By Elizabeth Ingram, managing editor of PennWell’s Hydro Group
Innovation is alive and well in power generation, as five presentations given during a recent session at POWER-GEN International clearly illustrate.
Session 16B, Smart Analytics to Improve Power Plant Performance, was a testament to the spirit of innovation and the ability of the power generation industry to adapt to both the challenges and opportunities presented by constantly changing technology.
This session was intended to explore how power plants are leveraging plant data and monitoring and diagnostics to enhance unit performance. And the audience received this information and more.
The session kicked off with Jon Pastuszynski with GP Strategies Corp. discussing a generation asset management system, used to “consolidate individual site operational data at the corporate level.” The system can be used to benchmark actual equipment performance against what is expected and offers other features, including virtual plant technology so the owner can run full simulations of various scenarios and advanced pattern recognition to predict changes in temperature, vibration and more.
Harry Winn with Emerson Power and Water Solutions presented a case study of the monitoring system installation at Duke Energy’s Roxboro coal-fired plant. The system collects data from more than 10,000 measuring devices and greater than 450,000 individual distributed control system (DCS) data points. He discussed client tools being the “heart of the system,” which also offers a trending package for analysis.
Next up was Karen Ratcliff with Siemens Energy, who covered some of the specific functionalities her company can offer in the area of reducing performance degradation, particularly using analytics to identify control and performance issues. She said that by 2018, 60% of utilities will have more than half of their IT portfolio in the cloud and 25% of future IT budgets will be for integrating new technology with legacy systems.
Jeff Benoit with Ansaldo Energia discussed the company’s integrated plant support system, which assists utilities with predictive maintenance. Important features of the system include auto tuning independent of the control system and real-time estimation of key operational parameters. Along with a couple of other presenters, he discussed the fact that system data can be accessed via a web portal app.
Finally, Juhan Lee with KOEN (Korea Energy) presented the company’s custom-designed predictive monitoring and diagnostic center. The system has three components to collect data, provide predictive data modeling and monitor the status of the operating system for failure prediction. He said that since the system was implemented about two years ago, 144 abnormal events have been detected, saving the company more than $625,000.
Clearly, innovation exists, and it’s saving utilities time and money.