Intelligent control system for green energy industry

Abstract

The invention relates to the technical field of green energy industry, and discloses an intelligent control system for green energy industry, which comprises an equipment information acquisition module, an equipment information analysis module, an equipment evaluation module and an early warning module, the equipment information acquisition module acquires battery operation parameters, equipment operation state data and battery capacity data of energy storage equipment, and the equipment information analysis module calculates a battery operation index, an equipment operation index, a charging rate, a discharging rate and an equipment comprehensive coefficient according to the acquired data. The equipment evaluation module compares the equipment comprehensive coefficient with an equipment operation coefficient threshold value to judge whether the energy storage equipment is abnormal or not, so that the operation condition of the energy storage equipment is comprehensively analyzed in multiple aspects, the performance and the service life of the energy storage equipment are more accurately evaluated, problems and defects existing in the operation process of the energy storage equipment can be found, and the energy storage equipment can be more accurately evaluated. Maintenance and optimization are carried out in time, and the fault occurrence frequency and the maintenance cost are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of green energy industry, and in particular to an intelligent control system for green energy industry. Background Art

[0002] The green energy industry is a broad, technology-intensive and far-reaching field. It is committed to the development and utilization of renewable energy resources that have minimal or even beneficial impacts on the environment. With the increasingly severe global climate change problem and the gradual depletion of traditional fossil energy, the development of the green energy industry has become an inevitable trend. Green energy, such as solar energy, wind energy, hydropower, biomass energy, etc., is not only highly renewable, but also has less pollution to the environment during development and use. It is an important way to achieve sustainable development. In recent years, the global green energy industry has shown a booming development trend. On the one hand, technological progress has promoted the continuous decline in costs, making green energy more economical and feasible; on the other hand, policy support and market demand have also promoted the rapid development of the industry. In the future, with the breakthrough of energy storage technology and the construction of smart grids, the stability and reliability of green energy will be further improved, and its share in the energy structure will continue to increase.

[0003] Energy storage devices play a vital role in the green energy industry. They balance electricity supply and demand and improve energy efficiency by storing and releasing energy. However, existing energy storage devices cannot predict equipment failures during operation, causing small problems to become major failures, thereby affecting the service life of the equipment, increasing the maintenance cost of the equipment, affecting the stability of energy production, and having an adverse impact on the entire green energy industry. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides an intelligent control system for the green energy industry, which has the advantages of comprehensively analyzing the operating status of energy storage equipment from multiple aspects, more accurately evaluating its performance and lifespan, helping to discover problems and deficiencies in the operation of energy storage equipment, and timely performing maintenance and optimization, thereby reducing the frequency of failures and maintenance costs.

[0005] (II) Technical solution To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent control system for the green energy industry, comprising an equipment information collection module, an equipment information analysis module, an equipment evaluation module and an early warning module; The device information acquisition module is used to collect battery operating parameters and device operating status data of the energy storage device by connecting to the monitor, and collects battery capacity data by connecting to the battery management system and numbers them accordingly to form a battery operating parameter data set, a device operating status data set, and a battery capacity data set, which are then saved and sent to the device information analysis module; The device information analysis module calculates the battery operation index based on the battery operation parameter data set , calculate the equipment operation index based on the equipment operation status data set , calculate the charging rate based on the battery capacity data set and the discharge rate The device information analysis module is based on the battery operation index , Equipment Operation Index , Charging rate and the discharge rate Calculate the comprehensive coefficient of equipment Send to the device evaluation module; The equipment evaluation module is internally provided with an equipment operation index threshold, and the equipment comprehensive coefficient Compare with the equipment operation coefficient threshold to determine whether there is an abnormality in the energy storage equipment, and send a signal to the early warning module if an abnormality is determined; The early warning module issues an early warning according to the received abnormal signal.

[0006] Preferably, the expression of the battery operation parameter data set is: ,in, Represents the battery voltage data in the battery operating parameter data set, Represents the battery current data in the battery operating parameter data set, Represents the battery temperature data in the battery operating parameter data set, Represents the specific quantity of corresponding data collection.

[0007] Preferably, the expression of the equipment operation status data set is: ,in, Represents the vibration data of the equipment during operation. Represents the noise data during equipment operation. Represents the response time of the device operation. Represents the specific quantity of corresponding data collection.

[0008] Preferably, the expression of the battery capacity data set is: ,in, and Respectively represent the first battery capacity data and the last battery capacity data in the battery capacity data set. The battery capacity data representing the battery capacity data set has indivual.

[0009] Preferably, the battery operation index The calculation formula is as follows: In the above formula, , , are the standard values ​​of battery voltage data, battery current data, and battery temperature data under standard conditions, respectively. is the battery runtime.

[0010] Preferably, the equipment operation index The calculation formula is: In the above formula, Represents the maximum vibration data during equipment operation. Represents the minimum vibration data during equipment operation. Represents the standard vibration value of the equipment during operation. Represents the maximum noise data during equipment operation. Represents the minimum noise data during equipment operation. Standard noise value during equipment operation, Represents the maximum response time of the device operation. Represents the minimum response time of the device operation. Represents the standard response time of the device operation.

