Energy storage energy management system and method supporting one-key fault diagnosis and one-key debugging

Abstract

This application provides an energy storage management system and method supporting one-click fault diagnosis and one-click debugging. The system includes a data acquisition unit, a one-click fault diagnosis unit, a one-click debugging unit, a human-machine interaction unit, a communication unit, a storage unit, an alarm unit, and a core control unit. The data acquisition unit collects real-time operating parameters, status, and environmental data of the energy storage device and transmits them to the core control unit. After receiving instructions, the one-click fault diagnosis unit performs multi-dimensional fusion analysis based on real-time data, historical data, and a fault knowledge base to determine the fault type, locate the device, and generate a diagnostic report. The one-click debugging unit automatically calls corresponding parameters and processes to complete configuration, collaborative debugging, and functional verification according to the device type, operating scenario, and debugging requirements, and generates a debugging report. The human-machine interaction unit provides an operation interface and status display. This application effectively solves the problem of adaptability to the high-efficiency operation and maintenance requirements of energy storage systems through an integrated diagnosis and debugging mechanism.

Description

Technical Field

[0001] This application relates to the field of energy storage system technology, and in particular to an energy storage management system and method that supports one-click fault diagnosis and one-click commissioning. Background Technology

[0002] As the core control unit of an energy storage system, the energy management system undertakes core functions such as monitoring energy storage equipment, charging and discharging control, energy dispatching, and operation and maintenance management. It directly determines the operational safety, energy efficiency, and economic performance of the energy storage system. Currently, the installed capacity of energy storage systems continues to expand, and the number of diverse and heterogeneous devices integrated within these systems, such as battery modules, energy storage converters, battery management systems, metering equipment, and temperature control equipment, is rapidly increasing. This significantly increases the control complexity of multi-device collaborative operation, placing higher demands on the operation and maintenance capabilities of the energy management system. It urgently needs to adapt to the efficient operation and maintenance requirements of large-scale energy storage scenarios and match the intelligent and intensive development trend of the energy storage industry.

[0003] The industry generally adopts a manual operation and maintenance debugging mode, in which operation and maintenance personnel manually retrieve the operating parameters of each device, check the communication links and control logic segment by segment, and in the debugging phase, for different device types and operating scenarios, the operating parameters are configured one by one and the functional verification is carried out step by step. In some scenarios, a third-party debugging team needs to be introduced to provide support. The entire process relies entirely on the experience of the personnel.

[0004] However, the above solutions have several limitations: Firstly, fault diagnosis relies on manual experience, is cumbersome, and requires high levels of expertise from personnel, making it prone to missed or incorrect diagnoses, and resulting in low efficiency in fault location in complex scenarios. Secondly, the commissioning process lacks unified standards, parameter configuration and verification procedures are greatly affected by differences in personnel operation, leading to unstable commissioning quality. Furthermore, fault diagnosis and commissioning are independent of each other, requiring the entire commissioning process to be repeated after fault repair, adding extra maintenance costs and time. At the same time, existing diagnostic methods rely solely on single parameter threshold judgments, failing to achieve multi-dimensional data fusion analysis and early fault warning, thus failing to meet the requirements for the safe and stable operation of energy storage systems. Summary of the Invention

[0005] This application provides an energy storage management system and method that supports one-click fault diagnosis and one-click debugging, in order to solve the problem that energy storage management systems cannot adapt to the high-efficiency operation and maintenance needs of large-scale energy storage scenarios.

[0006] The first aspect of this application provides an energy storage management system that supports one-click fault diagnosis and one-click debugging, including: The data acquisition unit is used to collect the operating parameters, status data and environmental data of each device in the energy storage system in real time, and transmit the collected data to the core control unit after preprocessing. The one-click fault diagnosis unit is connected to the core control unit and the data acquisition unit. It is used to receive one-click fault diagnosis commands, perform multi-dimensional fusion analysis based on the real-time data collected by the data acquisition unit, the historical data stored in the storage unit, and the fault knowledge base, so as to determine the fault type, locate the faulty device, and generate a fault diagnosis report. The one-click debugging unit is connected to the core control unit and the data acquisition unit. It is used to receive one-click debugging commands and, according to the equipment type, operating scenario and debugging requirements of the energy storage system, call the corresponding debugging parameters and debugging process to complete the parameter configuration, collaborative debugging and functional verification of each device, and generate a debugging report. The human-machine interaction unit is used to provide an operating interface for users, to issue the one-click fault diagnosis command and one-click debugging command, and to display the real-time operating status, fault diagnosis results and debugging progress of the energy storage system. The communication unit is used to enable communication between the energy storage management system and various devices in the energy storage system, the remote management platform, and external terminals. The storage unit is used to store real-time and historical data, fault knowledge base, standard parameter library, fault diagnosis report and debugging report collected by the data acquisition unit; An alarm unit is used to receive fault information transmitted by the one-key fault diagnosis unit and issue an alarm signal of the corresponding level according to the fault level. The core control unit is connected to the one-key fault diagnosis unit and the one-key debugging unit respectively, and is used to coordinate the operation of the data acquisition unit, the one-key fault diagnosis unit, the one-key debugging unit, the human-machine interaction unit, the communication unit, the storage unit and the alarm unit.

[0007] By setting up a one-click fault diagnosis unit, multi-dimensional fusion analysis is performed based on real-time data from the data acquisition unit, historical data from the storage unit, and the fault knowledge base to automatically determine the fault type and locate the faulty device, effectively improving fault troubleshooting efficiency and diagnostic accuracy. At the same time, a one-click debugging unit is set up to automatically call the corresponding debugging parameters and processes according to the equipment type, operating scenario, and debugging requirements to complete parameter configuration, collaborative debugging, and functional verification, reducing debugging complexity and human operation differences. The core control unit coordinates the operation of each unit, enabling fault diagnosis and debugging functions to work together, reducing system downtime, and improving the operation and maintenance efficiency and operational stability of the energy storage system.

[0008] Optionally, the one-key fault diagnosis unit includes: The fault data preprocessing module is used to receive real-time data transmitted by the data acquisition unit, perform noise reduction, filtering and outlier removal on the real-time data, and extract fault feature parameters; the fault knowledge base stores feature parameters, fault causes, handling methods and historical fault cases of various faults in the energy storage system. The fault identification module is used to compare the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault type and fault level. The fault location module is used to locate the faulty device, component, and location based on the fault identification results and the location information of each device and the communication link status collected by the data acquisition unit. The diagnostic report generation module is used to generate a standardized fault diagnosis report based on the fault identification results, fault location results, and processing methods in the fault knowledge base. The fault knowledge base update module is used to update the fault characteristics and handling methods in the fault knowledge base based on the fault handling results and new fault cases.

[0009] By setting up a fault data preprocessing module to perform noise reduction, filtering, and outlier removal on real-time data and extract fault feature parameters, a precise data foundation is provided for subsequent identification. The fault identification module compares the preprocessed fault feature parameters with fault features in a fault knowledge base that stores various fault feature parameters, fault causes, handling methods, and historical fault cases to identify the fault type and level. Combined with the device location information and communication link status collected by the data acquisition unit, the fault identification accuracy and location efficiency are improved. The diagnostic report generation module automatically generates standardized diagnostic reports based on the identification results, location results, and handling methods in the knowledge base, making it easy for maintenance personnel to quickly obtain handling guidance. The fault knowledge base update module updates the fault features and handling methods in the knowledge base based on actual fault handling results and new fault cases, so that the diagnostic capabilities are continuously optimized as operational data accumulates.

[0010] Optionally, the one-click debugging unit includes: The debugging mode selection module has multiple built-in debugging modes, including system initialization debugging, device-specific debugging, collaborative debugging, post-fault repair debugging, and customized debugging. The parameter configuration module stores a standard parameter library for different devices and different operating scenarios, supports custom modification and saving of parameters, and integrates a device integration engine to adapt the debugging parameter configuration of newly added devices according to the differences in local energy scenarios. The debugging execution module is used to send debugging instructions to the core control unit according to the selected debugging mode and parameter configuration, so that the core control unit can work with each energy storage device to complete parameter configuration, functional testing and collaborative verification operations according to the preset debugging process, and collect the operating data of each device in real time during the debugging process to dynamically adjust the debugging parameters. The debugging and verification module is used to perform functional verification on the debugged energy storage system. It verifies whether the operating parameters and collaborative working status of each device meet the preset operating parameter thresholds and collaborative working logic. If the verification fails, it returns to the debugging process and adjusts the parameters until the verification passes. The debugging report generation module is used to generate the debugging report after debugging is completed. The debugging report includes debugging time, debugging mode, debugging parameters, debugging process, verification results and optimization suggestions, and stores the debugging report in the storage unit.

