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An optimal operation of wind energy storage system for frequency control based on model predictive control

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  • Khalid, M.
  • Savkin, A.V.

Abstract

A method for an efficient operation of a battery energy storage system (BESS) associated with frequency control problem is presented in this paper. A control system model is proposed to simulate the operation of BESS, and a controller is designed. The strategy is based on model predictive control to ensure the optimal operation of BESS in the presence of system constraints. A frequency prediction model based on Grey theory is also designed to optimize the performance of the predictive controller. The method is tested using real measurements from a power grid. The simulation results depict the effectiveness of the proposed approach.

Suggested Citation

  • Khalid, M. & Savkin, A.V., 2012. "An optimal operation of wind energy storage system for frequency control based on model predictive control," Renewable Energy, Elsevier, vol. 48(C), pages 127-132.
    • Handle: RePEc:eee:renene:v:48:y:2012:i:c:p:127-132
    DOI: 10.1016/j.renene.2012.03.038
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    References listed on IDEAS

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    1. Sebastián, R. & Quesada, J., 2006. "Distributed control system for frequency control in a isolated wind system," Renewable Energy, Elsevier, vol. 31(3), pages 285-305.
    2. Sebastián, R. & Alzola, R. Peña, 2010. "Effective active power control of a high penetration wind diesel system with a Ni–Cd battery energy storage," Renewable Energy, Elsevier, vol. 35(5), pages 952-965.
    3. El Mokadem, M. & Courtecuisse, V. & Saudemont, C. & Robyns, B. & Deuse, J., 2009. "Experimental study of variable speed wind generator contribution to primary frequency control," Renewable Energy, Elsevier, vol. 34(3), pages 833-844.
    4. Breton, Simon-Philippe & Moe, Geir, 2009. "Status, plans and technologies for offshore wind turbines in Europe and North America," Renewable Energy, Elsevier, vol. 34(3), pages 646-654.
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    Cited by:

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    3. Platero, C.A. & Nicolet, C. & Sánchez, J.A. & Kawkabani, B., 2014. "Increasing wind power penetration in autonomous power systems through no-flow operation of Pelton turbines," Renewable Energy, Elsevier, vol. 68(C), pages 515-523.
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    5. Kou, Peng & Gao, Feng & Guan, Xiaohong, 2015. "Stochastic predictive control of battery energy storage for wind farm dispatching: Using probabilistic wind power forecasts," Renewable Energy, Elsevier, vol. 80(C), pages 286-300.
    6. Akram, Umer & Nadarajah, Mithulananthan & Shah, Rakibuzzaman & Milano, Federico, 2020. "A review on rapid responsive energy storage technologies for frequency regulation in modern power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    7. Wenhao Zhuo & Andrey V. Savkin, 2019. "Profit Maximizing Control of a Microgrid with Renewable Generation and BESS Based on a Battery Cycle Life Model and Energy Price Forecasting," Energies, MDPI, vol. 12(15), pages 1-17, July.
    8. Elio Chiodo & Davide Lauria & Fabio Mottola & Daniela Proto & Domenico Villacci & Giorgio Maria Giannuzzi & Cosimo Pisani, 2022. "Probabilistic Description of the State of Charge of Batteries Used for Primary Frequency Regulation," Energies, MDPI, vol. 15(18), pages 1-24, September.
    9. Ibrahim Alotaibi & Mohammed A. Abido & Muhammad Khalid & Andrey V. Savkin, 2020. "A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources," Energies, MDPI, vol. 13(23), pages 1-41, November.
    10. Pandey, Shashi Kant & Mohanty, Soumya R. & Kishor, Nand, 2013. "A literature survey on load–frequency control for conventional and distribution generation power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 318-334.
    11. Wenhao Zhuo & Andrey V. Savkin & Ke Meng, 2019. "Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads," Energies, MDPI, vol. 12(11), pages 1-15, June.
    12. Paletta, Quentin & Hu, Anthony & Arbod, Guillaume & Lasenby, Joan, 2022. "ECLIPSE: Envisioning CLoud Induced Perturbations in Solar Energy," Applied Energy, Elsevier, vol. 326(C).

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