Novel power system data management method

Abstract

The invention is suitable for the technical field of data processing, and provides a novel power system data management method. The method comprises the following steps that: a first server side receives new energy power data generated by each novel power system side, and classifies and stores the received new energy power data; the second server side responds to the data calling request, calls the new energy power data of the target category from the first server side, and stores the new energy power data of the target category by adopting a plurality of storage queues; the second server side responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading side according to the priority sequence of the multiple storage queues; and the data reading end processes the read new energy electric power data and displays the data in a regional map, wherein the regional map comprises the new energy electric power information of each novel electric power system end. According to the method, the new energy power data reading efficiency and the data search time can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular to a novel power system data management method. Background Art

[0002] New energy refers to clean and renewable energy generated by using constantly updated resources in nature, such as solar energy, wind energy, etc., as well as biomass energy, geothermal energy, etc. Compared with traditional thermal power generation, new energy power generation has the advantages of environmental protection and sustainability, and is an important direction for future power development.

[0003] Renewable energy power generation involves many system platforms, and the data information format generated by each system platform is inconsistent. In addition, due to the large scale of the new energy power system, a large amount of power data is generated every day. The amount of data involved in the power data process in various new energy power events is huge. Monitoring personnel need to monitor and analyze some important data to understand the operating status of the power system in a timely manner and ensure the stable operation of the power system. This has become an urgent problem that needs to be solved at this stage. Summary of the invention

[0004] In view of this, an embodiment of the present application provides a novel power system data management method, which can improve the data reading efficiency and data search time of new energy power data.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] The present application provides a novel power system data management method, including:

[0007] The first server receives the new energy power data generated by each new power system, and classifies and stores the received new energy power data;

[0008] The second server side responds to the data retrieval request, retrieves the new energy power data of the target category from the first server side, and stores the new energy power data of the target category in a plurality of storage queues, wherein the plurality of storage queues have different priorities, and one storage queue corresponds to one new type of power system end in one target category;

[0009] The second server end responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues;

[0010] The data reading end processes the read new energy power data and displays it in a regional map, and the regional map contains the new energy power information of each new power system end.

[0011] In some embodiments, the first server sets a first identification information for each received new energy power data, the second server sets a second identification information for each retrieved new energy power data, and determines the association relationship between the first identification information and the second identification information;

[0012] The novel power system data management method further includes:

[0013] The second server receives a data tracing request sent by the data reading end, wherein the data tracing request includes new energy power data that needs to be traced;

[0014] The second server determines the second identification information of the new energy power data that needs to be traced, and determines the corresponding first identification information according to the association relationship;

[0015] The second server sends the determined first identification information to the first server;

[0016] The first server determines source information of the new energy power data that needs to be traced based on the first identification information.

[0017] In some embodiments, the novel power system data management method further includes:

[0018] When the data reading end determines that the new energy power data is abnormal, the data reading end sends abnormal information to the second server end, where the abnormal information includes the second identification information of the new energy power data;

[0019] The second server determines the storage queue having data anomaly according to the second identification information in the anomaly information;

[0020] The second server side adjusts the priority of the storage queue according to whether there are data anomalies in each storage queue and the historical reading frequency of the stored new energy power data; among which, the priority of the storage queue with a high historical reading frequency is lowered, and the priority of the storage queue with data anomalies is increased.

[0021] In some embodiments, the novel power system data management method further includes:

[0022] The second server determines the historical waiting time for reading the new energy power data in each storage queue;

[0023] Determine the longest waiting time for reading and the average waiting time for reading of each storage queue according to the historical waiting time for reading;

[0024] The longest waiting time for reading and the average waiting time for reading of each storage queue are weighted and summed to obtain the estimated waiting time for reading of each storage queue; wherein the weight coefficient of the longest waiting time for reading is fixed, and the weight coefficient of the average waiting time for reading is proportional to the difference between the longest waiting time for reading and the average waiting time for reading;

[0025] Increase the priority of storage queues that have an evaluation wait time greater than the time threshold.

