New energy power generation data integrity monitoring system

Abstract

A new energy power generation data integrity monitoring system relates to the technical field of data monitoring and comprises a cloud server, and the cloud server is in communication connection with a data acquisition module, a data storage module, a data analysis module, a data integrity monitoring module, a client, a data traceability module and a data integrity guarantee module. The data acquisition module acquires electric energy data; the data storage module stores electric energy data; the data analysis module performs electric energy data integrity analysis, and the data integrity monitoring module is used for constructing an electric energy aging window and verifying the integrity of the to-be-detected electric energy data; the client is used for sending a request query data packet for querying the electric energy data to the cloud server; the data tracing module traces the non-integrity reason of the non-integrity electric energy data; the data integrity guarantee module is used for carrying out data integrity guarantee operation on the non-integrity electric energy data; and the accuracy and integrity of electric energy data transmission are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of data monitoring technology, specifically a data integrity monitoring system for new energy power generation. Background Technology

[0002] In existing technologies, when facing edge computing environments, the massive number of power terminal devices on the network edge side of the power monitoring system continuously generate a large amount of power data. This power data comes from different types of devices. If this data is directly uploaded to the cloud, there will be problems such as poor real-time performance, high bandwidth requirements, and high energy consumption.

[0003] Therefore, existing technologies often use a cloud-edge collaboration approach to store and manage large amounts of diverse and heterogeneous power data. However, cloud servers and edge nodes are not entirely reliable. Power data has extremely high requirements for timeliness and accuracy. Data may be lost during data transmission between cloud servers and edge nodes, causing indirect economic losses to the power system due to data loss. How to achieve dataset integrity monitoring and protection between cloud servers and edge nodes is a problem that we urgently need to solve. Here, we provide a new energy power generation data integrity monitoring system. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention aims to provide a new energy power generation data integrity monitoring system, comprising a cloud server, wherein the cloud server is communicatively connected to a data acquisition module, a data storage module, a data analysis module, a data integrity monitoring module, a client, a data traceability module, and a data integrity assurance module;

[0005] The data acquisition module is connected to the cloud server in a distributed manner through IoT nodes, and is used to collect power data from several edge terminal nodes.

[0006] The data storage module is used to store the collected power data of several edge terminal nodes and package the power data into data packets;

[0007] The data analysis module is used to perform power data integrity analysis based on the data packets received by the cloud server in the current collection period, and to divide the power data in the data packets into integrity data and data to be tested based on the power data integrity analysis results.

[0008] The data integrity monitoring module is used to construct a power timeliness window for the data to be tested based on the power data integrity analysis results, and to verify the integrity of the power data to be tested by whether the edge terminal node can resend the power data to be tested within the power timeliness window.

[0009] The client is used to send a request data packet to the cloud server to query power data.

[0010] The data tracing module is used to trace the cause of the incompleteness of incomplete power data based on the feedback string group sent by the cloud server to the edge terminal node;

[0011] The data integrity assurance module is used to perform data integrity assurance operations for non-integrity electrical energy data.

[0012] Furthermore, the process of storing the collected power data of several edge terminal nodes and packaging the power data into data packets by the data storage module includes:

[0013] The data storage module is used to store the power data of several edge terminal nodes, classify the power data of several edge terminal nodes, package the power data of the same edge terminal node in the same collection period into a data packet, set the corresponding edge terminal node identity tag on the data packet, and obtain the collection record of the corresponding edge terminal node. The collection record includes the collection time and collection period.

[0014] Furthermore, the data analysis module performs power data integrity analysis based on the data packets received by the cloud server during the current collection period. The process of dividing the power data in the data packets into intact data and data to be tested based on the power data integrity analysis results includes:

[0015] Select the energy data received in the tth second of the current collection period of the cloud server as s1, perform digest calculation on the received energy data s1 to obtain the digest value m1 of the energy data; add the time character t to the end of the digest value m1 to form the feedback string m1(t), and send the feedback string m1(t) to the edge terminal node.

