
Regional Solar Power Forecasting with Deep Learning
Spatiotemporal forecasting of regional photovoltaic production from Meteosat image sequences using a ConvLSTM model trained and evaluated against measured production and a persistence baseline.
Portfolio of completed projects and client solutions

Spatiotemporal forecasting of regional photovoltaic production from Meteosat image sequences using a ConvLSTM model trained and evaluated against measured production and a persistence baseline.

Scientific framework for evaluating solar forecasts beyond average error metrics, using Temporal Distortion Mix and a ramp metric to assess timing errors and rapid irradiance variations.

Controlled simulator of 3D cloud scenes, generating synthetic satellite and ground-camera views to validate voxel-based reconstruction, cloud localization, and shadow prediction for solar forecasting.

Fusion of ground-based sky-camera and geostationary satellite imagery to reconstruct cloud geometry and forecast solar irradiance and cloud shadows from 10 minutes to several hours ahead.

Processing and deconvolution of SAX eddy-current signals to help engineers assess steam-generator support-plate clogging during periodic inspections.

Development and industrialization of engineer-facing software combining signal alignment, DTW, and statistical anomaly detection to prioritize atypical steam-generator inspection signals for expert review.

At the intersection of biodiversity and wind energy, this project analyzes bird behavior around turbines using camera detections and 3D radar trajectories. It examines flight movements, responses to acoustic deterrence, and links with weather and turbine operation.

End-to-end production platform using machine learning for site-specific solar-generation and facility-load forecasts, refreshed every 15 minutes over a three-day horizon and integrated with downstream energy-management workflows.

End-to-end development and modernization of a data platform spanning production ingestion, analytics engineering, quality controls, and reporting for operational, business, and customer-facing use cases.

Reliability analytics for 70,000+ managed EV chargers, reconstructing consistent per-port uptime from operational state, connectivity, asset history, and downtime exclusions for operational and customer-facing reporting.