AI system
- System
-
ENEA machine-learning heatwave grid-failure forecasting model
- Model
-
Not assessed
- Release
-
Not assessed
- Application developer
-
ENEA with Politecnico di Bari and Università Roma Tre
- Role
-
Not assessed
- Configuration
-
Not assessed
- Inputs and outputs
-
Not assessed
- Autonomy
-
Not assessed
- Workflow
-
Historical grid-failure and temperature data for Italian urban networks. A research consortium of a public agency and two universities.
- Human oversight
-
Not assessed
- Relation to AI
-
The system's existence and purpose come from a registry summary of press reports. No evaluation, deployment or outcome was found, so no AI contribution to any event can be assessed.
- AI contribution
-
Not assessed
Benefits
- Outcome identifiers
-
Not assessed
- Benefit
-
The OECD AI Incidents Monitor records that ENEA, Politecnico di Bari and Università Roma Tre developed and tested an ML system to predict heatwave-induced grid failures (May 2023); no outcome given.
- Category
-
Reduced Risk
- Status
-
Not assessed
- Beneficiary groups
-
Society. Organizations.
- Beneficiaries
-
Not assessed
- Reach
-
Not assessed
- Distribution and access
-
Not assessed
- Duration
-
Not assessed
- Expected?
-
Yes
- Costs and harms
-
Not assessed
Measurement
- Studies
-
Not assessed
- Study design
-
Not assessed
- Measurement
-
Not assessed
- Setting and sample
-
Not assessed
- Measures
-
Not assessed
- Comparison
-
Not assessed
- Results
-
Not assessed
- Additional value from AI
-
Not assessed
- Limitations
-
Not assessed
- Denominators
-
Not assessed
- Materials for replication
-
Not assessed
Money
- Kind of value
-
Not assessed
- Amount
-
Not assessed
- Currency and prices
-
Not assessed
- Period and unit
-
Not assessed
- Realization
-
Not assessed
- Recipients and payers
-
Not assessed
- Gross or net
-
Not assessed
- Included costs
-
Not assessed
- Comparison
-
Not assessed
- Method
-
Not assessed
- Return and payback
-
Not assessed
People and places
- Participants
-
Developer: ENEA with Politecnico di Bari and Università Roma Tre.
- Jurisdictions
-
Benefit:
Italy. Developer: Italy. - Ownership and control
-
Not assessed
- Dependencies
-
Not assessed
- Cross-border connections
-
Not assessed
- Geopolitical implications
-
Not assessed
Follow-up
- Conditions for replication
-
Operational deployment by a distribution operator. Reporting of forecasts against realized failures.
- Replication attempts
-
Not assessed
- Later findings
-
No development after the May 2023 announcement was found; the ENEA release as mirrored names only the RAFAEL project and an IEEE Transactions paper, with no figures.
- Availability
-
Not assessed
- Institutional decision
-
Not assessed
- Grounds
-
Not assessed
- Action and result
-
Not assessed
- Success criterion
-
Not assessed
Evidence
- Source numbers
-
AIBD-0171-source-0001
- Citations
-
Numbered references below.
- Language
-
Not assessed
- Source relationships
-
Independent
- Original evidence
-
Not assessed
- Access and versions
-
Not assessed
- Supported findings
-
Not assessed
- Evidence links
-
Not assessed
- Evidence strength
-
Not assessed
- Missing evidence
-
Not assessed
Grades
- Assessed benefits
-
Society. Organizations.
- Depth
-
Not assessed
- Reasons
-
Society: No avoided blackout or deployment is documented. Organizations: No grid operator use is documented.
- Observed or intended
-
Not assessed
- Rubric
-
Not assessed
- Assessor and date
-
Not assessed
- Alternative assessments
-
Not assessed
- Fill
-
Listed, not verified
Entry details
- Kind
-
Not assessed
- Related entries
-
Not assessed
- Field
-
Energy. Electricity distribution resilience.
- Purpose
-
The system was built to forecast heatwave-related failures on electricity networks so operators can act in advance. The record documents development and testing only.
- Dates
-
Date basis unassessed: 2023 (precision unassessed). Updated: 21 October 2026.
- Stage
-
Not assessed
- Version
-
SHA-256: d2e6e36c5834…
References
- Other identifiers
-
Not assessed
- Category mappings
-
Not assessed
- Brief
-
Not assessed
- Revisions
-
5 revisions. Latest: 21 October 2026.
Sources
-
Registry label Independent author
OECD AI Incidents Monitor, record 2023-05-24-c85b, 'AI System Developed to Prevent Heatwave-Induced Blackouts in Italy'
Researchers from ENEA, Politecnico di Bari, and Università Roma Tre developed and tested an AI-based system using machine learning to predict and prevent electrical grid failures caused by heatwaves.