Remote intelligent control method and device for energy storage equipment

Abstract

The invention discloses a remote intelligent control method and device for energy storage equipment, and relates to the technical field of intelligent control, and the device comprises a data acquisition module, a data preprocessing module, a battery monitoring module, a priority management module, a remote control module and a report generation module. The data acquisition module comprises a plurality of sensors and is responsible for acquiring key parameters of the battery and monitoring voltage, current, temperature and charge-discharge power of the battery through different types of sensors; through cooperative work of the data acquisition module, the preprocessing module and the battery health monitoring module, key parameters of the energy storage equipment are monitored in real time, noise and abnormal values are removed through an algorithm, the accuracy of acquired data is ensured, the battery monitoring module evaluates equipment health according to the safety value of the equipment, potential safety problems are found in time, and the safety of the energy storage equipment is ensured. And corresponding management strategies are adopted according to different security levels, so that the overall operation efficiency of the equipment is improved, and the service life of the equipment is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control, and particularly to a remote intelligent control method and device for energy storage equipment. Background Technique

[0002] As a key component in modern energy systems, energy storage equipment plays a crucial role in promoting the optimization of the energy structure, improving energy utilization efficiency, and ensuring the stability of power supply. The demand for energy storage technology is gradually increasing. Especially in the large-scale integration of renewable energy and the construction of smart grids, the importance of energy storage equipment is even more prominent. Among them, battery energy storage technology has become one of the most widely used technologies due to its high efficiency, environmental friendliness, and strong adjustability;

[0003] However, the energy storage system faces problems such as battery performance degradation, temperature changes, and unstable charge and discharge efficiency. These problems directly affect the economy, reliability, and safety of energy storage equipment. How to improve the intelligent level of the energy storage system, optimize the charge and discharge strategy, and extend the battery life has become the key research direction;

[0004] In view of the above technical deficiencies, a solution is proposed. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a remote intelligent control method and device for energy storage equipment.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A remote intelligent control method and device for energy storage equipment, including a data acquisition module, a data preprocessing module, a battery monitoring module, a priority management module, a remote control module, and a report generation module;

[0007] The data acquisition module includes multiple sensors, which are responsible for collecting key parameters of the battery. The voltage, current, temperature, and charge and discharge power of the battery are monitored through different types of sensors, and the collected data will be transmitted to the preprocessing module;

[0008] The data preprocessing module consists of a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithm to clean the data, remove noise and eliminate outliers, and fuse the data from different sensors. The integrity monitoring unit checks the integrity of the data and transmits the processed data to the battery monitoring module;

[0009] The battery monitoring module calculates the safety value SV of the energy storage equipment based on the collected battery data, evaluates the health status of the equipment, classifies the energy storage equipment into different safety levels (Level A, Level B, Level C) according to the calculated safety value SV of the energy storage equipment, and executes corresponding management strategies according to the safety level;

[0010] The priority management module adjusts the charging and discharging strategies according to electricity prices, electricity consumption demands, and remaining battery power. When the electricity price is low, the device chooses to charge; when the electricity price is high, the device chooses to discharge. It assigns priorities to each battery pack based on the charging and discharging efficiency and remaining battery power of the battery pack, thereby improving the overall device efficiency;

[0011] The remote control module is responsible for the centralized management and control of the device. The administrator monitors the device status and performs corresponding operations through the intelligent terminal. The remote control module can switch to the standby network in case of network failures to ensure that the device operation is not interrupted;

[0012] The report generation module generates dynamic reports based on the operating status of the energy storage device. The administrator can view the status data of the device at any time, which helps the administrator make timely decisions during the device operation.

[0013] The data acquisition module includes battery voltage sensors, current sensors, temperature sensors, and internal resistance sensors. Two different types of each sensor are used. The data acquisition module monitors the key parameters of the battery through the sensors and uses the collectData(sensorID, samplingRate) method to collect data from each sensor. Here, sensorID is used to mark the unique identifier of the sensor, and samplingRate is used to specify the sampling frequency. The collected data includes the voltage, current, temperature, and charging and discharging power of the battery. Finally, the collected battery data is transmitted to the preprocessing module.

