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Energy Demand Forecasting & Analytics

Active

State & Local

Response Deadline09/04/2026, 09:00:00 PM UTC

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

AI Contract Overview

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The Energy Demand Forecasting and Analytics subcontract is issued by the Florida Administrative Services Procurement Division. The project focuses on the development of data-driven models to analyze historical energy usage within Orange County buildings. These models will be used to predict future demand patterns, identify risks associated with peak loads, and uncover opportunities for demand reduction. The solicitation was posted on August 21, 2026, with a response deadline of September 4, 2026. This opportunity falls under NAICS code 541620, which pertains to environmental consulting services. Interested parties can find further details through the Orange County procurement portal.

General Info

Florida subcontract for data-driven energy demand forecasting and analytics in Orange County.

Agency

Florida → Administrative Svcs., Procurement DivisionView Agency

NAICS

541620 - Environmental Consulting ServicesView NAICS

Place of Performance

FL, USA

Set-Aside

NONE

Documents

This scope was carved out of Y26-07-SS.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Managing and Trading Electric Power Demand

AI Contract Breakdown

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No contract breakdown available.

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Timeline

PostedAug 21

subcontract

Response DeadlineSep 4

Submission deadline

Response Deadline

09/04/2026, 09:00:00 PM UTCin 9 days

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Organization & Contact Information

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AgencyFlorida → Administrative Svcs., Procurement Division

ContactsNo contacts available

OfficeN/A

Organization / Agency

Florida → Administrative Svcs., Procurement Division

View Agency Profile

Office AddressN/A

ContactsNo contact information available

Full Description

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Develop data-driven models to analyze historical energy usage across Orange County buildings, predict future demand patterns, and identify peak load risks and demand reduction opportunities.

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