[0011] The debugging mode selection module offers multiple debugging modes, including built-in system initialization debugging, individual device debugging, collaborative debugging, post-fault repair debugging, and customized debugging, adapting to the debugging needs of different operation and maintenance scenarios. The parameter configuration module stores a standard parameter library for different devices and operating scenarios and supports custom modification. It also integrates a device integration engine to adapt the debugging parameter configuration of newly added devices according to local energy scenario differences, improving the efficiency and compatibility of debugging parameter settings. The debugging execution module sends debugging commands to the core control unit according to the selected mode and parameter configuration to link each energy storage device to complete parameter configuration, functional testing, and collaborative verification according to the preset debugging process. During the debugging process, it collects the operating data of each device in real time to dynamically adjust the debugging parameters, improving the automation and adaptability of the debugging process. The debugging verification module performs functional verification on the debugged system. If the verification fails, it returns to the debugging process and adjusts the parameters until the verification passes, ensuring the debugging quality. The debugging report generation module generates a debugging report containing debugging time, debugging mode, debugging parameters, debugging process, verification results, and optimization suggestions after debugging is completed and stores it in the storage unit, making the debugging process traceable.

[0012] Optionally, the core control unit includes at least two processing cores, integrating reinforcement learning algorithms to optimize energy dispatch strategies and equipment control parameters based on the operating status and debugging results of the energy storage system; The core control unit also has a built-in fault emergency handling module, which is used to disconnect the faulty device from the energy storage system when a serious fault is detected, and to activate the emergency power supply scheme to limit the scope of the fault and ensure the power supply continuity of the energy storage system under abnormal operating conditions.

[0013] Optionally, the data acquisition unit adopts a distributed acquisition architecture, setting up multiple acquisition nodes, with each acquisition node corresponding to a group of energy storage devices; the preprocessing includes data noise reduction, outlier removal, and data standardization, improving the accuracy and reliability of the acquired data and providing data support for fault diagnosis and debugging.

[0014] Optionally, the storage unit adopts a distributed storage structure for encrypted data storage, supports fast index-based queries, and uses blockchain notarization technology to prevent tampering of operation records, fault diagnosis reports, and debugging reports, thereby ensuring the credibility and integrity of system operation and maintenance data.

[0015] Optionally, the human-machine interaction unit supports hierarchical permission management, which includes administrator permissions, maintenance personnel permissions, and viewing personnel permissions. The human-machine interaction unit also supports remote operation, allowing users to issue one-click fault diagnosis commands and one-click debugging commands through the cloud platform, and view system operating status and reports, thereby expanding the system's remote management and control capabilities and reducing the frequency of on-site maintenance.

[0016] Optionally, a remote operation and maintenance unit is also included, which is connected to the core control unit and the communication unit to realize remote monitoring, remote fault diagnosis, remote debugging and remote parameter updates of the energy storage management system, expand the remote control function of the system, reduce the frequency of on-site manual intervention and reduce the on-site operation and maintenance cost of energy storage systems in remote areas.

[0017] Optionally, it also includes a one-click deployment unit, which is connected to the core control unit and storage unit for fully automated one-click rapid deployment of the energy storage system.

[0018] A second aspect of this application provides an energy storage management method supporting one-click fault diagnosis and one-click debugging, characterized in that it is applied to the energy storage management system supporting one-click fault diagnosis and one-click debugging provided in the first aspect, the method comprising: The system receives a one-click fault diagnosis command through the human-computer interaction unit and transmits the one-click fault diagnosis command to the one-click fault diagnosis unit. After receiving the one-click fault diagnosis command, the one-click fault diagnosis unit obtains the real-time operating data of each device in the energy storage system from the data acquisition unit, and calls historical data and fault knowledge base from the storage unit. The real-time operating data is denoised and outlier removed by the fault data preprocessing module, and fault feature parameters are extracted. The fault identification module compares the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault. If no fault is detected, the system will send a message to the human-computer interaction unit indicating that it is operating normally. If a fault is detected, the fault location module locates the equipment and location where the fault occurred, and the diagnostic report generation module generates a fault diagnosis report. The fault diagnosis report is transmitted to the human-machine interaction unit and the storage unit, and the fault information is transmitted to the alarm unit so that the alarm unit can issue an alarm signal. The system receives a one-click debugging command through the human-computer interaction unit and transmits the one-click debugging command to the one-click debugging unit. After receiving the one-click debugging instruction, the one-click debugging unit retrieves the corresponding standard debugging parameters from the storage unit; The debugging execution module sends debugging instructions to the core control unit, which then links with each energy storage device to complete parameter configuration, functional testing, and collaborative verification operations according to a preset debugging process. During the debugging process, the core control unit collects the operating data of each device in real time to dynamically adjust the debugging parameters. The debugging and verification module is used to verify the functionality of the debugged system and check whether the operating parameters and collaborative working status of each device meet the preset standards. If the verification is successful, a debugging report is generated through the debugging report generation module, and the debugging report is transmitted to the human-computer interaction unit and the storage unit. If the verification fails, return to the debug execution module, adjust the parameters, and debug again.

[0019] Using the above method, upon receiving a one-click fault diagnosis command, real-time operating data is acquired from the data acquisition unit, and historical data and fault knowledge base are called. After noise reduction and outlier removal by the fault data preprocessing module, fault feature parameters are extracted. The fault identification module compares the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault. If a fault is identified, the fault location module locates the faulty device and its location, and the diagnostic report generation module generates a fault diagnosis report, improving fault troubleshooting efficiency and location accuracy. Upon receiving a one-click debugging command, the corresponding standard debugging parameters are called, and the debugging execution module sends debugging commands to the core control unit to link each energy storage device to complete parameter configuration, functional testing, and collaborative verification operations according to the preset debugging process. During the debugging process, real-time operating data of each device is collected to dynamically adjust the debugging parameters. The debugging verification module verifies the function of the debugged system. If the verification fails, the system returns to the debugging execution module to adjust the parameters and re-debug until the verification passes, reducing the reliance on human experience in the debugging process and ensuring debugging quality.

[0020] As can be seen from the above technical solutions, this application provides an energy storage management system and method that supports one-click fault diagnosis and one-click debugging. The energy storage management system includes: a data acquisition unit, used to collect operating parameters, status data, and environmental data of each device in the energy storage system in real time, and transmit the collected data to the core control unit after preprocessing; a one-click fault diagnosis unit, connected to the core control unit and the data acquisition unit, used to receive one-click fault diagnosis commands, perform multi-dimensional fusion analysis based on the real-time data collected by the data acquisition unit, the historical data stored in the storage unit, and the fault knowledge base, to determine the fault type and locate the faulty device, and generate a fault diagnosis report; and a one-click debugging unit, connected to the core control unit and the data acquisition unit, used to receive one-click debugging commands, and call the corresponding debugging parameters and debugging procedures according to the device type, operating scenario, and debugging requirements of the energy storage system, to complete the parameter configuration, collaborative debugging, and functional verification of each device, and generate a debugging report. The system comprises the following components: a report unit; a human-machine interface unit (HMI unit) for providing users with an operating interface, issuing one-click fault diagnosis and one-click debugging commands, and displaying the real-time operating status, fault diagnosis results, and debugging progress of the energy storage system; a communication unit for enabling communication between the energy storage management system and various devices within the energy storage system, a remote management platform, and external terminals; a storage unit for storing real-time and historical data collected by the data acquisition unit, a fault knowledge base, a standard parameter library, fault diagnosis reports, and debugging reports; and an alarm unit for receiving fault information transmitted by the one-click fault diagnosis unit and issuing alarm signals of corresponding levels based on the fault level. The core control unit is connected to both the one-click fault diagnosis unit and the one-click debugging unit, coordinating the operation of the data acquisition unit, one-click fault diagnosis unit, one-click debugging unit, HMI unit, communication unit, storage unit, and alarm unit to address the problem that the energy storage management system cannot adapt to the efficient operation and maintenance requirements of large-scale energy storage scenarios. Attached Figure Description

[0021] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The overall structural block diagram of the energy storage management system supporting one-click fault diagnosis and one-click debugging provided in this application; Figure 2 Internal structural block diagram of the one-click fault diagnosis unit in the energy storage energy management system that supports one-click fault diagnosis and one-click debugging provided in this application; Figure 3Internal structural block diagram of the one-click debugging unit in the energy storage energy management system that supports one-click fault diagnosis and one-click debugging provided in this application; Figure 4 A flowchart illustrating the one-click fault diagnosis process in the energy storage energy management method supporting one-click fault diagnosis and one-click debugging provided in this application. Figure 5 A flowchart illustrating the one-click debugging process in the energy storage energy management method supporting one-click fault diagnosis and one-click debugging provided in this application; Figure 6 A flowchart illustrating the one-click deployment process in the energy storage energy management method that supports one-click fault diagnosis and one-click debugging provided in this application. Detailed Implementation

[0023] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application.

