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Two-Stage Stochastic Market Clearing of Energy and Reserve in the Presence of Coupled Fuel Cell-Based Hydrogen Storage System with Renewable Resources

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Whole Energy Systems

Part of the book series: Power Systems ((POWSYS))

Abstract

The enhancing influence level of renewable energy sources (RESs), particularly wind energy sources (WESs), leads to technical challenges in power system operation procedures, such as changing the traditional operation scheduling. Due to maintaining the power balance among generation and utilization, the outstanding facility to tackle the intermittency essence of WES is a fuel cell-based hydrogen storage system (HSS). Furthermore, providing more operational flexibility has been obtained from taking into account both energy and reserve markets. For this purpose, the current chapter presents a two-stage stochastic network-constrained market-clearing approach with the integration of fuel cell-based HSS and WES to obtain optimal scheduling of conventional units and provide energy and reserve services. The introduced structure is applied to a six-bus system to specify the applicability and implementation of the model. Numerical results denoted that the integrated fuel cell-based HSS and WES decrease the whole operating expenditure, load shedding, and wind power curtailment.

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References

  1. IRENA (2019) and Abu Dhabi, Future of wind: Deployment, investment, technology, grid integration and socio – Economic aspects (A Global Energy Transformation paper) International Renewable Energy Agency.

    Google Scholar 

  2. Heydarian-Forushani, E., Golshan, M. E. H., & Shafie-khah, M. (2016). Flexible interaction of plug-in electric vehicle parking lots for efficient wind integration. Applied Energy, 179, 338–349.

    Article  Google Scholar 

  3. Wang, S., Yang, H., Pham, Q. B., Khoi, D. N., & Nhi, P. T. T. (2020). An ensemble framework to investigate wind energy sustainability considering climate change impacts. Sustainability, 12(3), 876.

    Article  Google Scholar 

  4. Ela, E., et al. (2016). Wholesale electricity market design with increasing levels of renewable generation: Incentivizing flexibility in system operations. The Electricity Journal, 29(4), 51–60.

    Article  Google Scholar 

  5. Alipour, M., Mohammadi-Ivatloo, B., Moradi-Dalvand, M., & Zare, K. (2017). Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets. Energy, 118, 1168–1179.

    Article  Google Scholar 

  6. Daneshvar, M., Mohammadi-Ivatloo, B., Zare, K., & Asadi, S. (2020). Two-stage stochastic programming model for optimal scheduling of the wind-thermal-hydropower-pumped storage system considering the flexibility assessment. Energy, 193.

    Google Scholar 

  7. García-Garre, A., Gabaldón, A., Álvarez-Bel, C., Ruiz-Abellón, M. D. C., & Guillamón, A. (2018). Integration of demand response and photovoltaic resources in residential segments. Sustainability, 10(9), 3030.

    Article  Google Scholar 

  8. Xu, Q., Ding, Y., & Zheng, A. (2017). An optimal dispatch model of wind-integrated power system considering demand response and reliability. Sustainability, 9(5), 758.

    Article  Google Scholar 

  9. Aliasghari, P., Mohammadi-Ivatloo, B., Alipour, M., Abapour, M., & Zare, K. (2018). Optimal scheduling of plug-in electric vehicles and renewable micro-grid in energy and reserve markets considering demand response program. Journal of Cleaner Production, 186, 293–303.

    Article  Google Scholar 

  10. Mirzaei, M. A., Sadeghi Yazdankhah, A., & Mohammadi-Ivatloo, B. (2019). Stochastic security-constrained operation of wind and hydrogen energy storage systems integrated with price-based demand response. International Journal of Hydrogen Energy, 44(27), 14217–14227.

    Article  Google Scholar 

  11. Yu, D., Wang, J., Li, D., Jermsittiparsert, K., & Nojavan, S. (2019). Risk-averse stochastic operation of a power system integrated with hydrogen storage system and wind generation in the presence of demand response program. International Journal of Hydrogen Energy, 44(59), 31204–31215.

    Article  Google Scholar 

  12. 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.

    Google Scholar 

  13. 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.

    Google Scholar 

  14. Seyyedeh-Barhagh, S., Majidi, M., Nojavan, S., & Zare, K. (2019). Optimal scheduling of hydrogen storage under economic and environmental priorities in the presence of renewable units and demand response. Sustainable Cities and Society, 46.