[0026] In some embodiments, the renewable energy power data includes text and images, and the data reader processes the read renewable energy power data and displays it on the regional map, including:

[0027] Extracting a first keyword from the text in the read new energy power data, and converting the first keyword into a first feature vector;

[0028] Extracting a second keyword from an image in the read new energy power data, and converting the second keyword into a second feature vector;

[0029] Determining associated text and image according to the first feature vector and the second feature vector;

[0030] storing the associated texts and images according to the corresponding new power system terminals;

[0031] The renewable energy power information of each new power system is displayed on the regional map.

[0032] In some embodiments, the displaying of the renewable energy power information of each new power system end in the regional map includes:

[0033] In response to a data display instruction input by a user, a first picture including new energy power information is generated, and the picture is overlaid on a geographical location where the new power system end is located in the regional map;

[0034] In response to the user's preset operation in the first picture, jump to the web page corresponding to the preset URL, and the web page displays historical data of new energy power information.

[0035] In some embodiments, the novel power system data management method further includes:

[0036] For the new energy power data of the same new power system end, the second server end calculates a first distance between a first feature vector at a first moment and a first feature vector at a second moment, and a second distance between a second feature vector at the first moment and a second feature vector at the second moment, the second moment being a moment next to the first moment;

[0037] If the first distance and the second distance are both less than the distance threshold, the second server end does not send the new energy power data at the second moment to the data reading end, and the data reading end continues to display the new energy power data at the first moment; otherwise, the second server end sends the new energy power data at the second moment to the data reading end, and the data reading end processes and displays the new energy power data at the second moment in the regional map.

[0038] In some embodiments, the novel power system data management method further includes:

[0039] The second server end encrypts the new energy power data by using the public key of the first encryption algorithm before sending the new energy power data to the data reading end, and generates the public key of the second encryption algorithm;

[0040] Encrypting the private key of the first encryption algorithm by using the public key of the second encryption algorithm, and sending the private key of the first encryption algorithm and the private key of the second encryption algorithm to the data reading end;

[0041] The data reading end decrypts the encrypted private key of the first encryption algorithm by using the private key of the second encryption algorithm, and uses the decrypted private key of the first encryption algorithm to decrypt the new energy power data.

[0042] In some embodiments, the novel power system data management method further includes:

[0043] Setting the MAC address of the data reading end that has the permission to access each storage queue and the MAC address of the data reading end that does not have the permission to access each storage queue;

[0044] After receiving the data reading request, the second server determines whether the data reading end corresponding to the data reading request has access rights according to the MAC address in the data reading request;

[0045] After determining that the data reading end corresponding to the data reading request has access rights, the second server end responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues.

[0046] In some embodiments,

[0047] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0048] In an embodiment of the present application, the first server end receives the new energy power data generated by each new power system end, and classifies and stores the received new energy power data; the second server end responds to the data retrieval request, retrieves the new energy power data of the target category from the first server end, and stores the new energy power data of the target category using multiple storage queues; the second server end responds to the data reading request, and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues; the data reading end processes the read new energy power data and displays it in the regional map.

[0049] In the embodiment of the present application, a two-layer server structure of a first server end and a second server end is used to realize that before the data reading end reads the new energy power data, the second server end pre-calls the corresponding new energy power data from the first server end, thereby improving the reading efficiency of the new energy power data; the second server end adopts a multi-priority parallel storage queue structure, which can shorten the data search time; by dynamically adjusting the storage queue priority, the storage queue priority and the data status can be kept dynamically synchronized. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0051] Figure 1 It is a structural diagram of a novel power system data management system provided by an embodiment of the present application;

[0052] Figure 2 It is a flow chart of a novel power system data management method provided in an embodiment of the present application;

[0053] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The present application is described more clearly below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the effects of the present application, but are not intended to limit the present application in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present application. These all fall within the scope of protection of the present application.