[0024] To address the issue of energy storage management systems being unable to adapt to the high-efficiency operation and maintenance requirements of large-scale energy storage scenarios, see [link to relevant documentation]. Figure 1 This application provides an energy storage management system that supports one-click fault diagnosis and one-click debugging in some embodiments. It includes a data acquisition unit, a one-click fault diagnosis unit, a one-click debugging unit, a human-machine interaction unit, a communication unit, a storage unit, an alarm unit, and a core control unit. The units interact with each other and transmit commands through an internal bus (e.g., a controller area network bus) or a communication module to ensure transmission stability and real-time performance.

[0025] The data acquisition unit is used to collect the operating parameters, status data and environmental data of each device in the energy storage system in real time, and transmits the collected data to the core control unit after preprocessing.

[0026] In some embodiments, the data acquisition unit adopts a distributed acquisition architecture, with multiple acquisition nodes set up at the energy storage system site. Each acquisition node corresponds to a set of energy storage devices (including battery modules, energy storage converters, battery management systems, meters, etc.). The acquisition frequency can be adaptively adjusted within the range of 1 to 60 seconds / time according to operation and maintenance requirements (the default setting is 10 seconds / time). The acquisition accuracy meets the accuracy requirements of battery voltage ±0.01V, current ±0.1A, temperature ±0.5℃, and energy storage converter output power ±0.5kW. The data acquisition unit collects real-time operating parameters of each device (such as voltage, current, temperature, and remaining power of the battery module; output power, conversion efficiency, and switching status of the energy storage converter; operating and communication status of the battery management system; and metering data), status data, and environmental data (such as temperature and humidity of the environment where the energy storage system is located). The unit preprocesses the collected data, including data noise reduction (using filtering algorithms to eliminate noise interference introduced during signal transmission, such as amplitude limiting filtering or median filtering), outlier removal (identifying and removing abnormal data points that significantly deviate from the normal range based on statistical analysis methods, such as using the Laida criterion or box plot method), and data standardization (mapping data of different dimensions and orders of magnitude to a unified standard range). After preprocessing, the data is transmitted to the core control unit, the one-click fault diagnosis unit, and the storage unit, providing accurate and reliable data support for subsequent fault diagnosis and debugging operations.

[0027] The one-click fault diagnosis unit, connected to the core control unit and data acquisition unit, receives one-click fault diagnosis commands issued by the user through the human-machine interface unit. Based on real-time data collected by the data acquisition unit, historical data stored in the storage unit, and a fault knowledge base, the one-click fault diagnosis unit performs multi-dimensional fusion analysis. Specifically, it simultaneously extracts current operating status characteristics from real-time data, mines fault evolution patterns from historical data, and matches known fault patterns from the fault knowledge base. This comprehensive judgment determines the fault type and locates the faulty equipment (precisely down to a single device or device component level). After diagnosis, a standardized fault diagnosis report is automatically generated. This multi-dimensional fusion analysis mechanism effectively overcomes the shortcomings of single-parameter threshold judgment methods, such as low diagnostic accuracy and inability to provide early warnings.

[0028] The specific implementation of multi-dimensional fusion analysis is as follows: First, real-time data, historical data, and knowledge base data are aligned on the timeline to form a multi-source data set at the same moment; then, key feature parameters are extracted from each data source, including instantaneous deviation features of real-time data, trend change features of historical data, and fault mode features in the knowledge base; finally, the three types of features are comprehensively judged by a weighted voting algorithm or a Bayesian fusion model, and the fault type and confidence score are output.

[0029] See Figure 2 In some embodiments, the one-click fault diagnosis unit includes: The fault data preprocessing module is used to receive real-time data transmitted by the data acquisition unit, perform noise reduction, filtering and outlier removal on the real-time data, and extract fault feature parameters; the fault knowledge base stores the feature parameters, causes, handling methods and historical fault cases of various faults in the energy storage system.

[0030] It should be understood that real-time data includes multi-dimensional parameters such as battery voltage, current, temperature, remaining power, PCS output power, conversion efficiency, and switching status, BMS operating and communication status, meter readings, and ambient temperature and humidity. Noise reduction can be achieved using wavelet transform or Kalman filtering algorithms to eliminate noise interference in signal transmission. Filtering can be performed using low-pass or band-pass filters to extract effective signal frequency bands. Outlier removal is based on the Laida criterion or box plot method to identify and remove abnormal data points that significantly deviate from the normal range. Fault characteristic parameters include parameter deviation (the amount and rate of deviation between measured and rated values), rate of change (the slope of parameter change per unit time, used to identify sudden parameter trends), and fluctuation amplitude (the maximum fluctuation range of parameters within a certain time window, used to identify unstable parameter states), providing an accurate data foundation for subsequent fault identification. Characteristic parameters of various faults in energy storage systems include: overcharge faults (voltage exceeding the upper limit for more than 3 seconds), over-discharge faults (voltage below the lower limit for more than 2 seconds), abnormal battery temperature faults (temperature exceeding the limit for more than 60°C) and abnormal temperature rise rate (temperature rise rate greater than 5°C / min), PCS communication faults (communication timeout and data loss for more than 500ms or data loss rate greater than 5%), abnormal PCS power faults (output power exceeding the rated value for more than 120%) and sudden drop in conversion efficiency (conversion efficiency decreases by more than 10 percentage points), BMS faults (BMS communication interruption for more than 3 seconds) and BMS internal protection action characteristics, and communication link interruption (signal loss for less than -90dBm) and excessive bit error rate (bit error rate greater than 10⁻⁻⁶). 6 Various faults include: battery overcharging may be caused by improper charging strategy parameter settings or BMS equalization failure; solutions include adjusting charging strategy parameters, replacing the BMS equalization module, checking the heat dissipation device, and restarting the communication link.

[0031] The fault knowledge base can continuously optimize the diagnostic model using deep learning algorithms. Specifically, it trains on historical fault data based on convolutional neural networks or long short-term memory networks to extract deep mapping relationships between fault features and operating parameters, continuously improving the accuracy and generalization ability of fault diagnosis. It also supports automatic updates of fault cases (the system automatically enters new cases based on actual fault handling results) and manual additions (maintenance personnel can manually enter special fault cases), so that the knowledge base can be continuously enriched and improved as maintenance data accumulates.

[0032] The fault identification module is used to compare the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault type and fault level.

[0033] Specifically, the fault identification module compares pre-processed fault characteristic parameters (such as battery voltage deviation ΔV, temperature change rate dT / dt, PCS power fluctuation amplitude ΔP, etc.) with fault features in the fault knowledge base item by item. It uses a feature vector similarity matching algorithm to calculate the Euclidean distance or cosine similarity between the real-time feature vector and the feature template of each fault type, and takes the fault type with the highest similarity as the identification result. This identifies the fault type (such as battery overcharge, battery over-discharge, abnormal temperature, PCS communication failure, PCS power failure, BMS failure, communication link interruption, etc.) and fault level (minor fault, general fault, or severe fault). The fault level classification criteria can be as follows: minor faults correspond to parameters deviating from the rated value within 5% and do not affect normal system operation; general faults correspond to parameters deviating from the rated value between 5% and 20% and affecting the function of local equipment; severe faults correspond to parameters deviating from the rated value more than 20% or posing a safety risk and requiring immediate handling.

[0034] In the preferred implementation of this embodiment, the fault identification accuracy is no less than 90%, and in the optimal embodiment it can reach over 92%. Simultaneously, the fault identification module also has an early fault warning function. When the real-time monitored fault characteristic parameters approach but have not yet reached the fault threshold set in the fault knowledge base (e.g., the battery temperature is close to but has not yet exceeded the temperature alarm threshold, or the voltage drop rate is abnormally accelerated but has not yet reached the over-discharge judgment standard), the system automatically generates a warning signal and pushes it to the alarm unit and the human-machine interaction unit, enabling early fault detection and early handling, and preventing the fault from escalating.

