4 papers
A Data-driven Dynamic Rating Forecast Method and Application for Power Transformer Long-term Planning
Ming Dong
This paper presents a data-driven method for producing annual continuous dynamic rating of power transformers to serve the long-term planning purpose. Historically, research works…
Multi-year Long-term Load Forecast for Area Distribution Feeders based on Selective Sequence Learning
Ming Dong, Jian Shi, QingXin Shi
Long-term load forecast (LTLF) for area distribution feeders is one of the most critical tasks frequently performed in electric distribution utility companies. For a specific plann…
Combining Unsupervised and Supervised Learning for Asset Class Failure Prediction in Power Systems
Ming Dong
In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical or mechanical characteristics. Predicting failures for diffe…
A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction
Ming Dong, L. S. Grumbach
Distribution feeder long-term load forecast (LTLF) is a critical task many electric utility companies perform on an annual basis. The goal of this task is to forecast the annual lo…