[0055] In order to make the purpose, technical solutions and advantages of the present application clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0056] See also Figure 1 The novel power system data management system provided in the embodiment of the present application may include a first server end 11, a second server end 12 and a data reading end 13. The number of the data reading end 13 may be one or more.

[0057] The first server end 11 is used to receive the new energy power data generated by each new power system end 14, and classify and store the received new energy power data.

[0058] The second server end 12 is used to respond to the data retrieval request, retrieve the new energy power data of the target category from the first server end, and store the new energy power data of the target category using multiple storage queues, the multiple storage queues have different priorities, and one storage queue corresponds to a new type of power system end in a target category.

[0059] The second server end 12 is further used to respond to a data reading request and send the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues.

[0060] The data reading terminal 13 is used to process the read new energy power data and display it in a regional map, and the regional map contains the new energy power information of each new power system terminal.

[0061] Based on the above-mentioned novel power system data management system, the present application embodiment also provides a novel power system data management method, see Figure 2 The novel power system data management method provided in the embodiment of the present application may include the following steps:

[0062] Step 201: The first server receives the new energy power data generated by each new power system, and classifies and stores the received new energy power data.

[0063] Exemplarily, the first server end may send a new energy power data acquisition instruction to each new power system end; the new power system end responds to the instruction and sends the generated new energy power data to the first server end.

[0064] In step 202 , the second server side responds to the data retrieval request, retrieves the target category of renewable energy power data from the first server side, and stores the target category of renewable energy power data in a plurality of storage queues.

[0065] The priorities of the multiple storage queues are different, and one storage queue corresponds to one new type of power system terminal in one target category.

[0066] In the embodiment of the present application, the renewable energy power data is classified and stored in step 201, which can facilitate the second server end to retrieve the renewable energy power data of the target category in step 202. Moreover, in step 201, the first server end can obtain the renewable energy power data and classify and store it in advance, rather than obtaining and classifying and storing it when the data reading end needs to use some renewable energy power data, thereby improving the efficiency of the data reading end in reading data.

[0067] In some scenarios, the data retrieval request may be sent by a data reader to the second server, and the data retrieval request may include a certain category of renewable energy power data or certain categories of renewable energy power data required by the data reader. The categories of renewable energy power data may be divided according to information such as business type, site, and data meaning.

[0068] In some other scenarios, the data retrieval request may be a request preset in the second server, and the user presets the data retrieval request in the second server according to actual work needs.

[0069] In some other scenarios, the data retrieval request may be generated by the second server to determine the data that needs to be retrieved in advance from the first server based on the historical data read by each data reader from the second server.

[0070] Step 203: the second server end responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues.

[0071] In an embodiment of the present application, the new energy power data of the target category is stored in multiple storage queues, and the priority of each storage queue is set. The priority of the storage queue of the new energy power data of the target category with high importance is set to high, the priority of the storage queue of the new energy power data of the target category with medium importance is set to medium, and the priority of the storage queue of the new energy power data of the target category with low importance is set to low, so that the new energy power data of the target category with high importance can be sent to the data reading end in priority, so that the data reading end can process the new energy power data of the target category with high importance in priority.

[0072] In step 204, the data reading end processes the read new energy power data and displays it in a regional map, wherein the regional map includes new energy power information of each new power system end.

[0073] In this step, the new energy power data contains text and images, and the data reading end processes the read new energy power data and displays it in the regional map, which may include: extracting a first keyword from the text in the read new energy power data, and converting the first keyword into a first feature vector; extracting a second keyword from the image in the read new energy power data, and converting the second keyword into a second feature vector; determining associated text and image according to the first feature vector and the second feature vector; storing the associated text and image according to the corresponding new power system end; and displaying the new energy power information of each new power system end in the regional map.

[0074] Exemplarily, the display of the new energy power information of each new power system end in the regional map may include: responding to a data display instruction input by a user, generating a first picture containing the new energy power information, and overlaying the picture to the geographical location of the new power system end in the regional map; responding to a preset operation of the user on the first picture, jumping to a web page corresponding to a preset URL (Uniform Resource Locator), and the web page displays historical data of the new energy power information.