[0014] The data preprocessing module includes a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithms to identify and remove the noise during the acquisition process, and eliminates unreasonable abnormal data points. The abnormal data is caused by sensor failures and environmental interferences. By processing, the data is smoothed, and the data from different sensors is combined. The weighted average and Kalman filter algorithms are used for data fusion, and cross-verification is performed through multiple algorithms. The data cleaning unit uses the applyKalmanFusion method to fuse the data. The integrity check unit uses the checkDataIntegrity function to check whether all key data points are correctly recorded through the verification mechanism. When missing data and abnormal data are found, it notifies the administrator for inspection, and transmits the processed battery data to the battery monitoring module.

[0015] The battery monitoring module analyzes the battery health status based on the collected battery information data, calculates the energy storage device safety value SV of the energy storage device through a calculation formula. The input battery data includes the voltage, current, and temperature of the battery. Based on the energy storage device safety value SV, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level.

[0016] The battery monitoring module calculates the safety value SV of the energy storage device to evaluate the safety status of the energy storage device. It is obtained by comprehensively calculating the voltage, resistance, and temperature parameters of each small battery in the energy storage device through a formula, and can warn of potential safety problems. The specific calculation formula for the safety value SV of the energy storage device is as follows:

[0017]

[0018] Vi represents the voltage value of the i-th battery, Vmax is the maximum allowable voltage of this type of battery; Ri represents the resistance value of the i-th battery, Rmax is the maximum allowable resistance of this type of battery; Ti represents the temperature of the i-th battery, Tmax is the maximum safe operating temperature of this type of battery; P represents the weight coefficient of the comprehensive safety of the battery;

[0019] The lower the safety value of the energy storage device, the safer the energy storage device; a higher safety value of the energy storage device indicates that there are safety hazards in the energy storage device; based on the safety value SV of the energy storage device, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level. The safety levels are divided as follows:

[0020] Level A (safety level): When the safety value SV of the energy storage device ≤ 0.5, the energy storage device is operating within the safe range, and the voltage, resistance, and temperature of the battery are all within the normal range without intervention. Continue to monitor and regularly check the battery status;

[0021] Level B (warning level): When the safety value 0.5 < SV ≤ 0.8, the battery parameters of the energy storage device begin to show a trend of deviating from the normal range, and there are potential risks. Reduce the charging and discharging power of the device to 60% of the demand value, reduce the device load, and increase the fan speed of the heat dissipation device to prevent the battery from overheating;

[0022] Level C (hazard level): When the safety value SV of the energy storage device > 0.8, it is determined that there are serious safety hazards in the energy storage device. Start emergency protection measures, cut off the power supply of the battery pack, start the cooling device to cool down forcibly, avoid high-temperature risks, and notify the operation and maintenance personnel for repair.

[0023] The priority management module adjusts the charging and discharging strategy according to the electricity price, electricity demand value, and remaining power of the energy storage device. When the electricity price is low, the device will choose to charge and store the electricity in the energy storage device; when the electricity price is high, the device will choose to discharge and sell the electricity to the factory and the power grid. According to the production demand of the factory and the fluctuation of the power grid electricity price, different charging and discharging priorities are assigned to each battery pack according to the remaining power and efficiency of the battery pack. The battery pack with better charging and discharging efficiency is given the first-level priority, the battery pack with medium charging and discharging efficiency is given the second-level priority, and the battery pack with poor charging and discharging efficiency is given the third-level priority. When multiple battery packs are operating simultaneously, the first-level and second-level priority batteries are preferentially used to improve the efficiency of the entire device.

[0024] The remote control module is responsible for centralized management and control of energy storage devices. The cloud server and energy storage devices communicate bidirectionally through a wireless network. Administrators can monitor and control through smart terminals, view the operating status of the equipment and perform corresponding operations, and add backup network connection paths. The remote control module detects failures in the main network through the NetworkRedundancyProtocol function. When the main network link is interrupted, it switches to the backup network to avoid operation interruption, ensuring that the equipment continues to operate according to the predetermined strategy. When the network delay exceeds the set threshold, it switches to the backup network to avoid operation interruption. When the network is interrupted, the remote control module temporarily saves the operation instructions and automatically synchronizes the data after the network is restored.