[0016] Set the power data received by the cloud server at the (t+1)th second of the current collection period as s2. Calculate the digest of the received power data s2 to obtain the digest value m2. Add the time character t+1 to the first segment of the digest value m2 to form the feedback string m2(t+1). Send the feedback string m2(t+1) to the edge terminal node. Repeat the above cloud server operation in this way.

[0017] If the cloud server receives power data sent by the edge terminal node every second during the current collection cycle, and the edge terminal node receives the corresponding power data feedback string every second, then all power data sent by the edge terminal node during the current collection cycle will be marked as complete power data.

[0018] If the cloud server does not receive the power data s1 sent by the edge terminal node in the t-th second of the current collection cycle, the power data sent by the edge terminal node in the t-th second of the current collection cycle will be marked as the power data to be measured.

[0019] Furthermore, the data integrity monitoring module constructs a power timeliness window for the data to be tested based on the power data integrity analysis results. The process of verifying the integrity of the power data to be tested based on whether the edge terminal node can resend the power data to be tested within the power timeliness window includes:

[0020] The timeliness of power data corresponding to several edge terminal nodes is obtained using big data methods, a power timeliness window is constructed, and the length T of the power timeliness window is determined based on the timeliness.

[0021] If the cloud server does not receive the power data s1 sent by the edge terminal node in the current collection period t seconds, it determines the power timeliness window length T of the edge terminal node, opens the power timeliness window in the t seconds, generates a null value k in the t seconds, adds the time character t to the end of the null value k to form the k(t) feedback string, and sends the k(t) feedback string to the edge terminal node.

[0022] When the edge terminal node receives the k(t) feedback string, it resends the power data s1 of the t-th second to the cloud service.

[0023] If the cloud server does not receive the power data s1 resent by the edge terminal node in the t+1 second, but receives the power data s2 sent by the edge terminal node in the t+1 second, it performs a digest calculation on the received power data s2 to obtain the digest value m2 of the power data, adds the time character t+1 to the end of the digest value m2 to form the feedback string m2(t+1), and merges the feedback string k(t) and the feedback string m2(t+1) into the feedback string group {k(t), m2(t+1)}, and sends the feedback string group {k(t), m2(t+1)} to the edge terminal node;

[0024] Similarly, if the cloud server receives the energy data s1 at the t-th second within the energy availability window length T, it generates the feedback string group {m1(t), m2(t+1), ..., mn(t+n-1)} within the energy availability window length T and sends it to the edge terminal node, where (t+n-1) is less than or equal to (t+T).

[0025] If the cloud server does not receive the energy data s1 of the t-th second within the energy availability window length T, then it generates the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)} within the energy availability window length T and sends it to the edge terminal node, where (t+n-1) is less than or equal to (t+T).

[0026] When the cloud server receives the power data s1 within the power time window length T and the edge terminal node receives the feedback string group {m1(t), m2(t+1), ..., mn(t+n-1)}, the power data to be tested is marked as complete power data.

[0027] When the cloud server does not receive power data s1 within the power time window length T and the edge terminal node receives the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)}, the power data to be tested is marked as incomplete power data.

[0028] Furthermore, the process by which the data tracing module traces the cause of incompleteness in incomplete electrical energy data based on the feedback string group sent by the cloud server to the edge terminal node includes:

[0029] Based on the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)} fed back by the cloud server to the edge terminal node, the collection time t of the missing power data in the collection period where the incomplete power data is located is obtained, and the power data of the corresponding edge terminal node in the current collection period within the collection time t is queried in the data storage module according to the collection time t.

[0030] When no energy data for acquisition time t is found in the data storage module, the cause of the incomplete energy data integrity anomaly is marked as an abnormality of the data acquisition device, and a data acquisition device fault warning message is generated for the edge terminal node where the incomplete energy data is located.