[0075] For example, a user can click on the first picture in the display interface of the data reading end, and the data reading end responds to the click operation and jumps to a web page corresponding to a preset URL, which displays the historical data of the new energy power information of the new power system end corresponding to the first picture. Different first pictures correspond to different URLs, and different first pictures are subjected to preset operations to jump to different web pages to display the historical data of the new energy power information of the corresponding new power system end.

[0076] In some embodiments, the above process of extracting the first keyword from the text may include: segmenting the text to determine the first frequency and position of each word in the text; determining the first span of each word in the text based on the distance between the first position and the second position of each word in the text; wherein the first position is the position of the first appearance in the text, the second position is the position of the last appearance in the text, and the distance between the first position and the second position is the number of words between the first position and the second position; determining a target word whose first frequency is greater than a threshold, and taking a first preset number of words with the largest first span among the target words as candidate keywords for the text, and the number of candidate keywords is the first preset number; determining the second frequency and second span of each candidate keyword in other texts; calculating the product of the first frequency and the first span, and the product of the second frequency and the second span, and recording the candidate keyword with the largest product difference as the first keyword of the text, and the number of first keywords is the second preset number, which is less than the first preset number.

[0077] Exemplarily, the first frequency is the number of times a word appears in a text, the second frequency is the number of times the candidate keyword appears in other texts, and the span is the number of words between the first position and the second position.

[0078] In some embodiments, the process of extracting the second keyword from the image may include: filtering and denoising the image; inputting an image sample containing tag information into an image segmentation model to train the image segmentation model; wherein the tag information includes the image category and the segmentation position of the image area; using the trained image segmentation model to segment the image that has been filtered and denoised to obtain at least one image area; identifying text from the image area, and extracting the second keyword from the identified text.

[0079] Exemplarily, the above-mentioned filtering and denoising of images can be implemented based on convolutional neural networks. Specifically, in order to train a filtering and denoising model with excellent performance, a large number of noisy images need to be prepared as training sets. At the same time, corresponding noise-free images need to be prepared as labels. The image denoising model based on convolutional neural networks consists of multiple convolutional layers, pooling layers, and fully connected layers. Among them, the convolutional layer is responsible for learning features from the input image, the pooling layer is responsible for reducing the feature dimension, and the fully connected layer is responsible for mapping the learned features to the labels. During the training process, the input image is convolved with the filter learned by the convolutional layer to obtain a denoised image; by comparing the difference between the denoised image and the label, the loss function is calculated and the filter parameters are updated by backpropagation; the above process is repeated until the model performance meets the expected requirements.

[0080] In this embodiment, there may be multiple image categories, and each category of images corresponds to a segmentation position of an image area. The image area contains text or pictures, and the segmentation position of the image area containing text is different from the segmentation position of the image area containing pictures.

[0081] For example, the image category can be determined based on the site, image content, etc. For example, the image categories of the images of renewable energy power data generated by different sites are different; or, the image content in the image is different, and the corresponding image category is also different. Among them, the image content can be the model of the equipment in the image, or the header title of the table in the image, etc., which is not limited.

[0082] In some embodiments, the image category is determined based on text in a preset area of ​​the image, for example, based on the header text of a table in the image. The above-mentioned use of a trained image segmentation model to segment the image after filtering and denoising to obtain at least one image area may include: inputting the image after filtering and denoising to the trained image segmentation model; the image segmentation model extracts text from a preset area of ​​the image, determines the image category based on the text, and retrieves the segmentation position of the image area corresponding to the image category; the image segmentation model segments the image based on the segmentation position of the image area to obtain at least one image area.

[0083] In this embodiment, for a specific image category, the position of the text contained therein in the image is fixed, so the segmentation position of the image region can be set in advance according to the image category. Specifically, the segmentation position of the image region can be set manually, or the segmentation position of the image region can be set by learning through a neural network model.

