IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v176y2016icp65-73.html
   My bibliography  Save this article

Sharing wind power forecasts in electricity markets: A numerical analysis

Author

Listed:
  • Exizidis, Lazaros
  • Kazempour, S. Jalal
  • Pinson, Pierre
  • de Greve, Zacharie
  • Vallée, François

Abstract

In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

Suggested Citation

  • Exizidis, Lazaros & Kazempour, S. Jalal & Pinson, Pierre & de Greve, Zacharie & Vallée, François, 2016. "Sharing wind power forecasts in electricity markets: A numerical analysis," Applied Energy, Elsevier, vol. 176(C), pages 65-73.
    • Handle: RePEc:eee:appene:v:176:y:2016:i:c:p:65-73
    DOI: 10.1016/j.apenergy.2016.05.052
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916306468
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.05.052?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mahmoudi, Nadali & Saha, Tapan K. & Eghbal, Mehdi, 2014. "Modelling demand response aggregator behavior in wind power offering strategies," Applied Energy, Elsevier, vol. 133(C), pages 347-355.
    2. Rahimiyan, Morteza, 2014. "A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors," Applied Energy, Elsevier, vol. 122(C), pages 62-72.
    3. Ederer, Nikolaus, 2015. "The market value and impact of offshore wind on the electricity spot market: Evidence from Germany," Applied Energy, Elsevier, vol. 154(C), pages 805-814.
    4. Jónsson, Tryggvi & Pinson, Pierre & Madsen, Henrik, 2010. "On the market impact of wind energy forecasts," Energy Economics, Elsevier, vol. 32(2), pages 313-320, March.
    5. Rahimiyan, Morteza & Morales, Juan M. & Conejo, Antonio J., 2011. "Evaluating alternative offering strategies for wind producers in a pool," Applied Energy, Elsevier, vol. 88(12), pages 4918-4926.
    6. Xiao, Yunpeng & Wang, Xifan & Wang, Xiuli & Dang, Can & Lu, Ming, 2016. "Behavior analysis of wind power producer in electricity market," Applied Energy, Elsevier, vol. 171(C), pages 325-335.
    7. Li, Gong & Shi, Jing, 2012. "Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions," Applied Energy, Elsevier, vol. 99(C), pages 13-22.
    8. Arjmand, Reza & Rahimiyan, Morteza, 2016. "Statistical analysis of a competitive day-ahead market coupled with correlated wind production and electric load," Applied Energy, Elsevier, vol. 161(C), pages 153-167.
    9. Baringo, L. & Conejo, A.J., 2013. "Correlated wind-power production and electric load scenarios for investment decisions," Applied Energy, Elsevier, vol. 101(C), pages 475-482.
    10. Morales, Juan M. & Zugno, Marco & Pineda, Salvador & Pinson, Pierre, 2014. "Electricity market clearing with improved scheduling of stochastic production," European Journal of Operational Research, Elsevier, vol. 235(3), pages 765-774.
    11. Gabriel, Steven A. & Leuthold, Florian U., 2010. "Solving discretely-constrained MPEC problems with applications in electric power markets," Energy Economics, Elsevier, vol. 32(1), pages 3-14, January.
    12. Geoffrey Pritchard & Golbon Zakeri & Andrew Philpott, 2010. "A Single-Settlement, Energy-Only Electric Power Market for Unpredictable and Intermittent Participants," Operations Research, INFORMS, vol. 58(4-part-2), pages 1210-1219, August.
    13. Morales, J.M. & Mínguez, R. & Conejo, A.J., 2010. "A methodology to generate statistically dependent wind speed scenarios," Applied Energy, Elsevier, vol. 87(3), pages 843-855, March.
    14. Vilim, Michael & Botterud, Audun, 2014. "Wind power bidding in electricity markets with high wind penetration," Applied Energy, Elsevier, vol. 118(C), pages 141-155.