[0025] The report generation module generates a dynamic report according to the operating status of the energy storage device. The report generation module uses the function generateDynamicReport(systemData) to generate a dynamic report, where systemData is the collected energy storage device status data battery voltage, temperature, and charge and discharge power. The administrator can view the report content at any time.

[0026] The specific method of the remote intelligent control method for energy storage equipment is as follows:

[0027] S1, the data acquisition module collects the battery voltage, current, temperature, charge and discharge power battery data through the sensor and transmits it to the data preprocessing unit;

[0028] S2, the data preprocessing module cleans and fuses the data, uses Kalman filtering and weighted average algorithm to remove noise and eliminate abnormal data, and then performs data fusion, and then checks the data integrity to ensure that there is no missing record of key data;

[0029] S3, the battery monitoring module calculates the energy storage device safety value SV according to the collected data, and divides the equipment into different safety levels according to the energy storage device safety value SV to execute corresponding management strategies;

[0030] S4, the priority management module adjusts the charging and discharging strategy according to the electricity price, electricity demand and the remaining power of the energy storage device to optimize the charging and discharging efficiency of the device;

[0031] S5, the remote control module is responsible for the centralized management and control of the energy storage equipment, ensuring the stability of equipment operation, real-time monitoring of equipment status and making adjustments;

[0032] S6. The report generation module generates a dynamic report according to the operating status of the equipment.

[0033] The present invention provides a remote intelligent control method and device for energy storage equipment. Compared with the prior art, it has the following beneficial effects:

[0034] Through the collaborative work of the data acquisition module, the preprocessing module, and the battery health monitoring module, the present invention monitors the key parameters of the energy storage device in real time, removes noise and outliers through algorithms to ensure the accuracy of the collected data. The battery monitoring module evaluates the device health based on the safety values of the device, discovers potential safety problems in a timely manner, and adopts corresponding management strategies according to different safety levels, thereby improving the overall operating efficiency of the device and extending the service life of the device;

[0035] Through the priority management module, the present invention adjusts the charge and discharge strategies according to electricity prices, electricity demand, and remaining power, selects to charge when the electricity price is low, and discharges when the electricity price is high, saving the usage cost of the enterprise. The device can preferentially allocate tasks to the battery pack with higher charge and discharge efficiency, thereby improving the charge and discharge efficiency of the overall device, optimizing the use and management of resources, and achieving the maximization of cost savings and resource utilization. Brief Description of the Drawings

[0036] Figure 1 It is a schematic diagram of the principle framework of the present invention. Detailed Embodiment

[0037] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0038] Please refer to Figure 1 , this application provides a remote intelligent control method and device for an energy storage device, including a data acquisition module, a data preprocessing module, a battery monitoring module, a priority management module, a remote control module, and a report generation module;

[0039] The data acquisition module includes multiple sensors, which are responsible for collecting the key parameters of the battery, monitoring the voltage, current, temperature, and charge and discharge power of the battery through different types of sensors, and the collected data will be transmitted to the preprocessing module;

[0040] The data preprocessing module consists of a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithms to clean the data, removes noise and eliminates outliers, and fuses the data from different sensors. The integrity monitoring unit checks the integrity of the data and transmits the processed data to the battery monitoring module;

[0041] The battery monitoring module calculates the safety value SV of the energy storage device based on the collected battery data, evaluates the health status of the device, classifies the energy storage device into different safety levels (Level A, Level B, Level C) according to the calculated safety value SV of the energy storage device, and executes corresponding management strategies according to the safety levels;

[0042] The priority management module adjusts the charge and discharge strategies according to the electricity price, electricity demand, and remaining power. When the electricity price is low, the device chooses to charge; when the electricity price is high, the device chooses to discharge; assigns priorities to each battery pack according to the charge and discharge efficiency and remaining power of the battery pack, thereby improving the overall device efficiency;

[0043] The remote control module is responsible for the centralized management and control of the device. The administrator monitors the device status and performs corresponding operations through the intelligent terminal. The remote control module can switch to the standby network in case of a network failure to ensure that the device operation is not disturbed;

[0044] The report generation module generates a dynamic report based on the operation status of the energy storage device. The administrator can view the status data of the device at any time, which helps the administrator make timely decisions during the device operation.