[0084] In this step, the image may be an image of some standard file. For the image of the standard file, the image area where the content to be extracted is located can be extracted from the image first, and then keyword extraction is performed in the extracted image area.

[0085] Specifically, the implementation process of "recognizing text from an image region and extracting a second keyword from the recognized text" may include: converting the image region into a text image to be recognized, extracting connected regions from the text image to be recognized, and obtaining multiple connected regions; determining the contour of each character in each connected region, segmenting the contour to obtain multiple characters and recording the positional relationship of each character in the connected region; recognizing each character, and generating the text to be extracted based on the positional relationship of each character in the connected region; and extracting the second keyword from the text to be extracted. Among them, converting the image region into a text image to be recognized may be converting the image region into a grayscale image to obtain a text image to be recognized.

[0086] Exemplarily, a standard file usually includes a file name and specific file content, so in this step, the second keyword can be extracted from the text corresponding to the file name portion, or the second keyword can be extracted from the text corresponding to the file name and specific file content.

[0087] Exemplarily, connected region extraction is performed on a text image to be recognized to obtain multiple connected regions, which may include: determining the grayscale value of each pixel in the text image to be recognized, and determining a pixel cluster in each row of pixels in the text image to be recognized based on the grayscale value of each pixel, wherein each pixel in the pixel cluster is connected and the grayscale values ​​are preset grayscale values; determining pixel clusters that are interconnected between pixels in different rows based on the positions of each pixel cluster to obtain connected regions; wherein, in the same connected region, there are pixels located in the same column between pixel clusters in adjacent rows.

[0088] Specifically, in the text image to be recognized, the grayscale values ​​of the pixels corresponding to the text characters are the same. Therefore, the grayscale values ​​of the pixels in each row of the text image to be recognized can be compared with the preset grayscale value, and the pixels with the same grayscale value as the preset grayscale value can be found to find the pixels of the text characters. If these pixels are connected, they form a pixel cluster. Thus, the pixel clusters in each row of pixels are found, and it is determined that the connected pixel clusters form multiple connected areas, which are the areas where the text characters are located.

[0089] In some embodiments, the above-mentioned determination of associated text and image based on the first feature vector and the second feature vector may include: for any first feature vector, calculating the cosine similarity between the first feature vector and each second feature vector; associating the first feature vector with the second feature vector with the smallest cosine similarity to obtain associated text and image.

[0090] Among them, cosine similarity is the cosine value of the angle between two vectors, which is used to measure the consistency of the directions of the two vectors. The larger the cosine similarity, the smaller the angle between the two vectors and the higher the directional consistency; the smaller the cosine similarity, the larger the angle between the two vectors and the lower the directional consistency.

[0091] In some embodiments, the process of converting the first keyword of each text into a first feature vector may include: there are multiple first keywords, each row of elements in the first feature vector corresponds to a first keyword, and the value of the element corresponding to each first keyword is calculated according to the frequency of occurrence of each first keyword in the target text multiplied by the span and the preset weight to obtain the first feature vector.

[0092] The process of converting the second keyword of each image into a second feature vector may include: there are multiple second keywords, each row of elements in the second feature vector corresponds to a second keyword, and the value of the element corresponding to each second keyword is calculated according to the frequency of occurrence of each second keyword in the target image multiplied by the span and the preset weight to obtain the second feature vector.

[0093] In some embodiments, the first server side sets a first identification information for each new energy power data received, and the second server side sets a second identification information for each new energy power data retrieved, and determines the association relationship between the first identification information and the second identification information.

[0094] The novel power system data management method may further include: the second server end receives a data tracing request sent by the data reading end, the data tracing request contains the new energy power data that needs to be traced; the second server end determines the second identification information of the new energy power data that needs to be traced, and determines the corresponding first identification information according to the association relationship; the second server end sends the determined first identification information to the first server end; the first server end determines the source information of the new energy power data that needs to be traced according to the first identification information.

