Improved Peak Load Estimation from Single and Multiple Consumer Categories

Paper i 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)