Mitigation of grid parameter uncertainties for the steady-state operation of a model-based voltage controller in distribution systems

Abstract

This paper deals with the impact of line impedances uncertainties on model-based voltage controllers for distribution networks in the context of secondary to tertiary control levels (i.e., 30 min control horizon). The study proposes two methodologies: (i) centralized and (ii) distributed approaches, to estimate grid impedances by relying on static historical measurement data and adjust the parameters of a model-based voltage controller. Furthermore, an online impedance tuning scheme is proposed to successively fine-tune the impedance estimation over successive control periods (along several days). The simulations results highlight the preciseness of the proposed methodologies, with both centralized and distributed able to estimate the grid impedances within an acceptable accuracy (between 4% and 7% of error). Moreover, the proposed tuning algorithm shows to be very effective, where the estimation error can be lowered under 1%. Finally, robustness studies are performed to test the proposed methodologies in the presence of measurement noises. Through this study, the robustness of the proposed tuning scheme can be validated, in which the algorithm is able to correct massive impedance errors after three months of tuning rounds only.