Electric power seeing economic analysis decision support system based on multi-source heterogeneous data

Abstract

The invention belongs to the technical field of decision support systems, and discloses an electric power seeing economic analysis decision support system based on multi-source heterogeneous data, and the system comprises a data integration module which is configured to receive and process multi-source heterogeneous data from a plurality of sources; the entity matching sub-module is configured to construct various indexes by using names, attributes and contextual information commonly existing in entities; the policy research module is configured to research key policy documents and tasks; the industry analysis module is configured to perform power demand influence analysis on the focused industry and output an industry analysis report; the data fusion analysis module is configured to collect related economic data in a normalized manner; and a decision support module configured to receive the report. The problems that in the prior art, only internal data of an electric power system are depended, correlation analysis with external economic data is neglected, the analysis result is one-sided, and the actual condition of economic operation cannot be comprehensively reflected are solved.

Description

Technical Field

[0001] The present application belongs to the technical field of decision support systems, and specifically relates to an electric power economic analysis decision support system based on multi-source heterogeneous data. Background Art

[0002] In today's society, electricity is an important cornerstone of national economic development, and its operation is closely related to economic development. Therefore, it is of great practical significance to gain insight into economic operation through electricity data and provide a scientific basis for decision-making. However, traditional electricity data analysis methods are often limited by the singleness of data sources and the limitations of analysis dimensions, making it difficult to fully and deeply reflect economic structure and characteristics, thus affecting the scientificity and accuracy of decision-making.

[0003] Existing technologies have obvious deficiencies in supporting economic analysis and decision-making in the electricity sector. On the one hand, existing technologies often rely only on internal data of the power system and ignore the correlation analysis with external economic data, resulting in one-sided analysis results that cannot fully reflect the actual situation of economic operation. On the other hand, the analysis dimension of existing technologies is relatively single, lacking the exploration of deep-level characteristics of economic structure, and it is difficult to reveal the potential laws and trends in economic development. In addition, the decision-making support function of existing technologies is relatively weak, and it cannot provide decision makers with scientific and accurate decision-making basis. Summary of the invention

[0004] The embodiment of the present application provides an electric power economic analysis decision support system based on multi-source heterogeneous data, thereby solving the problem that the prior art often relies only on internal data of the power system and ignores the correlation analysis with external economic data, resulting in one-sided analysis results that cannot fully reflect the actual situation of economic operation.

[0005] In order to achieve the above-mentioned object, an embodiment of the present invention provides a power economic analysis decision support system based on multi-source heterogeneous data, comprising:

[0006] A data integration module configured to receive and process multi-source heterogeneous data from multiple sources, wherein the multi-source heterogeneous data includes power data and economic data;

[0007] An entity matching submodule is configured to utilize the name, attribute and context information commonly found in entities, construct multiple indexes to reduce the computational space while generating high-quality candidate sets, and define a computational method for measuring entity similarity to determine whether entity pairs match;

[0008] The policy research module is configured to study key policy documents and tasks, conduct comprehensive analysis to improve decision-making, and output policy analysis reports;

[0009] The industry analysis module is configured to analyze the impact of electricity demand on key industries, design application scenarios for the electricity-based economy theme, and output industry analysis reports;

[0010] The data fusion analysis module is configured to collect relevant economic data on a regular basis, realize the fusion analysis of internal and external data, and output the economic structure and characteristics report;

[0011] The decision support module is configured to receive the policy analysis report, industry analysis report and economic structure and characteristics report to provide a scientific basis for decision-making.

[0012] In a possible implementation, the data integration module is configured to receive and process multi-source heterogeneous data from multiple sources, and the module includes a data receiving submodule, a data preprocessing submodule, a data classification and storage submodule, and a data output submodule.

[0013] In one possible implementation, the data preprocessing submodule includes a data cleaning unit, a data format conversion unit, and a data verification unit. The data cleaning unit is used to remove noise, outliers, and duplicate data from the received data; the data format conversion unit converts the data into a unified format; and the data verification unit verifies the integrity of the data.

[0014] In one possible implementation, the data classification and storage submodule includes a data classification unit and a storage management unit. The data classification unit divides the processed data into power data and economic data according to the data type; the storage management unit stores the classified data in corresponding databases respectively and sets corresponding access rights.

