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Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty

Published: 30 October 2013
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Abstract

Hydroelectric power plants are important energy resources as they are environmentally friendly, have low level of potential risks and they are relatively cheap. If properly utilized, it can replace some thermal power plants and hence decrease the harmful effects to the environment. A Pumped Hydro Storage System which is a special type of hydroelectric power plant can be used to store energy and to use the water more efficiently. When the energy demand and the energy price are high (peak hours), the water at upper reservoir is used to generate electricity and the water is stored in the lower reservoir. Revenue is gained from the power sale to the market. When the demand and the energy price are low (off peak hours), the water at lower reservoir is pumped back to the upper reservoir. Cheap electricity is used to pump the water. The hourly market price and water inflow are uncertain. The main objective of a company is to find an operation schedule that will maximize its revenue. In this paper we develop a model that includes hourly inflow and power price data and delivers an operation schedule. Historical water inflow and power price data are used to generate scenarios. A real case study is developed to validate the model based on the historical river data and electricity prices.

Published in International Journal of Environmental Monitoring and Analysis (Volume 1, Issue 5)
DOI 10.11648/j.ijema.20130105.14
Page(s) 188-193
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Pumped Hydro Storage Systems, Electricity Price, Optimization, Scheduling

References
[1] Ikudo, A, (2009), "Maximizing Gross Margin of a Pumped Storage Hydroelectric Facility under Uncertainty in Price and Water Inflow", M.Sc. Thesis, The Ohio State University avaiable online at: http://etd.ohiolink.edu/send-pdf.cgi/Ikudo%20Akina.pdf?osu1243970453
[2] Levine, J.G.(2007) "Pumped hydroelectric energy storage and spatial diversity of wind resources as methods of improving utilization of renewable energy sources", Thesis, University of Colorado, available online at: http://www.colorado.edu/engineering/ energystorage/ files/ MSThesis_JGLevine_final.pdf
[3] Kapsalli, M., Kaldellis, J.K., (2010), "Combining hydro and variable wind power generation by means of pumped-storage under economically viable terms",Applied Energy, Vol. 87(11), pp. 3475–3485
[4] Yang, C, (2012), "Pumped Hydroelectric Storage", Wiley Encyclopedia of Energy, avaible online at:, http://www.duke.edu/~cy42/PHS.pdf
[5] Yang, C.J., Jackson, R.B., (2011), "Opportunities and barriers to pumped-hydro energy storage in the United States", Renewable and Sustainable Energy Reviews, Vol.15, pp. 839–844
[6] Zhao, G, Davison, M., (2009a), "Optimal Control of Hydroelectric Facility Incorporating Pump Storage", Renewable Energy, Vol.34(4), pp.1064-1077.
[7] Zhao, G., Davison, M., (2009b),"Valuing hydrological forecasts for a pumped storage assisted hydro facility", Journal of Hydrology, Vol.373(3-4), pp. 453–462
[8] Zhu, C. J, Zhou, J. Z, Yang, J. J, Wu, W, "Optimal Scheduling of Hydropower Plant with Unceartinity Energy Price Risk", International Conference on Power System Technology, 22-26 October, 2006, Chongqing, China
Cite This Article
  • APA Style

    Ahmet Yucekaya, Seda S. Metin. (2013). Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty. International Journal of Environmental Monitoring and Analysis, 1(5), 188-193. https://doi.org/10.11648/j.ijema.20130105.14

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    ACS Style

    Ahmet Yucekaya; Seda S. Metin. Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty. Int. J. Environ. Monit. Anal. 2013, 1(5), 188-193. doi: 10.11648/j.ijema.20130105.14

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    AMA Style

    Ahmet Yucekaya, Seda S. Metin. Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty. Int J Environ Monit Anal. 2013;1(5):188-193. doi: 10.11648/j.ijema.20130105.14

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  • @article{10.11648/j.ijema.20130105.14,
      author = {Ahmet Yucekaya and Seda S. Metin},
      title = {Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty},
      journal = {International Journal of Environmental Monitoring and Analysis},
      volume = {1},
      number = {5},
      pages = {188-193},
      doi = {10.11648/j.ijema.20130105.14},
      url = {https://doi.org/10.11648/j.ijema.20130105.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20130105.14},
      abstract = {Hydroelectric power plants are important energy resources as they are environmentally friendly, have low level of potential risks and they are relatively cheap. If properly utilized, it can replace some thermal power plants and hence decrease the harmful effects to the environment. A Pumped Hydro Storage System which is a special type of hydroelectric power plant can be used to store energy and to use the water more efficiently. When the energy demand and the energy price are high (peak hours), the water at upper reservoir is used to generate electricity and the water is stored in the lower reservoir. Revenue is gained from the power sale to the market. When the demand and the energy price are low (off peak hours), the water at lower reservoir is pumped back to the upper reservoir. Cheap electricity is used to pump the water. The hourly market price and water inflow are uncertain. The main objective of a company is to find an operation schedule that will maximize its revenue. In this paper we develop a model that includes hourly inflow and power price data and delivers an operation schedule. Historical water inflow and power price data are used to generate scenarios. A real case study is developed to validate the model based on the historical river data and electricity prices.},
     year = {2013}
    }
    

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  • TY  - JOUR
    T1  - Scheduling Pumped Hydro Power Storage Systems under Price and Flow Uncertainty
    AU  - Ahmet Yucekaya
    AU  - Seda S. Metin
    Y1  - 2013/10/30
    PY  - 2013
    N1  - https://doi.org/10.11648/j.ijema.20130105.14
    DO  - 10.11648/j.ijema.20130105.14
    T2  - International Journal of Environmental Monitoring and Analysis
    JF  - International Journal of Environmental Monitoring and Analysis
    JO  - International Journal of Environmental Monitoring and Analysis
    SP  - 188
    EP  - 193
    PB  - Science Publishing Group
    SN  - 2328-7667
    UR  - https://doi.org/10.11648/j.ijema.20130105.14
    AB  - Hydroelectric power plants are important energy resources as they are environmentally friendly, have low level of potential risks and they are relatively cheap. If properly utilized, it can replace some thermal power plants and hence decrease the harmful effects to the environment. A Pumped Hydro Storage System which is a special type of hydroelectric power plant can be used to store energy and to use the water more efficiently. When the energy demand and the energy price are high (peak hours), the water at upper reservoir is used to generate electricity and the water is stored in the lower reservoir. Revenue is gained from the power sale to the market. When the demand and the energy price are low (off peak hours), the water at lower reservoir is pumped back to the upper reservoir. Cheap electricity is used to pump the water. The hourly market price and water inflow are uncertain. The main objective of a company is to find an operation schedule that will maximize its revenue. In this paper we develop a model that includes hourly inflow and power price data and delivers an operation schedule. Historical water inflow and power price data are used to generate scenarios. A real case study is developed to validate the model based on the historical river data and electricity prices.
    VL  - 1
    IS  - 5
    ER  - 

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Author Information
  • Department of Industrial Engineering, Kadir Has University, Fatih, Istanbul, Turkey

  • Department of Industrial Engineering, Kadir Has University, Fatih, Istanbul, Turkey

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