Marketization trend data analysis decision-making method and system

Abstract

The invention discloses a marketization trend data analysis decision-making method and system, and the method comprises the steps: obtaining fifth power load data through processing original data, namely first power load data, and obtaining a power load data quality analysis report and the target total operation cost of all units according to the fifth power load data; and the power load data quality analysis report and the target total operation cost of all the units are used for marketization trend decision making, so that the data source of the marketization trend decision making is more sufficient and reliable.

Description

Technical Field

[0001] The present application belongs to the technical field of data processing, and in particular, relates to a market trend data analysis and decision-making method and system. Background Art

[0002] In the current power market environment, it is very important to regulate the operation of power grid connection and the management of power auxiliary services. However, the existing data analysis and application systems are insufficient in the analysis and application of market trends, unable to fully mine data, and unable to meet the needs of market participants for accurate decision-making and efficient operation. Summary of the invention

[0003] The purpose of this application is to provide a market-oriented trend data analysis and decision-making method to improve the adequacy of power data mining and analysis.

[0004] A first aspect of an embodiment of the present application provides a market trend data analysis and decision-making method, comprising:

[0005] According to the preset data collection rules, first power load data is obtained from the data server, the first power load data is subjected to a first preprocessing to obtain second power load data, and the second power load data is subjected to a second preprocessing to obtain third power load data; the first preprocessing includes noise removal, error correction and format conversion; the second preprocessing includes data verification, data conversion and data loading;

[0006] Extract the third power load data according to the preset rules of the data evaluation index to obtain fourth power load data; perform third preprocessing on the fourth power load data to obtain fifth power load data; obtain a power load data quality analysis report based on the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values ​​and correcting errors;

[0007] Obtaining target total operating costs of all units in the power plant according to the fifth circuit load data;

[0008] The power load data quality analysis report and the target total operating cost of all units are used for decision-making on market trends.

[0009] In one embodiment, obtaining the output target value of each unit according to the fifth circuit load data includes:

[0010] According to the output value and operating cost of each unit, the total operating cost function of all units is obtained;

[0011] According to the upper and lower limit constraints of the unit's output and the power balance constraints of all units, an external point penalty function is constructed;

[0012] Constructing an objective function according to the total operating cost function and the exterior point penalty function;

[0013] Based on the objective function, the target total operating cost of all units and the output value corresponding to each unit are obtained.

[0014] In one implementation manner, the total operating cost function of all units is obtained according to the output value and operating cost of each unit, including:

[0015]

[0016] Among them, C i is the operating cost function of unit i, and is related to the output P i Where N is the total number of units.

[0017] In one implementation manner, the external point penalty function is constructed according to the upper and lower limit constraints of the unit output and the power balance constraints of all units, including:

[0018] The upper and lower limits of the unit's output are satisfied: P i,min ≤P i ≤P i,max , for i=1,2,3,...,N;

[0019] The system power balance constraints meet: Where P deman d is the total power demand of the system;

[0020] The exterior point penalty function P(x) is as follows:

[0021]

[0022] Where r is the penalty factor.

[0023] In one implementation manner, the objective function F(x)=f(x)+P(x).

[0024] In one implementation manner, obtaining the target total operating cost of all units and the output value corresponding to each unit based on the objective function includes:

[0025] Increasing the value of the penalty factor until the target total operating cost of the unit meets the preset rules;

[0026] The output value of each unit corresponding to the target total operating cost of the unit that meets the preset rules is obtained.

[0027] The second aspect of the present application provides a market trend data analysis and decision-making system, including:

[0028] A data acquisition management module, configured to obtain first power load data from a data server according to a preset data acquisition rule, perform a first preprocessing on the first power load data to obtain second power load data, and perform a second preprocessing on the second power load data to obtain third power load data; the first preprocessing includes noise removal, error correction, and format conversion; the second preprocessing includes data verification, data conversion, and data loading;

[0029] A data quality analysis module, configured to extract the third power load data according to a preset rule of a data evaluation index to obtain fourth power load data; perform a third preprocessing on the fourth power load data to obtain fifth power load data; and obtain a power load data quality analysis report according to the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values, and correcting errors;

[0030] An auxiliary service analysis and assessment management analysis module, used to obtain the target total operating cost of all units in the power station according to the fifth circuit load data;

[0031] The market forecasting and analysis module is used to use the power load data quality analysis report and the target total operating costs of all units for decision-making on market trends.

