Optimize decisions, reduce computing requirements and unburden IT with the highest-quality, AI-embedded short- and very-short-term energy forecasts – delivered as a service

Screenshot of SAS Energy Forecasting cloud accurate robust energy forecasts with highlights

SAS Energy Forecasting Cloud

From generation to distribution, get repeatable, traceable and defensible energy forecasts in the cloud. Scale up and down depending on the requirements of your business.

Key features

Automation, scalability, statistical sophistication and transparency for operating more efficiently and effectively at all levels of decision making.

As a service

Delivers the quality energy forecasts you’ve come to expect from SAS Energy Forecasting without having to maintain software in your facilities. Lets you scale up and down as your business demands.

Load forecasting

Automates and streamlines data ingestion for very-short-term and short-term forecasting, including these models: GLM, ARIMA, NN, UCM, ESM.

Renewables forecasting

Provides an automated, scalable solution for traditional load forecasting and extends the capabilities to effectively model renewable generation resources, such as solar and wind, with advanced machine learning and deep learning algorithms – ultimately producing a net load forecast that supports the needs of expanding diverse energy grids.

Advanced forecasting algorithms

Enables hourly and sub-hourly forecasting based on trusted data and advanced forecasting algorithms. Ensures reliable data with data quality capabilities.

High-performance load forecasting

Enables utilities to operate more efficiently by maximizing value from existing planning resources and improving forecast performance.

Single administration & reporting interface

Provides a visual interface for viewing forecasting results from the forecast workbench. Autocharting capabilities mean no coding is required.

Flexibility & scalability

Automated champion model selection and forecasting are available as a service. The completely redesigned architecture is compact, cloud native and fast.

Improved load forecasting performance & operations planning capabilities

Improves forecasting across all locations and levels of aggregation with repeatable, scalable and traceable results.

Better trading & contract purchase decisions

Lets modelers incorporate quantifiable variability and confidence limits when making operational and financial decisions through statistical and visual indications of the likely range of forecasted outcomes.

Maximum ROI from smart meters & advanced metering infrastructure using all data

Makes better predictions about energy demand possible with accurate predictive models based on data from more sources, including smart meters and IoT-connected devices.

Ability to do more with existing planning & forecasting resources

Eliminates the need to train forecasters on multiple software tools via a common forecasting methodology and data integration processes across forecasting horizons.

Get to know SAS Energy Forecasting Cloud

Recommended resources

Executive Summary

How AI Is Powering Accurate, Scalable Load and Generation Forecasting


How AI Is Powering Accurate, Scalable Load and Generation Forecasting

Solution Brief

Optimize decisions, unburden IT with energy forecasts as a service

White Paper

How does forecasting enhance smart grid benefits?

White Paper

When One Size No Longer Fits All – Electric Load Forecasting With a Geographic Hierarchy