[0015] In a possible implementation, the entity matching submodule further includes:

[0016] Name index building unit, which performs word segmentation and standardization on entity names and builds an inverted index to achieve fast retrieval and preliminary matching based on names;

[0017] The attribute index building unit extracts and classifies the attribute information of the entity and builds a corresponding index for each attribute type to support refined attribute-based matching;

[0018] The context index building unit uses the context information of the entity to build a context index to enhance the accuracy and robustness of entity matching.

[0019] In a possible implementation, the entity matching submodule further includes:

[0020] The candidate set generation unit uses the above-mentioned multiple indexes to generate a high-quality candidate entity pair set by setting reasonable retrieval strategies and filtering conditions for subsequent similarity calculation and matching judgment;

[0021] A similarity calculation unit, which defines and implements a variety of similarity calculation methods, including but not limited to string-based similarity calculation, attribute-based similarity calculation, and context-based similarity calculation, to comprehensively evaluate the matching degree of candidate entity pairs;

[0022] The matching judgment unit performs matching judgment on candidate entity pairs according to the preset similarity threshold and matching rules, outputs the matching results, and provides matching confidence indicators for user reference.

[0023] In one possible implementation, the policy research module includes:

[0024] The data collection submodule is used to collect key policy documents and related information from multiple channels such as official websites, news media, and policy databases;

[0025] The data preprocessing submodule is used to clean, classify, and annotate the collected policy documents and related information to form structured data for subsequent analysis;

[0026] The policy analysis submodule uses natural language processing technology and data mining technology to conduct text analysis, keyword extraction, and topic modeling on policy documents to identify policy highlights, policy trends, and policy impacts;

[0027] The policy comparison unit is used to compare and analyze different policy documents, reveal the connections and differences between policies, and provide reference for decision-making.

[0028] In a possible implementation, the policy research module further includes: a report generation submodule, which automatically generates a formatted policy analysis report based on the policy analysis results and a preset report template;

[0029] The report generation submodule is also configured with an interactive editing function, allowing users to edit and adjust the automatically generated reports.

[0030] In a possible implementation, the industry analysis module includes:

[0031] The industrial data collection submodule is used to obtain relevant data of key industrial sectors from multiple sources;

[0032] Data preprocessing submodule, which is used to clean and organize the collected industrial data and remove outliers and duplicate data;

[0033] The power demand impact analysis submodule uses the collected and pre-processed industrial data to establish a mathematical model to analyze the changing trend of power demand in the industrial sector and the impact of power demand changes on the industrial economy.

[0034] In a possible implementation, the industry analysis module further includes:

[0035] Application scenario design submodule, which designs the application scenario of electricity economy based on the results of power demand impact analysis;

[0036] Report generation submodule, which automatically generates industry analysis reports based on the results of power demand impact analysis and application scenario design;

[0037] The report generation submodule also has the function of report customization, and users can choose the content and display format of the report according to their needs.

[0038] In a possible implementation, the data fusion analysis module includes:

[0039] The data collection submodule, which obtains relevant economic data from multiple data sources on a regular basis through the set collection strategy;

[0040] The data preprocessing submodule is used to clean, convert the format, and standardize the collected raw data to ensure data quality and consistency;

[0041] The data fusion submodule uses data matching, correlation analysis and other technical means to fuse the pre-processed internal and external data; the data fusion submodule is further configured with a data verification mechanism to verify the accuracy and completeness of the fused data;

[0042] The economic structure and characteristics analysis submodule uses the integrated data to deeply analyze the components, development changes and characteristics of the economic structure through statistical analysis, trend prediction, association mining and other methods;

[0043] The report generation submodule automatically generates an economic structure and characteristics report based on the analysis results of the economic structure and characteristics and combined with the preset report template.

[0044] In a possible implementation, the decision support module includes:

[0045] A report receiving submodule, which is used to receive and integrate policy analysis reports, industry analysis reports, and economic structure and characteristics reports from different analysis modules;

[0046] The data analysis submodule performs in-depth analysis on the received reports, extracts key indicators, trends and correlation factors to form a comprehensive decision-making data set;

[0047] The scenario simulation submodule is based on a comprehensive decision-making data set. By setting different policy, industry and economic scenarios, it simulates and predicts the possible results and impacts under various scenarios.

