IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v248y2025ics0960148125007359.html

Improvement of wind power utilization through flexible operation of data center in wind parks

Author

Listed:
  • Ahmadi, Mehdi
  • Knorr, Lukas
  • Meschede, Henning

Abstract

Wind energy's pivotal role in renewable transitions is hindered by grid integration challenges, notably limited distribution line capacity to handle wind-generated power efficiently. A solution to strengthen the effectiveness of wind power (WP) distribution systems involves integrating data centers (DCs) as flexible loads within WP plants. This approach introduces a novel dynamic load-shifting model aligning DC operations with wind energy availability, considering ambient temperature effects on cooling systems consumption. The model optimizes renewable energy (RE) usage and minimizes grid dependence by adjusting load schedules based on WP fluctuations, temperature changes, and electricity pricing. This model identifies specific controllable loads in DCs and employs adaptive and lexicographic optimization framework using Mixed-Integer Linear Programming to address system uncertainties. A case study highlights the model's effectiveness: WP share compared to not using DC integration surged to 91.3 % during peak wind periods, and WP utilization reached 88.9 % during low wind periods, significantly enhancing RE distribution efficiency compared to conditions without DC integration. Furthermore, the model optimizes cost efficiency by achieving a 52.6 % cost reduction during low-demand periods via strategic load shifting. Moreover, a stochastic solution analysis quantifies the benefit of incorporating uncertainty, revealing cost savings between 3.33 % and 16.63 % over deterministic models.

Suggested Citation

  • Ahmadi, Mehdi & Knorr, Lukas & Meschede, Henning, 2025. "Improvement of wind power utilization through flexible operation of data center in wind parks," Renewable Energy, Elsevier, vol. 248(C).
  • Handle: RePEc:eee:renene:v:248:y:2025:i:c:s0960148125007359
    DOI: 10.1016/j.renene.2025.123073
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125007359
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2025.123073?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Wolf, Isabel & Holzapfel, Peter K.R. & Meschede, Henning & Finkbeiner, Matthias, 2023. "On the potential of temporally resolved GHG emission factors for load shifting: A case study on electrified steam generation," Applied Energy, Elsevier, vol. 348(C).
    2. Divkovic, Denis & Knorr, Lukas & Schwesig, Ramon & Meschede, Henning, 2024. "Effects on dimensioning of heat supply technologies for district heating under consideration of future developments regarding investment costs and emission factors," Energy, Elsevier, vol. 301(C).
    3. Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron, 2019. "Are complex energy system models more accurate? An intra-model comparison of power system optimization models," Applied Energy, Elsevier, vol. 255(C).
    4. Sobolewski, Robert Adam & Tchakorom, Médane & Couturier, Raphaël, 2023. "Gradient boosting-based approach for short- and medium-term wind turbine output power prediction," Renewable Energy, Elsevier, vol. 203(C), pages 142-160.
    5. Østergaard, Poul Alberg & Duic, Neven & Kalogirou, Soteris, 2024. "Sustainable development using integrated energy systems and solar, biomass, wind, and wave technology," Renewable Energy, Elsevier, vol. 235(C).
    6. Yuan, Xiaohui & Tan, Qingxiong & Lei, Xiaohui & Yuan, Yanbin & Wu, Xiaotao, 2017. "Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine," Energy, Elsevier, vol. 129(C), pages 122-137.
    7. Yan, Jie & Nuertayi, Akejiang & Yan, Yamin & Liu, Shan & Liu, Yongqian, 2023. "Hybrid physical and data driven modeling for dynamic operation characteristic simulation of wind turbine," Renewable Energy, Elsevier, vol. 215(C).
    8. Sujin Kim & Raghu Pasupathy & Shane G. Henderson, 2015. "A Guide to Sample Average Approximation," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 207-243, Springer.
    9. Wang, Jiangjiang & Deng, Hongda & Liu, Yi & Guo, Zeqing & Wang, Yongzhen, 2023. "Coordinated optimal scheduling of integrated energy system for data center based on computing load shifting," Energy, Elsevier, vol. 267(C).
    10. Yasuda, Yoh & Bird, Lori & Carlini, Enrico Maria & Eriksen, Peter Børre & Estanqueiro, Ana & Flynn, Damian & Fraile, Daniel & Gómez Lázaro, Emilio & Martín-Martínez, Sergio & Hayashi, Daisuke & Holtti, 2022. "C-E (curtailment – Energy share) map: An objective and quantitative measure to evaluate wind and solar curtailment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    11. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.
    12. Zhang, Yuning & Tang, Ningning & Niu, Yuguang & Du, Xiaoze, 2016. "Wind energy rejection in China: Current status, reasons and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 322-344.
    13. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    14. Raftery, Adrian E. & Dean, Nema, 2006. "Variable Selection for Model-Based Clustering," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 168-178, March.
    15. Qi, Ye & Dong, Wenjuan & Dong, Changgui & Huang, Caiwei, 2019. "Understanding institutional barriers for wind curtailment in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 476-486.
    16. Tomin, Nikita & Shakirov, Vladislav & Kurbatsky, Victor & Muzychuk, Roman & Popova, Ekaterina & Sidorov, Denis & Kozlov, Alexandr & Yang, Dechang, 2022. "A multi-criteria approach to designing and managing a renewable energy community," Renewable Energy, Elsevier, vol. 199(C), pages 1153-1175.
    17. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    18. Güğül, Gül Nihal & Gökçül, Furkan & Eicker, Ursula, 2023. "Sustainability analysis of zero energy consumption data centers with free cooling, waste heat reuse and renewable energy systems: A feasibility study," Energy, Elsevier, vol. 262(PB).
    19. Meschede, Henning, 2019. "Increased utilisation of renewable energies through demand response in the water supply sector – A case study," Energy, Elsevier, vol. 175(C), pages 810-817.
    20. Khasanzoda, Nasrullo & Zicmane, Inga & Beryozkina, Svetlana & Safaraliev, Murodbek & Sultonov, Sherkhon & Kirgizov, Alifbek, 2022. "Regression model for predicting the speed of wind flows for energy needs based on fuzzy logic," Renewable Energy, Elsevier, vol. 191(C), pages 723-731.
    21. Meschede, Henning, 2020. "Analysis on the demand response potential in hotels with varying probabilistic influencing time-series for the Canary Islands," Renewable Energy, Elsevier, vol. 160(C), pages 1480-1491.
    Full references (including those not matched with items on IDEAS)

