Energy storage system state monitoring method based on wireless communication

Abstract

The invention discloses an energy storage system state monitoring method based on wireless communication, and the method comprises the steps: collecting the voltage, current, temperature, power and other real-time data of a battery in an energy storage system through a wireless communication module, defining data objects, and enabling each data object to comprise a data unique identifier, a data value, a data state and other attributes; then establishing a double linked list to store information of the data object, and setting a state threshold value; the current value of the data object is compared with a state threshold value, whether the data object reaches an alarm or fault state or not is judged, and the state of the data object and double linked list information are updated; the system sends the newest state and related information of a data object to a remote cloud platform or a control center through a wireless communication module, and performs smooth processing on real-time data according to a moving average algorithm, thereby reducing short-term fluctuation, dynamically adjusting a threshold value, ensuring efficient and safe operation of the energy storage system, and improving the energy storage efficiency. And real-time, accurate and reliable monitoring and management of the state of the energy storage system are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage system monitoring, and in particular to a method for monitoring the state of an energy storage system based on wireless communication. Background Art

[0002] Energy storage systems refer to technical systems that can store energy and release it for use when needed. The main function of energy storage systems is to store excess energy during non-high demand periods and release it when energy demand is high or supply is insufficient, thereby balancing energy supply and demand. Energy storage systems are widely used in renewable energy (such as solar and wind energy), power grid dispatching, electric vehicles, portable electronic devices and other fields.

[0003] Most existing energy storage system monitoring methods rely on wired communications, which limits the flexibility and scalability of the system. Especially in large-scale distributed energy storage applications, it is particularly important to use wireless communications for system monitoring, control and management. However, problems such as data transmission delay, data interference and data packet loss in wireless communications may lead to insufficient monitoring accuracy and real-time performance of the energy storage system. Based on the above reasons, the present invention proposes a method for monitoring the status of an energy storage system based on wireless communications. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the shortcomings of the prior art, the present invention first collects real-time data such as battery voltage, current, temperature, power, etc. in the energy storage system through a wireless communication module, and defines data objects, each of which contains attributes such as data unique identification, data value, and data status; then establishes a bidirectional linked list to store the information of the data object, and sets a state threshold. The current value of the data object is compared with the state threshold to determine whether the data object has reached an alarm or fault state, and updates the data object state and bidirectional linked list information; the system sends the latest state and related information of the data object to the remote cloud platform or control center through the wireless communication module, and smoothes the real-time data according to the sliding average algorithm to reduce short-term fluctuations, dynamically adjust the threshold, ensure the efficient and safe operation of the energy storage system, and realize real-time, accurate, and reliable monitoring and management of the energy storage system state. During the entire monitoring process, the system repeatedly performs operations such as data collection, state judgment, and updating of bidirectional linked lists through polling and monitoring mechanisms, thereby ensuring the integrity and real-time nature of the monitoring data and providing comprehensive and accurate data analysis and strategy adjustment.

[0006] (II) Technical solution

[0007] To achieve the above object, the present invention provides the following technical solution: a method for monitoring the state of an energy storage system based on wireless communication, comprising the following steps:

[0008] S1: Obtain extreme value data within the monitoring period of the energy storage system;

[0009] S2: Establish a bidirectional linked list and state threshold;

[0010] S3: comparison of data value with state threshold;

[0011] S4: Update the data object status and the bidirectional linked list;

[0012] S5: Polling and monitoring.

[0013] Preferably, the definition of the extreme value data is to define each collected extreme value data as a data object, and the data object has the following properties:

[0014] Data unique identifier (ID): used to identify data objects;

[0015] Data value: the actual data collected;

[0016] Data status: the status after comparing the collected value with the preset status threshold;

[0017] Status Occurrence Count: records the number of times the data object status changes, used to identify frequently occurring problems.

[0018] Preferably, the data acquisition for the energy storage system is based on the real-time data of each sensor in the energy storage system collected by a wireless communication module, and the wireless communication module includes one or more of Wi-Fi, LoRa or Zigbee, and the real-time data includes battery voltage, current, temperature and power.

