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Power Forecasting for Renewable Energy

XenonStack · Intelligence & Research

No attestation published

Certification per AWS Marketplace.

Provenance reach3 of 12 layers traced

Evidence tier Source Confirmed · 4 captures on record

User ratingNot rated0 reviews on the listing
Runs onUnknownProfessional service
ProvenanceUnknown33% of the provenance layers this product can disclose
Evidence riskHighSign in to see the basis for this band.

What the publisher says

As described on AWS Marketplace.

Perks:

**Reusable and Easy Deployment:** Our solution is designed to be reusable, so it can be easily deployed on AWS infrastructure and does not require significant modifications when applied to different farms or projects.

Show the rest of the publisher’s description (4 more lines)

**Accurate and Reliable Power Forecasts:** Our solution uses advanced analytics and machine learning to provide accurate power forecasts, which can help you make better decisions and improve operational efficiency.

**Cost-Optimized Solution:** Serverless Architecture in AWS enables our Solution to deliver forecast in minimal cost & efficient resource utilization and eliminating the need for extensive infrastructure investments & management.

**Continuous Improvement and Refresh:** We continuously improve our solution by monitoring the performance of the models using KPIs such as nMAE. If the performance exceeds the acceptable threshold, the models are retrained and refreshed to maintain accuracy.

**Data Security and Compliance:** Our solution complies with AWS security guidelines and protocols to protect and ensure the integrity of your data. We also have compliance support embedded within our system to meet regulatory standards.

Highlights

Highlighted by the publisher on AWS Marketplace.

Accurate Power Forecasting Our solution uses machine learning algorithms and ensemble modeling techniques to provide highly accurate power forecasts by incorporating data from multiple weather sources to ensure reliable and precise forecasting.

Occupational Hazard Reduction It enables users to forecast power to minimize occupational hazards. For instance, during unfavorable weather conditions such as a disaster or severe wind, our forecasting helps to prevent accidents by pausing production and ensuring safety measures are taken.

Cost Regulation and Future Planning With our efficient power forecasting capabilities, users can regulate costs by optimizing power consumption, systematic resource allocation, and planning future energy needs.

Agent build and provenance

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Compliance

Government
  • FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27

Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.

Vendor

External enrichment · as of 2026-08-29

CompanyXenonStack IncAutomated
HQUnited States of AmericaAutomated
IndustryTechnologyAutomated
Websitehttps://www.xenonstack.com/

Sources

Marketplace listingaws.amazon.comSource
App certificationaws.amazon.comSource

Linked repositories

RepositoriesUnknownUnknown

Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.

Pricing
Unknown
Not stated
Delivery
Professional service
Power Forecasting Support: **System Support:** This solution provides robust system support to ensure the smooth operation and reliability of the power forecasting models. We address failures of models through proactive monitoring and troubleshooting mechanisms. Alerts for Model Failures We have set up alerts using AWS SNS (Simple Notification Service), ensuring reliable and scalable communication regarding model failures, to promptly notify the stakeholders in case of model failures. These alerts are triggered whenever an issue is detected within the model. CloudWatch for Log Capture To assist in troubleshooting and root cause analysis of model failures, we have enabled CloudWatch logs. It captures detailed logs of relevant events related to the models valuable for diagnosing any issues occurring during the forecasting process.
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