Breakdowns happen to mechanical and electrical equipment – including Duke Energy power plants. Imagine the benefits if the equipment could tell us when a breakdown is about to occur.
Duke Energy has an effort underway to increase the use of predictive maintenance using various sensor devices, which is moving the company in the right direction.
Right now, more than 30,000 sensors are in place on critical company machinery at several coal and gas-fired power plants. Among other things, a breakdown at these plants could mean less efficient plants would be brought online to take their place. A negative both financially and environmentally.
Predictive maintenance examines data gathered from sensors on large pieces of equipment – like transformers at a power plant. Company experts can sort through the data to find irregularities that suggest a breakdown is likely.
From there, company technicians can apply analytical tools or physically examine the equipment to gather additional data to see if any action is needed.
An example at the Sutton Power Plant in North Carolina illustrates how the process works:
Data gathered by the sensors indicated a breakdown might occur at a main transformer at the plant. An in-person inspection confirmed the finding.
But there was one problem: The weather was extremely cold during that time, and the plant was needed to meet the critically high demand for electricity.
In the end, the transformer was closely monitored for a short time until the extreme cold subsided and the transformer was fixed before any breakdown occurred.
Duke Energy’s team has dozens of such examples where data gathered from sensors helped solve a potential problem.
In the future, Duke Energy will continue to use new technologies to maintain reliability at its power plants – making sure the cleanest and most cost-effective plants are running to meet the needs of its customers.