[0031] When the data storage module retrieves power data at acquisition time t, it marks the cause of the incomplete power data as a network latency between the edge terminal node and the cloud server, and performs data integrity assurance operations between the edge terminal node and the cloud server.

[0032] Furthermore, the process by which the data integrity assurance module performs data integrity assurance operations for incomplete electrical energy data includes:

[0033] When incomplete power data is generated due to network latency between edge terminal nodes and cloud servers, the maximum allowable data packet transmission volume of the cloud server data packet transmission process is obtained, and the data packet transmission process of the cloud server is divided into a power data window and a data query window. The power data window is used to receive data packets from edge terminal nodes, and the data query window is used to send client request query data packets.

[0034] The sum of the maximum allowed data packet transmission volume of the power data window and the maximum allowed data packet transmission volume of the data query window is equal to the maximum allowed data packet transmission volume of the cloud server.

[0035] A speed-reduction strategy is adopted for the data query window, and the timing of the speed-reduction strategy is determined based on the maximum allowed data packet transmission volume of the power data window and the actual data packet volume received by the power data window.

[0036] Furthermore, the process by which the data integrity assurance module adopts a speed-down strategy for the data query window includes:

[0037] The maximum number of allowed request query data packets for the data query window is initialized to one. Whenever the cloud server terminal sends a feedback string to the edge terminal node, the maximum number of allowed request query data packets for the data query window is increased by one.

[0038] Furthermore, the process by which the data integrity assurance module determines when the data query window ends its rate-reduction strategy based on the maximum allowed data packet transmission volume of the power data window and the actual data packet volume received by the power data window includes:

[0039] Set the data packet redundancy limit. When the maximum allowed data packet transmission volume of the power data window exceeds the sum of the actual data packet volume received by the power data window and the data packet redundancy limit, the data query window speed reduction strategy will end.

[0040] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention ensures the accuracy of data received by the cloud server through a power data reception and feedback mechanism between the cloud server and edge terminal nodes; and sets a power timeliness window for missing power data not received by the cloud server. The cloud server generates a corresponding feedback string group based on whether it has received the missing power data resent by the edge terminal node within the power timeliness window, and traces the cause of the incompleteness of the missing power data based on the feedback string group. This allows relevant personnel to quickly understand the cause of the missing power data, reduces indirect economic losses caused by missing power data, and ensures the integrity of power data based on the cause of incompleteness, significantly improving the accuracy and integrity of power data transmission. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of a new energy power generation data integrity monitoring system according to an embodiment of this application. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0043] like Figure 1 As shown, the new energy power generation data integrity monitoring system includes a cloud server, which is communicatively connected to a data acquisition module, a data storage module, a data analysis module, a data integrity monitoring module, a client, a data traceability module, and a data integrity assurance module.

[0044] The data acquisition module is connected to the cloud server in a distributed manner through IoT nodes, and is used to collect power data from several edge terminal nodes.

[0045] The data storage module is used to store the collected power data of several edge terminal nodes and package the power data into data packets;

[0046] The data analysis module is used to perform power data integrity analysis based on the data packets received by the cloud server in the current collection period, and to divide the power data in the data packets into integrity data and data to be tested based on the power data integrity analysis results.

[0047] The data integrity monitoring module is used to construct a power timeliness window for the data to be tested based on the power data integrity analysis results, and to verify the integrity of the power data to be tested by whether the edge terminal node can resend the power data to be tested within the power timeliness window.

[0048] The client is used to send a request data packet to the cloud server to query power data.

[0049] The data tracing module is used to trace the cause of the incompleteness of incomplete power data based on the feedback string group sent by the cloud server to the edge terminal node;

[0050] The data integrity assurance module is used to perform data integrity assurance operations for non-integrity electrical energy data.

