Increase gas generation plant net capacity using Reliability Performance Monitoring center

Industry: Utilities - Power Generation

Use Case: Gas Turbines

The increase in worldwide use of relatively clean-burning natural gas has restructured global gas markets. For existing providers in the natural gas services business, this has meant operating in an increasingly competitive - and regulated - market. As a consequence, this international utility services company revenues shrank, leading them to consider employing the latest digital technologies to better utilize production data. In doing so, they hoped to improve their competitiveness - and increase profitability, improve compliance with PPAs, reduce their exposure to the spot market, and recognize new revenues through excess energy sales.

Their first digitization project was targeted at its Reliability Performance Monitoring (RPM) center that monitors its fleet of combined-cycle natural gas turbines totaling over 4 GW of capacity. The center wanted to leverage OSIsoft PI Asset Frameworks (AFs), time-series, and transactional maintenance records from SAP to increase net capacity by maximizing turbine utilization. This required improving turbine reliability by using more effective maintenance strategies to reduce unscheduled forced outages.


The existing RPM Center was established 5 years earlier as a comprehensive asset management platform for 4 GW of operating capacity across their 8 sites. Staffed by a small, dedicated team, their focus was in two areas: 1. Condition Based Monitoring (CBM) to improve turbine reliability, reduce operating & maintenance (O&M) costs, and increase Asset Utilization, and 2. Performance Monitoring to increase production while reducing fuel consumption. Much of the center’s infrastructure was built around legacy applications housing inflexible dashboards that were difficult to customize and adapt to reflect new data sources, slowing their decision making. Coupled with the desire to take advantage of the latest technologies, a new, digital approach was needed.

The team chose OSIsoft PI System as the core of the new system, providing a standardized, single source of truth to store plant information, including DCS and historian data, predictive maintenance results, and day ahead market analytics. An Asset Framework (AF) was built to support analysis using PI ProcessBook - displaying important variables using trends and XY plots.

Building the AF however, took considerable time. Each site engineer needed to assemble maintenance data from SAP with over 10k tags/plant from OSIsoft PI (measuring pump vibration and temperature). Using spreadsheets proved ineffective as it not only introduced errors but was slow, impacting their ability to monitor turbine efficiency. And because new data was manually assembled within spreadsheets, KPIs that tracked excess energy were built site-by-site leveraging those same spreadsheets to display scheduled and unscheduled availability. This made comparing KPIs for like-units between sites difficult - which in turn - slowed access to turbine performance data, and impacting contractual production vs potential capacity decision making.

I want to know where I have bad data before performing analysis as we waste so much time on work we cannot use. Reliability Manager, RPM Center

Maintenance also suffered as crews did not have enough time - nor insight - to perform corrective maintenance tasks efficiently. An investigation by the monitoring center’s data analyst also showed that data quality was an issue - especially with null and flat-lined values. This resulted in day ahead market analytics incorrectly forecasting demand leading to increased spot trading. Laborious data cleansing tasks by the PI admin and data managers to address the quality issue further impacted the team's ability to respond quickly.


With increasing pressure to reduce the spot trading volatility, and the inability to incorporate maintenance data to improve turbine reliability, the monitoring team was introduced to Element by OSIsoft to address their continued data challenges. Element AssetHub was chosen and hosted on Element’s Azure tenant. By connecting to OSIsoft PI server data archives, and contextualizing maintenance records from SAP, AssetHub would create Asset Twins of the gas plant and turbines. Data could then be constructed as hierarchies and shared as OSIsoft PI AFs with PI ProcessBook users to support new dashboards and KPIs.


With AssetHub, data is shared as AFs that drive real-time monitoring dashboards and KPIs within PI ProcessBook.

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In addition, the team experienced:

Increased asset utilization through prioritized maintenance

  • Operators and the maintenance team have a ‘second set of eyes’ as historical maintenance records are contextualized alongside time-series data across all sites using AFs. Dashboards now provide earlier warning of equipment issues, helping to prioritize work and organizing resources and maintenance/crews in a timely fashion, increasing uptime and asset utilization.

4x improved efficiency building AFs with reduced O&M costs

  • KPIs roll-up new data automatically and span multiple sites. This removes the burdensome hand-coding of individual site spreadsheets and provides a way for engineers to compare like-unit performance to resolve issues consistently across sites. AssetHub builds - and automatically updates - AFs to reflect changes in production data, allowing engineers to focus on improvement activities without additional resources, increasing their efficiency 4x, and reducing costs.

Higher production and lower risk

  • AssetHub lowers risks and unlocks higher production by increasing compliance with PPAs, reducing exposure to spot markets, and materializing excess energy sales. Data is now trusted as Data Quality reports identify issues before analysis, reducing the risk of inaccurate predictions and ineffective maintenance tasks, improving asset lifecycle management.

AssetHub improved the efficiency of building AFs by 4x, reducing our O&M costs. Overall data quality also improved, minimizing the risk of incorrect day-ahead analysis. By helping to improve our maintenance prioritization, we increased turbine uptime and revenues. Service Director, RPM Center

A future project will leverage AssetHub to expand the reach of the RPM Center. By utilizing the teams new digital tooling and expertise, the customer goals are to add new revenue streams by servicing external customers in adjacent markets.