[0032] In one embodiment, the data acquisition management module includes a data interface unit, a data acquisition unit, a first data preprocessing unit, a data cache unit, and a data transmission unit;

[0033] The data interface unit is used to obtain the power plant operation data of the safety zone I data acquisition server through a unified data interface. The data interface unit has the same data source as the dispatch center data, meets the data security compliance requirements, and ensures that the data transmission channel is unobstructed. The data interface unit supports TCP / IP, UDP, and OPC data interface protocols, and adapts to the data output formats of multiple systems;

[0034] The data acquisition unit is used to actively acquire first power load data from a data source according to a preset time interval or event trigger mechanism; the first power load data includes the collection of real-time data, historical data and batch data;

[0035] The first data preprocessing unit is used to preliminarily screen and sort the collected first power load data, remove obvious noise and erroneous data, and perform a unified conversion of the data format to obtain the second power load data;

[0036] The data cache unit is used to store the collected data to prevent data loss or interruption during transmission. When a network or system failure occurs, the data that has not been successfully transmitted is saved and resent after recovery;

[0037] The data transmission unit is used to obtain third power load data by verifying, encrypting and compressing the second power load data;

[0038] The data quality analysis module includes a data access unit, a data evaluation index setting unit, a data cleaning unit, a data analysis unit and a data quality report generation unit;

[0039] The data access unit is used to obtain the fourth power load data from the third power load data according to the preset rules of the data evaluation index from the data acquisition management module; the fourth power load data includes real-time operation data and historical data;

[0040] The data evaluation index setting unit is used to determine the indexes for evaluating data quality, and the indexes include accuracy, completeness, consistency, timeliness, and availability;

[0041] The data cleaning unit is used to detect and process duplicate data, missing data and erroneous data on the fourth power load data, identify and correct abnormal values, so as to obtain fifth power load data;

[0042] The data analysis unit is used to analyze the characteristics and rules of the data using a preset statistical analysis method and a preset data mining algorithm;

[0043] The data quality report generating unit is used to generate a power load data quality analysis report according to the analysis results, wherein the power load data quality analysis report includes an overall assessment of data quality, existing problems and improvement suggestions;

[0044] The auxiliary service analysis and assessment management analysis module also includes a data extraction unit, a service type classification unit, a service quality evaluation unit, an assessment index calculation unit, a comparison analysis unit and a result output unit;

[0045] The data extraction unit is used to extract data related to the auxiliary service from the database, including service type, provision time, and service volume;

[0046] The service type classification unit is used to classify different auxiliary services, including peak load regulation, frequency regulation, standby, and reactive power compensation;

[0047] The service quality evaluation unit is used to preset auxiliary service analysis standards and indicators and assessment analysis indicators to evaluate the quality level of each auxiliary service;

[0048] The assessment index calculation unit is used to calculate the values ​​of various assessment indicators according to preset assessment regulations;

[0049] The comparison and analysis unit is used to compare and analyze the actual service situation with the assessment standard to find out the gaps and advantages;

[0050] The result output unit is used to generate an analysis report and assessment results of the auxiliary service, including service quality evaluation, assessment score, and improvement suggestions;

[0051] The market forecasting and analysis module also includes a data collection unit, a second data preprocessing unit, a feature engineering unit, a model selection and training unit, a model evaluation and optimization unit, a scenario simulation unit, and a result output and visualization unit;

[0052] The data collection unit is responsible for acquiring data related to the power market from multiple data sources, including historical market data, macroeconomic data, weather data, policies and regulations;

[0053] The second data preprocessing unit is used to clean, organize and convert the collected data, and process missing values ​​and abnormal values ​​to make the data suitable for subsequent analysis and modeling;

[0054] The feature engineering unit is used to extract specific features from the original data, including seasonal features, trend features, and periodic features;

[0055] The model selection and training unit is used to select an adaptive prediction model based on data characteristics and prediction requirements, and train it through historical data, wherein the prediction model includes at least one of a time series model and a machine learning model;

[0056] The model evaluation and optimization unit is used to evaluate the trained model using multiple evaluation indicators, and adjust and optimize the model according to the evaluation results;

[0057] The scenario simulation unit is used to simulate and predict market trends according to different preset scenarios, including policy changes, major project construction, and extreme weather;

[0058] The result output and visualization unit is used to output the prediction results in the form of clear and intuitive charts and reports.