[0051] It should be further explained that, in the specific implementation process, the data storage module stores the collected power data from several edge terminal nodes, and the process of packaging the power data into data packets includes:

[0052] The data storage module is used to store the power data of several edge terminal nodes, classify the power data of several edge terminal nodes, package the power data of the same edge terminal node in the same collection period into a data packet, set the corresponding edge terminal node identity tag on the data packet, and obtain the collection record of the corresponding edge terminal node. The collection record includes the collection time and collection period.

[0053] It should be further explained that, in the specific implementation process, the data analysis module performs power data integrity analysis based on the data packets received by the cloud server during the current collection period. The process of dividing the power data in the data packets into complete data and data to be tested based on the power data integrity analysis results includes:

[0054] Select the energy data received in the tth second of the current collection period of the cloud server as s1, perform digest calculation on the received energy data s1 to obtain the digest value m1 of the energy data; add the time character t to the end of the digest value m1 to form the feedback string m1(t), and send the feedback string m1(t) to the edge terminal node.

[0055] Set the power data received by the cloud server at the (t+1)th second of the current collection period as s2. Calculate the digest of the received power data s2 to obtain the digest value m2. Add the time character t+1 to the first segment of the digest value m2 to form the feedback string m2(t+1). Send the feedback string m2(t+1) to the edge terminal node. Repeat the above cloud server operation in this way.

[0056] If the cloud server receives power data sent by the edge terminal node every second during the current collection cycle, and the edge terminal node receives the corresponding power data feedback string every second, then all power data sent by the edge terminal node during the current collection cycle will be marked as complete power data.

[0057] If the cloud server does not receive the power data s1 sent by the edge terminal node in the t-th second of the current collection cycle, the power data sent by the edge terminal node in the t-th second of the current collection cycle will be marked as the power data to be measured.

[0058] It should be further explained that, in the specific implementation process, the data integrity monitoring module constructs a power timeliness window for the data to be tested based on the power data integrity analysis results. The process of verifying the integrity of the power data to be tested based on whether the edge terminal node can resend the power data to be tested within the power timeliness window includes:

[0059] The timeliness of power data corresponding to several edge terminal nodes is obtained using big data methods, a power timeliness window is constructed, and the length T of the power timeliness window is determined based on the timeliness.

[0060] If the cloud server does not receive the power data s1 sent by the edge terminal node in the current collection period t seconds, it determines the power timeliness window length T of the edge terminal node, opens the power timeliness window in the t seconds, generates a null value k in the t seconds, adds the time character t to the end of the null value k to form the k(t) feedback string, and sends the k(t) feedback string to the edge terminal node.

[0061] When the edge terminal node receives the k(t) feedback string, it resends the power data s1 of the t-th second to the cloud service.

[0062] If the cloud server does not receive the power data s1 resent by the edge terminal node in the t+1 second, but receives the power data s2 sent by the edge terminal node in the t+1 second, it performs a digest calculation on the received power data s2 to obtain the digest value m2 of the power data, adds the time character t+1 to the end of the digest value m2 to form the feedback string m2(t+1), and merges the feedback string k(t) and the feedback string m2(t+1) into the feedback string group {k(t), m2(t+1)}, and sends the feedback string group {k(t), m2(t+1)} to the edge terminal node;

[0063] Similarly, if the cloud server receives the energy data s1 at the t-th second within the energy availability window length T, it generates the feedback string group {m1(t), m2(t+1), ..., mn(t+n-1)} within the energy availability window length T and sends it to the edge terminal node, where (t+n-1) is less than or equal to (t+T).

[0064] If the cloud server does not receive the energy data s1 of the t-th second within the energy availability window length T, then it generates the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)} within the energy availability window length T and sends it to the edge terminal node, where (t+n-1) is less than or equal to (t+T).

[0065] When the cloud server receives the power data s1 within the power time window length T and the edge terminal node receives the feedback string group {m1(t), m2(t+1), ..., mn(t+n-1)}, the power data to be tested is marked as complete power data.