[0019] Preferably, the bidirectional linked list is established by: establishing a bidirectional linked list for each data object to store the information of the data object, and the bidirectional linked list structure can provide efficient addition, deletion and query operations;

[0020] The state threshold preset: multiple state thresholds are preset according to the working requirements and safety standards of the equipment, and the thresholds can be dynamically adjusted through wireless communication to adapt to different operating conditions and environmental changes.

[0021] Preferably, the comparison of the data value with the state threshold comprises the following steps:

[0022] S11: The wireless communication module transmits the monitoring data of the energy storage system to the cloud platform or the remote monitoring center regularly or in real time. After receiving the data, the monitoring center will perform status analysis on each data object;

[0023] S12: The monitoring system compares the current value of the data object with the corresponding state threshold;

[0024] S13: If the data value reaches or exceeds the preset threshold, the data object enters the next step of operation, otherwise, continue to capture the next data object and repeat this step until all data objects are checked.

[0025] Preferably, the wireless communication module encapsulates the collected data into a format suitable for transmission, sends the data to a cloud platform or a remote monitoring center via Wi-Fi, Zigbee, LoRa, or NB-IoT wireless communication protocols, and uses TCP / IP, UDP, or MQTT protocols to achieve data communication transmission.

[0026] Preferably, the updating of the data object state and the bidirectional linked list comprises the following steps:

[0027] S21: Searching for data object: Searching in the bidirectional linked list whether the data object already exists. If it does exist, update the number of occurrences of its state, and update the state of the data object according to the new collected data;

[0028] S22: inserting a new data object: if the data object does not exist in the bidirectional linked list, it means that the data object is a new data object, and the system inserts it into the linked list;

[0029] S23: Data transmission and alarm: Through the wireless communication module, the system sends the latest status and related information of the data object to the cloud platform or control center, and prompts the user or maintenance personnel to take necessary measures through the alarm mechanism.

[0030] Preferably, the polling and monitoring comprises the following steps:

[0031] S31: Repeat: Repeat steps S3 and S4 until all monitored data objects are processed. During the process, the system continuously polls and monitors the data objects and updates their status in a timely manner;

[0032] S32: Real-time data update: The system regularly transmits real-time data through wireless communication, compares and analyzes the new data with historical data, and adjusts the operation strategy of the energy storage system;

[0033] S33: Dynamically adjust thresholds: Based on long-term data accumulation and environmental changes, the system can receive control instructions through wireless communication and dynamically adjust status thresholds or operating strategies to ensure efficient and safe operation of the energy storage system.

[0034] Preferably, in the process of comparing and analyzing the new data with the historical data, the real-time data is smoothed by sliding average to reduce short-term fluctuations or noise in the data, thereby helping the system to more stably monitor and adjust the state of the energy storage system. The sliding average formula is: Where n is the size of the sliding window, which represents the number of data points used to calculate the average; Data[i] is the i-th data point in the window.

[0035] (III) Beneficial effects

[0036] Compared with the prior art, the present invention provides a method for monitoring the state of an energy storage system based on wireless communication, which has the following beneficial effects: the present invention first collects real-time data such as battery voltage, current, temperature, power, etc. in the energy storage system through a wireless communication module, and defines data objects, each of which contains attributes such as data unique identification, data value, and data state. Subsequently, a bidirectional linked list is established to store the information of the data object, and a state threshold is set. The current value of the data object is compared with the state threshold to determine whether the data object has reached an alarm or fault state, and the data object state and bidirectional linked list information are updated. The system sends the latest state and related information of the data object to a remote cloud platform or a control center through a wireless communication module, and smoothes the real-time data according to a sliding average algorithm to reduce short-term fluctuations, dynamically adjust the threshold, ensure the efficient and safe operation of the energy storage system, and realize real-time, accurate, and reliable monitoring and management of the state of the energy storage system. During the entire monitoring process, the system repeatedly performs operations such as data collection, state judgment, and updating of bidirectional linked lists through polling and monitoring mechanisms, thereby ensuring the integrity and real-time nature of the monitoring data, and providing comprehensive and accurate data analysis and strategy adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of the monitoring method of the present invention;

