Peaker Plant Start Reliability: Fixing Failed Starts with AI

Why Failed Starts Matter on a Peaker

A peaker is paid to be there when called.

A baseload unit starts a few times a year. A peaking unit may start many times a week, often from cold, and is expected to reach load in a set time. Long idle spells between runs give small faults time to build where nobody sees them. Each start is a test of the starting system, ignition, fuel supply and controls. When a start fails, the operator usually resets and tries again, and the event is noted in a shift log. Weeks later, nobody can say whether the last four failures had one cause or four. The same weak part fails again on the next cold morning. Our peaker specialists can review how your failed starts are recorded today.

How Starting Reliability Is Measured

Successful starts divided by attempted starts.

In North America, NERC's Generating Availability Data System (GADS) defines starting reliability as actual unit starts divided by attempted unit starts, times 100 percent. GADS bases its equations on IEEE Standard 762. The gap between attempted and actual starts is the count of startup failure events. The measure is only as good as the counting. If a retry after a failed start is not logged as a new attempt, the failure disappears from the number. The worked example below is illustrative. Check how your plant counts attempts in a short session.

Illustrative figures. Follow the current GADS Data Reporting Instructions for formal reporting.

Where in the Start Sequence Starts Fail

Knowing the failed step narrows the cause fast.

A gas turbine start runs through a fixed sequence set by the OEM and the control system. The details differ by unit, but most follow a similar path: start permissives, cranking and purge, ignition, fuel admission and acceleration, then synchronizing to the grid. Each step has its own common causes of failure. Recording the step where a start stopped is the single most useful piece of data for finding the cause. Talk through your sequence with our controls team.

General examples. Your OEM manuals and control logic set the real steps and limits.

Start Sequence Data for Every Attempt

Save the start while it happens, not from memory afterwards.

Most of the data needed to explain a failed start already exists in the control system and historian. The problem is that nobody pulls it together per attempt. Start analytics saves a record for every start command: the time of each step, the key signals during that step and where the sequence stopped. Operators add a short note by voice if they saw something the signals did not. Over a season, these records become the evidence for each cause. Records are kept per unit, so a pattern on one machine is not hidden by good results on another. Map your signals in a working session.

Grouping Failed Starts by Cause

A rate by unit says where. A cause count says what to fix.

Once each failed start has a step and a cause, patterns appear that a single success rate hides. The AI compares the signals from each failed attempt with past failures and suggests a likely cause. A technician confirms or changes it after checking the equipment. The illustrative quarter below matches the totals in the box above: six failed starts across three units, with igniters behind half of them. The unit with the lowest rate has two separate causes, so one fix will not be enough. Across the fleet, igniter work would address more failures than any other single change. Review your own failure history with our reliability team.

Illustrative figures, rounded to one decimal place.

Turning Repeat Issues into PM Tasks

A cause that repeats needs a task, not another reset.

When the same cause shows up more than once, the agent proposes a preventive task: what to check, how often and on which units. A maintenance planner reviews the proposal and decides whether it goes into the PM program. Tasks are timed around dispatch, so checks happen in standby windows rather than when the unit is needed. After the task is in place, the agent watches whether that cause stops recurring. If it keeps returning, the task itself is reviewed rather than simply repeated. Plan your first tasks in a short session.

Tracking Start Success by Unit

One number per unit, with the causes behind it.

Starting reliability is tracked by unit and by month, next to the causes that pulled it down. Plant managers see which units need attention before the peak season. Dispatch and trading teams get an honest view of which units are most likely to answer the first call. Trends over several seasons show whether PM changes are working, and a unit whose rate falls after a repair is flagged so the work can be checked. Ask our team how the reports are set up for your plant.

Peaker Start Reliability Checklist

Eight checks before the next peak season.

Use this checklist for one peaking site first. Tick items already in place. Get help with any gaps from our setup team.

Start Reliability Mistakes to Avoid

A good start rate built on poor counting helps nobody.

These are common patterns that keep failed starts coming back. A short start data review can find them.

How iFactory Runs Peaker Start Reliability Analytics

Start Analytics and an AI agent, on your own network.

iFactory's Start Analytics saves start sequence data per attempt, classifies failed steps by cause, turns repeat issues into PM tasks and tracks start success rate by unit. It runs on an on-prem AI server inside your plant.

Cause confirmation, PM changes and dispatch decisions remain with your team. Figures on this page are worked examples.

Turnkey AI: Delivered, Connected and Live in 6–12 Weeks

You do not build this. It arrives ready.

iFactory ships as a pre-configured NVIDIA AI server with the software pre-loaded, racked and ready. Rack it, plug in power and Ethernet, and the AI is live on your network. Our team handles cabling, network setup, PLC, SCADA, DCS and CMMS integration, historian and start sequence signal mapping, operator training and 24×7 remote monitoring. Data stays on your network. For a scope matched to your plant, request a turnkey quote.

Frequently Asked Questions