[0045] The data acquisition module includes battery voltage sensors, current sensors, temperature sensors, and internal resistance sensors. Two different types of sensors are used. The data acquisition module monitors the key parameters of the battery through the sensors, and uses the collectData(sensorID, samplingRate) method to collect data from each sensor. Among them, sensorID is used to mark the unique identifier of the sensor, and samplingRate is used to specify the sampling frequency. The collected data includes the voltage, current, temperature, and charge and discharge power of the battery. Finally, the collected battery data is transmitted to the preprocessing module.

[0046] The Kalman filter can estimate the data based on the noise and uncertainty input by the sensors, providing more accurate results. In the collected battery voltage, current, temperature and other data, the Kalman filter helps to remove the noise introduced by environmental interference and sensor problems;

[0047] Perform weighted merging on the collected data from different sensors to ensure more reliable data fusion. For example, among multiple battery voltage sensors, some sensors have larger errors and need to be given lower weights. Weighted average is used to fuse data from different sensors (such as battery voltage sensors, temperature sensors, etc.) to ensure the consistency and accuracy after data fusion. Use numpy.average() combined with the weights parameter to achieve weighted average;

[0048] Data is collected from the specified sensor (designated by the unique identifier sensorID) at the specified frequency (samplingRate) by calling collectData(sensorID, samplingRate). The sensors in the device communicate with the central control system. Usually, the SPI communication protocol is used to obtain data. The platform Arduino can be utilized to collect data using their sensor interfaces.

[0049] The data preprocessing module includes a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithms to identify and remove noise during the acquisition process, and eliminates unreasonable abnormal data points. The abnormal data is caused by sensor failures and environmental interferences. By processing, the data is smoothed, and data from different sensors is combined. The weighted average and Kalman filter algorithms are used for data fusion, and cross-verification is performed through multiple algorithms. The data cleaning unit uses the applyKalmanFusion method to fuse the data. The integrity check unit uses the checkDataIntegrity function to check whether all key data points are correctly recorded using a verification mechanism. When missing data and abnormal data are found, the administrator is notified for inspection, and the processed battery data is transmitted to the battery monitoring module.

[0050] In the data cleaning unit, the Kalman filter is used to remove noise from the data collected by the sensors, especially to remove outliers introduced by sensor failures or environmental interferences in data such as battery voltage, current, and temperature. Filterpy is a Python library for implementing the Kalman filter. It can handle Kalman filters of different dimensions. filterpy.kalman.KalmanFilter can be applied to one-dimensional, two-dimensional, and multi-dimensional Kalman filtering processes.

[0051] During the processing, checking the integrity of the data can ensure that all data obtained by the system meets the expectations, avoiding misjudgments of the system caused by missing or incorrect data. Pandas provides very convenient data processing and integrity checking functions. Missing values can be detected through pandas.DataFrame.isnull(), and incomplete data rows can be deleted through dropna().

[0052] The battery monitoring module analyzes the battery health status based on the collected battery information data. The safety value SV of the energy storage device is calculated through a calculation formula. The input battery data includes the voltage, current, and temperature of the battery. Based on the safety value SV of the energy storage device, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level.

