Battery storage systems are an essential component of a solar power plant. However, a weak module within the battery storage system can greatly impact the overall performance of the system.

What is Weak Module Identification?

Weak Module Identification is a feature developed by Prescinto for battery storage systems. It uses a proprietary algorithm to analyze the charging and discharging characteristics of the battery system to identify any anomalies in the behavior of individual modules. These modules are then classified into three categories: good, average, and weak.

• Good modules are those that perform consistently and meet the specified voltage and temperature thresholds. 
• Average modules may have some slight variations in performance but are still considered functional. 
• Weak modules have significant variations in performance and do not meet the specified voltage and temperature thresholds, indicating they may need to be replaced or repaired.

How does Weak Module Identification Work?

The algorithm works by drawing a correlation between individual modules within a block over a period of 7 or more cycles. It looks for any signs of abnormal behavior in the module’s discharge voltage and temperature. A module in good condition will consistently discharge at the rated voltage, and any deviation from this indicates a problem. Similarly, the temperature of the battery increases during charging and discharging. A temperature profile that exceeds the rated temperature also indicates a problem with the module.

Benefits of Weak Module Identification

• Identifies weak modules: By identifying weak modules, the feature allows for early detection and replacement of these modules, preventing them from impacting the overall performance of the battery storage system.
• Improves system performance: By eliminating weak modules, the performance of the battery storage system is improved, increasing the overall efficiency of the solar power plant.
• Customizable thresholds: The temperature threshold can be set on the Prescinto platform, allowing users to gain insights into the health of individual modules based on their specific needs.

Use Case

A solar power plant in the United States was facing a decline in its battery storage system’s performance. Upon implementing Weak Module Identification, the plant was able to identify and replace several weak modules within the system. This resulted in an improvement in the overall performance of the battery storage system, leading to an increase in energy generation of 1.3%.

Conclusion

Weak Module Identification is a valuable tool for maximizing the performance of a battery storage system. By identifying weak modules and replacing them, the overall efficiency of the solar power plant is improved, leading to increased energy generation and cost savings. With the ability to customize thresholds, the feature is adaptable to the specific needs of the user.