[0048] The decision-making recommendation generation submodule combines scenario simulation results and risk assessment to automatically generate scientific recommendations for decision-making;

[0049] The interactive interface submodule provides an operating interface for users to interact with the decision support module, supporting users to view analysis reports, adjust simulation parameters, receive decision suggestions, and provide feedback on decision results.

[0050] In a possible implementation, the scenario simulation submodule is further configured with a risk assessment function for assessing potential risks and uncertainties in different scenarios and providing risk warnings for decision making;

[0051] The decision suggestion generation submodule also has the suggestion priority sorting function, which sorts the suggestions according to the impact and risk level of the simulation results to highlight the key suggestions;

[0052] The interactive interface submodule is further configured with a permission management function to ensure that different users access corresponding functions and data according to their roles and permissions.

[0053] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0054] The embodiment of the present invention provides an electric power economic analysis decision support system based on multi-source heterogeneous data. The decision support module of the present invention provides a comprehensive scientific basis for decision-making by integrating multiple functional sub-modules such as report reception, data analysis, scenario simulation, decision suggestion generation, and interactive interface. This module not only improves the scientific nature and transparency of the decision-making process, but also enhances the pertinence and effectiveness of decision-making through risk assessment and suggestion priority sorting functions. The overall technical solution has demonstrated significant practicality and innovation in the field of decision support.

[0055] The invention proposes a power economic analysis decision support system based on multi-source heterogeneous data. By innovatively integrating multi-source heterogeneous data and building multiple functional modules, it realizes a comprehensive analysis of economic structure and characteristics and scientific support for decision-making. The system solves technical problems such as single data source, limited analysis dimension and insufficient decision-making basis in the traditional economic analysis and decision-making process, and brings significant technical effects.

[0056] First, the system has realized the regular collection of relevant economic data and effectively integrated internal and external data through the data fusion analysis module. This innovative measure not only broadens the channels for data acquisition, but also improves the quality and accuracy of data, laying a solid foundation for subsequent in-depth analysis.

[0057] Secondly, the system has a strong ability to analyze economic structure and characteristics. By using the integrated multi-dimensional data, the system can deeply analyze the components, development changes and characteristics of the economic structure, providing decision makers with a more comprehensive and objective economic analysis perspective.

[0058] In addition, the decision support module of the system can receive and analyze policy, industry and economic reports from different modules to provide a scientific basis for decision-making. Through scenario simulation and risk assessment functions, the system can predict the possible results and impacts under different policy, industry and economic scenarios, helping decision makers to formulate and adjust policies more scientifically and reduce decision-making risks.

[0059] Finally, the system also provides an interactive interface submodule to support users to conveniently interact with the system, view analysis reports, adjust simulation parameters, receive decision suggestions, etc. This functional design improves the system's usability and user experience, allowing decision makers to use the system more efficiently for decision support.

[0060] In summary, the power economic analysis decision support system based on multi-source heterogeneous data proposed in the present invention has achieved remarkable results in solving the technical problems in the traditional economic analysis decision-making process, and has provided decision makers with more scientific, comprehensive and efficient economic analysis decision support services. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0062] Figure 1 A schematic diagram of the structure of an electric power economic analysis decision support system based on multi-source heterogeneous data provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] In the description of the embodiments of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limitations on the present invention. The terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance. In addition, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to the specific circumstances.

[0065] like Figure 1 As shown, the power economic analysis decision support system based on multi-source heterogeneous data provided by the embodiment of the present invention includes:

[0066] A data integration module configured to receive and process multi-source heterogeneous data from multiple sources, wherein the multi-source heterogeneous data includes power data and economic data;

[0067] An entity matching submodule is configured to utilize the name, attribute and context information commonly found in entities, construct multiple indexes to reduce the computational space while generating high-quality candidate sets, and define a computational method for measuring entity similarity to determine whether entity pairs match;

[0068] The policy research module is configured to study key policy documents and tasks, conduct comprehensive analysis to improve decision-making, and output policy analysis reports;

[0069] The industry analysis module is configured to analyze the impact of electricity demand on key industries, design application scenarios for the electricity-based economy theme, and output industry analysis reports;

[0070] The data fusion analysis module is configured to collect relevant economic data on a regular basis, realize the fusion analysis of internal and external data, and output the economic structure and characteristics report;

[0071] The decision support module is configured to receive the policy analysis report, industry analysis report and economic structure and characteristics report to provide a scientific basis for decision-making.