[0095] In some embodiments, the new power system data management method may further include: when the data reading end determines that there is an abnormality in the new energy power data, the data reading end sends the abnormal information to the second server end, and the abnormal information includes the second identification information of the new energy power data; the second server end determines the storage queue with data abnormality according to the second identification information in the abnormal information; the second server end adjusts the priority of the storage queue according to whether there is data abnormality in each storage queue and the historical reading frequency of the stored new energy power data; wherein, the priority of the storage queue with a high historical reading frequency is lowered, and the priority of the storage queue with data abnormality is increased.

[0096] By adjusting the priority of the storage queue, the priority of the storage queue with a high historical reading frequency is lowered, the diversity of the reading priority of each category of data is maintained, the priority of the storage queue with data anomalies is increased, and the data with data anomalies is sent to the data reading end for priority processing, so that the priority of the storage queue can be dynamically synchronized with the new energy power data status.

[0097] In some embodiments, the novel power system data management method may further include: the second server side determines the historical waiting reading time of the new energy power data in each storage queue; determines the longest waiting reading time and the average waiting reading time of each storage queue based on the historical waiting reading time; performs weighted summation of the longest waiting reading time and the average waiting reading time of each storage queue to obtain the evaluated waiting reading time of each storage queue; wherein the weight coefficient of the longest waiting reading time is fixed, and the weight coefficient of the average waiting reading time is proportional to the difference between the longest waiting reading time and the average waiting reading time; and raises the priority of the storage queue whose evaluated waiting reading time is greater than the time threshold.

[0098] By adjusting the priority of the storage queue, the priority of the storage queue whose waiting time for reading is greater than the time threshold is increased, so as to improve the diversity of data reading priority and prevent the reading priority of each category of data from being unchanged.

[0099] In some embodiments, the new power system data management method may also include: for the new energy power data of the same new power system end, the second server end calculates the first distance between the first feature vector at the first moment and the first feature vector at the second moment, and the second distance between the second feature vector at the first moment and the second feature vector at the second moment, and the second moment is the next moment of the first moment; if the first distance and the second distance are both less than the distance threshold, the second server end does not send the new energy power data at the second moment to the data reading end, and the data reading end continues to display the new energy power data at the first moment; otherwise, the second server end sends the new energy power data at the second moment to the data reading end, and the data reading end processes and displays the new energy power data at the second moment in the regional map.

[0100] Specifically, if the first distance and the second distance are both less than the distance threshold, it means that the new energy power data at the first moment is relatively close to or has not changed with the new energy power data at the second moment. At this time, there is no need to send the new energy power data at the second moment to the data reading end. The data reading end continues to display the new energy power data at the first moment, which can save network resources.

[0101] In some embodiments, the new power system data management method may also include: before the second server sends the new energy power data to the data reading end, encrypts the new energy power data by the public key of the first encryption algorithm, and generates a public key of the second encryption algorithm; encrypts the private key of the first encryption algorithm by the public key of the second encryption algorithm, and sends the private key of the first encryption algorithm and the private key of the second encryption algorithm to the data reading end; the data reading end decrypts the encrypted private key of the first encryption algorithm by the private key of the second encryption algorithm, and uses the decrypted private key of the first encryption algorithm to decrypt the new energy power data.

[0102] In some embodiments, the novel power system data management method may further include: setting a MAC address of a data reading end that has permission to access each storage queue, and a MAC address of a data reading end that does not have permission to access each storage queue; after receiving a data reading request, the second server end determines whether the data reading end corresponding to the data reading request has access permission based on the MAC address in the data reading request; after determining that the data reading end corresponding to the data reading request has access permission, the second server end responds to the data reading request again, and sends the new energy power data stored in the multiple storage queues to the data reading end in the priority order of the multiple storage queues.