    15. Díaz, Guzmán & Gómez-Aleixandre, Javier & Coto, José, 2016. "Wind power scenario generation through state-space specifications for uncertainty analysis of wind power plants," Applied Energy, Elsevier, vol. 162(C), pages 21-30.
    16. Baringo, L. & Conejo, A.J., 2011. "Wind power investment within a market environment," Applied Energy, Elsevier, vol. 88(9), pages 3239-3247.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmed, Adil & Khalid, Muhammad, 2018. "An intelligent framework for short-term multi-step wind speed forecasting based on Functional Networks," Applied Energy, Elsevier, vol. 225(C), pages 902-911.
    2. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    3. Jin, Yuqing & Ju, Ping & Rehtanz, Christian & Wu, Feng & Pan, Xueping, 2018. "Equivalent modeling of wind energy conversion considering overall effect of pitch angle controllers in wind farm," Applied Energy, Elsevier, vol. 222(C), pages 485-496.
    4. Hao, Yan & Tian, Chengshi, 2019. "A novel two-stage forecasting model based on error factor and ensemble method for multi-step wind power forecasting," Applied Energy, Elsevier, vol. 238(C), pages 368-383.
    5. Yıldıran, Uğur & Kayahan, İsmail, 2018. "Risk-averse stochastic model predictive control-based real-time operation method for a wind energy generation system supported by a pumped hydro storage unit," Applied Energy, Elsevier, vol. 226(C), pages 631-643.
    6. Yakai Qiao & Hui Chen & Bo Fu, 2024. "Multi-Wind Turbine Wind Speed Prediction Based on Weighted Diffusion Graph Convolution and Gated Attention Network," Energies, MDPI, vol. 17(7), pages 1-15, March.
    7. Alvarez-Mendoza, Fernanda & Bacher, Peder & Madsen, Henrik & Angeles-Camacho, César, 2017. "Stochastic model of wind-fuel cell for a semi-dispatchable power generation," Applied Energy, Elsevier, vol. 193(C), pages 139-148.
    8. Xiao, Yunpeng & Wang, Xifan & Wang, Xiuli & Wu, Zechen, 2016. "Trading wind power with barrier option," Applied Energy, Elsevier, vol. 182(C), pages 232-242.
    9. Kenis, Michiel & Höschle, Hanspeter & Bruninx, Kenneth, 2022. "Strategic bidding of wind power producers in electricity markets in presence of information sharing," Energy Economics, Elsevier, vol. 110(C).
    10. Abbasi, Mohammad Hossein & Taki, Mehrdad & Rajabi, Amin & Li, Li & Zhang, Jiangfeng, 2019. "Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach," Applied Energy, Elsevier, vol. 239(C), pages 1294-1307.
    11. Bonou, Alexandra & Laurent, Alexis & Olsen, Stig I., 2016. "Life cycle assessment of onshore and offshore wind energy-from theory to application," Applied Energy, Elsevier, vol. 180(C), pages 327-337.
    12. Bjørndal, Endre & Bjørndal, Mette & Midthun, Kjetil & Tomasgard, Asgeir, 2018. "Stochastic electricity dispatch: A challenge for market design," Energy, Elsevier, vol. 150(C), pages 992-1005.
    13. Hao, Ying & Dong, Lei & Liao, Xiaozhong & Liang, Jun & Wang, Lijie & Wang, Bo, 2019. "A novel clustering algorithm based on mathematical morphology for wind power generation prediction," Renewable Energy, Elsevier, vol. 136(C), pages 572-585.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Arjmand, Reza & Rahimiyan, Morteza, 2016. "Statistical analysis of a competitive day-ahead market coupled with correlated wind production and electric load," Applied Energy, Elsevier, vol. 161(C), pages 153-167.
    2. Suomalainen, Kiti & Pritchard, Geoffrey & Sharp, Basil & Yuan, Ziqi & Zakeri, Golbon, 2015. "Correlation analysis on wind and hydro resources with electricity demand and prices in New Zealand," Applied Energy, Elsevier, vol. 137(C), pages 445-462.
