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AI AnalysisClassification & Focus Areas
"Predictive solar & BESS analytics using physics-informed AI for fault detection and root‑cause analysis — enables proactive maintenance for asset managers and O&M teams."
Domain Affinity
Technology Breakdown
Offerings Products & Services
GAIA
GAIA is an AI-powered operations assistant for solar and storage portfolios, automating performance analysis, issue ticketing, and report generation within a secure, closed cloud environment.
AI-driven Audit
AI-driven Audit delivers one-time diagnostic reports for solar assets, leveraging AI to quantify losses, predict failures, and provide actionable recommendations, with no hardware installation required.
Autopilot
Autopilot is a predictive maintenance platform that uses physics-informed AI to forecast faults and optimize performance in solar PV plants, integrating directly with existing SCADA and CMS systems.
Climate Risk Assessment
Climate Risk Assessment provides long-term solar irradiance and production forecasts using deep learning, achieving over 98% accuracy, for de-risking investment and operational decisions.
Case StudiesReferences & Success Stories
Galp's Journey: AI-Powered Solar Operations & Fault Detection
Galp, managing a 1.5 GW solar portfolio, partnered with SmartHelio to deploy AI-driven predictive maintenance, enabling detection of a central inverter failure 15 days in advance and optimizing cleaning schedules based on real-time soiling data, aiming to reduce maintenance costs by 20% and extend equipment life.
Case Study: Automatically Classify Losses in Solar Plants
By applying physics-based AI pattern recognition, SmartHelio enabled automatic loss classification, achieving 100% fault detection accuracy, saving 8-10 man-hours per week, and boosting energy production by 5-10%, with 31% of losses recoverable and 65% avoidable.
Predictive Analytics for C&I Solar: DayStar Case Study
Daystar Power, part of the Shell group, implemented SmartHelio's Autopilot across its African C&I portfolio, achieving a 10% performance increase, 100% fault detection accuracy within four months, and a 4x reduction in fault resolution time, while cutting onboarding time from two days to one minute.
SmartHelio Supports Verbund's Growth with Predictive Analytics
In partnership with VERBUND, Austria's largest electricity provider, SmartHelio analyzed two solar plants totaling 3.03 MW, identifying 9 fault types and detecting 5% underproduction. Predictive analytics allowed recovery of 80% of losses, with potential savings of €4,000/MW/year.
Case Study: Expected Energy Production, a 1.5GW lesson on SCADA PR
A leading solar company uncovered an 8.7% energy shortfall across its 1.5 GW portfolio using SmartHelio's Autopilot. In one 25 MW plant, performance ratio was boosted from 77.1% to 92%, recovering €8,500/MWp by recalibrating expected energy in real time.