Entries for Net Load Forecasting Prize

We combine satellite data with physics-based models and historical data series to produce probabilistic net load forecasts.

The TESLA probabilistic forecast is an extension of the accurate TESLA load forecasting system, which has over 30 years of industry use.

An AI-driven two stage approach of probabilistic net load forecasting through point forecast feature integration.

The load curve is represented by a series of shape functions that can be used for forward predictions. An AI method accelerates the process.

A net load forecasting model combining physics and machine learning algorithm.

Use machine learning methods to generate net load forecast with explanations.

Quantiles of hourly %-net load in a substation will be estimated using ensemble of several deterministic models trained on historical data.

We have been developing a novel sizing algorithm of a SPV plant and a forecasting method for short/long-term assessment-risk analysis.

The tool will predict net load of rural school district buildings that have electrified their fleet.

Load prediction using periodic trend data of past loads and public auxiliary data, fused using various machine learning techniques.