An intelligent report decision-making method and system for new energy power stations

Abstract

The present invention specifically provides an intelligent report decision method and system for a new energy power station, and relates to the field of intelligent report decision technology. The method of the present invention includes real-time acquisition of the collected data of each new energy power station; pre-processing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station; in response to the analysis instructions issued by the managers of each new energy power station, substituting the monitoring data corresponding to each new energy power station into the intelligent decision analysis model, and selectively obtaining the decision display scheme corresponding to each manager of each new energy power station; based on the decision display scheme, displaying the decision display scheme to the manager corresponding to the decision display scheme. The present invention can timely visualize and intuitively display the operation report of the new energy power station, and give corresponding decision suggestions, so that the manager can timely control and adjust the new energy power station according to the decision display scheme, thereby ensuring the safe and efficient operation of the new energy power station.

Description

Technical Field

[0001] The present invention relates to the field of intelligent report decision technology, and specifically provides an intelligent report decision method and system for a new energy power station. Background Art

[0002] With the rapid development of new energy technologies, the construction of new energy power stations has gradually increased. Real-time, efficient and accurate management of new energy power stations has become an important demand of the industry.

[0003] However, due to the different structures of new energy power stations, different new energy power stations collect different data information. The management method of new energy power stations in the existing technology generally adopts the generation of data reports in a unified format when managing multiple new energy power stations with different structures. This is not conducive to the precise management of different new energy power stations by different managers, and thus affects the decision-making efficiency and accuracy of different managers of different new energy power stations.

[0004] Accordingly, the art needs a new intelligent reporting decision-making solution for new energy power stations to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present invention is proposed to provide an intelligent report decision method and system for new energy power stations to solve or at least partially solve the technical problem that the management method of new energy power stations in the prior art generally adopts the generation of data reports in a unified format when managing multiple new energy power stations of different structures, which is not conducive to the precise management of different new energy power stations by different managers, thereby affecting the decision-making efficiency and accuracy of different managers of different new energy power stations.

[0006] In a first aspect, the present invention provides an intelligent report decision method for a new energy power station, the method is applied to an intelligent report decision system, the system interacts with multiple different new energy power stations, and the method comprises the following steps:

[0007] Obtain the collected data of each new energy power station in real time;

[0008] Pre-process the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station;

[0009] In response to the analysis instructions issued by the managers of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each manager of each new energy power station is selectively obtained, wherein the decision display scheme includes a visual display report and a decision suggestion;

[0010] Based on the decision display schemes corresponding to the various managers of each new energy power station, the decision display schemes are displayed to the managers corresponding to the decision display schemes.

[0011] In a technical solution of the above-mentioned intelligent report decision method for new energy power stations, a preset historical database is stored in the system, and the historical database stores multiple groups of historical monitoring data of each new energy power station, the monitoring time point of each group of historical monitoring data, and the historical environmental data corresponding to each group of historical monitoring data. Before the collected data of each new energy power station is preprocessed to obtain the monitoring data corresponding to each new energy power station, the method further includes:

[0012] Based on the collected data of each new energy power station and the preset historical database, determine whether it is necessary to re-acquire the collected data of the new energy power station:

[0013] If the judgment is yes, the collected data of the new energy power station is re-acquired, and based on the re-acquired collected data and a preset historical database, the step of "determining whether it is necessary to re-acquire the collected data of the new energy power station" is re-executed;

[0014] If the judgment is no, then based on the collected data of the new energy power station, "pre-processing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station" is executed.

[0015] In a technical solution of the intelligent report decision method for the new energy power station, a preset manager database is stored in the intelligent decision analysis model. In response to the analysis instructions issued by the managers of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each manager of each new energy power station is selectively obtained, including:

[0016] Get the number of the manager corresponding to each analysis instruction;

[0017] Based on the numbers of the managers corresponding to the respective analysis instructions and a preset manager database, a preset display option set corresponding to each manager is obtained;

[0018] Based on the preset display option set corresponding to each manager, a visualization display report template corresponding to each manager is constructed;

[0019] Based on the visualization report template corresponding to each manager and the monitoring data corresponding to each new energy power station, the decision display scheme corresponding to each manager of each new energy power station is selectively obtained. In a technical solution of the intelligent report decision method for new energy power stations,

[0020] In a technical solution of the intelligent report decision method for a new energy power station, a preset execution operation comparison table is stored in the intelligent decision analysis model. Before substituting the monitoring data corresponding to each new energy power station into the intelligent decision analysis model, the method further trains the intelligent decision analysis model through the following steps:

[0021] Taking each new energy power station as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include a group of monitoring data corresponding to the training sample and a group of environmental data corresponding to the monitoring data;

[0022] Obtain the visualization report template corresponding to each set of training samples;

[0023] Based on the visualization report template corresponding to each training sample set and each training sample set, select part of the monitoring data corresponding to the visualization report template in each training sample set;

[0024] Estimation is performed based on each group of training sample sets to obtain estimated monitoring data corresponding to each group of training sample sets;

[0025] Based on the visualization report template corresponding to each training sample set, the estimated monitoring data and part of the monitoring data of each training sample set, a visualization report corresponding to each training sample set is obtained, wherein the visualization report includes a current visualization report and an estimated visualization report;

[0026] Based on the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, a plurality of decision suggestions corresponding to each training sample set are formed, wherein the decision suggestions include current decision suggestions corresponding to the current visualization report and estimated decision suggestions corresponding to the estimated visualization report;

[0027] Based on the groups of decision suggestions corresponding to each group of training sample sets, select a group of decision suggestions as the decision suggestions corresponding to the training sample sets;

[0028] The decision suggestions corresponding to each group of training sample sets are compared with the historical decision suggestions corresponding to each group of training sample sets, and based on the comparison results, the training results of the intelligent decision analysis model are obtained.