[0038] Figure 2 It is the extreme value calculation and data object management diagram of the present invention;

[0039] Figure 3 It is a schematic diagram of the insertion operation of the bidirectional linked list of the present invention;

[0040] Figure 4 This is a working diagram of the wireless communication module of the present invention;

[0041] Figure 5 This is a flow chart of the updating and searching operation of a bidirectional linked list of the present invention;

[0042] Figure 6 The overall process of polling and monitoring of the present invention;

[0043] Figure 7 This is an application diagram of the sliding average of the present invention. DETAILED DESCRIPTION

[0044] In order to better understand the purpose, structure and function of the present invention, in order to realize accurate monitoring of the state of the energy storage system, the present invention first collects real-time data such as battery voltage, current, temperature, power, etc. in the energy storage system through a wireless communication module, and defines data objects, each of which contains attributes such as data unique identification, data value and data state. Then a two-way linked list is established to store the information of the data object, and a state threshold is set. The current value of the data object is compared with the state threshold to determine whether the data object has reached an alarm or fault state, and the data object state and two-way linked list information are updated. The system sends the latest state and related information of the data object to the remote cloud platform or control center through the wireless communication module, and smoothes the real-time data according to the sliding average algorithm to reduce short-term fluctuations, dynamically adjust the threshold, ensure the efficient and safe operation of the energy storage system, and realize real-time, accurate and reliable monitoring and management of the state of the energy storage system. During the entire monitoring process, the system repeatedly performs operations such as data collection, state judgment, and updating of the two-way linked list through polling and monitoring mechanisms, thereby ensuring the integrity and real-time nature of the monitoring data, and providing comprehensive and accurate data analysis and strategy adjustment. A method for monitoring the state of an energy storage system based on wireless communication of the present invention is further described in detail.

[0045] refer to Figure 1 , the present invention: a method for monitoring the state of an energy storage system based on wireless communication, comprising the following steps:

[0046] S1: Obtain extreme value data within the monitoring period of the energy storage system;

[0047] Specifically, the definition of the extreme value data is to define each collected extreme value data as a data object, and the data object has the following attributes:

[0048] Data unique identifier (ID): used to identify data objects;

[0049] Data value: the actual data collected;

[0050] Data status: the status after comparing the collected value with the preset status threshold;

[0051] Status Occurrence Count: records the number of times the data object status changes, used to identify frequently occurring problems.

[0052] The data acquisition for the energy storage system is based on the real-time data of each sensor in the energy storage system collected by the wireless communication module, the wireless communication module includes one or more of Wi-Fi, LoRa or Zigbee, and the real-time data includes battery voltage, current, temperature and power.

[0053] For further reference, Figure 2In the technical solution of this embodiment, extreme value data within the monitoring cycle of the energy storage system is obtained. In each monitoring cycle, the system will collect data of the same parameter in real time and calculate the maximum value (maximum value) and minimum value (minimum value) within the cycle. For example, the maximum and minimum values ​​of the battery voltage within a certain cycle, or the peak value of the current value, are calculated through extreme value calculation. For each collection cycle, the maximum and minimum values ​​will be recorded as data objects and uploaded to the cloud platform or remote monitoring center through the wireless communication module;

[0054] During the monitoring period, extreme values ​​(maximum and minimum values) are usually calculated by statistically calculating the raw data of each monitoring period to obtain the most extreme data point;

[0055] Maximum value: MaxValue=max(Data1,Data2,...,Data n )

[0056] Minimum value: MinValue=min(Data1,Data2,...,Data n )

[0057] Data1,Data2,...,Data n It is all the collected data within a monitoring cycle;

[0058] The definition of a data object includes data value, data state and number of state occurrences. The data state is obtained by comparing it with a preset threshold;

[0059] Each data object has a unique identifier (ID), which is used to search the bidirectional linked list. If the data object already exists, its attributes (state, number of state occurrences, etc.) are updated. If it does not exist, a new one is created and inserted.