[0103] Specifically, the MAC (Media Access Control Address) address of the user terminal with access rights and the MAC address of the user terminal without access rights corresponding to each preset characteristic identification information can be set. When the user wants to access a certain category of new energy power data or certain categories of new energy power data through the data reading end, the data reading end inputs a data reading request containing a characteristic identification, and the second server end responds to the data reading request and determines the target preset characteristic identification information consistent with the characteristic identification. Afterwards, the second server end determines whether the data reading end has the authority to access the new energy power data corresponding to the target preset characteristic identification information based on the MAC address of the data reading end. If authorized, the new energy power data corresponding to the target preset characteristic identification information is sent to the data reading end; otherwise, the new energy power data corresponding to the target preset characteristic identification information is not sent to the data reading end.

[0104] In the above-mentioned new power system data management method, the first server end receives the new energy power data generated by each new power system end, and classifies and stores the received new energy power data; the second server end responds to the data retrieval request, retrieves the new energy power data of the target category from the first server end, and stores the new energy power data of the target category using multiple storage queues; the second server end responds to the data reading request, and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues; the data reading end processes the read new energy power data and displays it in the regional map.

[0105] In the embodiment of the present application, a two-layer server structure of a first server end and a second server end is used to realize that before the data reading end reads the new energy power data, the second server end pre-calls the corresponding new energy power data from the first server end, thereby improving the reading efficiency of the new energy power data; the second server end adopts a multi-priority parallel storage queue structure, which can shorten the data search time; by dynamically adjusting the storage queue priority, the storage queue priority and the data status can be kept dynamically synchronized.

[0106] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0107] Figure 3 is a schematic diagram of an electronic device provided by an embodiment of the present invention, and the electronic device may be the first server end, the second server end or the data reading end. Figure 3 As shown, the electronic device 300 of this embodiment includes a processor 310 and a memory 320, wherein the memory 320 stores a computer program that can be run on the processor 310. When the processor 310 executes the computer program, the steps in the above-mentioned novel power system data management method embodiment are implemented.

[0108] The electronic device 300 may be a desktop computer, a notebook, a PDA, a cloud terminal device, etc. The electronic device may include, but is not limited to, a processor 310 and a memory 320. Those skilled in the art will appreciate that Figure 3 It is only an example of the electronic device 300 and does not constitute a limitation of the electronic device 300. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0109] The processor 320 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0110] The memory 320 may be an internal storage unit of the electronic device 300, such as a hard disk or memory of the electronic device 300. The memory 320 may also be an external storage device of the electronic device 300, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 300. Further, the memory 320 may also include both an internal storage unit of the electronic device 300 and an external storage device. The memory 320 is used to store the computer program and other programs and data required by the electronic device. The memory 320 may also be used to temporarily store data that has been output or is to be output.

[0111] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0112] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A novel power system data management method, characterized in that: include: The first server receives the new energy power data generated by each new power system, and classifies and stores the received new energy power data; The second server side responds to the data retrieval request, retrieves the new energy power data of the target category from the first server side, and stores the new energy power data of the target category in a plurality of storage queues, wherein the plurality of storage queues have different priorities, and one storage queue corresponds to one new type of power system end in one target category; The second server end responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues; The data reading end processes the read new energy power data and displays it in a regional map, and the regional map contains the new energy power information of each new power system end.

2. The novel power system data management method according to claim 1 is characterized in that: The first server sets a first identification information for each received new energy power data, the second server sets a second identification information for each retrieved new energy power data, and determines the association relationship between the first identification information and the second identification information; The novel power system data management method further includes: The second server receives a data tracing request sent by the data reading end, wherein the data tracing request includes new energy power data that needs to be traced; The second server determines the second identification information of the new energy power data that needs to be traced, and determines the corresponding first identification information according to the association relationship; The second server sends the determined first identification information to the first server; The first server determines source information of the new energy power data that needs to be traced based on the first identification information.

3. The novel power system data management method according to claim 1 is characterized in that: The novel power system data management method further includes: When the data reading end determines that the new energy power data is abnormal, the data reading end sends abnormal information to the second server end, where the abnormal information includes the second identification information of the new energy power data; The second server determines the storage queue having data anomaly according to the second identification information in the anomaly information; The second server side adjusts the priority of the storage queue according to whether there are data anomalies in each storage queue and the historical reading frequency of the stored new energy power data; among which, the priority of the storage queue with a high historical reading frequency is lowered, and the priority of the storage queue with data anomalies is increased.

