Investigating inclusion of linear sensitivity factors in analytical frequency constrained unit commitment formulation

Abstract

As power systems transition towards cleaner energy sources and reduce reliance on conventional generation sources, power systems become increasingly vulnerable to frequency instability following large disturbances due to lower inertia levels. To address this, frequency constraints are being integrated into unit commitment (UC) processes to ensure acceptable frequency deviations during contingencies. However, the inclusion of transmission constraints introduces significant computational complexity. This paper investigates an alternative approach to incorporating transmission line constraints into the analytical frequency-constrained UC (FCUC) problem, aiming to explore whether the computational burden can be reduced using linear sensitivity factors (LSFs) to represent transmission line parameters, aiming to improve computational efficiency. Findings obtained from the study indicate that LSF-based FCUC models offer comparable computational performance compared to DC-based FCUC models while showing reduced spillage under network congestions. These results highlight LSFs as a feasible approach for co-optimizing transmission and frequency constraints in low-inertia power systems, with further validations on larger networks recommended.

As power systems transition towards cleaner energy sources and reduce reliance on conventional generation sources, power systems become increasingly vulnerable to frequency instability following large disturbances due to lower inertia levels. To address this, frequency constraints are being integrated into unit commitment (UC) processes to ensure acceptable frequency deviations during contingencies. However, the inclusion of transmission constraints introduces significant computational complexity. This paper investigates an alternative approach to incorporating transmission line constraints into the analytical frequency-constrained UC (FCUC) problem, aiming to explore whether the computational burden can be reduced using linear sensitivity factors (LSFs) to represent transmission line parameters, aiming to improve computational efficiency. Findings obtained from the study indicate that LSF-based FCUC models offer comparable computational performance compared to DC-based FCUC models while showing reduced spillage under network congestions. These results highlight LSFs as a feasible approach for co-optimizing transmission and frequency constraints in low-inertia power systems, with further validations on larger networks recommended.