[0060] Maintaining data structures through search and insertion operations:

[0061] Find the data object (DataID) → if it already exists, update the data status and times; if it does not exist, insert a new data pair;

[0062] The above methods help the system process and analyze the data of each monitoring cycle, determine the status of the equipment, and finally generate data objects for further monitoring, analysis and control.

[0063] S2: Establish a bidirectional linked list and state threshold;

[0064] Specifically, the bidirectional linked list is established: a bidirectional linked list is established for each data object to store the information of the data object. The bidirectional linked list structure can provide efficient addition, deletion and query operations;

[0065] The state threshold preset: multiple state thresholds are preset according to the working requirements and safety standards of the equipment, and the thresholds can be dynamically adjusted through wireless communication to adapt to different operating conditions and environmental changes.

[0066] For further reference, Figure 3 In the technical solution of this embodiment, a bidirectional linked list and a state threshold are established. When inserting a new node into the bidirectional linked list, the pointers of the previous node and the next node need to be updated to ensure that the structure of the bidirectional linked list is not destroyed. The insertion operation:

[0067] Head insertion: insert a new node into the beginning of the linked list;

[0068] Tail insertion: insert a new node to the end of the linked list;

[0069] Middle insertion: insert a node at a specified position;

[0070] When searching, we usually search whether a data object already exists in a doubly linked list by traversing the linked list. Due to the characteristics of a doubly linked list, each node has pointers to the previous and next nodes, so we can start the search from the head or the tail.

[0071] Original linked list structure: head->node 1->node 2->node 3->tail;

[0072] Insert operation: We insert a new node between node 1 and node 2;

[0073] Insertion process: the front pointer of the new node points to node 1, the back pointer points to node 2, the back pointer of node 1 points to the new node, and the front pointer of node 2 points to the new node;

[0074] Update the linked list: After the insertion is completed, the connection of the linked list becomes: head->node 1->new node->node 2->node 3->tail.

[0075] S3: comparison of data value with state threshold;

[0076] Specifically, the comparison between the data value and the state threshold value includes the following steps:

[0077] S11: The wireless communication module transmits the monitoring data of the energy storage system to the cloud platform or the remote monitoring center regularly or in real time. After receiving the data, the monitoring center will perform status analysis on each data object;

[0078] S12: The monitoring system compares the current value of the data object with the corresponding state threshold;

[0079] S13: If the data value reaches or exceeds the preset threshold, the data object enters the next step of operation, otherwise, continue to capture the next data object and repeat this step until all data objects are checked.

[0080] For further reference, Figure 4 In the technical solution of this embodiment, the comparison between the data value and the state threshold is:

[0081] The wireless communication module encapsulates the collected data into a format suitable for transmission;

[0082] The data may include the following information:

[0083] Data Identifier: A unique ID that identifies the data.

[0084] Data value: specific monitoring value (such as battery voltage, temperature, etc.).

[0085] Timestamp: The time when the data was collected.

[0086] Device ID: Identifies the energy storage device from which the data comes.

[0087] The above data is sent to the cloud platform or remote monitoring center, usually through wireless communication protocols (such as Wi-Fi, Zigbee, LoRa, NB-IoT, etc.). Data transmission can use TCP / IP protocol, UDP or MQTT protocol, etc. The specific protocol depends on the communication requirements of the actual application.

[0088] After receiving the data, the cloud platform or remote monitoring center will decode and analyze it to restore the original monitoring data;

[0089] The parsing process includes: data verification, redundancy removal, error correction, etc. For example, if packet loss or data corruption occurs during data transmission, the receiving end may perform a retransmission mechanism or error checking.

[0090] After receiving the data, the cloud platform or remote monitoring center will make a status judgment on the data, and each data object will be compared with the preset status threshold;

[0091] Normal state: the data value is within the set threshold range;

[0092] Warning status: data value exceeds the normal range, but not serious;

[0093] Fault status: The data value seriously exceeds the threshold, which may mean device failure;

[0094] Based on these comparison results, the cloud platform will annotate the status of each data object and may send alerts or take other actions based on the status.

