Abstract
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 study 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.
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