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AI agent for plant managers

Solar PV Performance Monitoring Agent

Underperforming equipment found and fixed quickly

Solar PV Performance Monitoring Agent: what goes in, what the agent does and what you get

What it does

Solar sites can lose output quietly through soiling, inverter faults or failed strings. Each day this agent pulls production and irradiance data and calculates the performance ratio for each inverter and string. It compares units with each other and with the expected model. When one underperforms, it first checks whether the cause is a data problem or seasonal shading at that time of year. If the loss is real, it classifies the likely cause, estimates lost energy and revenue, and drafts a maintenance ticket. The engineer approves every ticket before a crew is sent. Problems the agent could not confirm are rechecked the next day. Edge case: snow cover across all inverters on the same day is noted as weather, not a fault, so no ticket is raised.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Daily check 2 USES A TOOL Pull production and irradiance data 3 DOES Calculate performance ratio per unit 4 CHECKS THE RESULT Is underperformance real and not data or weather? If not: mark as data or weather. Back to step 2. 5 DOES Classify causes and estimate losses 6 YOU APPROVE Engineer approves ticket 7 RESULT Maintenance ticket created
Read the steps as a list
  1. Daily check
  2. Pull production and irradiance data
  3. Calculate performance ratio per unit
  4. Is underperformance real and not data or weather?If not: mark as data or weather. Back to step 2.
  5. Classify causes and estimate losses
  6. Engineer approves ticketThe agent waits here for your OK.
  7. Maintenance ticket created

How it decides

It flags units whose performance ratio is below peers by more than the threshold for several days.

  • Compare with peer inverters
  • Ignore site-wide weather events
  • Estimate revenue loss

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Threshold (default 5%)
  • Days before alert
  • Revenue rate
  • Ticket format

What keeps you in control

It always asks you first

  • Dispatching technicians

Hard limits

  • Never changes inverter settings

It stops when

  • Done: tickets created
  • Stop: data feed down

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensOn July 18 inverter 7 at the 2.4 MW Ridge Road site showed a performance ratio of 0.71 while its peers ran at 0.83. The agent first checked the data. A pyranometer gap from 1 to 3 pm made the reading unreliable, so it went back and used satellite irradiance for those hours. The drop held, and string 7-4 read zero current. The engineer approved a ticket with an estimated loss of $36 per day.

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