    Google Scholar 

  15. Dhabi, A. (2019). Hydrogen: A renewable energy perspective. IRENA, International Renewable Energy Agency.

    Google Scholar 

  16. ThyssenKrupp’s “green hydrogen and renewable ammonia value chain. Ammon. Ind. ammoniaindustry.com/thyssenkrupps-green-hydrogen-and-renewable-ammonia-value-chain/.”

  17. Fernandez-Blanco, R., Arroyo, J. M., & Alguacil, N. (2014). Network-constrained day-ahead auction for consumer payment minimization. IEEE Transactions on Power Systems, 29(2), 526–536.

    Article  Google Scholar 

  18. Parvania, M., Fotuhi-Firuzabad, M., & Shahidehpour, M. (2014). Comparative hourly scheduling of centralized and distributed storage in day-ahead markets. IEEE Transactions on Sustainable Energy, 5(3), 729–737.

    Article  Google Scholar 

  19. Agabalaye-Rahvar, M., Mansour-Saatloo, A., Mirzaei, M. A., Mohammadi-Ivatloo, B., Zare, K., & Anvari-Moghaddam, A. (2020). Robust optimal operation strategy for a hybrid energy system based on gas-fired unit, power-to-gas facility and wind power in energy markets. Energies, 13(22).

    Google Scholar 

  20. Nasri, A., Kazempour, S. J., Conejo, A. J., & Ghandhari, M. (2016). Network-constrained AC unit commitment under uncertainty: A benders’ decomposition approach. IEEE Transactions on Power Systems, 31(1), 412–422.

    Article  Google Scholar 

  21. Tumuluru, V. K., & Tsang, D. H. K. (2018). A two-stage approach for network constrained unit commitment problem with demand response. IEEE Transactions on Smart Grid, 9(2), 1175–1183.

    Article  Google Scholar 

  22. Kia, M., Nazar, M. S., Sepasian, M. S., Heidari, A., & Siano, P. (2017). Optimal day ahead scheduling of combined heat and power units with electrical and thermal storage considering security constraint of power system. Energy, 120, 241–252.

    Article  Google Scholar 

  23. Nazari-Heris, M., Mohammadi-Ivatloo, B., & Asadi, S. (2020). Optimal operation of multi-carrier energy networks considering uncertain parameters and thermal energy storage. Sustainability, 12(12), 5158.

    Article  Google Scholar 

  24. Vahedipour-Dahraie, M., Najafi, H., Anvari-Moghaddam, A., & Guerrero, J. (2017). Study of the effect of time-based rate demand response programs on stochastic day-ahead energy and reserve scheduling in islanded residential Microgrids. Applied Sciences, 7(4).

    Google Scholar 

  25. Doostizadeh, M., Aminifar, F., Ghasemi, H., & Lesani, H. (2016). Energy and reserve scheduling under wind power uncertainty: An adjustable interval approach. IEEE Transactions on Smart Grid, 7(6), 2943–2952.

    Article  Google Scholar 

  26. Cobos, N. G., Arroyo, J. M., Alguacil, N., & Wang, J. (2018). Robust energy and reserve scheduling considering bulk energy storage units and wind uncertainty. IEEE Transactions on Power Systems, 33(5), 5206–5216.

    Article  Google Scholar 

  27. Mirzaei, M. A., Yazdankhah, A. S., Mohammadi-Ivatloo, B., Marzband, M., Shafie-khah, M., & Catalão, J. P. S. (2019). Stochastic network-constrained co-optimization of energy and reserve products in renewable energy integrated power and gas networks with energy storage system. Journal of Cleaner Production, 223, 747–758.

    Article  Google Scholar 

  28. Jain, I. P., Jain, P., & Jain, A. (2010). Novel hydrogen storage materials: A review of lightweight complex hydrides. Journal of Alloys and Compounds, 503(2), 303–339.

    Article  Google Scholar 

  29. Meregalli, V., & Parrinello, M. (2001). Review of theoretical calculations of hydrogen storage in carbon-based materials. Applied Physics A Materials Science & Processing, 72(2), 143–146.

    Article  Google Scholar 

  30. Demirci, U. B. (2017). Ammonia borane, a material with exceptional properties for chemical hydrogen storage. International Journal of Hydrogen Energy, 42(15), 9978–10013.