[0072] In this embodiment, the data integration module further includes:

[0073] A data preprocessing submodule is configured to clean, convert and standardize the received multi-source heterogeneous data;

[0074] The data storage submodule is configured to store the preprocessed data in a database for subsequent modules to call.

[0075] In this embodiment, the industry analysis module further includes: a trend prediction submodule, which is configured to predict the future power demand trend of each industry based on historical power data and industry data.

[0076] In this embodiment, the decision support module further includes: a visualization submodule, configured to display the received report in the form of a chart or a visualization interface to facilitate user understanding and decision-making.

[0077] In this embodiment, the system is connected to an external data source via a network interface to achieve real-time updating and acquisition of data.

[0078] The present invention proposes an electric power economic analysis decision support system based on multi-source heterogeneous data, which effectively integrates data from different sources through the data integration module, thereby improving the quality and availability of the data. The application of the entity matching submodule enables the system to accurately identify the same entities in different data sources, further improving the accuracy of data fusion. The policy research module, industrial analysis module and data fusion analysis module provide comprehensive data support and analysis reports for decision-making, which contributes to the scientific and refined decision-making. On the whole, the system has strong practicality and creativity, and can effectively promote industrial transformation and upgrading, improve energy utilization efficiency, and promote sustainable economic development.

[0079] In this embodiment, the data integration module is configured to receive and process multi-source heterogeneous data from multiple sources, and the multi-source heterogeneous data explicitly includes power data and economic data. The module includes a data receiving submodule, a data preprocessing submodule, a data classification and storage submodule, and a data output submodule, and each submodule works together to achieve efficient integration and processing of multi-source heterogeneous data.

[0080] In this embodiment, the data receiving submodule is configured with multiple adapters, each adapter corresponds to a data source type, and is used to achieve connection and data reception with different types of data sources to ensure stable data transmission.

[0081] In this embodiment, the data preprocessing submodule includes a data cleaning unit, a data format conversion unit, and a data verification unit. The data cleaning unit is used to remove noise, abnormal values, and duplicate data from the received data; the data format conversion unit converts the data into a unified format; and the data verification unit verifies the integrity of the data to ensure the accuracy of the data.

[0082] In this embodiment, the data classification and storage submodule includes a data classification unit and a storage management unit. The data classification unit classifies the processed data into power data and economic data according to the data type; the storage management unit stores the classified data in the corresponding databases and sets corresponding access rights.

[0083] The data output submodule is equipped with a data query interface and data export function, which supports users to query and export stored power data and economic data according to needs.

[0084] In this embodiment, a data monitoring submodule is also included to monitor the status of data receiving, processing and storage in real time, and to issue an alarm in time when an abnormality occurs, so as to ensure the stability and reliability of the data integration process. The data monitoring submodule is also equipped with a log recording function, which can record the operation history of the data integration process in detail, so as to facilitate subsequent problem tracking and troubleshooting.

[0085] The data integration module of the present invention realizes efficient reception, accurate processing, secure storage and convenient output of multi-source heterogeneous data through detailed sub-module design and collaborative working mechanism. This module not only improves data processing efficiency and accuracy, but also enhances the stability and reliability of the data integration process, providing strong technical support for data applications in the power and economic fields. At the same time, through the introduction of the data monitoring sub-module, the security and maintainability of the data integration process are further guaranteed.

[0086] In this embodiment, the entity matching submodule also includes:

[0087] The name index building unit performs word segmentation and standardization on entity names and builds an inverted index to achieve fast name-based retrieval and preliminary matching.

[0088] The attribute index building unit extracts and classifies the attribute information of the entity and creates a corresponding index for each attribute type to support refined attribute-based matching.

