SAS Energy Forecasting
SAS Energy Forecasting: A focused utility forecasting suite for hourly, hierarchical load planning and scenarios. Ranked #5 of 63 in Energy Analytics Software by our editors (8.6/10); pricing: Pricing on request; best for utilities prioritizing load forecasting.
At a glance
- Editor score8.6 / 10
- PricingPricing on request
- Best forUtilities prioritizing load forecasting
- Generation analyticsNo
- Facts checked29 Sep 2026
Where it wins
- Supports hourly forecasts across short- and long-term planning horizons.
- Combines smart-meter data, auditable lineage and data-quality capabilities.
- Tracks forecast accuracy and supports scenario planning and manual overrides.
Where it doesn't
- Focused on load forecasting rather than generation or predictive asset analytics.
- Pricing is provided by request rather than as a published list price.
- Enterprise fit may be excessive for organizations seeking a narrower-scale tool.
Our verdict on SAS Energy Forecasting
SAS Energy Forecasting helps utilities create and manage short- and long-term load forecasts for planning and operational decisions. It is aimed at enterprise utility teams that need hourly, hierarchical forecasting from smart-meter readings and other large datasets. Forecast generation can be automated, configured or handled manually, with overrides and locking available when teams need to control a forecast. The product is a focused choice for load forecasting rather than a broad energy analytics suite spanning generation and asset analytics.
Its strongest functional thread is the connection between forecast production and governance. Integrated data management includes auditable lineage and data-quality capabilities, while model-accuracy tracking supports monitoring performance and updating models. What-if analysis and scenario planning help teams examine alternative conditions, and a reporting interface supports web and mobile sharing. Buyers should consider how these workflows fit their planning process: the published capabilities emphasize consumption, grid and market analytics, but do not cover generation or predictive asset analytics.
Deployment is available in cloud and self-hosted forms, with hybrid deployment also specified. Listed integration options include data warehouses, ERP systems, GIS, CIS and SAS Analytics for IoT. SAS identifies the latter as enabling advanced AI and machine learning capabilities. Pricing is by request, and the product page offers pricing and demo requests; support channels include community, ticket and documentation. Utilities seeking load forecasting with lineage, scenario work and forecast-accuracy tracking should shortlist it. Organizations primarily seeking asset or generation analytics, or a publicly priced offering, should compare alternatives.
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SAS Energy Forecasting pricing
SAS Energy Forecasting fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Not verified |
| Generation analytics | No |
| Grid analytics | Yes |
| Consumption analytics | Yes |
| Predictive asset analytics | No |
| Energy-market analytics | Yes |
| Deployment options | Hybrid |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Support | Community, Tickets, Docs |
| Built for | Enterprise (editorial estimate) |
| Integrations | 5 integrations: Data warehouses, ERP systems, GIS, CIS, SAS Analytics for IoT |
| Pricing | Pricing on request |
| Website | sas.com |
| Facts checked | 29 Sep 2026 |
SAS Energy Forecasting integrations
SAS Energy Forecasting lists 5 integrations on its own site.
- Data warehouses
- ERP systems
- GIS
- CIS
- SAS Analytics for IoT
Alternatives to SAS Energy Forecasting
- AVEVA Apollo Energy AnalyticsCloud monitoring and maintenance workflows for solar, wind, and battery portfolios.9.3
- Vestas ScipherA cloud platform for portfolio-wide wind and solar monitoring, operations, and forecasting.9.1
- Clir Renewables Intelligence PlatformPortfolio analytics for renewable owners tracking performance, losses and risk.8.8
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SAS Energy Forecasting vs the competition
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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