[0011] Preferably, the charging rate The calculation method is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. Represents charging time.

[0012] Preferably, the discharge rate The calculation formula is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. Represents the discharge time.

[0013] Preferably, the equipment comprehensive coefficient The calculation formula is as follows: In the above formula, It is the weight factor in the comprehensive coefficient of the equipment.

[0014] Preferably, when the equipment comprehensive coefficient When the value is greater than the threshold of the equipment operation coefficient, it indicates that there is an abnormality in the energy storage equipment, and an abnormal signal is sent to the early warning module for early warning.

[0015] Compared with the prior art, the present invention provides an intelligent control system for the green energy industry, which has the following beneficial effects: 1. The present invention fully reflects the abnormal conditions of battery operation through the values ​​of voltage, current and temperature, thereby monitoring the battery, making it easy to respond and warn in time when an abnormal condition occurs, avoiding the problem that the operation of the energy storage device is affected by the abnormality of the battery. By collecting vibration data, noise data and response time during the operation of the equipment, wear, jamming, loose internal parts and the like that occur during the operation of the energy storage device can be discovered in time. Monitoring the response time can help understand the response speed of the energy storage device to instructions or load changes. If the response time is too long, it may mean that the equipment has a performance bottleneck or there is a problem with the control system.

[0016] 2. The present invention uses a comprehensive battery operation index , Equipment Operation Index , Charging rate and the discharge rate Calculate the comprehensive coefficient of equipment , to comprehensively analyze the operating status of energy storage equipment from multiple aspects, more accurately evaluate its performance and life, help to discover problems and deficiencies in the operation of energy storage equipment, perform maintenance and optimization in a timely manner, and reduce the frequency of failures and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the structural system of the present invention; DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1, an intelligent control system for the green energy industry, including an equipment information acquisition module, an equipment information analysis module, an equipment evaluation module and an early warning module; The equipment information acquisition module is used to collect the battery operating parameters and equipment operating status data of the energy storage equipment by connecting to the monitor, and collects the battery capacity data by connecting to the battery management system and numbers them accordingly to form a battery operating parameter data set, equipment operating status data set, and battery capacity data set, which are then saved and sent to the equipment information analysis module; The voltage, current, and temperature values ​​fully reflect the abnormal conditions of battery operation, so as to monitor the battery and make timely response warnings when abnormal conditions occur, so as to avoid the problem that the abnormality of the battery affects the operation of the energy storage device. The expression of the battery operation parameter data set is: ,in, Represents the battery voltage data in the battery operating parameter data set, Represents the battery current data in the battery operating parameter data set, Represents the battery temperature data in the battery operating parameter data set, Represents the specific quantity of corresponding data collection; By collecting vibration data, noise data and response time during the operation of the equipment, wear, jamming, loose internal parts and other conditions that occur during the operation of the energy storage equipment can be discovered in a timely manner. Monitoring the response time can help understand the response speed of the energy storage equipment to instructions or load changes. If the response time is too long, it may mean that the equipment has a performance bottleneck or a problem with the control system. The expression of the equipment operation status data set is: ,in, Represents the vibration data of the equipment during operation. Represents the noise data during equipment operation. Represents the response time of the device operation. Represents the specific quantity of corresponding data collection; Real-time monitoring of battery capacity can accurately determine the remaining power of the battery, avoid overcharging or over-discharging of the battery, and provide a strong data basis for analyzing the battery charge and discharge rate. The expression of the battery capacity data set is: ,in, and Respectively represent the first battery capacity data and the last battery capacity data in the battery capacity data set. The battery capacity data representing the battery capacity data set has indivual; The equipment information analysis module calculates the battery operation index based on the battery operation parameter data set , calculate the equipment operation index based on the equipment operation status data set , calculate the charging rate based on the battery capacity data set and the discharge rate , the device information analysis module is based on the battery operation index , Equipment Operation Index , Charging rate and the discharge rate Calculate the comprehensive coefficient of equipment Send to the device evaluation module; Battery running index The calculation formula is as follows: In the above formula, , , They are the standard values ​​of battery voltage data, battery current data, and battery temperature data under standard conditions. is the battery runtime; By comparing the battery's voltage data, current data, temperature data and operating time with the corresponding standard values, the battery's operating index is calculated comprehensively to monitor the battery's operating conditions and detect abnormal battery operation in a timely manner; Equipment operation index The calculation formula is: In the above formula, Represents the maximum vibration data during equipment operation. Represents the minimum vibration data during equipment operation. Represents the standard vibration value of the equipment during operation. Represents the maximum noise data during equipment operation. Represents the minimum noise data during equipment operation. Standard noise value during equipment operation, Represents the maximum response time of the device operation. Represents the minimum response time of the device operation. Represents the standard response time of the equipment operation; By analyzing the vibration value, noise value and response time of the equipment during operation, the equipment operation process is monitored and abnormal conditions in the equipment operation process are timely understood; Charging rate The calculation method is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. Represents charging time; By testing and analyzing the battery charging rate and predicting the battery performance under different working conditions, it is helpful to optimize the operation strategy of the energy storage equipment and improve its performance and reliability. At the same time, according to the battery performance degradation, the charging rate or other operating parameters can be adjusted in time to extend the battery life. Discharge rate The calculation formula is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. represents the discharge time; Through different discharge rate tests, the actual capacity of the battery under different usage conditions can be more accurately evaluated, which can help understand the performance consistency between different battery cells and ensure the stable performance of the entire energy storage system; Comprehensively analyzing the operating status of energy storage equipment from multiple aspects, more accurately evaluating its performance and lifespan, helping to identify problems and deficiencies in the operation of energy storage equipment, timely maintenance and optimization, reducing the frequency of failures and maintenance costs, and improving the comprehensive coefficient of equipment. The calculation formula is as follows: In the above formula, It is the weight factor in the comprehensive coefficient of the equipment; The equipment evaluation module has an internal equipment operation index threshold and sets the equipment comprehensive coefficient Compared with the equipment operation coefficient threshold, when the equipment comprehensive coefficient When the value is greater than the threshold of the equipment operation coefficient, it indicates that there is an abnormality in the energy storage equipment, and an abnormality signal is sent to the early warning module; The early warning module issues an early warning according to the abnormal signal received.

