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

• Published in: Electric power systems research Vol. 218; p. 109221
• Main Authors: Putratama, Muhammad Andy, Rigo-Mariani, Rémy, Debusschere, Vincent, Bésanger, Yvon
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2023; Elsevier
• Subjects: Distributed control; Distribution grid; Electric power; Engineering Sciences; Grid parameter; Impedance estimation; Model-based voltage controller; Optimal power flow (OPF); Distributed control; Model-based voltage controller; Optimal power flow (OPF); Grid parameter; Distribution grid; Impedance estimation; distribution grid; optimal power flow (OPF); grid parameter; distributed control; model-based voltage controller
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2023.109221

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. •Mitigation methods for grid parameter uncertainties in a model-based voltage control.•Proposed methods only rely on households’ smart meters data with 30 min time steps.•Robust impedance tuning strategy using voltage drop evaluations over one year.•Proposed methods could be solved in a distributed-manner.