[0066] When the cloud server does not receive power data s1 within the power time window length T and the edge terminal node receives the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)}, the power data to be tested is marked as incomplete power data.

[0067] It should be further explained that, in the specific implementation process, the data tracing module traces the cause of incompleteness in incomplete electrical energy data based on the feedback string group sent by the cloud server to the edge terminal node, including:

[0068] Based on the feedback string group {k(t), m2(t+1), ..., mn(t+n-1)} fed back by the cloud server to the edge terminal node, the collection time t of the missing power data in the collection period where the incomplete power data is located is obtained, and the power data of the corresponding edge terminal node in the current collection period within the collection time t is queried in the data storage module according to the collection time t.

[0069] When no energy data for acquisition time t is found in the data storage module, the cause of the incomplete energy data integrity anomaly is marked as an abnormality of the data acquisition device, and a data acquisition device fault warning message is generated for the edge terminal node where the incomplete energy data is located.

[0070] When the data storage module retrieves power data at acquisition time t, it marks the cause of the incomplete power data as a network latency between the edge terminal node and the cloud server, and performs data integrity assurance operations between the edge terminal node and the cloud server.

[0071] It should be further explained that, in the specific implementation process, the data integrity assurance module performs data integrity assurance operations for non-integrity electrical energy data, including:

[0072] When incomplete power data is generated due to network latency between edge terminal nodes and cloud servers, the maximum allowable data packet transmission volume of the cloud server data packet transmission process is obtained, and the data packet transmission process of the cloud server is divided into a power data window and a data query window. The power data window is used to receive data packets from edge terminal nodes, and the data query window is used to send client request query data packets.

[0073] The sum of the maximum allowed data packet transmission volume of the power data window and the maximum allowed data packet transmission volume of the data query window is equal to the maximum allowed data packet transmission volume of the cloud server.

[0074] A speed-reduction strategy is adopted for the data query window, and the timing of the speed-reduction strategy is determined based on the maximum allowed data packet transmission volume of the power data window and the actual data packet volume received by the power data window.

[0075] It should be further explained that, in the specific implementation process, the process by which the data integrity assurance module adopts a speed-down strategy for the data query window includes:

[0076] The maximum number of allowed request query data packets for the data query window is initialized to one. Whenever the cloud server terminal sends a feedback string to the edge terminal node, the maximum number of allowed request query data packets for the data query window is increased by one.

[0077] It should be further explained that, in the specific implementation process, the process by which the data integrity assurance module determines when the data query window ends its rate-reduction strategy based on the maximum allowed data packet transmission volume of the power data window and the actual data packet volume received by the power data window includes:

[0078] Set the data packet redundancy limit. When the maximum allowed data packet transmission volume of the power data window exceeds the sum of the actual data packet volume received by the power data window and the data packet redundancy limit, the data query window speed reduction strategy will end.

[0079] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A new energy power generation data integrity monitoring system comprising a cloud server, characterized in that, The cloud server is in communication connection with a data acquisition module, a data storage module, a data analysis module, a data integrity monitoring module, a client, a data traceability module and a data integrity guarantee module; The data acquisition module and the cloud server are connected in a distributed manner through an Internet of Things node, and are used to acquire electric energy data of a plurality of edge terminal nodes; The data storage module is used to store the acquired electric energy data of the plurality of edge terminal nodes, and package the electric energy data into data packets; The data analysis module is used to perform electric energy data integrity analysis according to the data packets received by the cloud server in a current acquisition period, and divide the electric energy data in the data packets into integrity data and to-be-tested data according to the electric energy data integrity analysis result; The data integrity monitoring module is used to construct an electric energy time window for the to-be-tested data according to the electric energy data integrity analysis result, and verify the integrity of the to-be-tested electric energy data according to whether the edge terminal node can resend the to-be-tested electric energy data within the electric energy time window; The client is used to send a request query data packet to the cloud server to query electric energy data; The data traceability module is used to trace the non-integrity reason of non-integrity electric energy data according to a feedback character string group sent by the cloud server to the edge terminal node; The data integrity guarantee module is used to perform data integrity guarantee operation for non-integrity electric energy data.