[0029] In a technical solution of the above-mentioned intelligent report decision method for a new energy power station, the step of obtaining multiple sets of training sample sets corresponding to each training sample includes:

[0030] Based on the preset historical database, multiple groups of historical monitoring data corresponding to each training sample and the monitoring time point corresponding to each group of historical monitoring data are randomly selected;

[0031] Based on the monitoring time point corresponding to each set of historical monitoring data and a preset historical database, determine the historical environmental data corresponding to each set of historical monitoring data;

[0032] Based on the monitoring time point corresponding to each set of historical monitoring data and the historical environmental data corresponding to each set of historical monitoring data, obtaining the estimated environmental data corresponding to each set of historical monitoring data;

[0033] Based on multiple groups of historical monitoring data corresponding to each training sample, historical environmental data corresponding to each group of historical monitoring data, and estimated environmental data corresponding to each group of historical monitoring data, multiple groups of training sample sets corresponding to each training sample are constructed.

[0034] In a technical solution of the intelligent report decision method for a new energy power station, based on the visualization report template corresponding to each training sample set and each training sample set, selecting part of the monitoring data corresponding to the visualization report template in each training sample set includes:

[0035] Based on the visualization report template corresponding to each group of training sample sets, multiple data categories matched by each group of training sample sets are determined;

[0036] Based on multiple data categories matched by each training sample set, each training sample set is screened, and part of the monitoring data corresponding to the visualization display report template in each training sample set is selected.

[0037] In a technical solution of the intelligent report decision method for a new energy power station, the visualization report template corresponding to each training sample set, the estimated monitoring data and part of the monitoring data of each training sample set are obtained to obtain the visualization report corresponding to each training sample set, including:

[0038] Based on the visualization report template corresponding to each set of training sample sets and the estimated monitoring data, construct an estimated visualization report corresponding to each set of training sample sets;

[0039] Based on the visualization report template corresponding to each training sample set and part of the monitoring data of each training sample set, a current visualization report corresponding to each training sample set is constructed;

[0040] Blurring the estimated visualization report corresponding to each group of training sample sets, and superimposing the blurred estimated visualization report corresponding to each group of training sample sets with the current visualization report corresponding to the training sample sets to form a superimposed current visualization report and an estimated visualization report;

[0041] The current visualization report and the estimated visualization report that are superimposed and displayed are used as the visualization display reports corresponding to the training sample set.

[0042] In a technical solution of the intelligent report decision method for a new energy power station, the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table constitute multiple groups of decision suggestions corresponding to each training sample set, including:

[0043] Based on each group of training sample sets and a preset execution operation comparison table, determining multiple groups of execution operations corresponding to each group of training sample sets, wherein the execution operations include multiple operation types and execution parameter values ​​corresponding to each operation type;

[0044] Based on the visualization report corresponding to each set of training sample sets, determine the current running status and estimated running status corresponding to each set of training sample sets;

[0045] Based on the current operating state and the estimated operating state corresponding to each group of training sample sets, generate a current adjustment suggestion corresponding to the current operating state corresponding to the training sample set and an estimated adjustment suggestion for the estimated operating state corresponding to the training sample set;

[0046] Based on the current adjustment suggestions and estimated adjustment suggestions corresponding to each training sample set, multiple groups of execution operations corresponding to each training sample set, and the identity information of the managers corresponding to each training sample set, multiple groups of decision suggestions corresponding to each training sample set are constructed.

[0047] In a technical solution of the intelligent report decision method for a new energy power station, the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table constitute multiple groups of decision suggestions corresponding to each training sample set, including:

[0048] Based on each group of training sample sets and a preset execution operation comparison table, determining multiple groups of execution operations corresponding to each group of training sample sets, wherein the execution operations include multiple operation types and execution parameter values ​​corresponding to each operation type;

[0049] Based on the visualization report corresponding to each set of training sample sets, determine the current running status and estimated running status corresponding to each set of training sample sets;

[0050] Based on the current operating state and the estimated operating state corresponding to each group of training sample sets, generate a current adjustment suggestion corresponding to the current operating state corresponding to the training sample set and an estimated adjustment suggestion for the estimated operating state corresponding to the training sample set;

[0051] Based on the current adjustment suggestions and estimated adjustment suggestions corresponding to each training sample set, multiple groups of execution operations corresponding to each training sample set, and the identity information of the managers corresponding to each training sample set, multiple groups of decision suggestions corresponding to each training sample set are constructed.

[0052] In a second aspect, the present invention provides an intelligent report decision system, which interacts with multiple different new energy power stations. The system includes a collection device, a preset historical database, an intelligent decision analysis model, and a control device. The collection device is respectively connected to different new energy power stations for real-time collection of data from each new energy power station. The intelligent decision analysis model stores a preset management personnel database and a preset execution operation comparison table. The control device includes a processor and a memory. The memory is suitable for storing multiple program codes. The program code is suitable for being loaded and run by the processor to execute the intelligent report decision method for new energy power stations described in any one of the technical solutions of the above-mentioned technical solutions of the intelligent report decision method for new energy power stations.

