Intelligent power consumption management method and system based on customer portrait

Abstract

The invention provides an intelligent power consumption management method based on a customer portrait. The method comprises the following steps: S1, collecting power consumption data of a user; s2, analyzing and processing the collected power consumption data, and constructing a customer portrait; s3, based on the customer portrait and the real-time power consumption data, intelligent power consumption analysis is carried out; s4, formulating a personalized power utilization strategy according to an intelligent power utilization analysis result; s5, applying the power utilization strategy to actual power utilization management, and monitoring the power utilization condition in real time; and S6, collecting feedback information of the user on the power utilization strategy, and optimizing and adjusting the power utilization strategy. The invention further discloses a corresponding method. By implementing the method and the system, the power utilization requirements of different user groups can be better met, and the intelligent and personalized level of power utilization management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent electricity management, and in particular to an intelligent electricity management method and system based on customer portraits. Background Art

[0002] In today's society, electricity has become an indispensable part of modern life. With the development of technology and the diversification of user needs, the intelligence and personalization of electricity management systems have become an urgent problem to be solved. Traditional electricity management systems often adopt a standardized, one-size-fits-all service model, which ignores the significant differentiated needs between different user groups.

[0003] As an important part of electricity consumption, commercial users' electricity consumption behavior is often closely related to operational efficiency. They not only pay attention to electricity costs, but also hope to optimize operational processes and improve overall efficiency through intelligent control of electrical equipment. However, existing electricity management systems often cannot meet their needs for refined management and intelligent control.

[0004] Industrial users have extremely high requirements for the stability and reliability of power supply. Their electricity consumption behavior is usually closely linked to production plans, and they need to reasonably arrange electricity consumption according to production needs to ensure the smooth progress of the production process. However, traditional power management systems often lack flexibility and intelligence, making it difficult to perform personalized power management according to the actual needs of industrial users.

[0005] As another important group of electricity consumers, residential users also have diverse and personalized electricity demands. They not only pay attention to the convenience of electricity use, but also pay more and more attention to energy conservation and environmental protection. However, existing electricity management systems can only provide basic electricity information and services, and cannot provide personalized energy-saving suggestions and services based on residential users' electricity habits and preferences.

[0006] In summary, the existing electricity management system has obvious deficiencies in meeting the diverse and personalized electricity needs of users. Therefore, there is an urgent need for a new method and system that can perform intelligent electricity management based on customer portraits to better meet the electricity needs of different user groups and improve the intelligence and personalization level of electricity management. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide an intelligent electricity management method and system based on customer portraits, which can better meet the electricity needs of different user groups and improve the intelligence and personalization level of electricity management.

[0008] The technical solution adopted by the present invention is that, as a first aspect of the present invention, a smart electricity management method based on customer portrait is provided, which comprises the following steps:

[0009] Step S1, collecting the user's electricity consumption data, including electricity consumption, electricity consumption time, electricity consumption equipment information, user behavior data and environmental data;

[0010] Step S2, analyzing and processing the collected electricity consumption data to construct a customer profile;

[0011] Step S3, performing intelligent power consumption analysis based on customer portraits and real-time power consumption data;

[0012] Step S4, formulating a personalized electricity consumption strategy according to the intelligent electricity consumption analysis results;

[0013] Step S5, applying the power consumption strategy to actual power consumption management and monitoring power consumption in real time;

[0014] Step S6, collecting user feedback on the power usage strategy, and optimizing and adjusting the power usage strategy.

[0015] Preferably, step S2 further comprises:

[0016] Step S21: data preprocessing, including cleaning, denoising and normalization;

[0017] Step S22: extracting key electricity consumption characteristics and behavior patterns using data mining and machine learning techniques;

[0018] Step S23: Based on the extracted features, cluster analysis and classification algorithms are used to divide user groups and construct customer portraits;

[0019] Step S24: Update customer profile regularly.

[0020] Preferably, the intelligent electricity consumption analysis in step S3 specifically includes:

[0021] Step S31: using the prediction model to predict the user's electricity consumption in the future;

[0022] Step S32: Evaluate and analyze the energy consumption of the equipment;

[0023] Step S33: Monitor the user's electricity usage behavior in real time by establishing an abnormal electricity usage detection model.