4. The novel power system data management method according to claim 1 is characterized in that: The novel power system data management method further includes: The second server determines the historical waiting time for reading the new energy power data in each storage queue; Determine the longest waiting time for reading and the average waiting time for reading of each storage queue according to the historical waiting time for reading; The longest waiting time for reading and the average waiting time for reading of each storage queue are weighted and summed to obtain the estimated waiting time for reading of each storage queue; wherein the weight coefficient of the longest waiting time for reading is fixed, and the weight coefficient of the average waiting time for reading is proportional to the difference between the longest waiting time for reading and the average waiting time for reading; Increase the priority of storage queues that have an evaluation wait time greater than the time threshold.

5. The novel power system data management method according to claim 1 is characterized in that: The renewable energy power data includes text and images. The data reader processes the read renewable energy power data and displays it on the regional map, including: Extracting a first keyword from the text in the read new energy power data, and converting the first keyword into a first feature vector; Extracting a second keyword from an image in the read new energy power data, and converting the second keyword into a second feature vector; Determining associated text and image according to the first feature vector and the second feature vector; storing the associated texts and images according to the corresponding new power system terminals; The renewable energy power information of each new power system is displayed on the regional map.

6. The novel power system data management method according to claim 5 is characterized in that: The display of the renewable energy power information of each new power system end in the regional map includes: In response to a data display instruction input by a user, a first picture including new energy power information is generated, and the picture is overlaid on a geographical location where the new power system end is located in the regional map; In response to the user's preset operation in the first picture, jump to the web page corresponding to the preset URL, and the web page displays historical data of new energy power information.

7. The novel power system data management method according to claim 5 is characterized in that: The novel power system data management method further includes: For the new energy power data of the same new power system end, the second server end calculates a first distance between a first feature vector at a first moment and a first feature vector at a second moment, and a second distance between a second feature vector at the first moment and a second feature vector at the second moment, the second moment being a moment next to the first moment; If the first distance and the second distance are both less than the distance threshold, the second server end does not send the new energy power data at the second moment to the data reading end, and the data reading end continues to display the new energy power data at the first moment; otherwise, the second server end sends the new energy power data at the second moment to the data reading end, and the data reading end processes and displays the new energy power data at the second moment in the regional map.

8. The novel power system data management method according to claim 5 is characterized in that: The determining the associated text and image according to the first feature vector and the second feature vector comprises: For any first eigenvector, calculate the cosine similarity between the first eigenvector and each second eigenvector; The first feature vector is associated with the second feature vector with the smallest cosine similarity to obtain associated text and image.

9. The novel power system data management method according to claim 1, characterized in that: The novel power system data management method further includes: The second server end encrypts the new energy power data by using the public key of the first encryption algorithm before sending the new energy power data to the data reading end, and generates the public key of the second encryption algorithm; Encrypting the private key of the first encryption algorithm by using the public key of the second encryption algorithm, and sending the private key of the first encryption algorithm and the private key of the second encryption algorithm to the data reading end; The data reading end decrypts the encrypted private key of the first encryption algorithm by using the private key of the second encryption algorithm, and uses the decrypted private key of the first encryption algorithm to decrypt the new energy power data.

10. The novel power system data management method according to claim 1, characterized in that: The novel power system data management method further includes: Setting the MAC address of the data reading end that has the permission to access each storage queue and the MAC address of the data reading end that does not have the permission to access each storage queue; After receiving the data reading request, the second server determines whether the data reading end corresponding to the data reading request has access rights according to the MAC address in the data reading request; After determining that the data reading end corresponding to the data reading request has access rights, the second server end responds to the data reading request and sends the new energy power data stored in the multiple storage queues to the data reading end according to the priority order of the multiple storage queues.

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