.CrossRef
28.
Zurück zum Zitat Carr, S., Zhang, F., Liu, F., Du, Z., & Maddy, J. (2016). Optimal operation of a hydrogen refuelling station combined with wind power in the electricity market. International Journal of Hydrogen Energy, 41(46), 21057–21066.CrossRef Carr, S., Zhang, F., Liu, F., Du, Z., & Maddy, J. (2016). Optimal operation of a hydrogen refuelling station combined with wind power in the electricity market. International Journal of Hydrogen Energy, 41(46), 21057–21066.CrossRef
29.
Zurück zum Zitat Isaac, N., & Saha, A. (2021). Analysis of refueling behavior of hydrogen fuel vehicles through a stochastic model using Markov Chain Process. Renewable and Sustainable Energy Reviews, 141, 110761.CrossRef Isaac, N., & Saha, A. (2021). Analysis of refueling behavior of hydrogen fuel vehicles through a stochastic model using Markov Chain Process. Renewable and Sustainable Energy Reviews, 141, 110761.CrossRef
30.
Zurück zum Zitat 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 Conversion and Management, 136, 404–417.CrossRef 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 Conversion and Management, 136, 404–417.CrossRef
31.
Zurück zum Zitat Mehrjerdi, H. (2019). Off-grid solar powered charging station for electric and hydrogen vehicles including fuel cell and hydrogen storage. International Journal of Hydrogen Energy, 44(23), 11574–11583.CrossRef Mehrjerdi, H. (2019). Off-grid solar powered charging station for electric and hydrogen vehicles including fuel cell and hydrogen storage. International Journal of Hydrogen Energy, 44(23), 11574–11583.CrossRef
32.
Zurück zum Zitat Majidi, M., & Zare, K. (2018). Integration of smart energy hubs in distribution networks under uncertainties and demand response concept. IEEE Transactions on Power Systems, 34(1), 566–574.CrossRef Majidi, M., & Zare, K. (2018). Integration of smart energy hubs in distribution networks under uncertainties and demand response concept. IEEE Transactions on Power Systems, 34(1), 566–574.CrossRef
33.
Zurück zum Zitat Mohammadi, M., Noorollahi, Y., & Mohammadi-Ivatloo, B. (2020). Fuzzy-based scheduling of wind integrated multi-energy systems under multiple uncertainties. Sustainable Energy Technologies and Assessments, 37, 100602.CrossRef Mohammadi, M., Noorollahi, Y., & Mohammadi-Ivatloo, B. (2020). Fuzzy-based scheduling of wind integrated multi-energy systems under multiple uncertainties. Sustainable Energy Technologies and Assessments, 37, 100602.CrossRef
34.
Zurück zum Zitat Jin, X., Mu, Y., Jia, H., Wu, J., Xu, X., & Yu, X. (2016). Optimal day-ahead scheduling of integrated urban energy systems. Applied Energy, 180, 1–13.CrossRef Jin, X., Mu, Y., Jia, H., Wu, J., Xu, X., & Yu, X. (2016). Optimal day-ahead scheduling of integrated urban energy systems. Applied Energy, 180, 1–13.CrossRef
35.
Zurück zum Zitat Jadidbonab, M., Madadi, S., & Mohammadi-Ivatloo, B. (2018). Hybrid strategy for optimal scheduling of renewable integrated energy hub based on stochastic/robust approach. Journal of Energy Management and Technology, 2(4), 29–38. Jadidbonab, M., Madadi, S., & Mohammadi-Ivatloo, B. (2018). Hybrid strategy for optimal scheduling of renewable integrated energy hub based on stochastic/robust approach. Journal of Energy Management and Technology, 2(4), 29–38.
36.
Zurück zum Zitat Mansour-Saatloo, A., Mirzaei, M. A., Mohammadi-Ivatloo, B., & Zare, K. (2020). A risk-averse hybrid approach for optimal participation of power-to-hydrogen technology-based multi-energy microgrid in multi-energy markets. Sustainable Cities and Society, 63, 102421.CrossRef Mansour-Saatloo, A., Mirzaei, M. A., Mohammadi-Ivatloo, B., & Zare, K. (2020). A risk-averse hybrid approach for optimal participation of power-to-hydrogen technology-based multi-energy microgrid in multi-energy markets. Sustainable Cities and Society, 63, 102421.CrossRef
37.
Zurück zum Zitat Najafi-Ghalelou, A., Nojavan, S., Zare, K., & Mohammadi-Ivatloo, B. (2019). Robust scheduling of thermal, cooling and electrical hub energy system under market price uncertainty. Applied Thermal Engineering, 149, 862–880.CrossRef Najafi-Ghalelou, A., Nojavan, S., Zare, K., & Mohammadi-Ivatloo, B. (2019). Robust scheduling of thermal, cooling and electrical hub energy system under market price uncertainty. Applied Thermal Engineering, 149, 862–880.CrossRef
38.
Zurück zum Zitat Rakipour, D., & Barati, H. (2019). Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response. Energy, 173, 384–399.CrossRef Rakipour, D., & Barati, H. (2019). Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response. Energy, 173, 384–399.CrossRef
Metadaten
Titel
Optimal Coalition Operation of Interconnected Hybrid Energy Systems Containing Local Energy Conversion Technologies, Renewable Energy Resources, and Energy Storage Systems
verfasst von
Behzad Motallebi Azar
Amir Mirzapour-Kamanaj
Rasool Kazemzadeh
Behnam Mohammadi-Ivatloo
Kazem Zare
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-030-87653-1_7