[0059] In one embodiment, the system further comprises a data fusion analysis module;

[0060] The data fusion analysis module includes a data source integration unit, a data standardization unit, a feature extraction unit, a data fusion algorithm unit, a correlation analysis unit and a visualization display unit;

[0061] The data source integration unit is used to integrate data from different data sources, including the dispatching center, power generation enterprises, and power grid companies;

[0062] The data standardization unit is used to standardize heterogeneous data from different sources and unify data formats, units and codes;

[0063] The feature extraction unit is used to extract key features from the standardized data, including the periodic characteristics of power supply and demand and the seasonal characteristics of ancillary service demand;

[0064] The data fusion algorithm unit is used to fuse multi-source data using a data fusion algorithm; the data fusion algorithm includes at least one of a weighted average method, a Kalman filter method, and a DS evidence theory;

[0065] The correlation analysis unit is used to mine the inherent correlation and potential laws between the fused data, wherein the inherent correlation and potential laws include the correlation between power price and supply and demand, and the correlation between auxiliary services and grid stability;

[0066] The visualization display unit is used to display the results of data fusion analysis in the form of charts and graphs.

[0067] In one embodiment, the system further includes an assessment alarm module and a unified data module;

[0068] The assessment alarm module includes a real-time monitoring unit, an assessment standard setting unit, a data analysis and comparison unit, an alarm rule formulation unit, an alarm generation and sending unit, and an alarm recording and statistics unit;

[0069] The real-time monitoring unit is used to track and monitor the operation of relevant data and business processes and obtain real-time status information;

[0070] The assessment standard setting unit is used to define and set specific standards and thresholds for various assessments, including data accuracy, service quality indicators, and response time;

[0071] The data analysis and comparison unit is used to compare and analyze the real-time monitored data with the preset assessment standards to determine whether there are any abnormalities or violations;

[0072] The alarm rule formulation unit is used to determine the alarm mode, level and notification object corresponding to different types of violations or abnormal situations;

[0073] The alarm generation and sending unit is used to generate corresponding alarm information when the monitoring data reaches the alarm condition, and send it to the preset personnel through the preset multiple channels; the preset multiple channels include SMS, email, and system pop-up window;

[0074] The alarm recording and statistics unit is used to record and store the generated alarm information, and to perform statistical analysis on the type, frequency, and processing status of the alarm;

[0075] The unified data module includes a data service interface unit, a metadata management unit, a master data management unit, a data maintenance unit, a security compliance management unit and a data storage unit.

[0076] Compared with the prior art, the present application has the following beneficial effects: the fifth power load data is obtained by processing the original data, the first power load data, and then the power load data quality analysis report and the target total operating cost of all units are obtained based on the fifth power load data. Then, the power load data quality analysis report and the target total operating cost of all units are used for decision-making on market trends, so that the data source for the decision on market trends is more sufficient and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 A schematic flow chart of a market trend data analysis and decision-making method provided in an embodiment of the present application;

[0078] Figure 2 A first exemplary principle block diagram of a market trend data analysis and decision-making system provided in an embodiment of the present application;

[0079] Figure 3 This is a second example principle block diagram of the market trend data analysis and decision-making system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0080] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0081] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0082] Figure 1 A flowchart of a method for market trend data analysis and decision-making provided by an embodiment of the present application is shown. For ease of explanation, only the part related to the present embodiment is shown, which is described in detail as follows:

[0083] A market trend data analysis and decision-making method, including S100-S400.

[0084] S100: Acquire first power load data from a data server according to preset data acquisition rules, perform a first preprocessing on the first power load data to obtain second power load data, and perform a second preprocessing on the second power load data to obtain third power load data; the first preprocessing includes noise removal, error correction and format conversion; the second preprocessing includes data verification, data conversion and data loading.

[0085] The frequency of collection can be adjusted according to the importance and real-time requirements of the data, for example, the first power load data can be collected from the dispatching center once every 5 minutes.

[0086] S200: Extract the third power load data according to preset rules of data evaluation indicators to obtain fourth power load data; perform third preprocessing on the fourth power load data to obtain fifth power load data; obtain a power load data quality analysis report based on the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values ​​and correcting errors.

[0087] Fifth, before the power load data is stored, it is verified, converted and loaded to ensure that other modules of the system can obtain the latest and accurate data in real time.