    3. Arjmand, Reza & Rahimiyan, Morteza, 2016. "Impact of spatio-temporal correlation of wind production on clearing outcomes of a competitive pool market," Renewable Energy, Elsevier, vol. 86(C), pages 216-227.
    4. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    5. Morales, Juan M. & Pineda, Salvador, 2017. "On the inefficiency of the merit order in forward electricity markets with uncertain supply," European Journal of Operational Research, Elsevier, vol. 261(2), pages 789-799.
    6. Li, Jinghua & Zhou, Jiasheng & Chen, Bo, 2020. "Review of wind power scenario generation methods for optimal operation of renewable energy systems," Applied Energy, Elsevier, vol. 280(C).
    7. González-Aparicio, I. & Zucker, A., 2015. "Impact of wind power uncertainty forecasting on the market integration of wind energy in Spain," Applied Energy, Elsevier, vol. 159(C), pages 334-349.
    8. Xiao, Yunpeng & Wang, Xifan & Wang, Xiuli & Wu, Zechen, 2016. "Trading wind power with barrier option," Applied Energy, Elsevier, vol. 182(C), pages 232-242.
    9. Xiao, Yunpeng & Wang, Xifan & Wang, Xiuli & Dang, Can & Lu, Ming, 2016. "Behavior analysis of wind power producer in electricity market," Applied Energy, Elsevier, vol. 171(C), pages 325-335.
    10. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2016. "How much is enough? Optimal support payments in a renewable-rich power system," Energy, Elsevier, vol. 117(P1), pages 300-313.
    11. Rahimiyan, Morteza, 2014. "A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors," Applied Energy, Elsevier, vol. 122(C), pages 62-72.
    12. Ordoudis, Christos & Pinson, Pierre & Morales, Juan M., 2019. "An Integrated Market for Electricity and Natural Gas Systems with Stochastic Power Producers," European Journal of Operational Research, Elsevier, vol. 272(2), pages 642-654.
    13. Hosseini, Seyyed Ahmad & Toubeau, Jean-François & De Grève, Zacharie & Vallée, François, 2020. "An advanced day-ahead bidding strategy for wind power producers considering confidence level on the real-time reserve provision," Applied Energy, Elsevier, vol. 280(C).
    14. Hain, Martin & Kargus, Tobias & Schermeyer, Hans & Uhrig-Homburg, Marliese & Fichtner, Wolf, 2022. "An electricity price modeling framework for renewable-dominant markets," Working Paper Series in Production and Energy 66, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    15. Bell, William Paul & Wild, Phillip & Foster, John & Hewson, Michael, 2017. "Revitalising the wind power induced merit order effect to reduce wholesale and retail electricity prices in Australia," Energy Economics, Elsevier, vol. 67(C), pages 224-241.
    16. Thomas Kleinert & Martin Schmidt, 2023. "Why there is no need to use a big-M in linear bilevel optimization: a computational study of two ready-to-use approaches," Computational Management Science, Springer, vol. 20(1), pages 1-12, December.
    17. Anna Schwele & Christos Ordoudis & Pierre Pinson & Jalal Kazempour, 2021. "Coordination of power and natural gas markets via financial instruments," Computational Management Science, Springer, vol. 18(4), pages 505-538, October.
    18. Vijay, Avinash & Fouquet, Nicolas & Staffell, Iain & Hawkes, Adam, 2017. "The value of electricity and reserve services in low carbon electricity systems," Applied Energy, Elsevier, vol. 201(C), pages 111-123.
    19. Huiru Zhao & Yuwei Wang & Mingrui Zhao & Qingkun Tan & Sen Guo, 2017. "Day-Ahead Market Modeling for Strategic Wind Power Producers under Robust Market Clearing," Energies, MDPI, vol. 10(7), pages 1-27, July.
    20. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:176:y:2016:i:c:p:65-73. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.