[0024] Preferably, step S4 further comprises:

[0025] Step S41: Considering the price fluctuations in the electricity market and user comfort, formulate a personalized electricity consumption strategy according to the intelligent electricity consumption analysis results and user needs;

[0026] Step S42: Pushing the formulated power usage strategy to the user through the user interface or mobile application;

[0027] Step S43: Dynamically adjust and optimize the power usage strategy based on user feedback and actual implementation status.

[0028] Preferably, step S5 further comprises:

[0029] Step S51, remotely controlling and automatically adjusting electrical equipment through an intelligent control system;

[0030] Step S52, establishing a real-time power consumption monitoring system to display power consumption data and equipment operation status;

[0031] Step S53, starting the emergency processing mechanism when abnormal power consumption or power system failure occurs.

[0032] Accordingly, as another aspect of the present invention, there is also provided an intelligent electricity management system based on customer portrait, which includes:

[0033] Data collection module, used to collect users' electricity consumption related data;

[0034] Customer portrait module, used to analyze and process the collected data and build customer portraits;

[0035] Intelligent analysis module, used for intelligent power consumption analysis based on customer portraits and real-time power consumption data;

[0036] A strategy formulation processing module is used to formulate personalized power consumption strategies based on intelligent analysis results;

[0037] A control execution module is used to apply the power consumption strategy to actual power consumption management and control power consumption equipment;

[0038] The monitoring and feedback module is used to monitor power usage in real time, collect user feedback information, and optimize power usage strategies.

[0039] Preferably, the customer portrait module further includes:

[0040] A data preprocessing unit is used to clean, denoise and normalize the collected raw power consumption data;

[0041] Feature extraction unit, used to extract key power consumption features and behavior patterns using data mining and machine learning techniques;

[0042] A user group division unit is used to divide user groups based on the extracted features and use cluster analysis and classification algorithms to build customer portraits;

[0043] The portrait updating unit is used to regularly update the customer portrait.

[0044] Preferably, the intelligent analysis module specifically includes:

[0045] The power consumption prediction unit is used to predict the power consumption of the user in the future by using a prediction model;

[0046] Energy consumption evaluation unit, used to evaluate and analyze the energy consumption of equipment;

[0047] The abnormal power consumption detection unit is used to monitor the user's power consumption behavior in real time by establishing an abnormal power consumption detection model.

[0048] Preferably, the policy formulation processing module further includes:

[0049] The strategy formulation unit is used to formulate personalized electricity consumption strategies based on the results of intelligent electricity consumption analysis and user needs, taking into account electricity market price fluctuations and user comfort;

[0050] A policy push unit, used to push the formulated power consumption policy to the user through the user interface or mobile application;

[0051] The strategy optimization unit is used to dynamically adjust and optimize the power consumption strategy based on user feedback and actual execution status.

[0052] Preferably, the control execution module further includes:

[0053] Remote control unit, used for remote control and automatic regulation of electrical equipment through intelligent control system;

[0054] Real-time monitoring unit, used to establish a real-time power consumption monitoring system to display power consumption data and equipment operating status;

[0055] The emergency processing unit is used to activate the emergency processing mechanism in case of abnormal power consumption or power system failure.

[0056] The implementation of the embodiments of the present invention has the following beneficial effects:

[0057] The present invention provides an intelligent electricity management method and system based on customer portrait, which builds a comprehensive and accurate customer portrait by collecting and analyzing the user's electricity consumption data, and performs intelligent electricity consumption analysis based on the portrait, formulates personalized electricity consumption strategies, realizes intelligent control and real-time monitoring, and finally realizes personalized management of the user's electricity consumption behavior.

[0058] In the present invention, by using data analysis algorithms and models, the user's electricity consumption data is deeply mined and analyzed, thereby realizing intelligent prediction and decision support for the user's electricity consumption behavior, and improving the intelligence level of electricity management.

[0059] In the present invention, a personalized electricity usage strategy is formulated based on multiple dimensions of information such as user type, electricity usage habits, and equipment energy consumption characteristics, and remote control and automated operation of equipment are achieved through an intelligent control system to meet users' diverse and personalized electricity needs.

[0060] In the present invention, through real-time monitoring and analysis of users' electricity usage behavior, abnormal electricity usage is discovered and handled in a timely manner, electricity usage schedules and equipment control strategies are optimized, electricity efficiency is improved, energy consumption levels are reduced, and the goal of energy conservation and emission reduction is achieved.