[0089] The context index building unit uses the context information of the entity, such as associated entities, timestamps, etc., to build a context index to enhance the accuracy and robustness of entity matching.

[0090] The candidate set generation unit comprehensively utilizes the above-mentioned multiple indexes and generates a high-quality candidate entity pair set by setting reasonable retrieval strategies and filtering conditions for subsequent similarity calculation and matching judgment.

[0091] Contains a similarity calculation unit, which defines and implements multiple similarity calculation methods, including but not limited to string-based similarity calculation, attribute-based similarity calculation, and context-based similarity calculation, to comprehensively evaluate the matching degree of candidate entity pairs.

[0092] The matching judgment unit performs matching judgment on candidate entity pairs according to the preset similarity threshold and matching rules, outputs the matching results, and provides matching confidence indicators for user reference.

[0093] The entity matching submodule of the present invention constructs multiple indexes to reduce the computational space and generate high-quality candidate sets by comprehensively utilizing the name, attributes and context information of the entity. At the same time, multiple similarity calculation methods are defined to comprehensively evaluate the matching degree of entity pairs, thereby improving the accuracy and efficiency of entity matching. This technical solution is not only practical, but also demonstrates creative application in entity matching tasks in a big data environment.

[0094] In this embodiment, the policy research module includes:

[0095] The data collection submodule is used to collect key policy documents and related information from multiple channels such as official websites, news media, and policy databases.

[0096] The data preprocessing submodule is used to clean, classify and label the collected policy documents and related information to form structured data for subsequent analysis.

[0097] The policy analysis submodule uses natural language processing technology and data mining technology to perform text analysis, keyword extraction, and topic modeling on policy documents to identify policy highlights, policy trends, and policy impacts.

[0098] The policy comparison unit is used to compare and analyze different policy documents, reveal the connections and differences between policies, and provide reference for decision-making.

[0099] The report generation submodule automatically generates a formatted policy analysis report based on the policy analysis results and the preset report template. The report content includes but is not limited to policy overview, interpretation of policy key points, policy trend forecast, and policy recommendations.

[0100] The report generation submodule is also equipped with an interactive editing function, allowing users to edit and adjust the automatically generated reports to meet individual needs.

[0101] The policy push submodule is used to deliver relevant policy analysis reports to users in a timely manner through email, SMS, APP push, etc. based on user concerns and needs.

[0102] The policy research module of the present invention achieves comprehensive and in-depth research and rapid response to key policy documents by integrating multiple links such as data collection, preprocessing, analysis and report generation. This module not only improves the accuracy and efficiency of policy analysis, but also enhances the pertinence and practicality of policy analysis reports through interactive editing and personalized push functions. The overall technical solution demonstrates innovative applications in the field of policy research and provides strong support for decision-making.

[0103] In this embodiment, the industry analysis module includes:

[0104] The industrial data collection submodule is used to obtain relevant data on key industrial sectors from multiple sources, including but not limited to industrial scale, production capacity, electricity consumption, production and sales data.

[0105] The data preprocessing submodule is used to clean and organize the collected industrial data, remove outliers and duplicate data, and ensure the accuracy and consistency of the data.

[0106] The power demand impact analysis submodule uses the collected and pre-processed industrial data to establish a mathematical model to analyze the changing trend of power demand in the industrial sector and the impact of power demand changes on the industrial economy.

[0107] The power demand impact analysis submodule further includes a forecasting unit, which uses a machine learning algorithm to forecast the power demand of an industry in the future based on historical data and current data.

[0108] The application scenario design sub-module designs thematic application scenarios of electricity-based economics based on the results of the electricity demand impact analysis, including but not limited to industrial electricity demand monitoring, industrial electricity efficiency evaluation, and industrial economic development trend forecasting.

[0109] The application scenario design submodule is also equipped with a user interaction function, allowing users to customize and adjust the parameters and display methods of the application scenario according to actual needs.

[0110] Report generation submodule: This module automatically generates an industry analysis report based on the results of power demand impact analysis and application scenario design. The report content covers industry power demand analysis, economic development trend forecast and recommended measures.