[0053] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0054] By preprocessing the collected data of each new energy power station acquired in real time, the monitoring data corresponding to each new energy power station is obtained, and the collected data is converted into a data format suitable for the intelligent decision-making analysis model to facilitate the analysis of the monitoring data by the intelligent decision-making analysis model. By responding to the analysis instructions issued by the management personnel, the monitoring data is substituted into the intelligent decision-making analysis model, and the decision display plan corresponding to each manager is selectively obtained, so that the corresponding new energy power station operation report can be visually and intuitively displayed in time in response to the analysis instructions of the management personnel, and corresponding decision suggestions can be given, so that the management personnel can control and adjust the new energy power station in time according to the decision display plan, thereby ensuring the safe and efficient operation of the new energy power station, and avoiding the management method of new energy power stations in the existing technology. When managing multiple new energy power stations with different structures, the management method generally adopts the generation of data reports in a unified format, which is not conducive to the precise management of different new energy power stations by different managers, thereby affecting the decision-making efficiency and accuracy of different managers of different new energy power stations. Technical problems.

[0055] In the technical solution of the present invention, in the model training, by taking each new energy power station as a training sample, and obtaining multiple groups of training sample sets for each training sample, and obtaining the visualization display report template corresponding to the training sample set, each group of training sample sets can generate an intuitive visualization report chart or image, so that the management personnel corresponding to the template can more intuitively understand and interpret the data of the new energy power station, and then select the matching part of the monitoring data through the visualization report template and the training sample set, and estimate the training sample set to obtain the corresponding estimated monitoring data, and obtain the corresponding visualization display report based on the part of the monitoring data and the estimated monitoring data, so that the visualization report can be generated. The visual display report simultaneously displays the current data and estimated data of the new energy power station, so that the management personnel can make advance deployment of the new energy power station through the visual display report, and then combine with the preset execution operation comparison table to form multiple corresponding groups of decision suggestions, and select one group of decision suggestions as the corresponding training sample set, so as to achieve a high degree of matching between the decision suggestions and the training sample set, thereby ensuring the normal operation of the new energy power station and the management personnel to carry out efficient energy management of the new energy power station, and compare it with the historical decision suggestions, and obtain the training results of the model according to the comparison results, so as to adjust and optimize the model in combination with the historical decision suggestions, so as to improve the accuracy and reliability of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In addition, similar numbers in the drawings represent similar components, wherein:

[0057] Figure 1 This is a flowchart of the main steps of an intelligent report decision-making method for a new energy power station according to an embodiment of the present invention;

[0058] Figure 2 It is a schematic diagram of the main structural block diagram of an intelligent report decision system according to an embodiment of the present invention.

[0059] Reference numerals list :

[0060] 200: intelligent report decision system; 201: control device; 2011: processor; 2012: memory; 2013: program code; 202: intelligent decision analysis model; 2021: management personnel database; 2022: execution operation comparison table; 203: collection device; 204: historical database. DETAILED DESCRIPTION

[0061] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0062] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, and memories, and may also include software parts, such as program codes, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware, or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store program codes, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, and the like. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B", and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0063] See attached Figure 1 , Figure 1 1 is a flow chart of the main steps of an intelligent report decision method for a new energy power station according to an embodiment of the present invention. Figure 1 As shown, the intelligent report decision method for a new energy power station in an embodiment of the present invention is applied to an intelligent report decision system, and the system interacts with multiple different new energy power stations. The method mainly includes the following steps S101-S104.

[0064] Step S101: acquiring the collected data of each new energy power station in real time;

[0065] Specifically, in some embodiments, the method of acquiring the collected data of the new energy power station can be real-time collection through various sensors installed on each new energy power station, and the collected data can be the operation data of the power station equipment. The setting of the type of collected data and the setting of the method of collecting data here are only exemplary descriptions. In actual tests, technical personnel in this field can make settings according to actual needs, which will not be repeated here.

[0066] Step S102: pre-processing the collected data of each new energy power station to obtain monitoring data corresponding to each new energy power station;

[0067] Furthermore, in some embodiments, a preset historical database is stored in the system, and the historical database stores multiple groups of historical monitoring data of each new energy power station, the monitoring time point of each group of historical monitoring data, and the historical environmental data corresponding to each group of historical monitoring data. Before preprocessing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station, the method further includes:

[0068] Based on the collected data of each new energy power station and the preset historical database, determine whether it is necessary to re-acquire the collected data of the new energy power station:

[0069] If the judgment is yes, the collected data of the new energy power station is re-acquired, and based on the re-acquired collected data and a preset historical database, the step of "determining whether it is necessary to re-acquire the collected data of the new energy power station" is re-executed;

[0070] If the judgment is no, then based on the collected data of the new energy power station, "pre-processing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station" is executed.

[0071] Specifically, in some embodiments, the preprocessing of the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station includes:

[0072] Perform data cleaning on the collected data of each new energy power station to obtain the cleaned collected data of each new energy power station;

[0073] Perform data conversion on the cleaned collected data of each new energy power station to obtain the collected data of each new energy power station in a unified data format;

[0074] The collected data of each new energy power station after the data format is unified is used as the monitoring data corresponding to each new energy power station.

[0075] Specifically, in some embodiments, the monitoring data includes data values ​​corresponding to a variety of different data types. Specifically, the monitoring data includes various key indicators of the new energy power station. The data type may be power generation, voltage, frequency, and power. The selection of data type here is only an exemplary description. In actual testing, those skilled in the art can make a selection according to actual needs, which will not be repeated here.