[0020] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent control system for the green energy industry, characterized in that: It includes equipment information collection module, equipment information analysis module, equipment evaluation module and early warning module; The device information acquisition module is used to collect battery operating parameters and device operating status data of the energy storage device by connecting to the monitor, and collects battery capacity data by connecting to the battery management system and numbers them accordingly to form a battery operating parameter data set, a device operating status data set, and a battery capacity data set, which are then saved and sent to the device information analysis module; The device information analysis module calculates the battery operation index based on the battery operation parameter data set , calculate the equipment operation index based on the equipment operation status data set , calculate the charging rate based on the battery capacity data set and the discharge rate The device information analysis module is based on the battery operation index , Equipment Operation Index , Charging rate and the discharge rate Calculate the comprehensive coefficient of equipment Send to the device evaluation module; The equipment evaluation module is internally provided with an equipment operation index threshold, and the equipment comprehensive coefficient Compare with the equipment operation coefficient threshold to determine whether the energy storage equipment is abnormal, and send a signal to the early warning module if it is abnormal; The early warning module issues an early warning according to the received abnormal signal.

2. The intelligent control system for the green energy industry according to claim 1, characterized in that: The expression of the battery operation parameter data set is: ,in, Represents the battery voltage data in the battery operating parameter data set, Represents the battery current data in the battery operating parameter data set, Represents the battery temperature data in the battery operating parameter data set, Represents the specific quantity of corresponding data collection.

3. The intelligent control system for the green energy industry according to claim 1 is characterized in that: The expression of the equipment operation status data set is: ,in, Represents the vibration data of the equipment during operation. Represents the noise data during equipment operation. Represents the response time of the device operation. Represents the specific quantity of corresponding data collection.

4. The intelligent control system for the green energy industry according to claim 1, characterized in that: The expression of the battery capacity data set is: ,in, and Respectively represent the first battery capacity data and the last battery capacity data in the battery capacity data set. The battery capacity data representing the battery capacity data set has indivual.

5. The intelligent control system for the green energy industry according to claim 2 is characterized in that: The battery operating index The calculation formula is as follows: In the above formula, , , are the standard values ​​of battery voltage data, battery current data, and battery temperature data under standard conditions, respectively. is the battery runtime.

6. The intelligent control system for the green energy industry according to claim 3 is characterized in that: The equipment operation index The calculation formula is: In the above formula, Represents the maximum vibration data during equipment operation. Represents the minimum vibration data during equipment operation. Represents the standard vibration value during equipment operation. Represents the maximum noise data during equipment operation. Represents the minimum noise data during equipment operation. Standard noise value during equipment operation, Represents the maximum response time of the device operation. Represents the minimum response time of the device operation. Represents the standard response time of the device operation.

7. The intelligent control system for the green energy industry according to claim 4, characterized in that: The charging rate The calculation method is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. Represents charging time.

8. The intelligent control system for the green energy industry according to claim 4 is characterized in that: The discharge rate The calculation formula is: In the above formula, Represents the mean of the last 5 battery capacity data in the battery capacity data set. Represents the discharge time.

9. The intelligent control system for the green energy industry according to claim 8, characterized in that: The equipment comprehensive factor The calculation formula is as follows: In the above formula, It is the weight factor in the comprehensive coefficient of the equipment.

10. The intelligent control system for the green energy industry according to claim 9, characterized in that: When the equipment comprehensive factor When the value is greater than the threshold of the equipment operation coefficient, it indicates that there is an abnormality in the energy storage equipment, and an abnormal signal is sent to the early warning module for early warning.

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