[0111] The report generation submodule also has the function of report customization. Users can choose the content and display format of the report as needed to meet the needs of different users.

[0112] The industrial analysis module of the present invention integrates multiple functions such as industrial data collection, preprocessing, power demand impact analysis, application scenario design and report generation, and realizes a comprehensive analysis of the impact of power demand on key industries and innovative design of application scenarios. This module not only improves the depth and breadth of industrial analysis, but also meets the personalized needs of users through customized report generation functions. The overall technical solution has demonstrated significant practicality and creativity in the fields of industrial economic analysis and power demand forecasting.

[0113] In this embodiment, the data fusion analysis module includes:

[0114] The data collection submodule obtains relevant economic data from multiple data sources on a regular basis through the set collection strategy. The data sources include but are not limited to public data, industry reports, internal enterprise data, and third-party data service platforms.

[0115] The data preprocessing submodule is used to clean, convert the format, and standardize the collected raw data to ensure data quality and consistency for subsequent fusion analysis.

[0116] The data fusion submodule uses data matching, correlation analysis and other technical means to fuse the pre-processed internal and external data to form a comprehensive, multi-dimensional economic data set. The data fusion submodule is further equipped with a data verification mechanism to verify the accuracy and completeness of the fused data and ensure the reliability of the analysis results.

[0117] The economic structure and characteristics analysis submodule uses the integrated data to deeply analyze the components, development changes and characteristics of the economic structure through statistical analysis, trend forecasting, association mining and other methods. The economic structure and characteristics analysis submodule also has a visual display function, which can intuitively present the analysis results in the form of charts, reports, etc., which is easy for users to understand and use.

[0118] The report generation submodule automatically generates an economic structure and characteristics report based on the analysis results of the economic structure and characteristics and the preset report template. The report content covers the current situation, development trend, characteristics analysis and recommended measures of the economic structure. The report generation submodule further supports customized output of the report. Users can customize the report content, format and output method according to their needs to meet personalized analysis report needs.

[0119] The data fusion analysis module of the present invention realizes the comprehensive fusion and in-depth analysis of economic data by integrating multiple links such as normalized data collection, preprocessing, fusion analysis and report generation. This module not only improves the efficiency and accuracy of data processing, but also enhances the intuitiveness and practicality of the analysis results through visualization and customized reporting functions. The overall technical solution has shown significant practicality and innovation in the fields of economic data analysis and structural feature mining.

[0120] In this embodiment, the decision support module includes:

[0121] The report receiving submodule is used to receive and integrate policy analysis reports, industry analysis reports, and economic structure and characteristics reports from different analysis modules.

[0122] The data analysis submodule performs in-depth analysis on the received reports, extracts key indicators, trends and correlation factors to form a comprehensive decision-making data set.

[0123] The scenario simulation submodule is based on a comprehensive decision-making data set. By setting different policy, industry and economic scenarios, it simulates and predicts the possible results and impacts under various scenarios. The scenario simulation submodule is further equipped with a risk assessment function to assess the potential risks and uncertainties under different scenarios and provide risk warnings for decision-making.

[0124] The decision-making suggestion generation submodule combines the scenario simulation results and risk assessment to automatically generate scientific suggestions for decision-making. The suggestions cover policy adjustments, industrial development strategies, and economic structure optimization directions. The decision-making suggestion generation submodule also has a suggestion priority sorting function. It sorts the suggestions according to the impact and risk level of the simulation results to highlight the key suggestions.

[0125] The interactive interface submodule provides an operation interface for users to interact with the decision support module, supporting users to view analysis reports, adjust simulation parameters, receive decision suggestions, and provide feedback on decision effects. The interactive interface submodule is further configured with a permission management function to ensure that different users access corresponding functions and data according to their roles and permissions.

[0126] The decision support module of the present invention provides a comprehensive scientific basis for decision-making by integrating multiple functional submodules such as report reception, data analysis, scenario simulation, decision suggestion generation, and interactive interface. This module not only improves the scientificity and transparency of the decision-making process, but also enhances the pertinence and effectiveness of decision-making through risk assessment and suggestion priority sorting functions. The overall technical solution has demonstrated significant practicality and innovation in the field of decision support.

