Real-time communication and data interaction method for coordinated operation of energy storage power station and power grid dispatching

Abstract

The invention discloses a real-time communication and data interaction method for cooperative operation of an energy storage power station and power grid dispatching, relates to the technical field of data processing, and solves the problems that transmission rate control only depends on a simple index and a fixed adjustment mode, cannot adapt to dynamic change of a network load, and is poor in reliability. In order to solve the technical problems of data redundancy and low transmission efficiency in the transmission process in the prior art, the data transmission rate can be adjusted more flexibly and accurately according to the real-time change of the network load by constructing a multi-dimensional load monitoring system and comprehensively considering multiple indexes such as the CPU utilization rate, the memory utilization rate, the network bandwidth utilization rate and the packet loss rate; the data transmission efficiency and the network utilization rate are improved, the stability and smoothness of data transmission are guaranteed, binary conversion, segmentation, recombination, encryption and other processing are carried out on data, the data are classified and recombined according to the sum of binary numbers, encryption is combined with parity, and the data security is enhanced; and adding a meta-information header to integrate data, and optimizing a transmission structure.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a real-time communication and data interaction method for the coordinated operation of an energy storage power station and power grid dispatching. Background Art

[0002] In scenarios where energy storage power stations operate in tandem with grid dispatchers, real-time communication and data exchange are crucial for achieving efficient coordinated control. With the advancement of intelligent and digital power systems, the types of data generated by energy storage power stations are becoming increasingly complex, including equipment operating status data, power regulation data, and fault alarm data. Grid dispatchers are placing increasingly stringent requirements on the real-time, accurate, and reliable transmission of this data.

[0003] Patent application publication number CN109039851A discloses an interactive data processing method, apparatus, computer device, and storage medium. The method comprises: conducting real-time interaction through virtual conversation members in a virtual conversation scenario; obtaining a trigger instruction for an asynchronous message; interrupting the real-time interaction that is mutually exclusive with the asynchronous message acquisition method when the asynchronous message acquisition method corresponding to the trigger instruction is mutually exclusive with the real-time interaction; obtaining an asynchronous message for playback in the virtual conversation scenario according to the trigger instruction; sending the obtained asynchronous message; and resuming the interrupted real-time interaction. This method integrates real-time interaction and asynchronous messaging, enabling users to increase the amount of interactive information by sending asynchronous interaction messages during real-time interactive communication.

[0004] Traditional data interaction methods often use fixed transmission strategies and simple classification methods, which are difficult to adapt to complex and changing network environments and diverse data needs. In terms of communication channel management, transmission rate adjustment is usually based on a single indicator, lacking multi-dimensional monitoring and dynamic optimization of network load; in the data classification process, the real-time characteristics of the data and differences in business needs are not fully considered, resulting in insufficient priority for key data transmission; the processing steps before data transmission are relatively extensive, without deep segmentation, reorganization and encryption of data, and unable to effectively guarantee data security and transmission efficiency. These problems limit the synergy between energy storage power stations and grid dispatching, making it difficult to meet the requirements of stable operation and efficient dispatching of new power systems. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a real-time communication and data interaction method for the coordinated operation of energy storage power stations and power grid dispatching, which solves the problems of relying solely on simple indicators and fixed adjustment methods for transmission rate control, being unable to adapt to dynamic changes in network load, and having data redundancy and low transmission efficiency during the transmission process.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a real-time communication and data interaction method for the coordinated operation of an energy storage power station and a power grid dispatcher, the method specifically comprising the following steps:

[0007] Calculate the transmission energy standard corresponding to the same type of communication data based on historical data, and obtain the judgment index by combining the average value. At the same time, compare it with the preset value to obtain the priority communication data and secondary communication data;

[0008] Determine the real-time load of the communication channel, generate information to reduce or increase the transmission speed, and perform linear adjustment processing based on the real-time communication data to generate data communication information;

[0009] The classified real-time communication data is reclassified to obtain real-time and periodic data. At the same time, an interaction strategy is formulated to generate interaction strategy information, and the data is evenly divided according to the corresponding data capacity to obtain an evenly divided data flow.