[0053] The battery monitoring module calculates the safety value SV of the energy storage device to evaluate the safety status of the energy storage device. It is obtained by comprehensively calculating the voltage, resistance, and temperature parameters of each small battery in the energy storage device through a formula, and can warn of potential safety problems. The specific calculation formula for the safety value SV of the energy storage device is:

[0054]

[0055] Vi represents the voltage value of the i-th battery, Vmax is the maximum allowable voltage of this type of battery; Ri represents the resistance value of the i-th battery, Rmax is the maximum allowable resistance of this type of battery; Ti represents the temperature of the i-th battery, Tmax is the maximum safe operating temperature of this type of battery; P represents the weight coefficient of the comprehensive safety of the battery;

[0056] The weight coefficient P = 0.1, and calculate the safety value SV of the energy storage device for each battery:

[0057] For example:

[0058] Battery 1:

[0059] V1 = 3.7V, Vmax = 4.2 V;

[0060] R1 = 0.05Ω, Rmax = 0.1 Ω;

[0061] T1 = 40 degrees Celsius, Tmax = 50 degrees Celsius;

[0062] Contribution of Battery 1:

[0063] (4.2 - 3.7)×(0.1÷0.05)×(50 - 40)×0.1 = (0.88×10×0.5×0.8)×0.1 = 0.0353;

[0064] Battery 2:

[0065] V2 = 3.5V, Vmax = 4.2 V;

[0066] R2 = 0.06Ω, Rmax = 0.1 Ω;

[0067] T2 = 42 degrees Celsius, Tmax = 50 degrees Celsius;

[0068] Contribution of Battery 2:

[0069] (4.2 - 3.5)×(0.1÷0.06)×(50 - 42)×0.1 = (0.8333×0.6×0.84)×0.1 = 0.0423;

[0070] SV = 0.0353 + 0.0423 = 0.0776;

[0071] The lower the safety value of the energy storage device, the safer the energy storage device; a higher safety value of the energy storage device indicates a potential safety hazard. Based on the safety value SV of the energy storage device, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level. The safety levels are divided as follows:

[0072] Level A (Safety Level): When the safety value SV of the energy storage device ≤ 0.5, the energy storage device operates within a safe range, and the voltage, resistance, and temperature of the battery are all within the normal range without intervention. Continue to monitor and regularly check the battery status;

[0073] Level B (Warning Level): When the safety value 0.5 < SV ≤ 0.8, the battery parameters of the energy storage device begin to show a trend of deviating from the normal range, presenting potential risks. Reduce the charge-discharge power of the device to 60% of the demand value, reduce the device load, and increase the fan speed of the heat dissipation device to prevent the battery from overheating;

[0074] Level C (Danger Level): When the safety value SV of the energy storage device > 0.8, it is determined that the energy storage device has serious safety hazards. Initiate emergency protection measures, cut off the power supply of the battery pack, start the cooling device to cool down forcibly, avoid high-temperature risks, and notify the operation and maintenance personnel for repair.

[0075] In the above example, SV = 0.0776, and the device is at Level A, that is, the device operates within a safe range, and the voltage, resistance, and temperature of the battery are all within the normal range.

[0076] The priority management module adjusts the charge-discharge strategy according to the electricity price, electricity demand value, and remaining power of the energy storage device. When the electricity price is low, the device will choose to charge and store the electricity in the energy storage device; when the electricity price is high, the device will choose to discharge and sell the electricity to the factory and the power grid. According to the production demand of the factory and the fluctuation of the power grid electricity price, different charge-discharge priorities are assigned to each battery pack according to the remaining power and efficiency of the battery pack. The battery pack with better charge-discharge efficiency is given a first-level priority, the battery pack with medium charge-discharge efficiency is given a second-level priority, and the battery pack with poor charge-discharge efficiency is given a third-level priority. In the case of multiple battery packs operating simultaneously, the first-level and second-level priority battery packs are preferentially used to improve the efficiency of the entire device.

[0077] When multiple battery packs operate simultaneously, the first-level and second-level priority battery packs are preferentially used for discharging or charging, thereby improving the efficiency of the overall energy storage system. According to the charge-discharge efficiency and remaining power of the battery pack, priorities are assigned to each battery pack. The battery pack with better charge-discharge efficiency is given a first-level priority, the battery pack with medium charge-discharge efficiency is given a second-level priority, and the battery pack with poor efficiency is given a third-level priority. Dynamic programming is used to optimize the priority allocation during the charge-discharge process, and the priorities are dynamically adjusted according to the battery efficiency and remaining power to ensure the maximization of the charge-discharge efficiency.