[0088] S300: According to the fifth circuit load data, the target total operating cost of all units in the power station is obtained. The target total operating cost of all units tends to be the minimum operating cost, but due to practical reasons, the target total operating cost of all units will not reach the minimum value. Generally, some preset indicators are set, as long as the target total operating cost of all units meets these preset indicators, for example, the target total operating cost is lower than the preset value.

[0089] S400: The power load data quality analysis report and the target total operating costs of all units are used for decision-making on market trends.

[0090] In this embodiment, the fifth power load data is obtained by processing the original data, the first power load data, and then the power load data quality analysis report and the target total operating cost of all units are obtained based on the fifth power load data. Then, the power load data quality analysis report and the target total operating cost of all units are used for decision-making on market trends, so that the data source for the decision on market trends is more sufficient and reliable.

[0091] In one embodiment, obtaining the output target value of each unit according to the fifth circuit load data includes:

[0092] According to the output value and operating cost of each unit, the total operating cost function of all units is obtained;

[0093] According to the upper and lower limit constraints of the unit's output and the power balance constraints of all units, an external point penalty function is constructed;

[0094] Constructing an objective function according to the total operating cost function and the exterior point penalty function;

[0095] Based on the objective function, the target total operating cost of all units and the output value corresponding to each unit are obtained.

[0096] In this embodiment, automatic generation control AGC is implemented, which automatically controls the cost of power generation to be maintained at a low value.

[0097] In one implementation manner, the total operating cost function of all units is obtained according to the output value and operating cost of each unit, including:

[0098]

[0099] Among them, C i is the operating cost function of unit i, and is related to the output P i Where N is the total number of units.

[0100] In one implementation manner, the external point penalty function is constructed according to the upper and lower limit constraints of the unit output and the power balance constraints of all units, including:

[0101] The upper and lower limits of the unit's output are satisfied: P i,min ≤P i ≤P i,max , for i=1,2,3,...,N;

[0102] The system power balance constraints meet: Where P demand is the total power demand of the system;

[0103] The exterior point penalty function P(x) is as follows:

[0104]

[0105] Where r is the penalty factor.

[0106] In one implementation manner, the objective function F(x)=f(x)+P(x).

[0107] In one implementation manner, obtaining the target total operating cost of all units and the output value corresponding to each unit based on the objective function includes:

[0108] Increasing the value of the penalty factor until the target total operating cost of the unit meets the preset rules;

[0109] The output value of each unit corresponding to the target total operating cost of the unit that meets the preset rules is obtained.

[0110] The target total operating cost of all units and the corresponding output value of each unit obtained by the above method will enable the power station to save more costs while outputting the same power.

[0111] For example, when the output of a unit exceeds the upper or lower limit, or the system power is unbalanced, the penalty function value will increase, forcing the algorithm to find a solution that satisfies the constraints in subsequent iterations. As the algorithm proceeds, the penalty factor r is gradually increased to increase the penalty for violating the constraints, prompting the algorithm to converge to the optimal solution that satisfies the constraints.

[0112] like Figure 2 As shown, the present application also provides a market trend data analysis and decision-making system, including a data collection management module 100, a data quality analysis module 200, an auxiliary service analysis and assessment management analysis module 300 and a market forecasting analysis module 400.

[0113] The data acquisition management module 100 is used to obtain first power load data from a data server according to preset data acquisition rules, perform a first preprocessing on the first power load data to obtain second power load data, and perform a second preprocessing on the second power load data to obtain third power load data; the first preprocessing includes noise removal, error correction and format conversion; the second preprocessing includes data verification, data conversion and data loading.

[0114] The data quality analysis module 200 is used to extract the third power load data according to the preset rules of the data evaluation index to obtain the fourth power load data; perform a third preprocessing on the fourth power load data to obtain the fifth power load data; and obtain a power load data quality analysis report according to the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values ​​and correcting errors;

[0115] The auxiliary service analysis and assessment management analysis module 300 is used to obtain the target total operating cost of all units in the power station according to the fifth circuit load data.

[0116] The market forecasting and analysis module 400 is used to use the power load data quality analysis report and the target total operating costs of all units for decision-making on market trends.

[0117] Please also see Figure 3 In one embodiment, the data acquisition management module includes a data interface unit, a data acquisition unit, a first data preprocessing unit, a data cache unit and a data transmission unit.