[0035] The fault location module is used to locate the faulty device, component, and location based on the fault identification results, combined with the location information of each device and the status of the communication link collected by the data acquisition unit.

[0036] Specifically, the fault location module is used to accurately locate the faulty device, component, and specific location based on the fault identification results (i.e., the confirmed fault type), combined with the location information of each device collected by the data acquisition unit (the physical location number and logical address of each battery module, PCS, BMS, and meter in the energy storage system) and the communication link status (the communication connection status, signal strength, packet loss rate, etc. between each device and the energy storage management system). The positioning accuracy can reach the level of a single battery module or device component (e.g., it can accurately locate "cell number 2 of battery module group 3" or "IGBT module of PCS number 1"). At the same time, it marks the scope of the fault impact (e.g., whether the fault only affects the normal charging and discharging operation of this group of batteries or affects the power output capability of the entire energy storage system), providing operation and maintenance personnel with accurate fault handling guidance.

[0037] The diagnostic report generation module is used to generate standardized fault diagnostic reports based on fault identification results, fault location results, and processing methods in the fault knowledge base.

[0038] Specifically, the diagnostic report generation module automatically generates standardized fault diagnostic reports based on fault identification results (fault type and level), fault location results (faulty equipment, components and specific locations, and scope of impact), and corresponding handling methods and emergency measures recorded in the fault knowledge base. The diagnostic report uses a unified template format and includes: fault occurrence time (accurate to the second), fault type, fault level, fault location (physical location and logical address), fault cause analysis (providing a list of possible causes and their probability ranking based on knowledge base matching), handling suggestions (operation steps ordered by priority), and emergency measures (temporary response plans before fault repair).

[0039] The fault knowledge base update module is used to update the fault characteristics and handling methods in the fault knowledge base based on the fault handling results and new fault cases.

[0040] Specifically, the fault knowledge base update module is used to automatically update the fault feature parameters (parameter correction and optimization of feature templates for existing fault types) and processing methods (adding actually verified effective processing methods to the knowledge base) in the fault knowledge base based on actual fault handling results (fault confirmation conclusions, actual handling methods and handling effects reported by operation and maintenance personnel) and newly emerging fault cases (fault modes not yet recorded in the knowledge base) during system operation, so that the accuracy of the fault diagnosis algorithm continues to improve as the system runs.

[0041] The complete workflow of the one-click fault diagnosis unit described in this embodiment is as follows: Figure 4As shown: Maintenance personnel issue a diagnostic command by clicking the "One-Click Fault Diagnosis" button on the human-machine interface unit. The command is transmitted to the one-click fault diagnosis unit. After receiving the command, the one-click fault diagnosis unit obtains real-time operating data of each device in the energy storage system from the data acquisition unit and retrieves historical data and fault knowledge base from the storage unit. The fault data preprocessing module performs noise reduction, filtering, and outlier removal on the real-time data and extracts fault feature parameters. The fault identification module compares the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault type and level. If no fault is identified, the system feedback "system is operating normally" is sent to the human-machine interface unit. If a fault is identified, the fault location module accurately locates the faulty device and its location (such as the third group of battery modules) based on the identification result, combined with the device location information and communication link status, and marks the fault. The impact scope (e.g., affecting only the charging and discharging operation of this battery group); the diagnostic report generation module automatically generates a standardized fault diagnosis report including the fault occurrence time, fault type, fault level, fault location, fault cause, handling suggestions, and emergency measures, which is transmitted to the human-machine interaction unit for maintenance personnel to view, and simultaneously stored in the storage unit for future reference; the fault information is synchronously transmitted to the alarm unit, which issues corresponding audible and visual alarms, SMS alarms, or cloud push alarms according to the fault level; maintenance personnel handle the fault according to the handling suggestions in the diagnostic report (e.g., checking the battery heat dissipation device or replacing the battery management system equalization module), and can issue a diagnostic command again after the fault is handled to verify whether the fault has been completely eliminated; the fault knowledge base update module automatically updates the relevant features and handling methods in the fault knowledge base according to the handling results of this fault, and continuously optimizes the fault diagnosis algorithm. The above complete process constitutes a closed-loop maintenance link for one-click fault diagnosis.

[0042] The one-click debugging unit connects to the core control unit and data acquisition unit to receive one-click debugging commands issued by the user through the human-machine interaction unit. The one-click debugging unit has multiple built-in debugging modes and a standard parameter library covering different equipment types and different operating scenarios. Based on the equipment type of the energy storage system (e.g., battery management system model, energy storage converter model), operating scenario (e.g., peak shaving and valley filling, frequency regulation and voltage regulation, emergency backup power) and debugging requirements, it calls the corresponding debugging parameters and debugging process to complete the parameter configuration, collaborative debugging and functional verification of each device, and generates a debugging report.

[0043] See Figure 3 In some embodiments, the one-click debugging unit includes: The debugging mode selection module has multiple built-in debugging modes, including system initialization debugging, device-specific debugging, collaborative debugging, post-fault repair debugging, and customized debugging.

[0044] Specifically, the debugging mode selection module will automatically pop up a debugging mode selection interface after receiving a one-click debugging command triggered by the user, allowing the user to select the debugging type. When the user does not actively select, the recommended debugging mode will be matched according to the current operating status of the energy storage system by default. System initialization debugging corresponds to the first debugging of a newly installed energy storage system (applicable to newly installed systems with an installed capacity in the range of 100kWh to 10MWh). Individual equipment debugging is for independent functional testing of a single added or replaced energy storage device (such as independent testing of a single PCS or a single battery cluster). Collaborative debugging is for verifying the linkage operation effect of all devices in the entire system (applicable to comprehensive verification after annual system maintenance or major renovation). Post-fault repair debugging is for verifying the equipment and related systems after the fault repair is completed (after repair, only the faulty equipment and its upstream and downstream related equipment are specifically debugged, the debugging scope is automatically defined by the fault location results, and the debugging time is usually 30 minutes to 2 hours). Customized debugging allows users to independently select the equipment and debugging items to be debugged according to their actual needs.

[0045] The parameter configuration module stores a standard parameter library for different devices and operating scenarios, supports custom modification and saving of parameters, and integrates a device integration engine to adapt the debugging parameter configuration of newly added devices according to the differences in local energy scenarios.

[0046] Specifically, in the parameter configuration module, the standard parameter library pre-stores the factory standard debugging parameters of mainstream models of energy storage converters, energy storage battery clusters, energy management platforms, and grid-connected equipment. At the same time, it will adapt the standard parameters according to different installed capacities and application scenarios, such as user-side peak-valley arbitrage, grid-side frequency and voltage regulation, and off-grid independent power supply. When a new model of equipment is connected, the equipment integration engine will automatically identify the equipment type and core parameters through the equipment communication protocol, and automatically pull the corresponding debugging parameters from the cloud parameter server to complete the adaptation. It also supports users to manually modify the parameters and store them in the custom parameter area for direct use in subsequent debugging of the same type of scenario.

[0047] The device integration engine's adaptation process is as follows: First, a device identification request is sent to the newly added device to obtain the device model and protocol version information; then, based on the model information, the cloud parameter server is queried to see if a matching parameter template exists; if it exists, it is automatically downloaded and applied; if it does not exist, the user is prompted to manually configure the parameters and save it as a new template for later use.

[0048] The debugging execution module is used to send debugging commands to the core control unit according to the selected debugging mode and parameter configuration, so that the core control unit can work with each energy storage device to complete parameter configuration, functional testing and collaborative verification operations according to the preset debugging process, and collect the operating data of each device in real time during the debugging process to dynamically adjust the debugging parameters.

[0049] Specifically, after the debugging execution module sends the debugging command, it will trigger the debugging operations of each device in sequence according to the preset timing of the debugging mode: during single device debugging, the power-on self-test, parameter writing, and functional testing are completed one by one; during collaborative debugging, the linkage test is completed step by step from the underlying device to the upper management system. After each step is completed, the running data of that node is collected and compared with the preset running parameter threshold and collaborative working logic. If the data deviation exceeds the allowable range, the debugging is immediately paused, the parameters are automatically corrected, the current step is re-executed, and the subsequent process continues.

[0050] The specific thresholds for dynamically adjusting parameters during the debugging process are: parameter correction is triggered when the voltage deviation exceeds ±2%, the current deviation exceeds ±3%, and the temperature deviation exceeds ±2℃.