[0076] In the above embodiment, the error rate of the collected data is reduced by analyzing and verifying the collected data, and the matching degree between the monitoring data and the intelligent decision-making analysis model is achieved by performing data cleaning and data conversion on the collected data that pass the verification, thereby improving the analysis accuracy of the monitoring data by the intelligent decision-making analysis model, thereby facilitating the intelligent decision-making analysis model to accurately evaluate and predict the future operation of the new energy power station, thereby improving the matching degree between the decision display plan output by the intelligent decision-making analysis model and the new energy power station.

[0077] Step S103: In response to the analysis instructions issued by the managers of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each manager of each new energy power station is selectively obtained, wherein the decision display scheme includes a visual display report and a decision suggestion;

[0078] Specifically, in some embodiments, a preset manager database is stored in the intelligent decision analysis model, and the manager database includes multiple managers corresponding to each new energy power station, identity information of each manager, and a set of display options preset by each manager. The identity information of the manager includes the number, report viewing authority, and operation level authority corresponding to the manager. In response to the analysis instructions issued by the managers of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each manager of each new energy power station is selectively obtained, including:

[0079] Get the number of the manager corresponding to each analysis instruction;

[0080] Based on the numbers of the managers corresponding to the respective analysis instructions and a preset manager database, a preset display option set corresponding to each manager is obtained;

[0081] Based on the preset display option set corresponding to each manager, a visualization display report template corresponding to each manager is constructed;

[0082] Based on the visualization report template corresponding to each manager and the monitoring data corresponding to each new energy power station, a decision display plan corresponding to each manager of each new energy power station is selectively obtained.

[0083] Specifically, in some embodiments, the decision display scheme corresponding to each manager of each new energy power station is selectively obtained based on the visualization display report template corresponding to each manager and the monitoring data corresponding to each new energy power station, including:

[0084] Based on the visualization report template corresponding to each manager and the monitoring data corresponding to each new energy power station, a visualization report corresponding to each new energy power station is obtained;

[0085] Obtain environmental data for each new energy power station;

[0086] Based on the visual display report corresponding to each new energy power station, the monitoring data corresponding to each new energy power station and the environmental data, the decision display plan corresponding to each manager of each new energy power station is selectively obtained.

[0087] Specifically, in some embodiments, the environmental data includes at least data values ​​of air temperature, air humidity, wind speed, wind direction, and air pollutant concentration.

[0088] Specifically, in some embodiments, the preset historical database also stores historical decision suggestions corresponding to each set of historical monitoring data.

[0089] Furthermore, in some embodiments, a preset execution operation comparison table is stored in the intelligent decision analysis model, and the execution operation comparison table includes multiple execution operations of different types, multiple execution parameter ranges corresponding to each execution operation, and execution results corresponding to each execution parameter range. Before substituting the monitoring data corresponding to each new energy power station into the intelligent decision analysis model, the method further trains the intelligent decision analysis model through the following steps:

[0090] Taking each new energy power station as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include a group of monitoring data corresponding to the training sample and a group of environmental data corresponding to the monitoring data;

[0091] Obtain the visualization report template corresponding to each set of training samples;

[0092] Based on the visualization report template corresponding to each training sample set and each training sample set, select part of the monitoring data corresponding to the visualization report template in each training sample set;

[0093] Estimation is performed based on each group of training sample sets to obtain estimated monitoring data corresponding to each group of training sample sets;

[0094] Based on the visualization report template corresponding to each training sample set, the estimated monitoring data and part of the monitoring data of each training sample set, a visualization report corresponding to each training sample set is obtained, wherein the visualization report includes a current visualization report and an estimated visualization report;

[0095] Based on the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, a plurality of decision suggestions corresponding to each training sample set are formed, wherein the decision suggestions include current decision suggestions corresponding to the current visualization report and estimated decision suggestions corresponding to the estimated visualization report;

[0096] Based on the groups of decision suggestions corresponding to each group of training sample sets, select a group of decision suggestions as the decision suggestions corresponding to the training sample sets;

[0097] The decision suggestions corresponding to each group of training sample sets are compared with the historical decision suggestions corresponding to each group of training sample sets, and based on the comparison results, the training results of the intelligent decision analysis model are obtained.

[0098] Specifically, in some embodiments, obtaining multiple groups of training sample sets corresponding to each training sample includes:

[0099] Based on the preset historical database, multiple groups of historical monitoring data corresponding to each training sample and the monitoring time point corresponding to each group of historical monitoring data are randomly selected;

[0100] Based on the monitoring time point corresponding to each set of historical monitoring data and a preset historical database, determine the historical environmental data corresponding to each set of historical monitoring data;

[0101] Based on the monitoring time point corresponding to each set of historical monitoring data and the historical environmental data corresponding to each set of historical monitoring data, obtaining the estimated environmental data corresponding to each set of historical monitoring data;

[0102] Based on multiple groups of historical monitoring data corresponding to each training sample, historical environmental data corresponding to each group of historical monitoring data, and estimated environmental data corresponding to each group of historical monitoring data, multiple groups of training sample sets corresponding to each training sample are constructed.

[0103] Specifically, in some embodiments, the method for obtaining the estimated environmental data and the estimated monitoring data may be to use a data analysis algorithm, or a trained neural network model, or predictive data generated by a machine learning model. The choice of acquisition method here is only an exemplary description. In actual testing, technical personnel in this field can make a choice based on actual needs, as long as the estimated environmental data can be obtained based on the monitoring time point and the historical environmental data corresponding to each group of historical monitoring data, and the estimated data can be obtained based on the training sample set to obtain the corresponding estimated monitoring data, which will not be repeated here.