[0118] The data interface unit is used to obtain the power plant operation data of the data acquisition server in the safety zone I through a unified data interface. The data interface unit has the same source as the dispatch center data, meets the data security compliance requirements, and ensures that the data transmission channel is unobstructed. The data interface unit supports TCP / IP, UDP, and OPC data interface protocols and adapts to the data output formats of multiple systems. When the system starts, the data interface unit of the data acquisition management module first establishes a connection with the dispatch center data server through forward isolation to obtain initialization configuration and parameter verification;

[0119] The data acquisition unit is used to actively acquire first power load data from a data source according to a preset time interval or event trigger mechanism; the first power load data includes the collection of real-time data, historical data and batch data;

[0120] The first data preprocessing unit is used to preliminarily screen and sort the collected first power load data, remove obvious noise and erroneous data, and perform a unified conversion of the data format to obtain the second power load data;

[0121] The data cache unit is used to store the collected data to prevent data loss or interruption during transmission. When a network or system failure occurs, the data that has not been successfully transmitted is saved and resent after recovery;

[0122] The data transmission unit is used to obtain third power load data by verifying, encrypting and compressing the second power load data;

[0123] The data quality analysis module includes a data access unit, a data evaluation index setting unit, a data cleaning unit, a data analysis unit and a data quality report generation unit;

[0124] The data access unit is used to obtain the fourth power load data from the third power load data according to the preset rules of the data evaluation index from the data acquisition management module; the fourth power load data includes real-time operation data and historical data;

[0125] The data evaluation index setting unit is used to determine the indexes for evaluating data quality, and the indexes include accuracy, completeness, consistency, timeliness, and availability;

[0126] The data cleaning unit is used to detect and process duplicate data, missing data and erroneous data on the fourth power load data, identify and correct abnormal values, so as to obtain fifth power load data;

[0127] The data analysis unit is used to analyze the characteristics and rules of the data using a preset statistical analysis method and a preset data mining algorithm;

[0128] The data quality report generating unit is used to generate a power load data quality analysis report according to the analysis results, wherein the power load data quality analysis report includes an overall assessment of data quality, existing problems and improvement suggestions;

[0129] The auxiliary service analysis and assessment management analysis module also includes a data extraction unit, a service type classification unit, a service quality evaluation unit, an assessment index calculation unit, a comparison analysis unit and a result output unit;

[0130] The data extraction unit is used to extract data related to the auxiliary service from the database, including service type, provision time, and service volume;

[0131] The service type classification unit is used to classify different auxiliary services, including peak load regulation, frequency regulation, standby, and reactive power compensation;

[0132] The service quality evaluation unit is used to preset auxiliary service analysis standards and indicators and assessment analysis indicators to evaluate the quality level of each auxiliary service;

[0133] The evaluation index calculation unit is used to calculate the values ​​of various evaluation indicators according to the preset evaluation regulations; wherein the predicted evaluation regulations can be based on the evaluation regulations in the "two detailed rules". The "two detailed rules" refer to the documents "Implementation Rules for the Management of Grid-connected Operation of Power Plants" and "Implementation Rules for the Management of Auxiliary Services of Grid-connected Power Plants" issued by the National Energy Administration, the State Electricity Regulatory Commission and various regional power regulatory agencies.

[0134] The comparison and analysis unit is used to compare and analyze the actual service situation with the assessment standard to find out the gaps and advantages;

[0135] The result output unit is used to generate an analysis report and assessment results of the auxiliary service, including service quality evaluation, assessment score, and improvement suggestions;

[0136] The market forecasting and analysis module also includes a data collection unit, a second data preprocessing unit, a feature engineering unit, a model selection and training unit, a model evaluation and optimization unit, a scenario simulation unit, and a result output and visualization unit;

[0137] The data collection unit is responsible for acquiring data related to the power market from multiple data sources, including historical market data, macroeconomic data, weather data, policies and regulations;

[0138] The second data preprocessing unit is used to clean, organize and convert the collected data, and process missing values ​​and abnormal values ​​to make the data suitable for subsequent analysis and modeling;

[0139] The feature engineering unit is used to extract specific features from the original data, including seasonal features, trend features, and periodic features;

[0140] The model selection and training unit is used to select an adaptive prediction model based on data characteristics and prediction requirements, and train it through historical data, wherein the prediction model includes at least one of a time series model and a machine learning model;

[0141] The model evaluation and optimization unit is used to evaluate the trained model using multiple evaluation indicators, and adjust and optimize the model according to the evaluation results;

[0142] The scenario simulation unit is used to simulate and predict market trends according to different preset scenarios, including policy changes, major project construction, and extreme weather;

[0143] The result output and visualization unit is used to output the prediction results in the form of clear and intuitive charts and reports.

