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Renewable Energy & Climate AI Strategy: opportunities, use cases & the operating model
AI turns weather uncertainty into bankable output: generation forecasting, PPA and market optimisation, and storage dispatch determine whether renewable assets clear the grid profitably.
Where AI creates value
Generation forecasting — Wind and solar output prediction by asset
Storage dispatch — Battery arbitrage and firming against price signals
Asset performance — Turbine and panel degradation and fault detection
PPA and market optimisation — Bidding and hedging across energy markets
Grid integration — Curtailment and congestion-aware scheduling
Siting and development — Resource assessment for new project pipelines
Top AI use cases
- Short-term solar and wind forecasting to reduce imbalance penalties
- Battery storage dispatch optimisation against day-ahead and intraday prices
- Drone and vision inspection of panels and turbine blades for faults
- PPA structuring and merchant bidding informed by price forecasts
- Curtailment prediction and congestion-aware generation scheduling
What has to change (operating model)
- Forecast accuracy embedded into PPA terms and market settlement obligations
- Grid-code compliance for AI-driven inverter and dispatch behaviour
- Merchant risk governance as assets shift from subsidised to market exposure
- Data-sharing standards with grid operators for forecasting and balancing
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