[0010] Perform binary conversion on the evenly divided data stream to obtain a converted evenly divided data stream, and divide it into secondary segments in sequence, and mark the secondary segments with the same sum of binary numbers as segments with the same value;

[0011] The data streams are combined according to the parity of the number of converted and evenly divided data streams to generate a combined package, and the combined packages are uniformly combined to generate a recombined data stream.

[0012] As a further solution of the present invention, the specific method of obtaining the judgment index is:

[0013] Classify the historical communication data by type, and obtain a set of communication data of the same type, denoted as i, where i = 1, 2, ..., j, where j represents the number of types of communication data of the same type;

[0014] For each type i, count the number of transmissions Ci within the time window T and obtain the single transmission volume L Ci , according to the formula Calculate the transmission energy standard K i , repeat the calculation of i for m time windows T, and get m K i value, and calculate m transmission energy standards K i The calculated average value is used as the judgment index for the same type of communication data i.

[0015] As a further solution of the present invention, the specific method of obtaining the priority communication data and the secondary communication data by comparing and classifying with the preset values is:

[0016] The obtained judgment index is compared with the preset value, and the specific value of the preset value is set by the operator. The same type of communication data corresponding to the judgment index greater than the preset value is classified as priority communication data, and the same type of communication data corresponding to the judgment index less than the preset value is classified as secondary communication data.

[0017] As a further solution of the present invention, the specific method of generating the transmission speed reduction or increase information is:

[0018] Acquire real-time communication data and classify it into priority communication data and secondary communication data, then obtain the real-time load corresponding to the communication channel and compare it with the load threshold;

[0019] If the real-time load is greater than the load threshold, a speed reduction transmission message is generated. Conversely, if the real-time load is less than the load threshold, a speed increase transmission message is generated.

[0020] As a further solution of the present invention, the specific method of generating data communication information is:

[0021] Then, a linear adjustment algorithm is selected for adjustment processing based on the generated speed reduction or speed increase transmission information, and priority communication processing is performed on the classified priority communication data. At the same time, it is sorted from large to small according to the obtained transmission energy standard. Secondly, the secondary communication data is sorted from large to small according to the transmission energy standard, and data communication information is generated.

[0022] As a further solution of the present invention, the specific method of obtaining the evenly divided data stream is:

[0023] Then, the classified real-time communication data is obtained, and a secondary analysis is performed on the obtained real-time communication data according to the real-time nature of the data to obtain real-time data and periodic data. Then, different interaction strategies are formulated for the classified real-time data and periodic data to generate interaction strategy information;

[0024] At the same time, all real-time communication data are labeled as n, and n=1, 2, ..., m, where m represents the amount of real-time communication data, and the obtained real-time communication data are evenly divided according to the data capacity to obtain evenly divided data streams and labeled as n1 and n2, and then interactive encryption processing is performed based on the obtained evenly divided data streams.

[0025] As a further solution of the present invention, the specific method of obtaining the segments with the same value is:

[0026] Perform binary conversion on the evenly divided data stream to obtain a converted evenly divided data stream. Sequentially take every four binary numbers in the converted evenly divided data stream as units to obtain secondary segments. All the converted evenly divided data streams are processed in sequence, and the sum of the binary numbers of each converted evenly divided data stream is calculated. Secondary segments with the same binary number sum are classified as segments with the same value.

[0027] As a further solution of the present invention, the specific method of generating the recombined data stream is:

[0028] Perform different reassembly and encryption processes based on the number of converted and evenly divided data streams. If the number of converted and evenly divided data streams is an odd number, select two groups of segments with the same numerical value in the odd digits in sequence and combine them into a combined package. Repeat this operation for all segments with the same numerical value.