[0144] In one embodiment, the system further comprises a data fusion analysis module;

[0145] The function of the data fusion analysis module is to integrate the relevant data of the "two rules" from different data sources. Use multi-dimensional data analysis methods to explore the potential associations and trends between data. The data fusion analysis module includes a data source integration unit, a data standardization unit, a feature extraction unit, a data fusion algorithm unit, a correlation analysis unit and a visualization display unit;

[0146] The data source integration unit is used to integrate data from different data sources, including but not limited to dispatch centers, power generation enterprises, and power grid companies;

[0147] The data standardization unit is used to standardize heterogeneous data from different sources and unify data formats, units and codes;

[0148] The feature extraction unit is used to extract key features from the standardized data, including the periodic characteristics of power supply and demand and the seasonal characteristics of ancillary service demand;

[0149] The data fusion algorithm unit is used to fuse multi-source data using a data fusion algorithm; the data fusion algorithm includes at least one of a weighted average method, a Kalman filter method, and a DS evidence theory;

[0150] The correlation analysis unit is used to mine the inherent correlation and potential laws between the fused data, wherein the inherent correlation and potential laws include the correlation between power price and supply and demand, and the correlation between auxiliary services and grid stability;

[0151] The visualization display unit is used to display the results of data fusion analysis in the form of charts and graphs.

[0152] In one embodiment, the system further includes an assessment alarm module and a unified data module;

[0153] The assessment alarm module mainly monitors data and analysis results in real time, issues early warnings for possible violations of the "two detailed rules", and generates detailed alarm information, including violations, involved entities, etc. The assessment alarm module includes a real-time monitoring unit, an assessment standard setting unit, a data analysis and comparison unit, an alarm rule formulation unit, an alarm generation and sending unit, and an alarm recording and statistics unit;

[0154] The real-time monitoring unit is used to track and monitor the operation of relevant data and business processes and obtain real-time status information;

[0155] The assessment standard setting unit is used to define and set specific standards and thresholds for various assessments, including but not limited to data accuracy, service quality indicators, and response time;

[0156] The data analysis and comparison unit is used to compare and analyze the real-time monitored data with the preset assessment standards to determine whether there are any abnormalities or violations;

[0157] The alarm rule formulation unit is used to determine the alarm mode, level and notification object corresponding to different types of violations or abnormal situations;

[0158] The alarm generation and sending unit is used to generate corresponding alarm information when the monitoring data reaches the alarm condition, and send it to the preset personnel through the preset multiple channels; the preset multiple channels include SMS, email, and system pop-up window;

[0159] The alarm recording and statistics unit is used to record and store the generated alarm information, and to perform statistical analysis on the type, frequency, and processing status of the alarm;

[0160] The unified data module includes a data service interface unit, a metadata management unit, a master data management unit, a data maintenance unit, a security compliance management unit and a data storage unit.

[0161] 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.

[0162] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0163] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0164] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0165] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0166] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0167] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These 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 application, and should all be included in the protection scope of the present application.

Claims

1. A market trend data analysis and decision-making method, characterized in that: include: Acquire first power load data from a data server according to a preset data acquisition rule, perform a first preprocessing on the first power load data to obtain second power load data, and perform a second preprocessing on the second power load data to obtain third power load data; The first preprocessing includes noise removal, error correction and format conversion; The second preprocessing includes data verification, data conversion and data loading; Extracting the third power load data according to a preset rule of the data evaluation index to obtain fourth power load data; Performing a third preprocessing on the fourth power load data to obtain fifth power load data; Obtaining a power load data quality analysis report based on the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values ​​and correcting errors; Obtaining target total operating costs of all units in the power plant according to the fifth circuit load data; The power load data quality analysis report and the target total operating cost of all units are used for decision-making on market trends.

