A Corrective Frequency-Constrained Unit Commitment with Data-driven Estimation of Optimal UFLS in Island Power Systems
Abstract
This paper presents a novel corrective fcuc formulation for island power systems by implementing data-driven constraint learning to estimate the optimal ufls. The Tobit model is presented to estimate the optimal amount of ufls using the initial rate of change of frequency. The proposed formulation enables co-optimizing operation costs and ufls. The aim is to account for optimal 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 ufls. The corrective fcuc is shown to be capable of reducing system operation costs without jeopardizing the quality of the frequency response in terms of ufls occurrence.
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