[0095] S4: Update the data object status and the bidirectional linked list;

[0096] Specifically, the updating of the data object state and the bidirectional linked list includes the following steps:

[0097] S21: Searching for data object: Searching in the bidirectional linked list whether the data object already exists. If it does exist, update the number of occurrences of its state, and update the state of the data object according to the new collected data;

[0098] S22: inserting a new data object: if the data object does not exist in the bidirectional linked list, it means that the data object is a new data object, and the system inserts it into the linked list;

[0099] S23: Data transmission and alarm: Through the wireless communication module, the system sends the latest status and related information of the data object to the cloud platform or control center, and prompts the user or maintenance personnel to take necessary measures through the alarm mechanism.

[0100] For further reference, Figure 5 In the technical solution of this embodiment, the data object state and the bidirectional linked list are updated, and the communication logic of the wireless communication module is:

[0101] Updating and searching data objects:

[0102] When updating the state of a data object, first determine whether the data object already exists by searching the bidirectional linked list. If it does exist, the system updates the state of the data object (such as increasing the number of warnings). If it does not exist, insert the new data object into the linked list.

[0103] Update process:

[0104] The system obtains new monitoring data (such as the latest battery voltage, temperature, etc.).

[0105] The status of the corresponding data object is updated based on this data and marked as normal, warning or fault.

[0106] If the data object already exists in the bidirectional linked list, the system will increase the "status occurrence count" of the data object (such as increasing the number of warnings, faults, etc.); if the data object does not exist in the bidirectional linked list, it will be inserted as a new data object.

[0107] S5: Polling and monitoring;

[0108] Specifically, the polling and monitoring includes the following steps:

[0109] S31: Repeat: Repeat steps S3 and S4 until all monitored data objects are processed. During the process, the system continuously polls and monitors the data objects and updates their status in a timely manner;

[0110] S32: Real-time data update: The system regularly transmits real-time data through wireless communication, compares and analyzes the new data with historical data, and adjusts the operation strategy of the energy storage system;

[0111] S33: Dynamically adjust thresholds: Based on long-term data accumulation and environmental changes, the system can receive control instructions through wireless communication and dynamically adjust status thresholds or operating strategies to ensure efficient and safe operation of the energy storage system.

[0112] For further reference, Figure 6 and Figure 7 In the technical solution of this embodiment, the polling and monitoring process involves the following key operations:

[0113] Repeat execution: The system will repeat steps S3 and S4 until all monitoring data objects are processed to ensure the integrity and real-time nature of data processing.

[0114] Real-time data update: The system regularly transmits real-time data via wireless communication and compares and analyzes new data with historical data;

[0115] Comparison of new data with historical data:

[0116] ΔData=CurrentData-PreviousData

[0117] In the statistical analysis of S5, real-time data is smoothed by sliding average to reduce short-term fluctuations or noise in the data, thereby helping the system to more stably monitor and adjust the state of the energy storage system. Real-time monitoring data (such as battery voltage, current, etc.) may be affected by various instantaneous fluctuations and noise. These short-term fluctuations do not necessarily reflect the true state of the equipment. The sliding average can smooth out these short-term fluctuations by calculating the average value of data within a certain period, making the data more stable and reliable;

[0118] Sliding average formula:

[0119] n is the size of the sliding window, which indicates the number of data points used to calculate the average;

[0120] Data[i] is the i-th data point in the window;

[0121] The sliding average helps to dynamically adjust the threshold of the system. As time goes by, the state of the energy storage device will gradually stabilize. The sliding average can more accurately calculate a suitable and stable threshold instead of relying on instantaneous numerical changes.

[0122] It is to be understood that the present invention is described by some embodiments, and it is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of the present invention.

Claims

1. A method for monitoring the state of an energy storage system based on wireless communication, characterized in that: The following steps are involved: S1: Obtain extreme value data within the monitoring period of the energy storage system; S2: Establish a bidirectional linked list and state threshold; S3: comparison of data value with state threshold; S4: Update the data object status and the bidirectional linked list; S5: Polling and monitoring.