2. The method according to claim 1, characterized in that The step of obtaining the target output value of each unit according to the fifth circuit load data includes: According to the output value and operating cost of each unit, the total operating cost function of all units is obtained; According to the upper and lower limit constraints of the unit's output and the power balance constraints of all units, an external point penalty function is constructed; Constructing an objective function according to the total operating cost function and the exterior point penalty function; Based on the objective function, the target total operating cost of all units and the output value corresponding to each unit are obtained.

3. The method according to claim 2, characterized in that The total operating cost function of all units is obtained according to the output value and operating cost of each unit, including: Among them, C i is the operating cost function of unit i, and is related to the output P i Where N is the total number of units.

4. The method according to claim 2, characterized in that According to the upper and lower limit constraints of the unit's output and the power balance constraints of all units, an external point penalty function is constructed, including: The upper and lower limits of the unit's output are satisfied: P i,min ≤P i ≤P i,max , for i=1,2,3,...,N; The system power balance constraints meet: Where Pd eman d is the total power demand of the system; The exterior point penalty function P(x) is as follows: Where r is the penalty factor.

5. The method according to claim 2, characterized in that The objective function F(x)=f(x)+P(x).

6. The method according to claim 5, characterized in that The obtaining of the target total operating cost of all units and the output value corresponding to each unit based on the objective function includes: Increasing the value of the penalty factor until the target total operating cost of the unit meets the preset rules; The output value of each unit corresponding to the target total operating cost of the unit that meets the preset rules is obtained.

7. A market trend data analysis and decision-making system, characterized in that: include: A data acquisition management module, configured to obtain first power load data from a data server according to a preset data acquisition rule, perform a first preprocessing on the first power load data to obtain second power load data, and perform a second preprocessing on the second power load data to obtain third power load data; The first preprocessing includes noise removal, error correction and format conversion; The second preprocessing includes data verification, data conversion and data loading; A data quality analysis module, configured to extract the third power load data according to a preset rule of a data evaluation index to obtain fourth power load data; Performing a third preprocessing on the fourth power load data to obtain fifth power load data; Obtaining a power load data quality analysis report based on the fifth power load data; the third preprocessing includes removing duplicate data, supplementing missing values ​​and correcting errors; An auxiliary service analysis and assessment management analysis module, used to obtain the target total operating cost of all units in the power station according to the fifth circuit load data; The market forecasting and analysis module is used to use the power load data quality analysis report and the target total operating costs of all units for decision-making on market trends.