[0104] Specifically, in some embodiments, based on the visualization report template corresponding to each training sample set and each training sample set, selecting part of the monitoring data corresponding to the visualization report template in each training sample set includes:

[0105] Based on the visualization report template corresponding to each group of training sample sets, multiple data categories matched by each group of training sample sets are determined;

[0106] Based on multiple data categories matched by each training sample set, each training sample set is screened, and part of the monitoring data corresponding to the visualization display report template in each training sample set is selected.

[0107] Specifically, in some embodiments, the visualization report corresponding to each training sample set is obtained based on the visualization report template corresponding to each training sample set, the estimated monitoring data, and part of the monitoring data of each training sample set, including:

[0108] Based on the visualization report template corresponding to each set of training sample sets and the estimated monitoring data, construct an estimated visualization report corresponding to each set of training sample sets;

[0109] Based on the visualization report template corresponding to each training sample set and part of the monitoring data of each training sample set, a current visualization report corresponding to each training sample set is constructed;

[0110] Blurring the estimated visualization report corresponding to each group of training sample sets, and superimposing the blurred estimated visualization report corresponding to each group of training sample sets with the current visualization report corresponding to the training sample sets to form a superimposed current visualization report and an estimated visualization report;

[0111] The current visualization report and the estimated visualization report that are superimposed and displayed are used as the visualization display reports corresponding to the training sample set.

[0112] Specifically, in some embodiments, the plurality of decision suggestions corresponding to each training sample set are formed based on the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, including:

[0113] Based on each group of training sample sets and a preset execution operation comparison table, determining multiple groups of execution operations corresponding to each group of training sample sets, wherein the execution operations include multiple operation types and execution parameter values ​​corresponding to each operation type;

[0114] Based on the visualization report corresponding to each set of training sample sets, determine the current running status and estimated running status corresponding to each set of training sample sets;

[0115] Based on the current operating state and the estimated operating state corresponding to each group of training sample sets, generate a current adjustment suggestion corresponding to the current operating state corresponding to the training sample set and an estimated adjustment suggestion for the estimated operating state corresponding to the training sample set;

[0116] Based on the current adjustment suggestions and estimated adjustment suggestions corresponding to each training sample set, multiple groups of execution operations corresponding to each training sample set, and the identity information of the managers corresponding to each training sample set, multiple groups of decision suggestions corresponding to each training sample set are constructed.

[0117] Specifically, in some embodiments, the types of operations performed include power plant operation adjustment, equipment maintenance, and fault warning.

[0118] Specifically, in some embodiments, based on the groups of decision suggestions corresponding to each group of training sample sets, selecting a group of decision suggestions as the decision suggestions corresponding to the training sample sets includes:

[0119] Perform simulations based on each group of decision suggestions corresponding to each group of training sample sets to obtain simulation data for each group of decision suggestions;

[0120] Based on the simulation data of each group of decision suggestions, the execution score and adjustment score of each group of decision suggestions are obtained;

[0121] Based on the execution score and the adjustment score of each group of decision suggestions, a group of decision suggestions is selected as the decision suggestions corresponding to the training sample set.

[0122] Specifically, in some embodiments, the simulation data includes data values ​​corresponding to a plurality of different data types, wherein the data type of the simulation data corresponds to the data type of the monitoring data, and the simulation data based on each group of decision suggestions, obtaining the execution score and adjustment score of each group of decision suggestions includes:

[0123] If the data value of any data type of the simulation data of the decision suggestion is better than the data value of the data type in the monitoring data of the training sample set corresponding to the decision suggestion, the execution score of the data type of the decision suggestion is recorded as "1"; otherwise, the execution score of the data type of the decision suggestion is recorded as "0";

[0124] If the execution score of the data type of the decision suggestion is recorded as "1", and the difference between the data value of any data type of the simulation data of the decision suggestion and the data value of the data type in the monitoring data of the training sample set corresponding to the decision suggestion exceeds the difference threshold corresponding to the data type, then the adjustment score of the data type of the decision suggestion is recorded as "1"; otherwise, the adjustment score of the data type of the decision suggestion is recorded as "0";

[0125] Specifically, the execution score of the decision suggestion is obtained by the following formula:

[0126] The execution score of the decision suggestion = the execution score of each data type * the sum of the weight coefficients corresponding to the data type;

[0127] Specifically, the adjustment score of the decision suggestion is obtained by the following formula:

[0128] The adjustment score of the decision suggestion = the adjustment score of each data type * the sum of the weight coefficients corresponding to the data type.

[0129] Specifically, in some embodiments, selecting a group of decision suggestions as the decision suggestions corresponding to the training sample set based on the execution score and the adjustment score of each group of decision suggestions includes:

[0130] Based on the execution scores and adjustment scores of the multiple groups of decision suggestions corresponding to each group of training sample sets, the multiple groups of decision suggestions corresponding to each group of training sample sets are preliminarily screened to select the multiple groups of decision suggestions corresponding to each group of training sample sets;

[0131] Sorting the execution scores and adjustment scores of the multiple decision suggestions corresponding to each of the screened training sample sets, and selecting a preset number of multiple decision suggestions corresponding to each of the training sample sets;

[0132] A cluster analysis is performed on a preset number of groups of decision suggestions corresponding to each group of training sample sets to obtain a group of decision suggestions corresponding to each group of training sample sets, and the decision suggestions are used as the decision suggestions corresponding to the training sample sets.

[0133] Specifically, in some embodiments, the preset number may be 3 or 4. The setting of the preset number here is only an exemplary description. In actual testing, those skilled in the art may set it according to actual needs, which will not be elaborated here.