[0051] The debugging and verification module is used to perform functional verification on the debugged energy storage system. It verifies whether the operating parameters and collaborative working status of each device meet the preset operating parameter thresholds and collaborative working logic. If the verification fails, it returns to the debugging process and adjusts the parameters until the verification passes.

[0052] Specifically, after all debugging steps are completed, the debugging and verification module starts a 15-30 minute load simulation run of the entire system. During the run, the output power, voltage, temperature of all devices, as well as the communication delay between devices (e.g., communication delay not exceeding 100ms) and command response speed (e.g., command response time not exceeding 200ms) are collected every minute. The preset parameter thresholds and collaborative logic requirements are compared. If any indicator fails to meet the requirements, the location and deviation value of the abnormal indicator are automatically recorded, a parameter adjustment plan is generated and returned to the debugging execution module to re-execute the corresponding debugging step until all indicators are verified.

[0053] The debug report generation module is used to generate a debug report after debugging is completed. The debug report includes the debugging time, debugging mode, debugging parameters, debugging process, verification results and optimization suggestions, and stores the debug report in the storage unit.

[0054] Specifically, after receiving the verification pass signal from the debugging verification module, the debugging report generation module automatically organizes all data from the start of debugging to the completion of verification, fills in the content according to the preset report template, generates an exportable PDF debugging report, and encrypts and stores the electronic version of the report in the local storage unit. It also supports synchronous uploading to the cloud operation and maintenance platform for subsequent operation and maintenance to access and view.

[0055] The complete workflow of the one-click debugging unit described in this embodiment is as follows: Figure 5As shown: Maintenance personnel issue debugging commands by clicking the "One-Click Debugging" button through the human-machine interface unit and select the debugging mode according to actual needs (e.g., selecting the "Debugging after Fault Repair" mode); the command is transmitted to the one-click debugging unit; after receiving the command, the one-click debugging unit retrieves the corresponding standard debugging parameters from the storage unit, and maintenance personnel can fine-tune the parameters according to actual operating conditions (e.g., adjusting the battery charging and discharging threshold, with the adjustment range not exceeding ±5% of the standard value); the debugging execution module sends debugging commands to the core control unit, and the core control unit, in conjunction with each energy storage device, completes parameter configuration, functional testing, and collaborative verification according to the preset debugging process. During the debugging process, the operating data of each device is collected in real time and the debugging parameters are dynamically adjusted; the debugging verification module performs functional verification on the debugged system, checking whether the operating parameters and collaborative working status of each device meet the preset standards. If verification passes, proceed to the next step; if verification fails, automatically return to the debugging execution module to adjust parameters and re-debug until verification passes. The debugging report generation module automatically generates a debugging report and transmits it to the human-machine interaction unit for maintenance personnel to view, while also storing it in the storage unit for future reference. After debugging, the core control unit, in conjunction with the one-click fault diagnosis unit, performs a fault review and diagnosis of the system to confirm that the fault has been completely eliminated and the system is operating normally, thus forming a complete closed-loop management link of "fault diagnosis - fault repair - one-click debugging - debugging verification - fault review". This post-fault repair debugging mode means that after fault elimination, only specific debugging and verification of the fault-related parts are required, without having to perform full system re-debugging, significantly reducing system downtime and recovery time.

[0056] The human-machine interface unit provides users with an operating interface, enabling them to issue one-click fault diagnosis commands and one-click debugging commands, and display the real-time operating status, fault diagnosis results, and debugging progress of the energy storage system.

[0057] Specifically, the human-machine interaction unit provides users with a visual operation interface, supporting users to issue one-click fault diagnosis commands and one-click debugging commands (users only need to click the "one-click diagnosis" or "one-click debugging" button on the interface to trigger the complete process). At the same time, it displays the operating status of the energy storage system in real time in a graphical and digital manner (including real-time parameters of each device, communication link status, etc.), fault diagnosis results (including fault type, fault level, fault location and handling suggestions), and debugging progress (including current execution steps, completed operations and estimated remaining time), making the operation convenient and intuitive.

[0058] In some embodiments, the human-machine interaction unit supports hierarchical permission management, which includes administrator permissions, operation and maintenance personnel permissions, and viewing personnel permissions. The human-machine interaction unit also supports remote operation, allowing users to issue one-click fault diagnosis commands and one-click debugging commands through the cloud platform, and view system operating status and reports.

[0059] Specifically, the human-computer interaction unit supports hierarchical permission management, including administrator permissions (allowing for parameter modification, fault handling, system configuration, and other operations), operation and maintenance personnel permissions (allowing for one-click diagnosis, one-click debugging, viewing reports, and other routine operation and maintenance operations), and viewing personnel permissions (allowing for viewing only the system's operating status and reports), ensuring the security and standardization of system operations; it also supports remote operation, allowing users to remotely issue one-click fault diagnosis commands and one-click debugging commands through the cloud platform and view the system's operating status and reports.

[0060] The communication unit is used to enable communication between the energy storage management system and various devices in the energy storage system, the remote management platform, and external terminals.

[0061] Specifically, the communication unit is used to realize the transmission of battery status data and the issuance of protection commands between the energy storage management system and the battery management system (BMS), the transmission of power dispatch commands and the feedback of operating status between the energy storage converter (PCS), and the acquisition of metering data with the electricity meter. It supports RS-485 serial communication (suitable for short-distance, low-speed but high-reliability device-level communication) and Ethernet communication (suitable for high-speed, long-distance system-level communication), and is compatible with the 104 protocol (suitable for remote control communication), Modbus protocol (suitable for field device communication) and IEC61850 protocol (suitable for digital substation and smart grid communication). It ensures the real-time performance and stability of data interaction between the system and various devices, and provides reliable communication support for data acquisition during fault diagnosis and command transmission during debugging.

[0062] The storage unit is used to store real-time and historical data collected by the data acquisition unit, fault knowledge base, standard parameter library, fault diagnosis report and debugging report.

[0063] Specifically, the fault knowledge base stores characteristic parameters, causes, handling methods, and historical fault cases of various faults in the energy storage system, while the standard parameter library stores standard debugging parameters for different equipment and different operating scenarios.

[0064] In some embodiments, the storage unit adopts a distributed storage structure for encrypted data storage, supports fast index-based queries, and uses blockchain notarization technology to prevent tampering of operation records, fault diagnosis reports, and debugging reports.

[0065] It should be understood that a distributed storage structure specifically distributes different types of data across multiple independent storage nodes. Real-time running data is stored on local high-speed storage nodes (which can use solid-state drives, with read / write latency not exceeding 5ms), while historical data, fault knowledge bases, standard parameter databases, and other less frequently accessed data are stored on remote, high-capacity storage nodes. This improves the read / write efficiency of high-frequency data and expands storage capacity to meet the long-term storage needs of large-volume data. Encrypted data storage specifically uses symmetric encryption algorithms (such as AES-256) to encrypt all stored data. Users need to verify their identity and authorization key before decryption and reading, preventing unauthorized theft and leakage of stored data. Index-based fast query specifically establishes timestamp indexes, data type indexes, and keyword indexes for different types of stored data collected at different times. During queries, target data can be located directly through the indexes without traversing the entire stored content, improving data retrieval efficiency. Blockchain-based evidence storage technology specifically generates a unique hash value (such as using the SHA-256 hash algorithm) for each generated operation record, fault diagnosis report, and debugging report. These hash values ​​are then packaged and stored in the blockchain node in chronological order of generation. Each newly stored hash value is associated with the hash value of the previous record for encrypted verification. If any content is tampered with, the corresponding hash value will change, and the association verification in the blockchain will fail. This achieves tamper-proof retention of operation records, fault diagnosis reports, and debugging reports, ensuring the traceability and authenticity of the relevant records.

[0066] The alarm unit is used to receive fault information transmitted by the one-key fault diagnosis unit and issue alarm signals of the corresponding level according to the fault level.

[0067] Specifically, the fault levels are divided into three categories: minor fault, general fault, and severe fault. The system automatically issues alarm signals according to the fault level. For example, a minor fault triggers a local audible and visual alarm (sound intensity not less than 75dB, and the light flashing yellow). A general fault triggers an SMS notification in addition to the audible and visual alarm (the notification is sent every 10 minutes for a total of 3 times). A severe fault simultaneously activates an audible and visual alarm (sound intensity not less than 90dB, and the light is solid red), an SMS alarm, and a cloud push alarm (the push is sent every 5 minutes until the fault is confirmed and resolved). This alerts maintenance personnel to handle the fault in a timely manner and automatically stores the alarm records in the storage unit for future reference.