[0029] If the number of converted and evenly divided data streams is even, select two groups of segments with the same value in the even position in order and combine them into a combined package. Repeat this operation for all segments with the same value.

[0030] All combined packets are merged into a reassembled data stream for interactive transmission.

[0031] The present invention provides a real-time communication and data interaction method for the coordinated operation of energy storage power stations and power grid dispatching. Compared with the existing technology, it has the following advantages:

[0032] This invention classifies communication data into priority and secondary communication data, and then performs a secondary classification based on time series characteristics and business needs to distinguish between real-time data and periodic data. This classification method can more accurately identify the importance and urgency of data, provide a basis for prioritizing the transmission of critical data, optimize the allocation of communication resources, and improve the response speed and accuracy of power grid scheduling and energy storage power station operations.

[0033] This invention builds a multidimensional load monitoring system that comprehensively considers multiple indicators, including CPU usage, memory usage, network bandwidth utilization, and packet loss rate, and uses a genetic algorithm to optimize load thresholds. Combined with an improved linear regulation algorithm and the introduction of a dynamic adjustment factor, this system can more flexibly and accurately adjust the data transmission rate based on real-time changes in network load. This avoids network congestion and resource waste, improves data transmission efficiency and network utilization, and ensures the stability and smoothness of data transmission.

[0034] This invention develops refined interaction strategies tailored to the characteristics of real-time and periodic data. Real-time data utilizes independent high-speed channels, low-latency protocols, and priority queues to ensure instant data interaction. For periodic data, intelligent scheduling, batch transmission, and compression technologies reduce network bandwidth usage. This meets the transmission requirements of different data types, improves the pertinence and effectiveness of data interaction, and enhances overall system performance.

[0035] This invention performs binary conversion, segmentation, reorganization, and encryption on data. Data integrity is ensured through CRC checksums and data padding. Data is reorganized by binary sum and encrypted using parity to enhance data security. Meta-information headers are added to integrate data and optimize transmission structures. This effectively prevents data leakage and tampering, reduces transmission redundancy, and improves data transmission efficiency and reliability, providing a solid data security guarantee for the coordinated operation of energy storage power stations and power grid dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a diagram of the steps of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0038] See also Figure 1 The present application provides a real-time communication and data interaction method for the coordinated operation of an energy storage power station and a power grid dispatcher, the method specifically comprising the following steps:

[0039] Step S1: Obtain historical communication records and corresponding communication data, classify the communication data according to data type, obtain the same type of communication data, and then calculate the transmission energy standard corresponding to the same type of communication data within time T. The specific calculation method is to label the same type of communication data as i, and i = 1, 2, ..., j, where j represents the number of types of communication data of the same type, and at the same time obtain the number of transmissions corresponding to the same type of data i within time T as Ci, and obtain the single transmission amount L corresponding to the transmission number Ci Ci , then according to the formula Calculate the transmission energy K corresponding to the same type of communication data i i Similarly, the transmission energy K of m data of the same type i within the same time T is i Perform calculations and calculate m transmission energy standards K i The average value of the calculated value is used as the judgment index of the same type of communication data i;

[0040] The obtained judgment index is compared with the preset value, and the specific value of the preset value is set by the operator. The same type of communication data corresponding to the judgment index greater than the preset value is classified as priority communication data, and the same type of communication data corresponding to the judgment index less than the preset value is classified as secondary communication data.

[0041] Step S2: Build a multi-dimensional load monitoring system. In addition to CPU usage, memory usage, and port queue length, add network bandwidth utilization, packet loss rate, delay jitter and other indicators to monitor. Compare the real-time load with the dynamic load threshold. The threshold is generated by a genetic algorithm based on historical load data, device performance parameters, business priority and other factors. At the same time, a configurable buffer range is set (such as a 5%-10% fluctuation in the threshold). When the real-time load exceeds the threshold range:

[0042] If it is greater than the upper threshold, the speed reduction mechanism is triggered, and speed reduction transmission information including speed reduction ratio, effective time and other information is generated.