8. The system according to claim 7, characterized in that The data acquisition management module includes a data interface unit, a data acquisition unit, a first data preprocessing unit, a data cache unit and a data transmission unit; The data interface unit is used to obtain the power plant operation data of the safety zone I data acquisition server through a unified data interface. The data interface unit has the same data source as the dispatch center data, meets the data security compliance requirements, and ensures that the data transmission channel is unobstructed. The data interface unit supports TCP / IP, UDP, and OPC data interface protocols, and adapts to the data output formats of multiple systems; The data acquisition unit is used to actively acquire first power load data from a data source according to a preset time interval or event trigger mechanism; The first power load data includes the collection of real-time data, historical data and batch data; The first data preprocessing unit is used to preliminarily screen and sort the collected first power load data, remove obvious noise and erroneous data, and perform a unified conversion of the data format to obtain the second power load data; The data cache unit is used to store the collected data to prevent data loss or interruption during transmission. When a network or system failure occurs, the data that has not been successfully transmitted is saved and resent after recovery; The data transmission unit is used to obtain third power load data by verifying, encrypting and compressing the second power load data; The data quality analysis module includes a data access unit, a data evaluation index setting unit, a data cleaning unit, a data analysis unit and a data quality report generation unit; The data access unit is used to obtain the fourth power load data from the third power load data according to a preset rule of data evaluation indicators from the data acquisition management module; The fourth power load data includes real-time operation data and historical data; The data evaluation index setting unit is used to determine the indexes for evaluating data quality, and the indexes include accuracy, completeness, consistency, timeliness, and availability; The data cleaning unit is used to detect and process duplicate data, missing data and erroneous data on the fourth power load data, identify and correct abnormal values, so as to obtain fifth power load data; The data analysis unit is used to analyze the characteristics and rules of the data using a preset statistical analysis method and a preset data mining algorithm; The data quality report generating unit is used to generate a power load data quality analysis report according to the analysis results, wherein the power load data quality analysis report includes an overall assessment of data quality, existing problems and improvement suggestions; The auxiliary service analysis and assessment management analysis module also includes a data extraction unit, a service type classification unit, a service quality evaluation unit, an assessment index calculation unit, a comparison analysis unit and a result output unit; The data extraction unit is used to extract data related to the auxiliary service from the database, including service type, provision time, and service volume; The service type classification unit is used to classify different auxiliary services, including peak load regulation, frequency regulation, standby, and reactive power compensation; The service quality evaluation unit is used to preset auxiliary service analysis standards and indicators and assessment analysis indicators to evaluate the quality level of each auxiliary service; The assessment index calculation unit is used to calculate the values ​​of various assessment indicators according to preset assessment regulations; The comparison and analysis unit is used to compare and analyze the actual service situation with the assessment standard to find out the gaps and advantages; The result output unit is used to generate an analysis report and assessment results of the auxiliary service, including service quality evaluation, assessment score, and improvement suggestions; The market forecasting and analysis module also includes a data collection unit, a second data preprocessing unit, a feature engineering unit, a model selection and training unit, a model evaluation and optimization unit, a scenario simulation unit, and a result output and visualization unit; The data collection unit is responsible for acquiring data related to the power market from multiple data sources, including historical market data, macroeconomic data, weather data, policies and regulations; The second data preprocessing unit is used to clean, organize and convert the collected data, and process missing values ​​and abnormal values ​​to make the data suitable for subsequent analysis and modeling; The feature engineering unit is used to extract specific features from the original data, including seasonal features, trend features, and periodic features; The model selection and training unit is used to select an adaptive prediction model based on data characteristics and prediction requirements, and train it through historical data, wherein the prediction model includes at least one of a time series model and a machine learning model; The model evaluation and optimization unit is used to evaluate the trained model using multiple evaluation indicators, and adjust and optimize the model according to the evaluation results; The scenario simulation unit is used to simulate and predict market trends according to different preset scenarios, including policy changes, major project construction, and extreme weather; The result output and visualization unit is used to output the prediction results in the form of clear and intuitive charts and reports.

9. The system according to claim 7, characterized in that The system also includes a data fusion analysis module; The data fusion analysis module includes a data source integration unit, a data standardization unit, a feature extraction unit, a data fusion algorithm unit, a correlation analysis unit and a visualization display unit; The data source integration unit is used to integrate data from different data sources, including the dispatching center, power generation enterprises, and power grid companies; The data standardization unit is used to standardize heterogeneous data from different sources and unify data formats, units and codes; The feature extraction unit is used to extract key features from the standardized data, including the periodic characteristics of power supply and demand and the seasonal characteristics of ancillary service demand; The data fusion algorithm unit is used to fuse multi-source data using a data fusion algorithm; the data fusion algorithm includes at least one of a weighted average method, a Kalman filter method, and a DS evidence theory; The correlation analysis unit is used to mine the inherent correlation and potential laws between the fused data, wherein the inherent correlation and potential laws include the correlation between power price and supply and demand, and the correlation between auxiliary services and grid stability; The visualization display unit is used to display the results of data fusion analysis in the form of charts and graphs.

10. The system according to claim 7, characterized in that The system also includes an assessment alarm module and a unified data module; The assessment alarm module includes a real-time monitoring unit, an assessment standard setting unit, a data analysis and comparison unit, an alarm rule formulation unit, an alarm generation and sending unit, and an alarm recording and statistics unit; The real-time monitoring unit is used to track and monitor the operation of relevant data and business processes and obtain real-time status information; The assessment standard setting unit is used to define and set specific standards and thresholds for various assessments, including data accuracy, service quality indicators, and response time; The data analysis and comparison unit is used to compare and analyze the real-time monitored data with the preset assessment standards to determine whether there are any abnormalities or violations; The alarm rule formulation unit is used to determine the alarm mode, level and notification object corresponding to different types of violations or abnormal situations; The alarm generation and sending unit is used to generate corresponding alarm information when the monitoring data reaches the alarm condition, and send it to the preset personnel through the preset multiple channels; the preset multiple channels include SMS, email, and system pop-up window; The alarm recording and statistics unit is used to record and store the generated alarm information, and Conduct statistical analysis on the types, frequencies, and processing status of alarms; The unified data module includes a data service interface unit, a metadata management unit, a master data management unit, a data maintenance unit, a security compliance management unit and a data storage unit.

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