Measurement-Based Robust Voltage Control for Active Distribution Networks Considering Uncertainty in the Estimated Model

An increasing number of distributed energy resources (DERs) have penetrated into distribution networks causing great challenges to energy management. The promising solution is measurement-based control of DERs for mitigating grid issues such as over/under voltages. However, most previous measurement-based voltage control methods assume the accuracy of measurements, with no regard for the possible existence of bad data in real practice. What's more, the uncertainty in the estimated system model may result in wrong control decisions. This paper presents a measurement-based robust voltage control for active distribution networks (ADNs) considering uncertainties in the estimated model of ADNs. Firstly, we leverage the robust recursive least squares (R2LS) regression method to estimate the voltage sensitivity coefficients. Then, the solution of the R2LS regression is embedded in a robust voltage control problem accounting for the bounded uncertainty in the estimated sensitivity coefficients. The proposed method is robust to bad data in measurements, and the bounded uncertainty in the estimated coefficients is also considered in a robust optimization framework, thus ensuring safe and reliable operation of the distribution networks. Numerical tests exhibit promising performance of the proposed method in voltage control.