[0068] The core control unit is connected to the one-key fault diagnosis unit and the one-key debugging unit respectively, and is used to coordinate the operation of the data acquisition unit, the one-key fault diagnosis unit, the one-key debugging unit, the human-machine interaction unit, the communication unit, the storage unit and the alarm unit.

[0069] It should be understood that the core control unit, as the core hub of the system, can receive data and instructions transmitted by each unit, and execute core functions of the energy storage system such as energy scheduling, charging and discharging control, and parameter management. At the same time, it can link the one-click fault diagnosis unit and the one-click debugging unit. After the fault diagnosis is completed, the diagnosis result can automatically trigger the corresponding debugging process without the need for manual re-initiation of the debugging command, so as to achieve collaborative closed-loop control of fault diagnosis and debugging.

[0070] In some embodiments, the core control unit includes at least two processing cores that integrate reinforcement learning algorithms to optimize energy dispatch strategies and equipment control parameters based on the operating status and commissioning results of the energy storage system.

[0071] Specifically, the core control unit adopts a dual-core processor architecture (including at least two processing cores, one core focusing on real-time control tasks, including real-time calculation and issuance of energy dispatch commands, equipment status monitoring and emergency response, and the other core focusing on data management and algorithm optimization—including historical data analysis, reinforcement learning model training and policy updates), and integrates reinforcement learning algorithms (specifically deep Q-networks or near-end policy optimization algorithms) to continuously optimize energy dispatch strategies and equipment control parameters based on the actual operating status of the energy storage system (including real-time operating parameters of each device, load demand curves, electricity price signals, etc.) and commissioning results (including actual response characteristics of the equipment and measured control accuracy data obtained during commissioning). For example, the system continuously adjusts the charging and discharging strategy through reinforcement learning to adapt to the daily cycle fluctuations of the electricity load, or optimizes the power allocation coefficient of the PCS to improve the overall conversion efficiency.

[0072] The specific training process of the reinforcement learning model is as follows: the state of charge (SOC), load demand, and electricity price signal of the energy storage system are used as state inputs, the charging and discharging power command is used as action outputs, and the reward function is to minimize operating costs and maximize equipment lifespan. The model adopts a combination of offline training and online fine-tuning. In the offline stage, the model is pre-trained based on historical operating data, and in the online stage, the model parameters are fine-tuned and updated every 24 hours based on actual operating feedback.

[0073] The core control unit also has a built-in fault emergency handling module, which is used to disconnect the faulty device from the energy storage system when a serious fault is detected, and to activate the emergency power supply scheme to limit the scope of the fault and ensure the power supply continuity of the energy storage system under abnormal operating conditions.

[0074] Specifically, the fault emergency handling module is used to automatically disconnect the electrical and communication connections between the faulty device and the energy storage system within 50ms when a serious fault is detected (such as excessive battery overcharge voltage, PCS output short circuit, or complete interruption of BMS communication, which endangers system safety). This isolates the fault source to prevent the fault from spreading. At the same time, it activates the emergency power supply guarantee mechanism according to the preset emergency power supply plan (such as switching to backup battery power, calling other PCS to share the load, or starting a diesel generator to supplement power supply). This ensures that the energy storage system can still maintain basic power supply functions under abnormal operating conditions, avoids the fault from expanding, and ensures the overall operational safety and power supply continuity of the energy storage system.

[0075] In some embodiments, a remote operation and maintenance unit is also included, which is connected to the core control unit and the communication unit, and is used to realize remote monitoring of the energy storage energy management system (real-time viewing of system operating status and equipment parameters), remote fault diagnosis (remotely triggering one-click debugging process through the cloud platform), remote debugging (remotely triggering one-click debugging process through the cloud platform), and remote parameter update (remotely issuing parameter configuration change instructions).

[0076] Specifically, the remote operation and maintenance unit includes a cloud data storage module, a remote command interaction module, and a local data caching module. The cloud data storage module stores the operational data, fault diagnosis records, and debugging results of the energy storage system throughout its entire lifecycle, allowing users to retrieve historical data for retrospective analysis at any time. The remote command interaction module establishes an encrypted transmission link (using the TLS 1.3 encryption protocol) with the core control unit through the communication unit, enabling the encrypted distribution of remote debugging commands and parameter update commands. It also transmits the real-time operating status and fault diagnosis results of the energy storage system back to the remote operation and maintenance terminal for operation and maintenance personnel to view and analyze. The local data caching module temporarily stores local operational data (with a cache capacity of not less than 10GB, capable of storing at least 7 days of operational data) when network communication is interrupted. Once communication is restored, the data is automatically synchronized to the cloud to prevent data loss. The complete workflow of the remote operation and maintenance unit is as follows: After logging in and authenticating through the cloud platform, the operation and maintenance personnel enter the remote operation and maintenance interface; select the target energy storage site and issue a remote fault diagnosis command or a remote debugging command; the command is transmitted in encrypted form to the communication unit of the on-site energy storage energy management system, and then forwarded by the communication unit to the core control unit; the core control unit calls the corresponding one-click fault diagnosis unit or one-click debugging unit to perform the operation according to the command type; after the operation is completed, the result report is transmitted back to the cloud platform in encrypted form for the operation and maintenance personnel to view and analyze.

[0077] In some embodiments, a one-click deployment unit is further included, connected to the core control unit and the storage unit, for realizing fully automated one-click rapid deployment of the energy storage system. The one-click deployment unit includes: The one-click deployment trigger module is used to receive one-click deployment commands issued by users through the human-computer interaction unit, and automatically execute subsequent full-process deployment operations in a single command trigger. The dual-layer parallel verification module is used to perform online verification of hardware devices and network operating environment verification in parallel during the pre-processing stage. It batch detects the online status of PCS, BMS and measurement and control equipment, and simultaneously verifies the connectivity and operating status of PoE power supply, IEC104 port, IEC61850 port and other communication ports, forming a deployment access threshold. The scenario intelligent adaptation module is used to call the standardized parameter template library from the storage unit, automatically identify and adapt to multiple business scenarios such as frequency regulation, energy storage, independent energy storage or thermal energy storage combination based on the site's preset parameters, and preset protection thresholds, SOC management and control strategies and AGC / AVC control strategies with one click. The batch networking configuration module is used to automatically complete the batch distribution and configuration of all station operation parameters, automatically generate and map complete point tables of remote signaling, telemetry, remote adjustment and remote control, automatically perform cross-protocol conversion between IEC104, IEC61850 and private protocols, and establish multi-level bidirectional communication links between the energy storage body, EMS, dispatch master station and cloud platform. The closed-loop function verification module is used to automatically perform in-depth function verification after the link is established, verifying the correctness of AGC response characteristics, frequency modulation dead zone, SOC control effect and protection action logic item by item. The fault tolerance fallback module is used to automatically trigger parameter rollback, audible and visual alarms, and retain fault logs when self-check or configuration judgment fails at any stage, and supports users to re-initiate one-click deployment after troubleshooting. After completing all verification, configuration and validation, the one-click deployment unit outputs complete configuration logs and running results, and switches the energy storage system to a fully automatic stable operation mode.

[0078] See Figure 6 This flowchart illustrates the complete implementation process of a fully automated one-click rapid deployment of an energy storage system, and constructs a complete closed-loop control logic from one-click triggering, automatic verification, intelligent adaptation, batch configuration, closed-loop verification to anomaly fallback.

[0079] The process begins with the user issuing a one-click deployment command, followed by parallel system hardware self-checks and operating environment verifications. This involves batch checking the online status of all station equipment, including PCS, BMS, and measurement and control systems, while simultaneously verifying network connectivity, power supply, and communication port operation. Once verification is successful, the system automatically loads standardized parameter templates. Based on preset station parameters, it intelligently matches multiple service scenarios such as frequency regulation, power distribution and storage, and thermal power storage, automatically adapting and pre-setting protection thresholds, SOC management, and AGC / AVC control strategies with a single click.

[0080] The system then automatically completes batch network configuration of all station operating parameters, automatically generates and maps complete point tables for remote signaling, telemetry, remote adjustment, and remote control, completes cross-protocol conversion, and quickly establishes bidirectional communication links between the energy storage unit, EMS, dispatching, and cloud platform. After the links are established, in-depth functional verification is automatically performed, verifying AGC response characteristics, frequency regulation dead zone, SOC control effect, and protection action logic item by item. After all verifications are passed, the system outputs complete configuration logs and operating results, officially completing deployment and entering fully automatic stable operation mode.