[0134] Specifically, in some embodiments, obtaining the training result of the intelligent decision analysis model based on the comparison result includes:

[0135] If the decision suggestion corresponding to the training sample set is better than the historical decision suggestion corresponding to the training sample set, then the training result of the training sample set is determined to be training success; otherwise, then the training result of the training sample set is determined to be training failure;

[0136] Based on the training results of each training sample set, the total success rate of the intelligent decision analysis model training is obtained;

[0137] If the total success rate of the training of the intelligent decision analysis model is lower than the preset total success rate threshold, the training result of the intelligent decision analysis model is judged as a training failure, and the training of the intelligent decision analysis model is re-executed; otherwise, the training result of the intelligent decision analysis model is judged as a training success.

[0138] Specifically, in some embodiments, the preset total success rate threshold may be 95% or 98%. The setting of the preset total success rate threshold is only an example. In actual testing, those skilled in the art may set it according to actual needs, which will not be elaborated here.

[0139] In the above embodiment, in the model training, by taking each new energy power station as a training sample, obtaining multiple groups of training sample sets for each training sample, and obtaining a visualization display report template corresponding to the training sample set, each group of training sample sets can generate an intuitive visualization report chart or image, so that the management personnel corresponding to the template can more intuitively understand and interpret the data of the new energy power station, and then select part of the monitoring data matching it through the visualization report template and the training sample set, and estimate the training sample set to obtain the corresponding estimated monitoring data, and obtain the corresponding visualization display report based on the part of the monitoring data and the estimated monitoring data, so that the visualization display The report shows the current data and estimated data of the new energy power station at the same time, so that the management personnel can make advance deployment of the new energy power station through the visual display report, and then combine with the preset execution operation comparison table to form multiple corresponding groups of decision suggestions, and select one group of decision suggestions corresponding to the training sample set, so as to achieve a high degree of matching between the decision suggestions and the training sample set, thereby ensuring the normal operation of the new energy power station and the management personnel to carry out efficient energy management of the new energy power station, and compare it with the historical decision suggestions, and obtain the training results of the model according to the comparison results, so as to adjust and optimize the model in combination with the historical decision suggestions, so as to improve the accuracy and reliability of the model.

[0140] Step S104: Based on the decision presentation plans corresponding to the respective managers of each new energy power station, the decision presentation plan is presented to the managers corresponding to the decision presentation plan.

[0141] Specifically, in some embodiments, after the decision display scheme corresponding to each manager of each new energy power station is displayed to the manager corresponding to the decision display scheme, the method further includes:

[0142] Obtaining feedback data from managers who display the decision display plan, wherein the feedback data at least includes whether the decision suggestion is approved and the adjustment of the decision suggestion;

[0143] And based on the feedback data from the managers, a preset historical database is selectively updated.

[0144] Based on the above steps S101 to S104, by preprocessing the collected data of each new energy power station in real time, the monitoring data corresponding to each new energy power station is obtained, and the collected data is converted into a data format suitable for the intelligent decision-making analysis model, so as to facilitate the analysis of the monitoring data by the intelligent decision-making analysis model. By responding to the analysis instructions issued by the management personnel, the monitoring data is substituted into the intelligent decision-making analysis model, and the decision display plan corresponding to each manager is selectively obtained, so as to respond to the analysis instructions of the management personnel, and timely visualize and intuitively display the corresponding new energy power station operation report, and give corresponding decision suggestions, so that the management personnel can control and adjust the new energy power station in time according to the decision display plan, thereby ensuring the safe and efficient operation of the new energy power station, and avoiding the management method of new energy power stations in the prior art. When managing multiple new energy power stations with different structures, the management method generally adopts the generation of data reports in a unified format, which is not conducive to the precise management of different new energy power stations by different managers, thereby affecting the decision-making efficiency and accuracy of different managers of different new energy power stations. Technical problems.

[0145] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art can understand that in order to achieve the effects of the present invention, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present invention.

[0146] Furthermore, the present invention also provides an intelligent report decision system.

[0147] See attached Figure 2 , Figure 2 FIG. 1 is a main structural block diagram of an intelligent report decision system according to an embodiment of the present invention. Figure 2As shown, the intelligent report decision system 200 in the embodiment of the present invention interacts with information between multiple different new energy power stations. The system mainly includes a collection device 203, a preset historical database 204, an intelligent decision analysis model 202 and a control device 201. The collection device 203 is respectively connected to different new energy power stations for real-time collection of data from each new energy power station. The intelligent decision analysis model 202 stores a preset management personnel database 2021 and a preset execution operation comparison table 2022. The control device 201 includes a processor 2011 and a memory 2012. The memory 2012 can be configured to store a program code 2013 for executing the intelligent report decision method for new energy power stations in the above method embodiment. The processor 2011 can be configured to execute the program code 2013 in the memory 2012, which includes but is not limited to the program code 2013 for executing the intelligent report decision method for new energy power stations in the above method embodiment. For the convenience of explanation, only the part related to the embodiment of the present invention is shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The control device 201 may be a control device 201 device including various electronic devices.

[0148] Specifically, in some embodiments, the historical database 204 stores multiple groups of historical monitoring data of each new energy power station, the monitoring time point of each group of historical monitoring data, and the historical environmental data corresponding to each group of historical monitoring data;

[0149] The manager database 2021 includes multiple managers corresponding to each new energy power station, identity information of each manager, and a set of display options preset by each manager. The identity information of the manager includes the number, report viewing authority, and operation level authority corresponding to the manager;

[0150] The execution operation comparison table 2022 includes multiple execution operations of different types, multiple execution parameter ranges corresponding to each execution operation, and execution results corresponding to each execution parameter range;

[0151] The preset historical database 204 also stores historical decision suggestions corresponding to each set of historical monitoring data.

