Dynamic Load Rating for Electric Power Asset Health
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Solution Overview
Problem
Current power systems face challenges in predicting the instantaneous ratings, health, and remaining life of electric power assets, leading to costly outages and inefficient maintenance due to fixed load ratings and inspection intervals, which do not account for asset health or varying failure modes.
Innovation Solution
A method involving sensors to measure temperature, current, and voltage, using basis functions to determine dynamic load ratings by isolating temperature changes caused by specific heating processes, allowing for real-time adjustment of load parameters and health trending of electric assets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed load ratings and fixed inspection intervals are used, then operational simplicity is maintained, but asset failure risk increases and maintenance efficiency decreases
Solution Approach 1:
The patent implements dynamic load ratings that automatically adjust based on real-time asset health conditions. The system transitions from static fixed ratings to dynamic ratings that change with asset state, using continuous monitoring of temperature, current, and voltage to determine appropriate load limits. This resolves the contradiction by making the system adaptive to actual asset conditions rather than relying on conservative fixed values.
Solution Approach 2:
The system employs continuous feedback loops where sensor data from the asset (temperature, current, voltage) is fed into health assessment models that determine current load ratings. These ratings are continuously updated based on changing asset conditions, creating a closed-loop control system that automatically adjusts operational parameters. This feedback mechanism enables reliable failure prevention without requiring complex manual intervention.
2Productivity
If fixed inspection intervals are used, then maintenance scheduling is simplified, but labor is wasted on unnecessary inspections and replacements
Solution Approach 1:
The system performs preliminary health assessments continuously in the background, analyzing sensor data and trending asset conditions before actual failure occurs. By detecting degradation trends early, the system enables proactive maintenance scheduling that targets only assets needing attention, avoiding both premature replacement and missed failures. This preliminary monitoring action optimizes maintenance resource allocation.
Solution Approach 2:
The asset health monitoring system operates autonomously, continuously self-assessing its own condition through embedded sensors and analysis algorithms. The system automatically determines its own health status, remaining useful life, and maintenance needs without external intervention. This self-service capability eliminates the need for manual fixed-schedule inspections, reducing labor waste while maintaining high maintenance efficiency.
3Power
If nominal load ratings are used without considering asset health, then operational capacity is maximized, but safety margin is reduced when assets are degraded
Solution Approach 1:
The system applies different load rating adjustments to different assets based on their individual health conditions. Each asset receives a customized dynamic rating reflecting its specific degradation state, rather than applying a uniform conservative limit to all assets. This localized approach maintains maximum operational capacity for healthy assets while providing appropriate safety margins for degraded assets, resolving the contradiction between capacity and safety.
Solution Approach 2:
The system dynamically changes the load rating parameter based on asset health conditions. When assets are healthy, ratings approach nominal values for maximum capacity. When degradation is detected, ratings are automatically reduced to maintain safety margins. This continuous parameter adjustment based on measured conditions optimizes both operational capacity and reliability without requiring binary safe/unsafe thresholds.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables more accurate and proactive management of electric assets by dynamically adjusting load ratings, reducing the risk of failures and associated costs, while providing predictive analytics for asset maintenance.
Implementation Method 1
measuring a temperature rise on a conductive path
Implementation Method 2
measuring a current on the conductive path
Implementation Method 3
measuring a voltage on the conductive path
Implementation Method 4
selecting a heating process associated with the load parameter... temperature changes due to a heating process other than the selected heating process
Data Source
AI summary
A method for determining a dynamic rating for a conductive path includes using a sensor to measure a value for a load parameter and selecting a heating process associated with the load parameter. A rated temperature change is changed by removing temperature changes due to a heating process other than the selected heating process to produce an impaired rated temperature change. A thermal load percentage is determined from the impaired rated temperature change. The thermal load percentage and the measured value are then used to determine the dynamic rating for the load parameter. A method also includes measuring a temperature rise, a current, and a voltage on the conductive path multiple times. Using at least two basis functions and the multiple measured temperature rises, currents and voltages, the values for at least two variables are determined. Trends in each variable are determined to determine a condition of electric equipment.