Stop chasing alarms.
Start capturing yield.
ClearSpot’s Solar O&M Mesh deploys specialized AI agents across monitoring, diagnostics and work orders — turning noisy data into prioritized actions, with quantified savings per MW for a 30 MW portfolio.
O&M teams know where they lost energy.
They rarely know how much per MW.
Most portfolios run on monthly PR reports, SCADA alarms and spreadsheets. Underperformance is found weeks later, root causes stay vague, and the financial impact per MW is almost never quantified in time to act.
PR achieved vs target — with hidden losses
Sites can hit contractual PR while still leaving significant MWh on the table through morning underperformance, unstable strings and inverter shutdowns that are statistically “tolerable” but financially meaningful.
Typical annualized loss per 1MW equivalent
Expected vs actual analysis over longer periods often reveals tens of MWh of lost production per 1MW block — translating into several thousand dollars in missed revenue without any “critical” alarm.
Degraded, but buried in the fleet average
Critical and degraded strings often compensate each other at fleet level. Portfolio reports look stable while micro‑cracks, hotspots and unstable output quietly erode future PR and availability.
Designed around a 30 MW
utility‑scale solar portfolio.
The Solar O&M Mesh is built for teams who already have SCADA, CMMS and drones — but lack the analytical capacity to turn raw data into quantified actions at the pace their portfolio grows.
On‑site O&M Provider
You own PR and availability SLAs for a cluster of utility‑scale assets. Every truck roll must be justified, but most investigations still start from raw SCADA charts.
Asset Owner / IPP
You manage around 30 MW of solar generation through third‑party O&M. You see monthly PR and revenue reports but not the full picture of avoidable losses and where to push your partners.
Portfolio Performance Team
You support a growing fleet and need to standardize how losses are measured. Engineers spend time on one‑off questions instead of running systematic, portfolio‑wide analysis.
6 AI agents for O&M.
One view of savings per MW.
Each agent owns part of the O&M lifecycle. Together they monitor, explain and quantify performance — down to specific strings, hours and components — with savings expressed in kWh and dollars per MW.
Performance Intelligence Agent
Continuously computes PR, availability and utilization across all assets, normalised for irradiance and temperature. Detects declining trends before they are visible in monthly reports.
Expected vs Actual Agent
Uses irradiance‑based benchmarks to compute expected energy, then compares to actual production to quantify shortfall in kWh, dollars and per‑MW intensity.
Root Cause & Degradation Agent
Correlates underperformance with inverter logs, string data and weather to classify losses: soiling, thermal, shading, inverter faults, clipping or structural degradation.
Soiling & Cleaning Agent
Estimates soiling losses by comparing clean reference behaviour with current performance and weather history, then proposes cleaning windows and quantifies recovery per MW.
Thermal Hotspot Agent
Ingests drone IR imagery and SCADA to detect thermal anomalies, rank them by risk and revenue impact, and propose inspection or replacement actions.
Work Order & Dispatch Agent
Transforms analysis into prioritized work orders, grouped by site and skill set. For each action, it attaches quantified loss avoided, so field teams know where to go first.
How the O&M Mesh translates
into savings on a 30 MW portfolio.
Based on typical utility‑scale portfolios around 30 MW, Solar O&M Mesh usually recovers 3–5% PR and saves several thousand dollars per MW per year in avoidable labor and energy losses.
| Category | Without O&M Mesh | With Solar O&M Mesh | Value per MW / year |
|---|---|---|---|
| PR shortfall | Unseen 2–4% below weather‑normalised best | 3–5% PR uplift through quantified loss targeting | +30–50 MWh / MW · $3k–$5k |
| Root‑cause analysis | Ad‑hoc, hours per issue | Automated, with cause & impact per incident | 20–40% engineer time freed |
| Soiling & cleaning | Fixed calendar or reactive cleaning | Cleaning triggered by $ loss per MW | 1–2% PR recovered |
| Thermal & string defects | Survey findings not tied to revenue | Hotspots ranked by kWh & $ at risk | $500–$1,000 per MW |
| Work order prioritisation | First‑in, first‑out, no value ranking | Queue sorted by loss avoided per hour spent | 15–30% labor cost saving |
| Total impact at 30 MW | Losses absorbed as “normal variability” | Energy and labor savings made explicit | $90k–$180k / year |
From raw SCADA data to
quantified savings at 30 MW.
The mesh layers on top of your existing stack, ingests telemetry and historical data, and starts scoring every loss event in kWh and dollars — so your team focuses only on the highest‑value actions.
Connect data sources
SCADA, weather, tariff and historical performance data are connected. Past expected vs actual behaviour is used to calibrate baselines for each asset.
Agents monitor & explain
Agents track PR, expected vs actual, string health, soiling and thermal anomalies, assigning a root cause and confidence to each loss pattern.
Losses quantified by MW
For every finding, the mesh computes kWh lost, dollar impact based on tariffs, and intensity per MW — so you see which sites matter most.
Actions prioritized
The Work Order Agent builds a queue sorted by loss avoided per hour of work, enabling field teams to maximize recovered revenue with minimal effort.
Built to sit on top of
your existing O&M stack.
Solar O&M Mesh doesn’t replace your SCADA, CMMS or BI tools. It plugs into them, adds an agentic analysis layer, and pushes insights wherever your team already works.