[0078] The remote control module is responsible for centralized management and control of energy storage devices. The cloud server and the energy storage devices communicate bidirectionally through a wireless network. Administrators can monitor and control through intelligent terminals, view the device operation status and perform corresponding operations, add backup network connection paths. The remote control module detects main network failures through the NetworkRedundancyProtocol function. When the main network connection is interrupted, it switches to the backup network to avoid operation interruption, ensuring that the device continues to operate according to the predetermined strategy. When the network latency exceeds the set threshold, it switches to the backup network to avoid operation interruption. When the network is interrupted, the remote control module temporarily saves operation instructions and automatically synchronizes data after the network is restored.

[0079] The report generation module generates dynamic reports based on the operation status of energy storage devices. The report generation module uses the function generateDynamicReport(systemData) to generate dynamic reports, where systemData is the collected status data of energy storage devices such as battery voltage, temperature, charge and discharge power. Administrators can view the report content at any time.

[0080] A remote intelligent control method for energy storage devices. The specific method is as follows:

[0081] S1. The data acquisition module collects battery data such as voltage, current, temperature, charge and discharge power through sensors and transmits them to the data preprocessing unit;

[0082] S2. The data preprocessing module cleans and fuses data. After using the Kalman filter and weighted average algorithm to remove noise and eliminate abnormal data and perform data fusion, it then checks data integrity to ensure that there are no missing records of key data;

[0083] S3. The battery monitoring module calculates the safety value SV of the energy storage device based on the collected data, and classifies the device into different safety levels according to the safety value SV of the energy storage device to execute corresponding management strategies;

[0084] S4. The priority management module adjusts the charge and discharge strategy according to electricity price, electricity demand and the remaining power of the energy storage device to optimize the charge and discharge efficiency of the device;

[0085] S5. The remote control module is responsible for centralized management and control of energy storage devices, ensuring the stability of device operations, real-time monitoring of device status and making adjustments;

[0086] S6. The report generation module generates dynamic reports based on the operation status of the device.

[0087] Furthermore, the present invention works in cooperation with a data acquisition module, a preprocessing module, and a battery health monitoring module to monitor the key parameters of the energy storage device in real time, and removes noise and outliers through algorithms to ensure the accuracy of the collected data. The battery monitoring module evaluates the device health based on the safety values of the device, timely discovers potential safety problems, and adopts corresponding management strategies according to different safety levels, thereby improving the overall operation efficiency of the device and extending the service life of the device.

[0088] Specific working process:

[0089] The data acquisition module monitors the voltage, current, temperature, and charge and discharge power of the battery through sensors, and transmits the collected battery data to the data preprocessing module. The data preprocessing module cleans and fuses the collected data, removes noise and abnormal data, and ensures the smoothness and accuracy of the data. Through data fusion and integrity check, it ensures that key data points are complete without omission. The processed data is transmitted to the battery monitoring module. The battery monitoring module calculates the safety value SV of the energy storage device based on the collected battery data, classifies the energy storage device into different safety levels according to the calculated safety value SV of the energy storage device, and executes corresponding management strategies according to the safety levels to ensure that the device operates within a safe range. The priority management module adjusts the charge and discharge strategy according to the electricity price, electricity demand, and remaining power of the energy storage device. When the electricity price is low, it charges the energy storage device; when the electricity price is high, the energy storage device discharges outward. By assigning different priorities to each battery pack, it optimizes the charge and discharge efficiency and improves the operation efficiency of the overall device. The remote control module is responsible for the centralized management and control of the energy storage device. The administrator monitors the device status through an intelligent terminal and makes adjustments when necessary to ensure the stable operation of the device.

