Extending AC Security Constrained Optimal Power Flow for Low Inertia Systems with Artificial Neural Network-based Frequency Stability Constraints

Auteurs

Alizadeh M.I., Capitanescu F., Barbeiro P.P., Gouveia J., Moreira C.L., Soares F.

Référence

IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2024, 2024

Description

Frequency stability in inverter-based renewable energy sources (RES)-dominated, low-inertia, power systems is a timely challenge. This paper employs a systematic approach, utilizing an artificial neural network (ANN) and dynamic simulation, to infer two key frequency stability indicators: nadir and rate of change of frequency (RoCoF). By reformulating the ANN mathematical model, these indicators are then integrated as mixed-integer non-linear constraints into a classical AC security-constrained optimal power flow (AC SCOPF), resulting in the proposed AC-F-SCOPF problem. The results of the proposed AC-F-SCOPF on the IEEE 39-bus system show that the problem identifies accurately the synchronous condensers which must run to ensure the frequency stability.

Lien

doi:10.1109/ISGTEUROPE62998.2024.10863287