[0061] In the present invention, power consumption data and equipment operation status are displayed through a visual interface, which is convenient for users to view and manage their power consumption at any time. At the same time, according to user feedback and actual implementation, the power consumption strategy is dynamically adjusted and optimized to ensure the feasibility and effectiveness of the strategy and improve user experience and satisfaction.

[0062] To sum up, the intelligent electricity management method and system based on customer portrait provided by the present invention not only improve the intelligence and personalization level of electricity management, but also meet the diversified and personalized electricity needs of users, and have significant social and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the drawings required for use in the embodiments of the present invention or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 A schematic diagram of the main process of an embodiment of a smart electricity management method based on customer portrait provided by the present invention;

[0065] Figure 2 A schematic diagram of the structure of an embodiment of a smart electricity management system based on customer portrait provided by the present invention;

[0066] Figure 3 for Figure 2 The structural diagram of the customer portrait module;

[0067] Figure 4 for Figure 2 The structural diagram of the intelligent analysis module;

[0068] Figure 5 for Figure 2 A schematic diagram of the structure of the strategy formulation processing module;

[0069] Figure 6 for Figure 2 Schematic diagram of the structure of the control execution module. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention 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 invention and are not intended to limit the present invention.

[0071] like Figure 1 As shown, a main flow diagram of an embodiment of a smart electricity management method based on customer portrait provided by the present invention is shown. In this embodiment, the method includes at least the following steps:

[0072] Step S1, collecting electricity consumption data, collecting users' electricity consumption related information through various channels, including but not limited to electricity consumption, electricity consumption time, electricity consumption equipment information, user behavior data and environmental data, etc., to achieve multi-dimensional data collection;

[0073] Step S2: Analyze and process the collected electricity consumption data, use data analysis algorithms and models to extract the user's electricity consumption characteristics and behavior patterns, and build a comprehensive and accurate customer portrait, where the customer portrait includes multiple dimensions of information such as user basic information, electricity consumption habits, equipment energy consumption characteristics, and electricity usage scenario preferences;

[0074] In a specific example, step S2 includes the following sub-steps:

[0075] Step S21: Data preprocessing, cleaning, denoising and normalizing the collected raw power consumption data, removing abnormal values ​​and erroneous data, and improving data quality; it can be understood that in this step, the collected raw data can be cleaned to remove abnormal power consumption data caused by equipment failure; the power consumption can be normalized to facilitate subsequent analysis;

[0076] Step S22: using data mining and machine learning techniques, extracting key features that can reflect the user's electricity consumption characteristics and behavior patterns from the preprocessed data, such as peak electricity consumption time, device usage frequency, energy consumption change trend, etc.; for example, in an actual scenario, through data mining technology, it is found that the peak electricity consumption of the residential user on weekdays is mainly concentrated between 7pm and 9pm, while the electricity consumption is relatively even throughout the day on weekends; through machine learning algorithms, it is identified that the air conditioner is a high-energy consumption device in the user's home;

[0077] Step S23: Based on the extracted features, cluster analysis and classification algorithms are used to divide users into different groups, and a personalized customer portrait is constructed for each user. The portrait is presented in a visual manner to facilitate users and managers to view and understand; for example, in an actual scenario, a customer portrait is constructed for the residential user, including basic information (such as family size, house area), electricity usage habits (such as electricity usage patterns on weekdays and weekends), equipment energy consumption characteristics (such as the energy consumption ratio of air conditioners), and electricity usage scenario preferences (such as preference for using air conditioners at night);

[0078] Step S24: Update the customer portrait regularly. With the change of the user's electricity consumption behavior and the introduction of new data, timely adjust and improve the customer portrait to ensure its accuracy and timeliness. It is understandable that with the change of seasons, the user's electricity consumption habits may change, such as the increase in the frequency of air conditioning use in summer. The system needs to regularly update the user portrait to reflect these changes.