[0090] Some of the data in the above formulas are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0091] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified and equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A remote intelligent control device for an energy storage device, characterized in that, Including: A data acquisition module, a data preprocessing module, a battery monitoring module, a priority management module, a remote control module, and a report generation module; The data acquisition module includes multiple sensors, which are responsible for collecting key parameters of the battery. The voltage, current, temperature, and charge-discharge power of the battery are monitored through different types of sensors, and the collected data will be transmitted to the preprocessing module; The data preprocessing module consists of a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithm to clean the data, remove noise and eliminate outliers, and fuse the data from different sensors. The integrity monitoring unit checks the integrity of the data and transmits the processed data to the battery monitoring module; The battery monitoring module calculates the safety value SV of the energy storage device based on the collected battery data, evaluates the health status of the device, classifies the energy storage device into different safety levels (Level A, Level B, Level C) according to the calculated safety value SV of the energy storage device, and executes corresponding management strategies according to the safety level; The priority management module adjusts the charge-discharge strategy according to the electricity price, electricity demand, and remaining battery power. When the electricity price is low, the device chooses to charge; when the electricity price is high, the device chooses to discharge; priorities are assigned to each battery pack according to the charge-discharge efficiency and remaining battery power of the battery pack, thereby improving the overall device efficiency; The remote control module is responsible for the centralized management and control of the device. The administrator monitors the device status and performs corresponding operations through the intelligent terminal. The remote control module can switch to the standby network in case of a network failure to ensure that the device operation is not interrupted; The report generation module generates a dynamic report according to the operating status of the energy storage device. The administrator can view the status data of the device at any time, which helps the administrator make timely decisions during the device operation.

2. The remote intelligent control device for an energy storage device according to claim 1, characterized in that, The data acquisition module includes a battery voltage sensor, a current sensor, a temperature sensor, and an internal resistance sensor. Two different types of each sensor are used. The data acquisition module monitors the key parameters of the battery through the sensors and uses the collectData(sensorID, samplingRate) method to collect data from each sensor, where sensorID is used to mark the unique identifier of the sensor, and samplingRate is used to specify the sampling frequency. The collected data includes the voltage, current, temperature, and charge-discharge power of the battery. Finally, the collected battery data is transmitted to the preprocessing module.

3. The remote intelligent control device for an energy storage device according to claim 1, characterized in that The data preprocessing module includes a data cleaning unit and an integrity monitoring unit. The data cleaning unit uses the Kalman filter and weighted average algorithm to identify and remove noise during the acquisition process, and eliminates unreasonable abnormal data points. The abnormal data is caused by sensor failures and environmental interference. By processing, the data is smoothed, and data from different sensors is combined. The weighted average and Kalman filter algorithms are used for data fusion, and cross-verification is performed through multiple algorithms. The data cleaning unit uses the applyKalmanFusion method to fuse the data. The integrity checking unit uses the checkDataIntegrity function to check whether all key data points are correctly recorded using a verification mechanism. When missing data and abnormal data are found, the administrator is notified for inspection, and the processed battery data is transmitted to the battery monitoring module.

4. The remote intelligent control device for an energy storage device according to claim 1, characterized in that, The battery monitoring module analyzes the battery health status based on the collected battery information data, calculates the safety value SV of the energy storage device through a calculation formula. The input battery data includes the voltage, current, and temperature of the battery. Based on the safety value SV of the energy storage device, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level.