[0152] Specifically, in some embodiments, the collection device 203 can be a monitoring device installed in a new energy power station, or it can be a sensor device installed in a new energy power station. The selection of the collection device 203 here is only an exemplary description. In actual testing, technical personnel in this field can make a selection according to actual needs, as long as the collection data of each new energy power station can be collected in real time through the collection device 203, it will not be repeated here.

[0153] In one implementation, the description of the specific implementation functions may refer to steps S101 to S104.

[0154] The intelligent report decision system 200 is used to execute Figure 1 The embodiment of the intelligent report decision method for a new energy power station shown in the figure has similar technical principles, technical problems solved and technical effects produced. Technical personnel in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the intelligent report decision system 200 can refer to the contents described in the embodiment of the intelligent report decision method for a new energy power station, which will not be repeated here.

[0155] It is understood by those skilled in the art that the present invention implements all or part of the processes in the method of the above embodiment, and can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0156] Furthermore, the intelligent report decision system 200 also includes a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program code 2013 for executing the intelligent report decision method for a new energy power station of the above-mentioned method embodiment. The program code 2013 can be loaded and run by the processor 2011 to implement the above-mentioned intelligent report decision method for a new energy power station. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium can be a memory 2012 device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0157] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor 2011 itself, or a part of the software, a part of the hardware, or a part of the combination of software and hardware in the processor 2011. Therefore, the number of each module in the figure is only schematic.

[0158] Those skilled in the art will appreciate that the modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present invention.

[0159] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. An intelligent report decision method for a new energy power station, characterized in that: The method is applied to an intelligent report decision system, wherein the system interacts with a plurality of different new energy power stations, and the method comprises the following steps: Obtain the collected data of each new energy power station in real time; Pre-process the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station; In response to the analysis instructions issued by the managers of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each manager of each new energy power station is selectively obtained, wherein the decision display scheme includes a visual display report and a decision suggestion; Based on the decision display schemes corresponding to the managers of each new energy power station, the decision display schemes are displayed to the managers corresponding to the decision display schemes; The system stores a preset historical database, which stores multiple groups of historical monitoring data of each new energy power station, the monitoring time point of each group of historical monitoring data, and the historical environmental data corresponding to each group of historical monitoring data. Before preprocessing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station, the method further includes: Based on the collected data of each new energy power station and the preset historical database, determine whether it is necessary to re-acquire the collected data of the new energy power station: If the judgment is yes, the collected data of the new energy power station is re-acquired, and based on the re-acquired collected data and the preset historical database, "determining whether it is necessary to re-acquire the collected data of the new energy power station" is re-executed; If the judgment is no, then based on the collected data of the new energy power station, "pre-processing the collected data of each new energy power station to obtain the monitoring data corresponding to each new energy power station" is performed; The intelligent decision analysis model stores a preset management personnel database. In response to the analysis instructions issued by the management personnel of each new energy power station, the monitoring data corresponding to each new energy power station is substituted into the intelligent decision analysis model, and the decision display scheme corresponding to each management personnel of each new energy power station is selectively obtained, including: Get the number of the manager corresponding to each analysis instruction; Based on the numbers of the managers corresponding to the respective analysis instructions and a preset manager database, a preset display option set corresponding to each manager is obtained; Based on the preset display option set corresponding to each manager, a visualization display report template corresponding to each manager is constructed; Based on the visualization report template corresponding to each manager and the monitoring data corresponding to each new energy power station, the decision display plan corresponding to each manager of each new energy power station is selectively obtained; The intelligent decision analysis model stores a preset execution operation comparison table. Before substituting the monitoring data corresponding to each new energy power station into the intelligent decision analysis model, the method further trains the intelligent decision analysis model through the following steps: Taking each new energy power station as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include a group of monitoring data corresponding to the training sample and a group of environmental data corresponding to the monitoring data; Obtain the visualization report template corresponding to each set of training samples; Based on the visualization report template corresponding to each training sample set and each training sample set, select part of the monitoring data corresponding to the visualization report template in each training sample set; Estimation is performed based on each group of training sample sets to obtain estimated monitoring data corresponding to each group of training sample sets; Based on the visualization report template corresponding to each training sample set, the estimated monitoring data and part of the monitoring data of each training sample set, a visualization report corresponding to each training sample set is obtained, wherein the visualization report includes a current visualization report and an estimated visualization report; Based on the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, a plurality of decision suggestions corresponding to each training sample set are formed, wherein the decision suggestions include current decision suggestions corresponding to the current visualization report and estimated decision suggestions corresponding to the estimated visualization report; Based on the groups of decision suggestions corresponding to each group of training sample sets, select a group of decision suggestions as the decision suggestions corresponding to the training sample sets; Comparing the decision suggestions corresponding to each set of training sample sets with the historical decision suggestions corresponding to each set of training sample sets, and obtaining the training results of the intelligent decision analysis model based on the comparison results; The intelligent decision analysis model stores a preset execution operation comparison table. Before substituting the monitoring data corresponding to each new energy power station into the intelligent decision analysis model, the method further trains the intelligent decision analysis model through the following steps: Taking each new energy power station as a training sample, obtaining multiple groups of training sample sets corresponding to each training sample, wherein the training sample sets include a group of monitoring data corresponding to the training sample and a group of environmental data corresponding to the monitoring data; Obtain the visualization report template corresponding to each set of training samples; Based on the visualization report template corresponding to each training sample set and each training sample set, select part of the monitoring data corresponding to the visualization report template in each training sample set; Estimation is performed based on each group of training sample sets to obtain estimated monitoring data corresponding to each group of training sample sets; Based on the visualization report template corresponding to each training sample set, the estimated monitoring data and part of the monitoring data of each training sample set, a visualization report corresponding to each training sample set is obtained, wherein the visualization report includes a current visualization report and an estimated visualization report; Based on the visualization report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, a plurality of decision suggestions corresponding to each training sample set are formed, wherein the decision suggestions include current decision suggestions corresponding to the current visualization report and estimated decision suggestions corresponding to the estimated visualization report; Based on the groups of decision suggestions corresponding to each group of training sample sets, select a group of decision suggestions as the decision suggestions corresponding to the training sample sets; The decision suggestions corresponding to each group of training sample sets are compared with the historical decision suggestions corresponding to each group of training sample sets, and based on the comparison results, the training results of the intelligent decision analysis model are obtained.