2. The new energy power generation data integrity monitoring system according to claim 1, characterized in that, The data storage module stores the acquired electric energy data of the plurality of edge terminal nodes, and packages the electric energy data into data packets, and the process includes: The data storage module is used to store electric energy data of a plurality of edge terminal nodes, and classify the electric energy data of the plurality of edge terminal nodes, package the electric energy data of the same edge terminal node in the same acquisition period into a data packet, set a corresponding edge terminal node identity tag on the data packet, and acquire an acquisition record of the corresponding edge terminal node, wherein the acquisition record includes acquisition time and acquisition period.

3. The new energy power generation data integrity monitoring system according to claim 2, characterized in that, The data analysis module performs electric energy data integrity analysis according to the data packets received by the cloud server in a current acquisition period, and divides the electric energy data in the data packets into integrity data and to-be-tested data according to the electric energy data integrity analysis result, and the process includes: The electric energy data received by the cloud server in the tthsecond of the current acquisition period is set as s1, the received electric energy data s1 is calculated to obtain the digest value m1 of the electric energy data, and the time character t is added to the tail of the digest value m1 to form the m1(t) feedback character string, and the m1(t) feedback character string is sent to the edge terminal node; The electric energy data sent by the edge terminal node and received by the cloud server in the t+1thsecond of the current acquisition period is set as s2, the received electric energy data s2 is calculated to obtain the digest value m2 of the electric energy data, and the time character t+1 is added to the head of the digest value m2 to form the m2(t+1) feedback character string, and the m2(t+1) feedback character string is sent to the edge terminal node; and the above cloud server operation is repeated. If the cloud server receives the power data sent by the edge terminal node every second in the current collection period, and the edge terminal node receives the corresponding feedback string of the power data every second, the power data sent by the edge terminal node in the current collection period is marked as complete power data; If the cloud server does not receive the power data s1 sent by the edge terminal node in the tth second in the current collection period, the power data in the tth second sent by the edge terminal node in the current collection period is marked as to-be-tested power data.

4. The new energy power generation data integrity monitoring system according to claim 3, characterized in that, The data integrity monitoring module constructs an energy time window for the to-be-tested data according to the energy data integrity analysis result, and verifies the integrity of the to-be-tested power data according to whether the edge terminal node can resend the to-be-tested power data within the energy time window, and the process includes: Using a big data method to obtain the timeliness time corresponding to the energy data of a plurality of edge terminal nodes, constructing an energy time window, and determining the energy time window length T according to the timeliness time; If the cloud server does not receive the power data s1 sent by the edge terminal node in the tth second in the current collection period, the energy time window length T of the edge terminal node is determined, and the energy time window is opened in the tth second, the null value k is generated in the tth second, and the time character t is added to the tail of the null value k to form the k(t) feedback string, and the k(t) feedback string is sent to the edge terminal node; When the edge terminal node receives the k(t) feedback string, the edge terminal node resends the power data s1 in the tth second to the cloud server; If the cloud server does not receive the power data s1 sent by the edge terminal node in the tth second in the current collection period, the energy time window length T of the edge terminal node is determined, and the energy time window is opened in the tth second, the null value k is generated in the tth second, and the time character t is added to the tail of the null value k to form the k(t) feedback string, and the k(t) feedback string is sent to the edge terminal node; In this way, if the cloud server receives the power data s1 in the tth second within the energy time window length T, the {m1(t), m2(t+1),..., mn(t+n-1)} feedback string group is generated within the energy time window length T and sent to the edge terminal node, and (t+n-1) is less than or equal to (t+T) ; If the cloud server does not receive the power data s1 in the tth second within the energy time window length T, the {k(t), m2(t+1),..., mn(t+n-1)} feedback string group is generated within the energy time window length T and sent to the edge terminal node, and (t+n-1) is less than or equal to (t+T) ; If the cloud server does not receive the power data s1 in the tth second within the energy time window length T, the {k(t), m2(t+1),..., mn(t+n-1)} feedback string group is generated within the energy time window length T and sent to the edge terminal node, and (t+n-1) is less than or equal to (t+T) ; When the cloud server receives the electric energy data s1 within the electric energy time window length T and the edge terminal node receives the feedback string group {m1(t), m2(t+1), …, mn(t+n-1)}, the to-be-tested electric energy data is marked as complete electric energy data; When the cloud server does not receive the electric energy data s1 within the electric energy time window length T and the edge terminal node receives the feedback string group {k(t), m2(t+1), …, mn(t+n-1)}, the to-be-tested electric energy data is marked as incomplete electric energy data.