2. A method for monitoring the state of an energy storage system based on wireless communication according to claim 1, characterized in that: The definition of the extreme value data is to define each collected extreme value data as a data object, and the data object has the following attributes: Data unique identifier (ID): used to identify data objects; Data value: the actual data collected; Data status: the status after comparing the collected value with the preset status threshold; Status Occurrence Count: records the number of times the data object status changes, used to identify frequently occurring problems.

3. A method for monitoring the state of an energy storage system based on wireless communication according to claim 2, characterized in that: The data acquisition for the energy storage system is based on the real-time data of each sensor in the energy storage system collected by the wireless communication module, the wireless communication module includes one or more of Wi-Fi, LoRa or Zigbee, and the real-time data includes battery voltage, current, temperature and power.

4. The method for monitoring the state of an energy storage system based on wireless communication according to claim 3, characterized in that: The bidirectional linked list is established: a bidirectional linked list is established for each data object to store the information of the data object. The bidirectional linked list structure can provide efficient addition, deletion and query operations; The state threshold preset: multiple state thresholds are preset according to the working requirements and safety standards of the equipment, and the thresholds can be dynamically adjusted through wireless communication to adapt to different operating conditions and environmental changes.

5. The method for monitoring the state of an energy storage system based on wireless communication according to claim 4, characterized in that: The comparison of the data value with the state threshold comprises the following steps: S11: The wireless communication module transmits the monitoring data of the energy storage system to the cloud platform or the remote monitoring center regularly or in real time. After receiving the data, the monitoring center will perform status analysis on each data object; S12: The monitoring system compares the current value of the data object with the corresponding state threshold; S13: If the data value reaches or exceeds the preset threshold, the data object enters the next step of operation, otherwise, continue to capture the next data object and repeat this step until all data objects are checked.

6. A method for monitoring the state of an energy storage system based on wireless communication according to claim 5, characterized in that: The wireless communication module encapsulates the collected data into a format suitable for transmission, sends the data to a cloud platform or a remote monitoring center via Wi-Fi, Zigbee, LoRa, or NB-IoT wireless communication protocols, and uses TCP / IP, UDP, or MQTT protocols to achieve data communication transmission.

7. A method for monitoring the state of an energy storage system based on wireless communication according to claim 6, characterized in that: The updating of the data object state and the bidirectional linked list comprises the following steps: S21: Searching for data object: Searching in the bidirectional linked list whether the data object already exists. If it does exist, update the number of occurrences of its state, and update the state of the data object according to the new collected data; S22: inserting a new data object: if the data object does not exist in the bidirectional linked list, it means that the data object is a new data object, and the system inserts it into the linked list; S23: Data transmission and alarm: Through the wireless communication module, the system sends the latest status and related information of the data object to the cloud platform or control center, and prompts the user or maintenance personnel to take necessary measures through the alarm mechanism.

8. The method for monitoring the state of an energy storage system based on wireless communication according to claim 7, characterized in that: The polling and monitoring includes the following steps: S31: Repeat: Repeat steps S3 and S4 until all monitored data objects are processed. During the process, the system continuously polls and monitors the data objects and updates their status in a timely manner; S32: Real-time data update: The system regularly transmits real-time data through wireless communication, compares and analyzes the new data with historical data, and adjusts the operation strategy of the energy storage system; S33: Dynamically adjust thresholds: Based on long-term data accumulation and environmental changes, the system can receive control instructions through wireless communication and dynamically adjust status thresholds or operating strategies to ensure efficient and safe operation of the energy storage system.

9. The method for monitoring the state of an energy storage system based on wireless communication according to claim 8, characterized in that: In the process of comparing and analyzing the new data with the historical data, the real-time data is smoothed by sliding average to reduce short-term fluctuations or noise in the data, thereby helping the system to more stably monitor and adjust the state of the energy storage system. The sliding average formula is: Where n is the size of the sliding window, which represents the number of data points used to calculate the average; Data[i] is the i-th data point in the window.

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