A Corrective Frequency-Constrained Unit Commitment with Data-driven Estimation of Optimal UFLS in Island Power Systems
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909677531430912 |
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| author | Sarvarizadeh, Miad Sigrist, Lukas Rouco, Almudena Rajabdorri, Mohammad Lobato, Enrique |
| author_facet | Sarvarizadeh, Miad Sigrist, Lukas Rouco, Almudena Rajabdorri, Mohammad Lobato, Enrique |
| contents | This paper presents a novel corrective \gls{fcuc} formulation for island power systems by implementing data-driven constraint learning to estimate the optimal \gls{ufls}. The Tobit model is presented to estimate the optimal amount of \gls{ufls} using the initial rate of change of frequency. The proposed formulation enables co-optimizing operation costs and \gls{ufls}. The aim is to account for optimal \gls{ufls} occurrences during operation planning, without increasing them. This would potentially reduce system operation costs by relaxing the reserve requirement constraint. The performance of the proposed formulation has been analyzed for a Spanish island power system through various simulations. Different daily demand profiles are analyzed to demonstrate the effectiveness of the proposed formulation. Additionally, a sensitivity analysis is conducted to demonstrate the effects of changing the cost associated with \gls{ufls}. The corrective \gls{fcuc} is shown to be capable of reducing system operation costs without jeopardizing the quality of the frequency response in terms of \gls{ufls} occurrence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_05062 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Corrective Frequency-Constrained Unit Commitment with Data-driven Estimation of Optimal UFLS in Island Power Systems Sarvarizadeh, Miad Sigrist, Lukas Rouco, Almudena Rajabdorri, Mohammad Lobato, Enrique Systems and Control This paper presents a novel corrective \gls{fcuc} formulation for island power systems by implementing data-driven constraint learning to estimate the optimal \gls{ufls}. The Tobit model is presented to estimate the optimal amount of \gls{ufls} using the initial rate of change of frequency. The proposed formulation enables co-optimizing operation costs and \gls{ufls}. The aim is to account for optimal \gls{ufls} occurrences during operation planning, without increasing them. This would potentially reduce system operation costs by relaxing the reserve requirement constraint. The performance of the proposed formulation has been analyzed for a Spanish island power system through various simulations. Different daily demand profiles are analyzed to demonstrate the effectiveness of the proposed formulation. Additionally, a sensitivity analysis is conducted to demonstrate the effects of changing the cost associated with \gls{ufls}. The corrective \gls{fcuc} is shown to be capable of reducing system operation costs without jeopardizing the quality of the frequency response in terms of \gls{ufls} occurrence. |
| title | A Corrective Frequency-Constrained Unit Commitment with Data-driven Estimation of Optimal UFLS in Island Power Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2507.05062 |