Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Solcast is a cloud-based software designed to deliver precise, reliable historical, current, and predictive solar irradiance, weather, and photovoltaic (PV) power data tailored for renewable energy needs, using a versatile REST API along with developer tools. By monitoring real-time satellite cloud coverage and integrating it with sophisticated weather models, it provides solar irradiance predictions that range from five minutes to 14 days ahead with exceptional spatial and temporal accuracy, in addition to offering historical data spanning from 2007 to a week prior for performance assessment. The platform accommodates various PV power forecasting models, including Rooftop PV, Advanced PV, and Premium PV, which evaluate both actual and anticipated output for solar installations of any size. Its API delivers data in user-friendly JSON or CSV formats, making it easy to integrate with energy management software, analytical platforms, or tailored workflows. Additionally, developers can utilize native HTTP clients or software development kits (SDKs) such as Python and C#, complete with code samples, to seamlessly access and implement this data. This comprehensive approach positions Solcast as a crucial resource for optimizing solar energy operations.
Description
TimesFM-3 represents an advanced time series foundation model that excels in highly precise multivariate forecasting with a single forward pass. This model, which consists of 330 million parameters, has undergone pre-training on a vast corpus of real-world and synthetic time series data, totaling over 1 trillion time points, thereby enhancing the effectiveness and zero-shot generalization capabilities seen in previous TimesFM iterations. It is adept at simultaneously predicting numerous coevolving time series and understanding dependencies that bolster accuracy without the need for task-specific fine-tuning. Furthermore, it accommodates multiple forecasting targets, including both point and quantile predictions, and incorporates past covariates that are only available historically, alongside dynamic covariates that pertain to future events such as planned promotions, holidays, or weather changes. Utilizing a decoder-only transformer architecture, TimesFM-3 processes sequential data in segments of 32 time steps, employing alternating causal temporal attention and full variate attention to integrate patterns across both time and interrelated series effectively. As a result, it provides a robust tool for forecasting complex time-dependent phenomena in various applications.
API Access
Has API
API Access
Has API
Integrations
C#
Google Sheets
JSON
Microsoft Excel
PVsyst
Python
System Advisor Model (SAM)
Integrations
C#
Google Sheets
JSON
Microsoft Excel
PVsyst
Python
System Advisor Model (SAM)
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Solcast
Founded
2016
Country
Australia
Website
solcast.com
Vendor Details
Company Name
Founded
1998
Country
United States
Website
research.google/blog/timesfm-3-a-zero-shot-foundation-model-for-multivariate-forecasting/
Product Features
Solar
2D/3D Drawing
Analytics / Reporting
Bill of Materials
CMMS
Estimating
Field Service Management
PV Animation
Permitting
Preventive Maintenance
Proposal Management
Solar Design
Solar Maintenance Management
Solar Monitoring
Solar Project Management
Solar Sales / CRM