Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Huaiguang Jiang, Fei Ding, Yingchen Zhang

Research output: NRELPoster


In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.
Original languageAmerican English
StatePublished - 2017

Publication series

NamePresented at the 2017 IEEE Power & Energy Society General Meeting, 16-20 July 2017, Chicago, Illinois

NREL Publication Number

  • NREL/PO-5D00-68861


  • distribution
  • load forecasting
  • reconfiguration
  • short-term


Dive into the research topics of 'Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration'. Together they form a unique fingerprint.

Cite this