[0081] If any step fails a self-check or configuration check, the system will immediately trigger an automatic rollback, simultaneously triggering an audible and visual alarm and storing a fault log, allowing users to troubleshoot and re-initiate one-click deployment.

[0082] This invention significantly shortens the construction and commissioning cycle of energy storage stations, eliminates manual configuration deviations, and ensures standardized and consistent implementation of all station parameters. The multi-level verification and fault-tolerant design greatly improves deployment reliability and grid connection security, and is suitable for large-scale batch replication and implementation in multiple scenarios, demonstrating outstanding engineering practicality and promotional value.

[0083] This application also provides an energy storage management method that supports one-click fault diagnosis and one-click debugging in some embodiments, applied to the energy storage management system that supports one-click fault diagnosis and one-click debugging provided in the above embodiments. The method includes: The human-computer interaction unit receives one-click fault diagnosis commands and transmits the one-click fault diagnosis commands to the one-click fault diagnosis unit. After receiving the one-click fault diagnosis command, the one-click fault diagnosis unit obtains the real-time operating data of each device in the energy storage system from the data acquisition unit, and retrieves historical data and fault knowledge base from the storage unit. The fault data preprocessing module performs noise reduction and outlier removal on real-time operating data and extracts fault feature parameters. The fault identification module compares the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault. If no fault is detected, the system will send a message to the human-machine interface unit indicating that it is operating normally. If a fault is detected, the fault location module locates the equipment and location where the fault occurred, and the diagnostic report generation module generates a fault diagnosis report. The fault diagnosis report is transmitted to the human-machine interaction unit and the storage unit, and the fault information is transmitted to the alarm unit so that the alarm unit can issue an alarm signal. The human-computer interaction unit receives one-click debugging commands and transmits them to the one-click debugging unit. After receiving the one-click debugging command, the one-click debugging unit retrieves the corresponding standard debugging parameters from the storage unit; The debugging execution module sends debugging commands to the core control unit, which then links with each energy storage device to complete parameter configuration, functional testing, and collaborative verification operations according to the preset debugging process. During the debugging process, the module also collects the operating data of each device in real time to dynamically adjust the debugging parameters. The debugging and verification module is used to verify the functionality of the debugged system and check whether the operating parameters and collaborative working status of each device meet the preset standards. If the verification is successful, a debugging report is generated through the debugging report generation module and transmitted to the human-computer interaction unit and the storage unit. If the verification fails, return to the debug execution module, adjust the parameters, and debug again.

[0084] Specifically, first, the user issues a one-click fault diagnosis command through the human-computer interaction unit (by clicking the "one-click diagnosis" button on the operation interface), and the human-computer interaction unit transmits the command to the one-click fault diagnosis unit.

[0085] Upon receiving a one-click fault diagnosis command, the one-click fault diagnosis unit initiates the diagnosis process: it acquires real-time operating data from each device in the energy storage system from the data acquisition unit and retrieves historical data and the fault knowledge base from the storage unit. The data acquisition unit then provides input to the diagnosis unit with the latest data from the current acquisition cycle (default 10 seconds / time).

[0086] Then, the real-time operating data is processed by the fault data preprocessing module to reduce noise (using filtering algorithms to eliminate signal noise), remove outliers (removing data points that deviate significantly from the normal range), and standardize the data. Based on this, fault characteristic parameters are extracted, including the deviation value, rate of change, and fluctuation amplitude of each operating parameter.

[0087] Next, the preprocessed fault feature parameters are compared with the fault features in the fault knowledge base in a multi-dimensional way through the fault identification module. The feature vector similarity matching method is used to calculate the similarity between the real-time feature vector and the feature template of each fault type in the knowledge base, so as to identify whether a fault exists and the specific type and level of the fault.

[0088] If no fault is detected, the system will send a message to the human-machine interface unit indicating that the system is operating normally, and the status will be displayed in green on the interface.

[0089] If a fault is detected, the fault location module, based on the fault identification results and combined with the location information of each device (the physical location number and logical address of each device in the system) and the communication link status (the connection status and signal quality of each link) collected by the data acquisition unit, accurately locates the specific device, component, and location of the fault (e.g., "the communication module of PCS No. 3" or "the No. 5 battery module of the second battery cluster"). The diagnostic report generation module automatically generates a standardized fault diagnosis report, which includes the fault occurrence time, fault type, fault level, fault location, fault cause, handling suggestions, and emergency measures.

[0090] The fault diagnosis report is transmitted to the human-machine interaction unit for operation and maintenance personnel to view, and at the same time to the storage unit for blockchain evidence storage and future reference; at the same time, the fault information is transmitted to the alarm unit, so that the alarm unit can issue corresponding alarm signals (audible and visual alarm, SMS alarm or cloud push alarm) according to the fault level (minor, general, severe).

[0091] After the fault is resolved, the user issues a one-click debugging command through the human-computer interaction unit (click the "one-click debugging" button on the operation interface). The human-computer interaction unit transmits the command to the one-click debugging unit, and the user selects the debugging mode according to the actual needs (for example, select the "fault repair debugging" mode for the fault repair scenario).

[0092] After receiving the one-click debugging command, the one-click debugging unit retrieves the standard debugging parameters corresponding to the debugging mode from the storage unit. Users can fine-tune the standard parameters according to the actual working conditions on site (the fine-tuning range does not exceed ±5% of the standard value, such as adjusting the battery charging and discharging voltage threshold or adjusting the PCS power response slope).

[0093] The debugging execution module sends debugging commands to the core control unit. The core control unit then links with each energy storage device to complete parameter configuration (sending debugging parameters to each device and confirming successful writing) and functional testing (performing single-function verification of the device, such as PCS charging and discharging function testing and BMS acquisition accuracy testing) in sequence according to the preset debugging process. During the debugging process, the system collects operational feedback data from each device in real time to dynamically adjust the debugging parameters (for example, if the response delay of a device exceeds expectations, the system automatically fine-tunes the communication parameters or timing arrangement, adjusting the step size to 1% of the standard value).

[0094] The debugging and verification module is used to verify the functionality of the debugged energy storage system. It checks whether the operating parameters (voltage, current, temperature, power, etc.) of each device are within the target range and whether the collaborative working status (communication delay not exceeding 100ms, command response time not exceeding 200ms, control accuracy not less than 98% of the rated value) meet the preset standards. Specifically, it verifies indicators such as charging and discharging control accuracy, energy dispatch efficiency, communication stability and the effectiveness of fault diagnosis function.

[0095] If the verification is successful, a standardized debugging report will be generated through the debugging report generation module (the report content includes debugging time, debugging mode, debugging parameters, debugging process record, verification results and optimization suggestions). The debugging report will be transmitted to the human-computer interaction unit for viewing, and at the same time transmitted to the storage unit for blockchain evidence storage and future reference.

[0096] If the verification fails, the system will automatically return to the debugging execution module, adjust the relevant parameters, and re-execute the debugging operation until the verification passes, thus forming a closed-loop iterative correction mechanism.

[0097] After debugging, the core control unit, in conjunction with the one-click fault diagnosis unit, performs a fault review and diagnosis to confirm that all system operating parameters are normal, there are no fault alarms, and the overall system operating status is stable, thus completing the complete closed-loop management process of "fault diagnosis - fault repair - one-click debugging - debugging verification - fault review".

[0098] The energy storage management method described in this embodiment organically connects the two core functions of one-click fault diagnosis and one-click debugging in the process. The diagnosis results provide accurate fault range and handling guidance for debugging. After debugging, the repair effect is confirmed by reviewing the diagnosis. This realizes the full automation, standardization and traceability of fault diagnosis and system debugging, effectively solving the technical problems of the separation of fault and debugging links, process fragmentation and high dependence on manual labor.