[0043] If it is less than the lower threshold, the speed increase mechanism is triggered and speed increase transmission information is generated;

[0044] An improved linear adjustment algorithm is used, and an adjustment factor α is introduced (dynamically determined based on network status and data type, ranging from 0.5 to 1.5). Taking CPU usage as an example, the adjustment formula is:

[0045] Speed reduction:

[0046] Speed up:

[0047] After receiving the adjustment information, the data sender performs rate adjustment by adjusting the TCP window size, UDP transmission frequency, and other methods, and provides real-time feedback on the adjustment status. After adjustment, the load and transmission quality are continuously monitored. If the expected effect is not achieved, secondary adjustment is initiated or a nonlinear adjustment algorithm is switched.

[0048] Priority queues are generated by sorting priority and secondary communication data by transmission energy index from large to small. When transmission energy indexes are the same, the priority is further differentiated by combining factors such as data generation time (newer data has higher priority) and service urgency.

[0049] Prioritize communication data transmission, adopt multi-path concurrent transmission and retransmission mechanisms to ensure reliability;

[0050] Secondary communication data dynamically allocates transmission resources based on the remaining channel bandwidth and load conditions, supporting batch transmission of data with high delay tolerance.

[0051] Step S3: After obtaining the classified priority communication data and secondary communication data, a dual judgment mechanism based on time series characteristics and business needs is constructed for secondary analysis, and a real-time monitoring module is deployed to evaluate the data update frequency and business response requirements. When the data update interval is less than the set threshold (such as 1 second) and the business requires that the data must be used for decision-making or control within a very short time (such as 500 milliseconds), it is determined to be real-time data. For example, real-time fault alarm data of energy storage power station equipment must be processed immediately once it is generated to ensure system safety;

[0052] By using historical data pattern matching algorithms, we analyze the data generation patterns. If the data exhibits stable periodic characteristics, such as grid load statistics generated every 15 minutes, equipment maintenance reports generated on a fixed date every month, and the periodic fluctuation range is within an acceptable error (such as ±5%), then it is determined to be periodic data.

[0053] Develop refined interaction strategies based on the characteristics of real-time and periodic data;

[0054] Real-time data interaction: Establish an independent high-speed transmission channel and adopt a low-latency communication protocol (such as UDP combined with QUIC protocol) to ensure that data is pushed to the target system immediately after it is generated. At the same time, set up a data priority queue. When network resources are tight, real-time data can preempt the transmission resources of other data to ensure instant data interaction. In addition, establish a data confirmation and retransmission mechanism. If the receiver does not feedback the confirmation information within the specified time (such as 1 second), the sender automatically retransmits the data to avoid data loss;

[0055] Periodic data exchange: Design an intelligent scheduling algorithm based on the data cycle. Before the start of the data cycle, wake up the data acquisition and transmission modules to perform data preprocessing and packaging. Use batch transmission combined with compression techniques (such as the Zstandard algorithm) to reduce the amount of data transmitted and reduce network bandwidth usage. For data that fails to transmit, record the failure time and cause, prioritize retransmission in the next cycle, and set a maximum number of retransmissions (e.g., three). If this number is exceeded, an alarm mechanism is triggered.

[0056] All real-time communication data are labeled as n, and n=1, 2, ..., m, where m represents the amount of real-time communication data. The obtained real-time communication data are evenly divided according to the data capacity to obtain evenly divided data streams and labeled as n1 and n2. Then, interactive encryption processing is performed based on the obtained evenly divided data streams.