    Article  Google Scholar 

  31. Heo, Y.-J., Yeon, S.-H., & Park, S.-J. (2019). Defining contribution of micropore size to hydrogen physisorption behaviors: A new approach based on DFT pore volumes. Carbon, 143, 288–293.

    Article  Google Scholar 

  32. Maniyali, Y., Almansoori, A., Fowler, M., & Elkamel, A. (2013). Energy hub based on nuclear energy and hydrogen energy storage. Industrial & Engineering Chemistry Research, 52(22), 7470–7481.

    Article  Google Scholar 

  33. Mansour-Satloo, A., Agabalaye-Rahvar, M., Mirazaei, M. A., Mohammadi-Ivatloo, B., Zare, K., & Anvari-Moghaddam, A. (2021). A hybrid robust-stochastic approach for optimal scheduling of interconnected hydrogen-based energy hubs. IET Smart Grid, 4(2), 241–254.

    Article  Google Scholar 

  34. Soroudi, A., Aien, M., & Ehsan, M. (2012). A probabilistic modeling of photo voltaic modules and wind power generation impact on distribution networks. IEEE Systems Journal, 6(2), 254–259.

    Article  Google Scholar 

  35. Mansour-Saatloo, A., Agabalaye-Rahvar, M., Mirzaei, M. A., Mohammadi-Ivatloo, B., & Zare, K. (2021). Chapter 9 – Economic analysis of energy storage systems in multicarrier microgrids. In B. Mohammadi-Ivatloo, A. Mohammadpour Shotorbani, & A. Anvari-Moghaddam (Eds.), Energy storage in energy markets (pp. 173–190). Academic Press.

    Chapter  Google Scholar 

  36. Alabdulwahab, A., Abusorrah, A., Zhang, X., & Shahidehpour, M. J. I. S. J. (2015). Stochastic security-constrained scheduling of coordinated electricity and natural gas infrastructures. IEEE Systems Journal, 11(3), 1674–1683.

    Article  Google Scholar 

  37. Sun, W. L. L., Xu, B., & Chai, T. (2010). The scheduling of steel-making and continuous casting process using branch and cut method via CPLEX optimization. In 5th International conference on computer sciences and convergence information technology, pp. 716–721.

    Google Scholar 

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Acknowledgements

This publication was partially supported by award NPRP12S-0125-190013 from the QNRF-Qatar National Research Fund, a member of The Qatar Foundation. The information and views set out in this publication are those of the authors and do not necessarily reflect the official opinion of the QNRF.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Masoud Agabalaye-Rahvar, Amin Mansour-Saatloo, Mohammad Amin Mirazaei & Kazem Zare

  2. Department of Electrical and Electronics Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey

    Behnam Mohammadi-Ivatloo

  3. Faculty of Electrical and ComputerEngineering, University of Tabriz, Tabriz, Iran

    Behnam Mohammadi-Ivatloo

  4. Department of Energy Technology, Aalborg University, Aalborg, Denmark

    Amjad Anvari-Moghaddam

Authors
  1. Masoud Agabalaye-Rahvar
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  2. Amin Mansour-Saatloo
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  3. Mohammad Amin Mirazaei
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  4. Behnam Mohammadi-Ivatloo
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  5. Kazem Zare
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  6. Amjad Anvari-Moghaddam
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Correspondence to Masoud Agabalaye-Rahvar .

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Editors and Affiliations

  1. Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, UK

    Vahid Vahidinasab

  2. Department of Electrical and Electronics Engineering, Muğla Sıtkı Koçman University, Muğla, Turkey

    Behnam Mohammadi-Ivatloo

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Agabalaye-Rahvar, M., Mansour-Saatloo, A., Mirazaei, M.A., Mohammadi-Ivatloo, B., Zare, K., Anvari-Moghaddam, A. (2022). Two-Stage Stochastic Market Clearing of Energy and Reserve in the Presence of Coupled Fuel Cell-Based Hydrogen Storage System with Renewable Resources. In: Vahidinasab, V., Mohammadi-Ivatloo, B. (eds) Whole Energy Systems . Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-87653-1_11

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  • DOI: https://doi.org/10.1007/978-3-030-87653-1_11

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  • Online ISBN: 978-3-030-87653-1

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