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Predictive Analytics to Address Condenser Degradation in a 1300 MW Coal Plant
BCT enabled predictive condenser monitoring and integrated maintenance systems to improve plant efficiency and reliability.
Client
- Client
Challenge- Solution
- Impact
Client
A leading U.S.-based power generation and transmission company operating a 1300 MW coal-fired supercritical boiler unit. The client is committed to reliable, efficient electricity production while maintaining strict operational safety and regulatory compliance.
Challenge
Ensuring uninterrupted power generation and optimal plant performance was critical for the client. However,
operational inefficiencies in the condenser system created risks that could lead to costly downtime and reduced
efficiency. These challenges not only impacted reliability but also increased operational complexity and
maintenance overheads.
The client’s condenser system was causing operational inefficiencies and risk of unplanned downtime:
1
High condenser back pressure leading to turbine trips
2
Heat rate losses reducing plant efficiency
3
Manual monitoring and diagnosis via Aspen Historian, leading to slower issue identification
4
Maintenance system (EAM Maximo) not integrated with operations, causing siloed decision-making
Solution
To overcome the operational challenges and reduce the risk of unplanned downtime, BCT designed and implemented a
predictive, integrated solution focused on monitoring condenser health, analyzing performance, and driving
data-driven maintenance decisions. By unifying operational and maintenance data, the solution provided visibility,
predictive intelligence, and actionable insights to boost plant reliability and efficiency.
1
Enabling Problem Identification and Root Cause Analysis – Continuous monitoring was deployed to detect condenser performance issues instantly, allowing operators to quickly identify root causes and take corrective action before problems escalated.
2
Predicting Condenser Parameters and Failure Patterns – Advanced predictive analytics were introduced to forecast potential condenser failures, enabling maintenance teams to proactively address risks before they disrupted plant operations.
3
Developing a Heat Rate Degradation Advisor and Intelligent Alarm Analysis – The solution incorporated a Heat Rate Degradation Advisor to evaluate the impact of condenser performance on energy output, while intelligent alarm analysis prioritized critical issues to reduce response times and improve efficiency.
4
Integrating Multiple Systems for Unified Insights – Data from Maximo, Aspentech OIS, and other legacy systems was consolidated into a single view, eliminating departmental silos and ensuring faster, well-informed decision-making.
5
Creating a Single Login Interface with Predictive Analytics – A centralized platform provided operators and maintenance teams with easy access to all critical data, enhanced by predictive insights that supported proactive maintenance planning and optimized performance seamlessly.
Impact
The predictive and integrated approach delivered significant improvements in operational efficiency, reliability,
and cost optimization. By combining monitoring with predictive intelligence, the solution empowered the client to
move from reactive maintenance to proactive performance management, ensuring sustainable plant operations and
reducing business risk.
1
Unified Operations and Maintenance Data – Consolidated data provided operators and maintenance teams with a single source of truth, enabling faster, more accurate, and well-coordinated decisions across departments.
2
Proactive Failure Prediction – Potential condenser failures were forecasted well in advance, minimizing turbine trips and unplanned downtime while ensuring uninterrupted operational continuity.
3
Improved Heat Rate Analysis – The solution enabled detailed analysis of heat rate performance before and after maintenance actions, helping optimize energy efficiency and reduce operational losses.
4
Enhanced Operational Reliability – Predictive analytics and integrated monitoring reduced unexpected performance issues, making plant operations more consistent, reliable, and resilient.
5
Cost and Resource Optimization – Early detection of issues lowered maintenance costs and prevented resource-intensive repairs, allowing teams to allocate time and effort more efficiently and improve overall productivity.
By integrating predictive analytics with operational and maintenance systems, BCT empowered the client to proactively manage condenser degradation, reduce turbine trip risks, and optimize plant heat rate performance. The solution delivered insights, smarter decision-making, and measurable improvements in operational efficiency.
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