Improved Peak Load Estimation from Single and Multiple Consumer Categories

Paper in proceeding, 2020

Velander’s formula and coincidence factors have traditionally been used to estimate peak load for new connections in the distribution grid. By re-evaluating their underlying assumptions, this paper proposes two improved models for aggregated peak load estimation (PLE). For single-category load aggregation, the proposed coincidence factor model, by incorporating an average correlation coefficient, improves the model fitting by 76%–96% as compared to the standard Rusck model. For multiple-category load aggregation, the proposed joint Gaussian regression model reduces the PLE bias from 3%–34% to 0.2%–3% compared to the traditional approach.
(see the full paper in 4 pages)