@article{34339,
  author = {Roel Dobbe and Werner van Westering and Stephan Liu and Daniel Arnold and Duncan S Callaway and Claire Tomlin},
  title = {Linear Single- and Three-Phase Voltage Forecasting and Bayesian State Estimation With Limited Sensing},
  abstract = {<p><span>Implementing state estimation in low and mediumvoltage power distribution is still challenging given the scale of many networks and the reliance of traditional methods on a large number of measurements. This paper proposes a method to improve voltage predictions in real-time by leveraging a limited set of real-time measurements. The method relies on Bayesian estimation formulated as a linear least squares estimation problem, which resembles the classical weighted least-squares (WLS) approach for scenarios where full network observability is not available. We build on recently developed linear approximations for unbalanced three-phase power flow to construct voltage predictions as a linear mapping of load predictions constructed with Gaussian processes. The estimation step to update the voltage forecasts in real-time is a linear computation allowing fast high-resolution state estimate updates. The uncertainty in forecasts can be determined a priori and smoothed a posteriori, making the method useful for both planning, operation and post-hoc analysis. The method outperforms conventional WLS and is applied to different test feeders and validated on a real test feeder with the utility Alliander in The Netherlands.</span></p>},
  year = {2020},
  journal = {IEEE Transactions on Power Systems},
  volume = {35},
  pages = {1674 - 1683},
  month = {11/2019},
  issn = {0885-8950},
  doi = {10.1109/TPWRS.2019.2955893},
  language = {eng},
}