5. The remote intelligent control device for an energy storage device according to claim 1, characterized in that, The battery monitoring module calculates the safety value SV of the energy storage device to evaluate the safety status of the energy storage device. It is obtained by comprehensively calculating the voltage, resistance, and temperature parameters of each small battery in the energy storage device through a formula, and can warn of potential safety problems. The specific calculation formula for the safety value SV of the energy storage device is: Vi represents the voltage value of the i-th battery, Vmax is the maximum allowable voltage of this type of battery; Ri represents the resistance value of the i-th battery, Rmax is the maximum allowable resistance of this type of battery; Ti represents the temperature of the i-th battery, Tmax is the maximum safe operating temperature of this type of battery; P represents the weight coefficient of the comprehensive battery safety; The lower the safety value of the energy storage device, the safer the energy storage device; a higher safety value of the energy storage device indicates potential safety hazards. Based on the safety value SV of the energy storage device, the energy storage device is divided into three safety levels, and corresponding management strategies are formulated for each level. The safety levels are divided as follows: Level A (safe level): When the safety value SV of the energy storage device ≤ 0.5, the energy storage device operates within a safe range, and the voltage, resistance, and temperature of the battery are all within the normal range without intervention. Continue to monitor and regularly check the battery status; Level B (warning level): When the safety value 0.5 < SV ≤ 0.8, the battery parameters of the energy storage device begin to show a trend of deviating from the normal range, and there are potential risks. Reduce the charging and discharging power of the device to 60% of the required value, reduce the device load, and increase the fan speed of the heat dissipation device to prevent the battery from overheating; Level C (dangerous level): When the safety value SV of the energy storage device > 0.8, it is determined that the energy storage device has serious safety hazards. Start emergency protection measures, cut off the power supply of the battery pack, start the cooling device to cool down forcibly, avoid high-temperature risks, and notify the operation and maintenance personnel for repair.

6. The remote intelligent control device for an energy storage device according to claim 1, characterized in that, The priority management module adjusts the charging and discharging strategy according to the electricity price, electricity demand value and the remaining power of the energy storage device. When the electricity price is low, the device will choose to charge and store the electricity in the energy storage device; when the electricity price is high, the device will choose to discharge and sell the electricity to the factory and the power grid. According to the factory production needs and the fluctuation of the power grid electricity price, different charging and discharging priorities are assigned to each battery pack according to the remaining power and efficiency of the battery pack. The battery pack with better charging and discharging efficiency is given a first-level priority, the battery pack with medium charging and discharging efficiency is given a second-level priority, and the battery pack with poor charging and discharging efficiency is given a third-level priority. When multiple battery packs are running at the same time, the batteries with the first and second priority levels are used first to improve the efficiency of the entire equipment.

7. The remote intelligent control device for an energy storage device according to claim 1, characterized in that The remote control module is responsible for centralized management and control of energy storage devices. The cloud server and energy storage devices communicate bidirectionally through a wireless network. Administrators can monitor and control through smart terminals, view the operating status of the equipment and perform corresponding operations, and add backup network connection paths. The remote control module detects failures in the main network through the NetworkRedundancyProtocol function. When the main network link is interrupted, it switches to the backup network to avoid operation interruption, ensuring that the equipment continues to operate according to the predetermined strategy. When the network delay exceeds the set threshold, it switches to the backup network to avoid operation interruption. When the network is interrupted, the remote control module temporarily saves the operation instructions and automatically synchronizes the data after the network is restored.

8. The remote intelligent control device for an energy storage device according to claim 1, characterized in that, The report generation module generates a dynamic report according to the operating status of the energy storage device. The report generation module uses the function generateDynamicReport(systemData) to generate a dynamic report, where systemData is the collected energy storage device status data battery voltage, temperature, and charge and discharge power. The administrator can view the report content at any time.

9. A remote intelligent control method for an energy storage device, based on the remote intelligent control device for an energy storage device according to any one of claims 1-8, characterized in that, The specific method of the remote intelligent control method for energy storage equipment is as follows: S1, the data acquisition module collects the battery voltage, current, temperature, charge and discharge power battery data through the sensor and transmits it to the data preprocessing unit; S2, the data preprocessing module cleans and fuses the data, uses Kalman filtering and weighted average algorithm to remove noise and eliminate abnormal data, and then performs data fusion, and then checks the data integrity to ensure that there is no missing record of key data; S3, the battery monitoring module calculates the energy storage device safety value SV according to the collected data, and divides the equipment into different safety levels according to the energy storage device safety value SV to execute corresponding management strategies; S4, the priority management module adjusts the charging and discharging strategy according to the electricity price, electricity demand and the remaining power of the energy storage device to optimize the charging and discharging efficiency of the device; S5, the remote control module is responsible for the centralized management and control of the energy storage equipment, ensuring the stability of equipment operation, real-time monitoring of equipment status and making adjustments; S6. The report generation module generates a dynamic report according to the operating status of the equipment.

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