[0099] As can be seen from the above technical solutions, this application provides an energy storage management system and method that supports one-click fault diagnosis and one-click debugging. The energy storage management system includes: a data acquisition unit, used to collect operating parameters, status data, and environmental data of each device in the energy storage system in real time, and transmit the collected data to the core control unit after preprocessing; a one-click fault diagnosis unit, connected to the core control unit and the data acquisition unit, used to receive one-click fault diagnosis commands, perform multi-dimensional fusion analysis based on real-time data collected by the data acquisition unit, historical data stored by the storage unit, and fault knowledge base, to determine the fault type and locate the faulty device, and generate a fault diagnosis report; and a one-click debugging unit, connected to the core control unit and the data acquisition unit, used to receive one-click debugging commands, and call corresponding debugging parameters and debugging processes according to the device type, operating scenario, and debugging requirements of the energy storage system to complete parameter configuration, collaborative debugging, and functional verification of each device. The system generates debugging reports; a human-machine interface unit provides users with an operating interface for issuing one-click fault diagnosis and debugging commands, and displays the real-time operating status, fault diagnosis results, and debugging progress of the energy storage system; a communication unit enables communication between the energy storage management system and various devices in the energy storage system, remote management platforms, and external terminals; a storage unit stores real-time and historical data collected by the data acquisition unit, a fault knowledge base, a standard parameter library, fault diagnosis reports, and debugging reports; an alarm unit receives fault information transmitted by the one-click fault diagnosis unit and issues alarm signals of corresponding levels according to the fault level; and a core control unit connects to the one-click fault diagnosis unit and the one-click debugging unit respectively, coordinating the operation of the data acquisition unit, one-click fault diagnosis unit, one-click debugging unit, human-machine interface unit, communication unit, storage unit, and alarm unit to solve the problem that the energy storage management system cannot adapt to the efficient operation and maintenance needs of large-scale energy storage scenarios.

Claims

1. An energy storage management system supporting one-click fault diagnosis and one-click debugging, characterized in that, include: The data acquisition unit is used to collect the operating parameters, status data and environmental data of each device in the energy storage system in real time, and transmit the collected data to the core control unit after preprocessing. The one-click fault diagnosis unit is connected to the core control unit and the data acquisition unit. It is used to receive one-click fault diagnosis commands, perform multi-dimensional fusion analysis based on the real-time data collected by the data acquisition unit, the historical data stored in the storage unit, and the fault knowledge base, so as to determine the fault type, locate the faulty device, and generate a fault diagnosis report. The one-click debugging unit is connected to the core control unit and the data acquisition unit. It is used to receive one-click debugging commands and, according to the equipment type, operating scenario and debugging requirements of the energy storage system, call the corresponding debugging parameters and debugging process to complete the parameter configuration, collaborative debugging and functional verification of each device, and generate a debugging report. The human-machine interaction unit is used to provide an operating interface for users, to issue the one-click fault diagnosis command and one-click debugging command, and to display the real-time operating status, fault diagnosis results and debugging progress of the energy storage system. The communication unit is used to enable communication between the energy storage management system and various devices in the energy storage system, the remote management platform, and external terminals. The storage unit is used to store real-time and historical data, fault knowledge base, standard parameter library, fault diagnosis report and debugging report collected by the data acquisition unit; An alarm unit is used to receive fault information transmitted by the one-key fault diagnosis unit and issue an alarm signal of the corresponding level according to the fault level. The core control unit is connected to the one-key fault diagnosis unit and the one-key debugging unit respectively, and is used to coordinate the operation of the data acquisition unit, the one-key fault diagnosis unit, the one-key debugging unit, the human-machine interaction unit, the communication unit, the storage unit and the alarm unit.

2. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The one-key fault diagnosis unit includes: The fault data preprocessing module is used to receive real-time data transmitted by the data acquisition unit, perform noise reduction, filtering and outlier removal on the real-time data, and extract fault feature parameters; the fault knowledge base stores feature parameters, fault causes, handling methods and historical fault cases of various faults in the energy storage system. The fault identification module is used to compare the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault type and fault level. The fault location module is used to locate the faulty device, component, and location based on the fault identification results and the location information of each device and the communication link status collected by the data acquisition unit. The diagnostic report generation module is used to generate a standardized fault diagnosis report based on the fault identification results, fault location results, and processing methods in the fault knowledge base. The fault knowledge base update module is used to update the fault characteristics and handling methods in the fault knowledge base based on the fault handling results and new fault cases.

3. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The one-click debugging unit includes: The debugging mode selection module has multiple built-in debugging modes, including system initialization debugging, device-specific debugging, collaborative debugging, post-fault repair debugging, and customized debugging. The parameter configuration module stores a standard parameter library for different devices and different operating scenarios, supports custom modification and saving of parameters, and integrates a device integration engine to adapt the debugging parameter configuration of newly added devices according to the differences in local energy scenarios. The debugging execution module is used to send debugging instructions to the core control unit according to the selected debugging mode and parameter configuration, so that the core control unit can work with each energy storage device to complete parameter configuration, functional testing and collaborative verification operations according to the preset debugging process, and collect the operating data of each device in real time during the debugging process to dynamically adjust the debugging parameters. The debugging and verification module is used to perform functional verification on the debugged energy storage system. It verifies whether the operating parameters and collaborative working status of each device meet the preset operating parameter thresholds and collaborative working logic. If the verification fails, it returns to the debugging process and adjusts the parameters until the verification passes. The debugging report generation module is used to generate the debugging report after debugging is completed. The debugging report includes debugging time, debugging mode, debugging parameters, debugging process, verification results and optimization suggestions, and stores the debugging report in the storage unit.

4. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The core control unit includes at least two processing cores and integrates reinforcement learning algorithms to optimize energy dispatch strategies and equipment control parameters based on the operating status and debugging results of the energy storage system. The core control unit also has a built-in fault emergency handling module, which is used to disconnect the faulty equipment from the energy storage system and activate the emergency power supply scheme when a serious fault is detected.

5. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The data acquisition unit adopts a distributed acquisition architecture, with multiple acquisition nodes, each corresponding to a set of energy storage devices; the preprocessing includes data noise reduction, outlier removal, and data standardization.

6. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The storage unit adopts a distributed storage structure for encrypted data storage, supports fast index-based queries, and uses blockchain notarization technology to prevent tampering of operation records, fault diagnosis reports, and debugging reports.

7. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, The human-computer interaction unit supports hierarchical permission management, which includes administrator permissions, operation and maintenance personnel permissions, and viewing personnel permissions. The human-computer interaction unit also supports remote operation, allowing users to issue one-click fault diagnosis commands and one-click debugging commands through the cloud platform, and view system operating status and reports.

8. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, It also includes a remote operation and maintenance unit, which is connected to the core control unit and the communication unit to realize remote monitoring, remote fault diagnosis, remote debugging and remote parameter updates of the energy storage management system.

9. The energy storage management system supporting one-click fault diagnosis and one-click debugging according to claim 1, characterized in that, It also includes a one-click deployment unit, which is connected to the core control unit and storage unit for fully automated one-click rapid deployment of the energy storage system.

10. An energy storage management method supporting one-click fault diagnosis and one-click debugging, characterized in that, The method, applied to the energy storage management system supporting one-click fault diagnosis and one-click debugging as described in any one of claims 1 to 9, comprises: The system receives a one-click fault diagnosis command through the human-computer interaction unit and transmits the one-click fault diagnosis command to the one-click fault diagnosis unit. After receiving the one-click fault diagnosis command, the one-click fault diagnosis unit obtains the real-time operating data of each device in the energy storage system from the data acquisition unit, and calls historical data and fault knowledge base from the storage unit. The real-time operating data is denoised and outlier removed by the fault data preprocessing module, and fault feature parameters are extracted. The fault identification module compares the preprocessed fault feature parameters with the fault features in the fault knowledge base to identify the fault. If no fault is detected, the system will send a message to the human-computer interaction unit indicating that it is operating normally. If a fault is detected, the fault location module locates the equipment and location where the fault occurred, and the diagnostic report generation module generates a fault diagnosis report. The fault diagnosis report is transmitted to the human-machine interaction unit and the storage unit, and the fault information is transmitted to the alarm unit so that the alarm unit can issue an alarm signal. The system receives a one-click debugging command through the human-computer interaction unit and transmits the one-click debugging command to the one-click debugging unit. After receiving the one-click debugging instruction, the one-click debugging unit retrieves the corresponding standard debugging parameters from the storage unit; The debugging execution module sends debugging instructions to the core control unit, which then links with each energy storage device to complete parameter configuration, functional testing, and collaborative verification operations according to a preset debugging process. During the debugging process, the core control unit collects the operating data of each device in real time to dynamically adjust the debugging parameters. The debugging and verification module is used to verify the functionality of the debugged system and check whether the operating parameters and collaborative working status of each device meet the preset standards. If the verification is successful, a debugging report is generated through the debugging report generation module, and the debugging report is transmitted to the human-computer interaction unit and the storage unit. If the verification fails, return to the debug execution module, adjust the parameters, and debug again.

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