    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. Knorr, Lukas & Schlosser, Florian & Horstmann, Nils & Divkovic, Denis & Meschede, Henning, 2024. "Flexible operation and integration of high-temperature heat pumps using large temperature glides," Applied Energy, Elsevier, vol. 368(C).
    2. Han, Yibo & Han, Kai & Wang, Yongzhen & Lin, Jiayu & Han, Juntao & Song, Kuo & Tang, Hao & Han, Te, 2025. "Bi-level optimization and sustainability assessment of data center integrated energy system based on emergy theory," Energy, Elsevier, vol. 334(C).
    3. López Prol, Javier & Zilberman, David, 2023. "No alarms and no surprises: Dynamics of renewable energy curtailment in California," Energy Economics, Elsevier, vol. 126(C).
    4. González-Sopeña, J.M. & Pakrashi, V. & Ghosh, B., 2021. "An overview of performance evaluation metrics for short-term statistical wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. Fu, Wenlong & Fang, Ping & Wang, Kai & Li, Zhenxing & Xiong, Dongzhen & Zhang, Kai, 2021. "Multi-step ahead short-term wind speed forecasting approach coupling variational mode decomposition, improved beetle antennae search algorithm-based synchronous optimization and Volterra series model," Renewable Energy, Elsevier, vol. 179(C), pages 1122-1139.
    6. Vadim Manusov & Pavel Matrenin & Muso Nazarov & Svetlana Beryozkina & Murodbek Safaraliev & Inga Zicmane & Anvari Ghulomzoda, 2023. "Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems," Sustainability, MDPI, vol. 15(2), pages 1-12, January.
    7. Bian, Yifan & Xie, Lirong & Ma, Lan & Cui, Chuanshi, 2025. "A novel two-stage energy sharing model for data center cluster considering integrated demand response of multiple loads," Applied Energy, Elsevier, vol. 384(C).
    8. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan, 2024. "A new shared energy storage business model for data center clusters considering energy storage degradation," Renewable Energy, Elsevier, vol. 225(C).
    9. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2022. "Accuracy indicators for evaluating retrospective performance of energy system models," Applied Energy, Elsevier, vol. 325(C).
    10. Bian, Yifan & Xie, Lirong & Ma, Lan & Zhang, Hangong, 2024. "A novel two-stage energy sharing method for data center cluster considering ‘Carbon-Green Certificate’ coupling mechanism," Energy, Elsevier, vol. 313(C).
    11. Barone, Giovanni & Buonomano, Annamaria & Giuzio, Giovanni Francesco & Palombo, Adolfo, 2023. "Towards zero energy infrastructure buildings: optimal design of envelope and cooling system," Energy, Elsevier, vol. 279(C).
    12. Walmsley, Timothy Gordon & Philipp, Matthias & Picón-Núñez, Martín & Meschede, Henning & Taylor, Matthew Thomas & Schlosser, Florian & Atkins, Martin John, 2023. "Hybrid renewable energy utility systems for industrial sites: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    13. Fan, Junqiu & Yan, Rujing & He, Yu & Zhang, Jing & Zhao, Weixing & Liu, Mingshun & An, Su & Ma, Qingfeng, 2025. "Stochastic optimization of combined energy and computation task scheduling strategies of hybrid system with multi-energy storage system and data center," Renewable Energy, Elsevier, vol. 242(C).
    14. Henning Meschede & Paul Bertheau & Siavash Khalili & Christian Breyer, 2022. "A review of 100% renewable energy scenarios on islands," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(6), November.
    15. repec:prg:jnlcfu:v:2022:y:2022:i:1:id:572 is not listed on IDEAS
    16. Sereshti, Narges & Adulyasak, Yossiri & Jans, Raf, 2024. "Managing flexibility in stochastic multi-level lot sizing problem with service level constraints," Omega, Elsevier, vol. 122(C).
    17. Shan, Kui & Wang, Shengwei & Zhuang, Chaoqun, 2021. "Controlling a large constant speed centrifugal chiller to provide grid frequency regulation: A validation based on onsite tests," Applied Energy, Elsevier, vol. 300(C).
    18. Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Fehler, Alexander & Gaumnitz, Felix & van Ouwerkerk, Jonas & Bußa, 2022. "Modeling flexibility in energy systems — comparison of power sector models based on simplified test cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    19. Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
    20. Hu, Jiaxiang & Hu, Weihao & Cao, Di & Sun, Xinwu & Chen, Jianjun & Huang, Yuehui & Chen, Zhe & Blaabjerg, Frede, 2024. "Probabilistic net load forecasting based on transformer network and Gaussian process-enabled residual modeling learning method," Renewable Energy, Elsevier, vol. 225(C).
    21. Andrikopoulos, Andreas & Merika, Anna & Stoupos, Nikolaos, 2025. "The effect of oil prices on the US shipping stock prices: The mediating role of freight rates and economic indicators," Journal of Commodity Markets, Elsevier, vol. 38(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:renene:v:248:y:2025:i:c:s0960148125007359. 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.journals.elsevier.com/renewable-energy .

    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.