[0057] Step S4, after obtaining the equally divided data streams n1 and n2, a standardized binary conversion protocol (such as the binary conversion rules corresponding to encoding methods such as ASCII, UTF-8, etc.) is used to convert the data elements in each data stream into binary format one by one to obtain the converted equally divided data stream. During the conversion process, a data type mapping table is established to record the correspondence between the original data type and the binary representation to facilitate subsequent data restoration. The integrity of the converted binary data stream is checked, and a check code is generated using the CRC (cyclic redundancy check) algorithm and attached to the end of the data stream. If the length of the binary data stream cannot be divided by 4, a fixed fill character (such as 0000) is used for tail padding to ensure the smooth progress of the subsequent segmentation operation;

[0058] Extract four consecutive binary numbers from the converted and evenly divided data stream in sequence as a basic segmentation unit, which serves as the smallest unit for data segmentation. For example, for the converted and evenly divided data stream "1010110011100010...", first extract "1010" as the first segmentation unit, then extract "1100" as the second segmentation unit, and so on. Use each segmentation unit as a boundary to segment the converted and evenly divided data stream to obtain multiple secondary segmentation segments. Establish a segmentation index table to record the starting position, length, and number of segmentation units contained in each secondary segmentation segment in the original evenly divided data stream, which facilitates data positioning and management;

[0059] The same segmentation operation is performed on all converted and equally divided data streams until all data streams are secondary segmented. During the processing, a progress monitoring module is set up to display the segmentation progress in real time. If there is a long period of no progress or an abnormal interruption, the error diagnosis and recovery mechanism is automatically triggered. If data is truncation during the segmentation process (such as network transmission interruption resulting in incomplete data stream), the data integrity is determined based on the checksum. If the data is incomplete, the truncation location is recorded, and the corresponding part of the data is requested to be resent from the data sender, and the segmentation operation is repeated.

[0060] Traverse all quadratic segments and use a parallel computing framework (such as Apache Spark) to sum the binary numbers in each quadratic segment. To avoid data overflow, choose an appropriate data type (such as a long integer or a high-precision numeric type) based on the size of the quadratic segment for the calculation. Finally, obtain the binary sum So corresponding to each quadratic segment, where o = 1, 2, ..., p, where p represents the number of quadratic segments. Build a hash map, using the binary sum So as the key value, and classify quadratic segments with the same sum into a set of segments with the same value. For each sum value, generate a unique identification number and store the corresponding segment with the same value in a container named by the identification number, denoted as Gu (u = 1, 2, ..., g, where g is the number of different sum values).

[0061] When the number of converted and evenly distributed data streams p is an odd number:

[0062] According to the order of data stream number, select the segment set G with the same value of odd bits (1st, 3rd, 5th...) o1 , G o2 Combine. Combine the data streams in the two sets into a combined package in a certain order (such as the original number order), and encrypt the data in the combined package using a symmetric encryption algorithm. The encryption key is associated with the data number and transmission time.

[0063] When the number of converted and evenly divided data streams p is an even number, the set of segments with the same value in the even-numbered bits (2nd, 4th, 6th, ...) is selected and combined according to the order of the data stream numbers, and the odd-numbered bits are processed in the same way to generate a combined packet;

[0064] Deeply integrate all the combined packages from the same group of converted and equally divided data streams. These packages are sorted according to pre-set priorities (e.g., data importance, transmission timeliness, etc.), and a header containing metadata such as data source, encryption method, and reassembly order is added to generate a complete reassembled data stream.

[0065] Some of the data in the above formulas are calculated based on their numerical values and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0066] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A real-time communication and data interaction method for coordinated operation of an energy storage power station and a power grid dispatcher, characterized in that: The method specifically comprises the following steps: Calculate the transmission energy standard corresponding to the same type of communication data based on historical data, and obtain the judgment index by combining the average value. At the same time, compare it with the preset value to obtain the priority communication data and secondary communication data; Determine the real-time load of the communication channel, generate information to reduce or increase the transmission speed, and perform linear adjustment processing based on the real-time communication data to generate data communication information; The classified real-time communication data is reclassified to obtain real-time and periodic data. At the same time, an interaction strategy is formulated to generate interaction strategy information, and the data is evenly divided according to the corresponding data capacity to obtain an evenly divided data flow. Perform binary conversion on the evenly divided data stream to obtain a converted evenly divided data stream, and divide it into secondary segments in sequence, and mark the secondary segments with the same sum of binary numbers as segments with the same value; The data streams are combined according to the parity of the number of converted and evenly divided data streams to generate a combined package, and the combined packages are uniformly combined to generate a recombined data stream.

2. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of obtaining the judgment index is: Classify the historical communication data by type, and obtain a set of communication data of the same type, denoted as i, where i = 1, 2, ..., j, where j represents the number of types of communication data of the same type; For each type i, count the number of transmissions Ci within the time window T and obtain the single transmission volume L Ci , according to the formula Calculate the transmission energy standard K i , repeat the calculation of i for m time windows T, and get m K i value, and calculate m transmission energy standards K i The calculated average value is used as the judgment index for the same type of communication data i.

3. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of obtaining the priority communication data and the secondary communication data by comparing and classifying with the preset values is as follows: The obtained judgment index is compared with the preset value, and the specific value of the preset value is set by the operator. The same type of communication data corresponding to the judgment index greater than the preset value is classified as priority communication data, and the same type of communication data corresponding to the judgment index less than the preset value is classified as secondary communication data.

4. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of generating the transmission speed reduction or increase information is: Acquire real-time communication data and classify it into priority communication data and secondary communication data, then obtain the real-time load corresponding to the communication channel and compare it with the load threshold; If the real-time load is greater than the load threshold, a speed reduction transmission message is generated. Conversely, if the real-time load is less than the load threshold, a speed increase transmission message is generated.

5. The real-time communication and data interaction method for coordinated operation of energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of generating data communication information is: Then, a linear adjustment algorithm is selected for adjustment processing based on the generated speed reduction or speed increase transmission information, and priority communication processing is performed on the classified priority communication data. At the same time, it is sorted from large to small according to the obtained transmission energy standard. Secondly, the secondary communication data is sorted from large to small according to the transmission energy standard, and data communication information is generated.

6. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of obtaining the evenly distributed data stream is: Then, the classified real-time communication data is obtained, and a secondary analysis is performed on the obtained real-time communication data according to the real-time nature of the data to obtain real-time data and periodic data. Then, different interaction strategies are formulated for the classified real-time data and periodic data to generate interaction strategy information; At the same time, all real-time communication data are labeled as n, and n=1, 2, ..., m, where m represents the amount of real-time communication data, and the obtained real-time communication data are evenly divided according to the data capacity to obtain evenly divided data streams and labeled as n1 and n2, and then interactive encryption processing is performed based on the obtained evenly divided data streams.

7. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of obtaining the segments with the same value is: Perform binary conversion on the evenly divided data stream to obtain a converted evenly divided data stream. Sequentially take every four binary numbers in the converted evenly divided data stream as units to obtain secondary segments. All the converted evenly divided data streams are processed in sequence, and the sum of the binary numbers of each converted evenly divided data stream is calculated. Secondary segments with the same binary number sum are classified as segments with the same value.

8. The real-time communication and data interaction method for coordinated operation of an energy storage power station and power grid dispatching according to claim 1 is characterized in that: The specific method of generating the recombined data stream is: Perform different reassembly and encryption processes based on the number of converted and evenly divided data streams. If the number of converted and evenly divided data streams is an odd number, select two groups of segments with the same numerical value in the odd digits in sequence and combine them into a combined package. Repeat this operation for all segments with the same numerical value. If the number of converted and evenly divided data streams is even, select two groups of segments with the same value in the even position in order and combine them into a combined package. Repeat this operation for all segments with the same value. All combined packets are merged into a reassembled data stream for interactive transmission.

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