Predictive Control Unit for Power Generation Maintenance Scheduling
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Solution Overview
Problem
Power generation facilities face challenges in scheduling maintenance to avoid outages during peak power generating seasons, as traditional methods do not effectively synchronize the end-of-life of multiple parts, leading to inefficient operation and increased costs.
Innovation Solution
A predictive control unit that utilizes lifing models and forecasting to simulate the operation of power generating units, generating setpoints to adjust operating conditions, such as firing temperature and fuel splits, to synchronize part life wear and minimize maintenance outages during peak demand periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional scheduled maintenance is performed based on expected wear, then part life management is simplified, but maintenance outages occur during peak power generating seasons causing productivity loss
Solution Approach 1:
The system performs preliminary actions by using the enhancer to simulate future operation and predict part life wear before actual maintenance is needed. This allows operators to proactively schedule maintenance during non-peak periods by anticipating when parts will reach end-of-life, rather than reactively responding to wear after it occurs.
Solution Approach 2:
The system makes the maintenance schedule dynamic by continuously updating predictions based on actual operating conditions and comparing them against simulated scenarios. This allows the maintenance timing to be optimized in real-time, shifting maintenance to non-peak periods while maximizing power generation during favorable economic conditions.
2Productivity
If power generation facilities operate continuously to meet market demand, then productivity is maximized, but part wear accelerates leading to premature failures
Solution Approach 1:
The system implements feedback by continuously monitoring actual part wear from operating facilities and comparing it against simulated wear predictions. This feedback loop allows the system to adjust operating recommendations and maintenance schedules dynamically, balancing continuous operation for productivity with wear management for reliability.
Solution Approach 2:
By simulating future wear patterns before they occur, the system allows operators to take preliminary actions to manage part life, such as adjusting operating parameters or scheduling maintenance before parts fail, thus maintaining reliability while preserving productivity.
3Reliability
If multiple parts are maintained separately according to individual wear schedules, then each part receives timely maintenance, but the number of maintenance outages increases
Solution Approach 1:
The system merges multiple individual maintenance schedules into a single coordinated maintenance event by predicting when multiple parts will reach end-of-life and scheduling their maintenance together during non-peak periods. This combining approach maintains the reliability of each part while significantly reducing the total number of separate outages.
Solution Approach 2:
The system performs preliminary analysis to identify opportunities to synchronize maintenance of multiple parts before the actual maintenance occurs. By predicting wear patterns and identifying overlapping end-of-life timelines, operators can proactively plan consolidated maintenance events that reduce total downtime.
Data Source
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AI summary
A power generation system (10) includes a power generating unit (16), a predictive control unit (12) that includes a memory (28) storing an enhancer (30) configured to simulate operation of the power generating unit (16) based on at least one lifing model (32) indicative of part life of the power generating unit (16) and at least one forecast (20) relating to predicted conditions affecting operation of the power generating unit (16) and a controller (26) configured to generate at least one setpoint indicative of operating conditions for the power generating unit (16) via the enhancer (30), and a regulatory unit (14) coupled to the power generating unit (16), wherein the regulatory unit (14) is configured to receive the at least one setpoint from the controller (26) and adjust operating conditions for the power generating unit (16) based on the at least one setpoint.