BESS Sensor Data Structuring for Fast Battery Anomaly Localization
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Solution Overview
Problem
Current systems face challenges in quickly detecting abnormal battery states in battery energy storage systems (BESS) using communication protocols like Modbus, DNP3.0, and IEC61850, as they struggle to intuitively analyze sensor data for battery current, voltage, and temperature, making it difficult to manage and predict potential risks effectively.
Innovation Solution
An apparatus and method for processing sensor data in BESS that structures data into binary sequences with time stamps, including information on battery bank, rack, module, and cell levels, allowing for rapid detection of abnormal situations by converting integer values into binary formats for intuitive analysis and quick location identification of battery issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If sensor data is collected using traditional communication protocols (Modbus, DNP3.0, IEC61850), then data collection capability is achieved, but the ability to quickly detect and locate abnormal battery states deteriorates
Solution Approach 1:
The patent segments sensor data into structured formats with distinct fields for battery bank, rack, module, and cell information. Each data packet is divided into specific components (e.g., bank ID, rack ID, module ID, cell ID, sensor type, measured value) that can be independently parsed and analyzed, enabling rapid localization of abnormal states without analyzing entire raw data streams.
Solution Approach 2:
The patent transforms raw sensor data into standardized parameters with specific data types (integers, real numbers, characters) and structured formats. By changing the parameter representation from unstructured raw data to structured formatted data with defined fields, the system enables faster detection and analysis of abnormal battery states while maintaining compatibility with existing communication protocols.
2Adaptability or versatility
If semi-structured sensor data (integers, real numbers, characters) is collected, then data collection flexibility is maintained, but intuitive analysis and judgment of ESS infrastructure structure deteriorates
Solution Approach 1:
The patent segments sensor data into clearly defined structured fields representing different levels of the ESS hierarchy (bank, rack, module, cell). Each field is assigned a specific data type and format, making the data intuitive to analyze while preserving the flexibility to collect various sensor types. The structured format naturally reflects the physical infrastructure structure, enabling easy correlation between data and actual system components.
Solution Approach 2:
The patent creates a universal structured data format that can accommodate multiple sensor types (current, voltage, temperature, humidity) and multiple communication protocols (Modbus, DNP3.0, IEC61850) through a single standardized schema. This universal format maintains data collection flexibility while enabling consistent and intuitive analysis across different ESS configurations and protocols.
3Adaptability or versatility
If traditional data collection methods are used, then system compatibility with existing protocols is maintained, but rapid detection and response to battery abnormalities deteriorates
Solution Approach 1:
The patent changes the parameter structure of collected data from protocol-specific raw formats to a unified structured format with standardized fields. This transformation maintains compatibility with existing communication protocols while enabling rapid detection and response to battery abnormalities through consistent data organization that can be quickly parsed and analyzed across different protocol implementations.
Solution Approach 2:
The patent introduces a structured data format as an intermediary layer between the communication protocols and the analysis system. This intermediary structure translates data from various protocols (Modbus, DNP3.0, IEC61850) into a unified format that preserves protocol compatibility while enabling fast and consistent detection and response to battery issues through standardized data organization.
Data Source
AI summary
The present invention relates to a technique for processing sensor data in a battery energy storage system (BESS). The present invention collects sensing data of battery cells through a BMS and transmits it in a Modbus TCP manner, wherein a frame of the Modbus communication protocol includes a function code and data, and the present invention also comprises a Modbus server, wherein the function code includes information of a battery cell having a minimum or maximum sensing value and location information in a rack of batteries; and a Modbus client, which is connected to the Modbus server by the Modbus communication protocol and receives the sensing data.