5. The new energy power generation data integrity monitoring system according to claim 4, characterized in that, The process in which the data provenance module traces the reason for the incompleteness of the incomplete electric energy data according to the feedback string group sent by the cloud server to the edge terminal node comprises: According to the feedback string group {k(t), m2(t+1), …, mn(t+n-1)} fed back by the cloud server to the edge terminal node, the acquisition time t of the missing electric energy data in the acquisition period of the incomplete electric energy data is obtained, and the electric energy data corresponding to the acquisition time t in the current acquisition period of the edge terminal node stored in the data storage module is queried; When the electric energy data of the acquisition time t is not queried in the data storage module, the completeness abnormality reason of the incomplete electric energy data is marked as data acquisition equipment abnormality, and data acquisition equipment fault warning information of the edge terminal node where the incomplete electric energy data is located is generated; When the electric energy data of the acquisition time t is queried in the data storage module, the completeness abnormality reason of the incomplete electric energy data is marked as network delay existing between the edge terminal node and the cloud server; and data integrity guarantee operation is performed between the edge terminal node and the cloud server.

6. The new energy power generation data integrity monitoring system according to claim 5, characterized in that, The process in which the data integrity guarantee module performs data integrity guarantee operation for the incomplete electric energy data comprises: When the incomplete electric energy data is generated due to network delay existing between the edge terminal node and the cloud server, the maximum allowed data packet transmission amount of the cloud server data packet transmission process is obtained, the data packet transmission process of the cloud server is divided into an electric energy data window and a data query window, the electric energy data window is used to receive data packets of the edge terminal node, and the data query window is used to send request query data packets of the client; The sum of the maximum allowed data packet transmission amount of the electric energy data window and the maximum allowed data packet transmission amount of the data query window is equal to the maximum allowed data packet transmission amount of the cloud server; A speed reduction strategy is adopted for the data query window, and it is judged when the speed reduction strategy of the data query window ends according to the maximum allowed data packet transmission amount of the electric energy data window and the actual data packet amount received by the electric energy data window.

7. The new energy power generation data integrity monitoring system according to claim 6, characterized in that, The process in which the data integrity guarantee module adopts the speed reduction strategy for the data query window comprises: The maximum allowed request query data packet number of the data query window is initialized, and the maximum allowed request query data packet number is set to one; and the maximum allowed request query data packet number of the data query window is increased by one each time the cloud server terminal sends a feedback string to the edge terminal node.

8. The new energy power generation data integrity monitoring system according to claim 7, characterized in that, The data integrity guarantee module judges when the data query window ends the speed reduction strategy according to the maximum allowed data packet transmission amount of the electric energy data window and the actual data packet amount received by the electric energy data window, and the process includes: A data packet redundancy amount is set, and when the maximum allowed data packet transmission amount of the electric energy data window is greater than the sum of the actual data packet amount received by the electric energy data window and the data packet redundancy amount, the speed reduction strategy of the data query window is ended.

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