BESS Rack Current Anomaly Detection for Intermittent Connections
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Solution Overview
Problem
BESS subsystems face issues with intermittent or loose connections in DC-bus or module-to-module connections, leading to electrical arcing, overheating, and thermal events, causing operational disruptions and equipment damage.
Innovation Solution
A data-driven approach is used to detect anomalies in rack current profiles by calculating current deltas and analyzing distribution profiles, with a classifier to predict faulty connections, and generating alerts for corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional connection monitoring methods are used, then system complexity is reduced, but detection precision and reliability of faulty connection identification deteriorate
Solution Approach 1:
The patent replaces traditional mechanical/connection-based monitoring methods with an electrical measurement system. By monitoring current profiles and calculating current deltas across multiple racks, the system detects faulty connections through electrical parameter analysis rather than physical inspection, significantly improving detection precision while maintaining manageable system complexity through software-based analysis.
Solution Approach 2:
The system implements continuous feedback by monitoring current profiles in real-time, calculating current deltas, and comparing them against thresholds. When anomalies are detected, the system provides feedback through alerts and notifications to operators, enabling timely intervention. This closed-loop feedback mechanism enhances detection reliability without requiring complex additional hardware.
2Productivity
If manual inspection methods are used, then equipment cost is reduced, but productivity and response time to faulty connections deteriorate
Solution Approach 1:
The system enables self-service monitoring where the BESS infrastructure automatically detects and reports its own connection faults through current profile analysis. The automated detection mechanism eliminates the need for continuous manual inspection, improving response time to faulty connections while reducing operational costs and preventing revenue loss from undetected issues.
Solution Approach 2:
Manual inspection processes are replaced with automated electrical monitoring systems that continuously analyze current profiles. This substitution dramatically improves productivity by enabling real-time detection of faulty connections, allowing operators to respond immediately and minimize revenue loss from system disruptions.
3Object-affected harmful factors
If connection faults are not detected early, then system operation continuity is maintained, but harmful effects from electrical arcing and overheating increase
Solution Approach 1:
The system performs preliminary detection of connection faults by continuously monitoring current profiles and calculating current deltas before electrical arcing or overheating occurs. By identifying anomalies in the current distribution across racks, the system enables preventive action to be taken, eliminating harmful effects before they can damage equipment or compromise system reliability.
Solution Approach 2:
The continuous feedback mechanism monitors current profiles and immediately detects deviations indicating faulty connections. This real-time feedback allows the system to identify and address connection issues before they progress to dangerous levels of electrical arcing or overheating, thereby preventing harmful effects while maintaining system reliability.
Data Source
AI summary
Systems and methods for detecting intermittent connections in a battery energy storage system (BESS) subsystem are disclosed. For each battery rack in the BESS subsystem, current time series data is received. A current rolling average is determined for each data point of the time series data by averaging current values of timestamps over a specified time interval. A current delta is determined for each data point, where the current delta is a difference between the current rolling average associated with the battery rack under analysis and a mean of the current rolling averages associated with the other battery racks in the BESS subsystem. A distribution profile of the current deltas is analyzed to detect a current anomaly at the respective battery rack. In response to detecting the current anomaly at the battery rack under analysis, an alert indicative of a faulty connection is displayed on a user interface.