2. The intelligent report decision method for a new energy power station according to claim 1 is characterized in that: The step of obtaining a plurality of training sample sets corresponding to each training sample comprises: Based on the preset historical database, multiple groups of historical monitoring data corresponding to each training sample and the monitoring time point corresponding to each group of historical monitoring data are randomly selected; Based on the monitoring time point corresponding to each set of historical monitoring data and a preset historical database, determine the historical environmental data corresponding to each set of historical monitoring data; Based on the monitoring time point corresponding to each set of historical monitoring data and the historical environmental data corresponding to each set of historical monitoring data, obtaining the estimated environmental data corresponding to each set of historical monitoring data; Based on multiple groups of historical monitoring data corresponding to each training sample, historical environmental data corresponding to each group of historical monitoring data, and estimated environmental data corresponding to each group of historical monitoring data, multiple groups of training sample sets corresponding to each training sample are constructed.

3. The intelligent report decision method for a new energy power station according to claim 2 is characterized in that: The selecting of part of the monitoring data corresponding to the visualization report template in each training sample set based on the visualization report template corresponding to each training sample set and each training sample set includes: Based on the visualization report template corresponding to each group of training sample sets, multiple data categories matched by each group of training sample sets are determined; Based on multiple data categories matched by each training sample set, each training sample set is screened, and part of the monitoring data corresponding to the visualization display report template in each training sample set is selected.

4. The intelligent report decision method for a new energy power station according to claim 3 is characterized in that: The visualization report corresponding to each training sample set is obtained based on the visualization report template corresponding to each training sample set, the estimated monitoring data, and part of the monitoring data of each training sample set, including: Based on the visualization report template corresponding to each set of training sample sets and the estimated monitoring data, construct an estimated visualization report corresponding to each set of training sample sets; Based on the visualization report template corresponding to each training sample set and part of the monitoring data of each training sample set, a current visualization report corresponding to each training sample set is constructed; Blurring the estimated visualization report corresponding to each group of training sample sets, and superimposing the blurred estimated visualization report corresponding to each group of training sample sets with the current visualization report corresponding to the training sample sets to form a superimposed current visualization report and an estimated visualization report; The current visualization report and the estimated visualization report that are superimposed and displayed are used as the visualization display reports corresponding to the training sample set.

5. The intelligent report decision method for a new energy power station according to claim 4 is characterized in that: The plurality of decision suggestions corresponding to each training sample set are formed based on the visualization display report corresponding to each training sample set, each training sample set and a preset execution operation comparison table, including: Based on each group of training sample sets and a preset execution operation comparison table, determining multiple groups of execution operations corresponding to each group of training sample sets, wherein the execution operations include multiple operation types and execution parameter values ​​corresponding to each operation type; Based on the visualization report corresponding to each set of training sample sets, determine the current running status and estimated running status corresponding to each set of training sample sets; Based on the current operating state and the estimated operating state corresponding to each group of training sample sets, generate a current adjustment suggestion corresponding to the current operating state corresponding to the training sample set and an estimated adjustment suggestion for the estimated operating state corresponding to the training sample set; Based on the current adjustment suggestions and estimated adjustment suggestions corresponding to each training sample set, multiple groups of execution operations corresponding to each training sample set, and the identity information of the managers corresponding to each training sample set, multiple groups of decision suggestions corresponding to each training sample set are constructed.

6. The intelligent report decision method for a new energy power station according to claim 5 is characterized in that: The selecting a group of decision suggestions as the decision suggestions corresponding to the training sample set based on the groups of decision suggestions corresponding to each group of training sample sets includes: Perform simulations based on each group of decision suggestions corresponding to each group of training sample sets to obtain simulation data for each group of decision suggestions; Based on the simulation data of each group of decision suggestions, the execution score and adjustment score of each group of decision suggestions are obtained; Based on the execution score and the adjustment score of each group of decision suggestions, a group of decision suggestions is selected as the decision suggestions corresponding to the training sample set.

7. An intelligent report decision system, characterized in that: The system exchanges information with multiple different new energy power stations. The system includes a collection device, a preset historical database, an intelligent decision analysis model and a control device. The collection device is respectively connected to different new energy power stations for real-time collection of data from each new energy power station. The intelligent decision analysis model stores a preset management personnel database and a preset execution operation comparison table. The control device includes a processor and a memory. The memory is suitable for storing multiple program codes, and is characterized in that the program code is suitable for being loaded and run by the processor to execute the intelligent report decision method for new energy power stations described in any one of claims 1 to 6.

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