An optimal operation strategy for collaborative flexibility provision of a carbon capture and utilization process with wind energy
- Author
- Arash Ebneali Samani (UGent) , Nezmin Kayedpour (UGent) , Farjam Kayedpour, Jeroen De Kooning (UGent) , Guillaume Crevecoeur (UGent) and Lieven Vandevelde (UGent)
- Organization
- Project
- Abstract
- Improving power system flexibility by responsive demand is essential for integrating wind energy with a high level of variability in power systems. Carbon dioxide-based chemical processes as energy-intensive industrial loads may offer a vast potential of new forms of flexible operation due to their existing control infrastructure and storage capabilities. However, a collaborative decision model is needed for optimal energy sharing among the chemical plant and the grid under the variations and uncertainties of wind power. This study develops an optimal two-stage stochastic programming model for a novel flexible operation strategy of the chemical process coupled with wind turbines. In the proposed control scheme, a small-scale wind farm provides the power input of a chemical plant. Wind turbines are connected to the grid and actively participate in the day-ahead energy and reserve markets, considering the chemical plant as a source of flexibility. An equivalent scenario-based model of the proposed optimization problem is suggested using the Group Method of Data Handling (GMDH) for a data-driven prediction of stochastic variables. Simulation results demonstrate the effectiveness and significance of the proposed approach for an optimal and collaborative contribution in ancillary market of a carbon dioxide-based chemical plant supplied by wind energy.
- Keywords
- Wind energy, Carbon dioxide-based chemical plant, Optimization, Flexible operation, Day-ahead market
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GW9AP7HEFW4RWBZ50X91QBBV
- MLA
- Ebneali Samani, Arash, et al. “An Optimal Operation Strategy for Collaborative Flexibility Provision of a Carbon Capture and Utilization Process with Wind Energy.” IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, vol. 14, no. 4, 2023, pp. 2432–44, doi:10.1109/tste.2023.3257044.
- APA
- Ebneali Samani, A., Kayedpour, N., Kayedpour, F., De Kooning, J., Crevecoeur, G., & Vandevelde, L. (2023). An optimal operation strategy for collaborative flexibility provision of a carbon capture and utilization process with wind energy. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 14(4), 2432–2444. https://doi.org/10.1109/tste.2023.3257044
- Chicago author-date
- Ebneali Samani, Arash, Nezmin Kayedpour, Farjam Kayedpour, Jeroen De Kooning, Guillaume Crevecoeur, and Lieven Vandevelde. 2023. “An Optimal Operation Strategy for Collaborative Flexibility Provision of a Carbon Capture and Utilization Process with Wind Energy.” IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 14 (4): 2432–44. https://doi.org/10.1109/tste.2023.3257044.
- Chicago author-date (all authors)
- Ebneali Samani, Arash, Nezmin Kayedpour, Farjam Kayedpour, Jeroen De Kooning, Guillaume Crevecoeur, and Lieven Vandevelde. 2023. “An Optimal Operation Strategy for Collaborative Flexibility Provision of a Carbon Capture and Utilization Process with Wind Energy.” IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 14 (4): 2432–2444. doi:10.1109/tste.2023.3257044.
- Vancouver
- 1.Ebneali Samani A, Kayedpour N, Kayedpour F, De Kooning J, Crevecoeur G, Vandevelde L. An optimal operation strategy for collaborative flexibility provision of a carbon capture and utilization process with wind energy. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY. 2023;14(4):2432–44.
- IEEE
- [1]A. Ebneali Samani, N. Kayedpour, F. Kayedpour, J. De Kooning, G. Crevecoeur, and L. Vandevelde, “An optimal operation strategy for collaborative flexibility provision of a carbon capture and utilization process with wind energy,” IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, vol. 14, no. 4, pp. 2432–2444, 2023.
@article{01GW9AP7HEFW4RWBZ50X91QBBV,
abstract = {{Improving power system flexibility by responsive demand is essential for integrating wind energy with a high level of variability in power systems. Carbon dioxide-based chemical processes as energy-intensive industrial loads may offer a vast potential of new forms of flexible operation due to their existing control infrastructure and storage capabilities. However, a collaborative decision model is needed for optimal energy sharing among the chemical plant and the grid under the variations and uncertainties of wind power. This study develops an optimal two-stage stochastic programming model for a novel flexible operation strategy of the chemical process coupled with wind turbines. In the proposed control scheme, a small-scale wind farm provides the power input of a chemical plant. Wind turbines are connected to the grid and actively participate in the day-ahead energy and reserve markets, considering the chemical plant as a source of flexibility. An equivalent scenario-based model of the proposed optimization problem is suggested using the Group Method of Data Handling (GMDH) for a data-driven prediction of stochastic variables. Simulation results demonstrate the effectiveness and significance of the proposed approach for an optimal and collaborative contribution in ancillary market of a carbon dioxide-based chemical plant supplied by wind energy.}},
author = {{Ebneali Samani, Arash and Kayedpour, Nezmin and Kayedpour, Farjam and De Kooning, Jeroen and Crevecoeur, Guillaume and Vandevelde, Lieven}},
issn = {{1949-3029}},
journal = {{IEEE TRANSACTIONS ON SUSTAINABLE ENERGY}},
keywords = {{Wind energy,Carbon dioxide-based chemical plant,Optimization,Flexible operation,Day-ahead market}},
language = {{eng}},
number = {{4}},
pages = {{2432--2444}},
title = {{An optimal operation strategy for collaborative flexibility provision of a carbon capture and utilization process with wind energy}},
url = {{http://doi.org/10.1109/tste.2023.3257044}},
volume = {{14}},
year = {{2023}},
}
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