[0127] The invention proposes a power economic analysis decision support system based on multi-source heterogeneous data. By innovatively integrating multi-source heterogeneous data and building multiple functional modules, it realizes a comprehensive analysis of economic structure and characteristics and scientific support for decision-making. The system solves technical problems such as single data source, limited analysis dimension and insufficient decision-making basis in the traditional economic analysis and decision-making process, and brings significant technical effects.

[0128] First, the system has realized the regular collection of relevant economic data and effectively integrated internal and external data through the data fusion analysis module. This innovative measure not only broadens the channels for data acquisition, but also improves the quality and accuracy of data, laying a solid foundation for subsequent in-depth analysis.

[0129] Secondly, the system has a strong ability to analyze economic structure and characteristics. By using the integrated multi-dimensional data, the system can deeply analyze the components, development changes and characteristics of the economic structure, providing decision makers with a more comprehensive and objective economic analysis perspective.

[0130] In addition, the decision support module of the system can receive and analyze policy, industry and economic reports from different modules to provide a scientific basis for decision-making. Through scenario simulation and risk assessment functions, the system can predict the possible results and impacts under different policy, industry and economic scenarios, helping decision makers to formulate and adjust policies more scientifically and reduce decision-making risks.

[0131] Finally, the system also provides an interactive interface submodule to support users to conveniently interact with the system, view analysis reports, adjust simulation parameters, receive decision suggestions, etc. This functional design improves the system's usability and user experience, allowing decision makers to use the system more efficiently for decision support.

[0132] In summary, the power economic analysis decision support system based on multi-source heterogeneous data proposed in the present invention has achieved remarkable results in solving the technical problems in the traditional economic analysis decision-making process, and has provided decision makers with more scientific, comprehensive and efficient economic analysis decision support services.

[0133] In this embodiment, it is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present invention is defined by the appended claims rather than the above description, and therefore it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention.

Claims

1. A power economic analysis decision support system based on multi-source heterogeneous data, characterized by: include: A data integration module configured to receive and process multi-source heterogeneous data from multiple sources, wherein the multi-source heterogeneous data includes power data and economic data; An entity matching submodule is configured to utilize the name, attribute and context information commonly found in entities, construct multiple indexes to reduce the computational space while generating high-quality candidate sets, and define a computational method for measuring entity similarity to determine whether entity pairs match; The policy research module is configured to study key policy documents and tasks, conduct comprehensive analysis to improve decision-making, and output policy analysis reports; The industry analysis module is configured to analyze the impact of electricity demand on key industries, design application scenarios for the electricity-based economy theme, and output industry analysis reports; The data fusion analysis module is configured to collect relevant economic data on a regular basis, realize the fusion analysis of internal and external data, and output the economic structure and characteristics report; The decision support module is configured to receive the policy analysis report, industry analysis report and economic structure and characteristics report to provide a scientific basis for decision-making.

2. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 1 is characterized by: The data integration module is configured to receive and process multi-source heterogeneous data from multiple sources, and the module includes a data receiving submodule, a data preprocessing submodule, a data classification and storage submodule, and a data output submodule.

3. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 2 is characterized by: The data preprocessing submodule includes a data cleaning unit, a data format conversion unit and a data verification unit. The data cleaning unit is used to remove noise, outliers and duplicate data in the received data; the data format conversion unit converts the data into a unified format; and the data verification unit verifies the integrity of the data.

4. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 3 is characterized by: The data classification and storage submodule includes a data classification unit and a storage management unit. The data classification unit divides the processed data into power data and economic data according to the data type; the storage management unit stores the classified data in the corresponding databases and sets corresponding access rights.

5. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 1 is characterized by: The entity matching submodule also includes: Name index building unit, which performs word segmentation and standardization on entity names and builds an inverted index to achieve fast retrieval and preliminary matching based on names; The attribute index building unit extracts and classifies the attribute information of the entity and builds a corresponding index for each attribute type to support refined attribute-based matching; The context index building unit uses the context information of the entity to build a context index to enhance the accuracy and robustness of entity matching.

6. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 5 is characterized by: The entity matching submodule also includes: A candidate set generation unit, which comprehensively utilizes the above-mentioned multiple indexes and generates a high-quality candidate entity pair set by setting retrieval strategies and filtering conditions for subsequent similarity calculation and matching judgment; A similarity calculation unit, which defines and implements a variety of similarity calculation methods, including but not limited to string-based similarity calculation, attribute-based similarity calculation, and context-based similarity calculation, to comprehensively evaluate the matching degree of candidate entity pairs; The matching judgment unit performs matching judgment on candidate entity pairs according to the preset similarity threshold and matching rules, outputs the matching results, and provides matching confidence indicators for user reference.

7. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 1 is characterized by: Policy studies modules include: The data collection submodule is used to collect key policy documents and related information from official websites, news media, and policy databases; The data preprocessing submodule is used to clean, classify, and annotate the collected policy documents and related information to form structured data for subsequent analysis; The policy analysis submodule uses natural language processing technology and data mining technology to conduct text analysis, keyword extraction, and topic modeling on policy documents to identify policy highlights, policy trends, and policy impacts; The policy comparison unit is used to compare and analyze different policy documents, reveal the connections and differences between policies, and provide reference for decision-making.

8. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 7 is characterized by: The Policy Research module also includes: Report generation submodule, which automatically generates a formatted policy analysis report based on the policy analysis results and the preset report template; The report generation submodule is also configured with an interactive editing function, allowing users to edit and adjust the automatically generated reports.

9. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 1 is characterized by: Industry analysis modules include: The industrial data collection submodule is used to obtain relevant data of key industrial sectors from multiple sources; Data preprocessing submodule, which is used to clean and organize the collected industrial data and remove outliers and duplicate data; The power demand impact analysis submodule uses the collected and pre-processed industrial data to establish a mathematical model to analyze the changing trend of power demand in the industrial sector and the impact of power demand changes on the industrial economy.

10. The power economic analysis decision support system based on multi-source heterogeneous data according to claim 9 is characterized by: The industry analysis module also includes: Application scenario design submodule, which designs the application scenario of electricity economy based on the results of power demand impact analysis; Report generation submodule, which automatically generates industry analysis reports based on the results of power demand impact analysis and application scenario design; The report generation submodule also has the report customization function, and users can choose the content and display format of the report according to their needs; The data fusion analysis module includes: The data collection submodule, which obtains relevant economic data from multiple data sources on a regular basis through the set collection strategy; The data preprocessing submodule is used to clean, convert the format, and standardize the collected raw data to ensure data quality and consistency; The data fusion submodule uses data matching and correlation analysis techniques to fuse the pre-processed internal and external data. The data fusion submodule is further configured with a data verification mechanism to verify the accuracy and integrity of the fused data. The economic structure and characteristics analysis submodule uses the integrated data to deeply analyze the components, development changes and characteristics of the economic structure through statistical analysis, trend prediction and association mining methods; Report generation submodule, which automatically generates economic structure and characteristics reports based on the analysis results of economic structure and characteristics and the preset report templates; The decision support modules include: A report receiving submodule, which is used to receive and integrate policy analysis reports, industry analysis reports, and economic structure and characteristics reports from different analysis modules; The data analysis submodule performs in-depth analysis on the received reports, extracts key indicators, trends and correlation factors to form a comprehensive decision-making data set; The scenario simulation submodule is based on a comprehensive decision-making data set. By setting different policy, industry and economic scenarios, it simulates and predicts the possible results and impacts under various scenarios. The decision-making recommendation generation submodule combines scenario simulation results and risk assessment to automatically generate scientific recommendations for decision-making; The interactive interface submodule provides an operation interface for users to interact with the decision support module, supporting users to view analysis reports, adjust simulation parameters, receive decision suggestions, and provide feedback on decision effects; The scenario simulation submodule is further configured with a risk assessment function to assess potential risks and uncertainties in different scenarios and provide risk warnings for decision-making; The decision suggestion generation submodule also has the suggestion priority sorting function, which sorts the suggestions according to the impact and risk level of the simulation results to highlight the key suggestions; The interactive interface submodule is further configured with a permission management function to ensure that different users access corresponding functions and data according to their roles and permissions.

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