[0079] Step S3, based on customer portraits and real-time electricity consumption data, intelligent electricity consumption analysis is performed, including electricity consumption forecasting, energy consumption assessment, abnormal electricity consumption detection and other functions, to provide decision support for electricity consumption management;

[0080] In a specific example, step S3 includes the following sub-steps:

[0081] Step S31: using prediction models such as time series analysis, regression analysis, neural networks, etc., combined with historical electricity consumption data, weather information, and seasonal factors, to predict the user's electricity consumption for a period of time in the future, and provide a basis for power supply planning and scheduling; for example, combining historical electricity consumption data and weather forecasts (such as the temperature will continue to rise in the next week), it can be predicted that the electricity consumption of a residential user next week will increase by 10% compared with this week;

[0082] Step S32: Evaluate and analyze the energy consumption of the equipment according to the user's electrical equipment information and actual power consumption, identify high-energy-consuming equipment and energy consumption anomalies, and provide a reference for the formulation of energy-saving measures; for example, evaluate the energy consumption of each device in a user's home and find that the energy consumption of the refrigerator is too high, which may be due to aging or improper settings;

[0083] Step S33: By establishing an abnormal power consumption detection model, the user's power consumption behavior is monitored in real time, and abnormal power consumption situations, such as sudden increases or decreases in power consumption, abnormal equipment operation for a long time, etc., are discovered in time, and an early warning signal is issued to ensure power safety and stable operation of the power system; for example, the system monitors that the power consumption in the user's home suddenly increases one night, and through intelligent analysis it is found that the abnormal energy consumption is caused by an air-conditioning failure, and the system issues an early warning signal in time.

[0084] Step S4, formulate a power consumption strategy, and formulate a personalized power consumption strategy based on the results of the intelligent power consumption analysis, combined with user needs and power supply conditions, such as optimizing power consumption time scheduling, equipment intelligent control strategy, energy-saving suggestions, etc.;

[0085] Furthermore, the step S4 includes the following sub-steps:

[0086] Step S41: formulate personalized electricity consumption strategies based on the results of intelligent electricity consumption analysis and user needs, including suggestions for optimizing electricity consumption time, intelligent equipment control solutions, energy-saving target setting, etc. The strategy formulation takes into account factors such as electricity market price fluctuations and user comfort. For example, based on the electricity consumption forecast results, it can be recommended that users use washing machines during periods when electricity prices are lower; and energy-saving suggestions can be provided for the problem of excessive energy consumption of refrigerators, such as adjusting refrigerator temperature settings.

[0087] Step S42: Pushing the formulated electricity usage strategy to the user through the user interface or mobile application, explaining the advantages and expected effects of the strategy to the user, and encouraging the user to adopt and implement it; for example, pushing the electricity usage strategy through the user's mobile phone APP, including the recommended electricity usage schedule and energy-saving tips;

[0088] Step S43: Dynamically adjust and optimize the power usage strategy based on user feedback and actual implementation to ensure the feasibility and effectiveness of the strategy; for example, based on user feedback (such as users indicating that it is inconvenient to use the washing machine at night), the system adjusts the power usage strategy and provides suggestions that are more suitable for users.

[0089] Step S5: Apply the formulated power consumption strategy to actual power consumption management, control and adjust the power consumption equipment through the intelligent control system, and monitor the power consumption in real time to ensure the effective implementation of the strategy;

[0090] In a specific example, step S5 includes the following sub-steps:

[0091] Step S51: connecting and communicating with the electrical equipment through the intelligent control system to realize remote control and automatic adjustment of the equipment, and controlling the on / off time, operating power and other parameters of the equipment according to the power consumption strategy; for example, the operation mode of the air conditioner can be automatically adjusted through the intelligent control system to operate in energy-saving mode during the period with lower electricity prices;

[0092] Step S52: Establish a real-time power consumption monitoring system to collect and monitor the user's power consumption in real time, including parameters such as current, voltage, and power, and display the power consumption data and equipment operation status through a visual interface, so that users and managers can view them at any time; for example, the real-time power consumption data and equipment operation status of the user's home are displayed through a visual interface, so that the user can view the power consumption of each device in the home at any time;

[0093] Step S53: When abnormal power consumption or power system failure occurs, the intelligent power management system can automatically start the emergency response mechanism and take corresponding measures, such as cutting off the power supply of the faulty equipment and starting the backup power supply, to ensure the safety of user power consumption and the stability of the power system.

[0094] Step S6: Collect user feedback on power usage strategies and actual power usage effect data, optimize and adjust the power usage strategies, and continuously improve the intelligent power management system.

[0095] In a specific example, step S6 includes the following sub-steps:

[0096] Step S61: Collect user feedback on the power usage strategy through user evaluation, questionnaire survey, system log, etc., to understand user satisfaction and opinions and suggestions; for example, collect user satisfaction and opinions and suggestions on the power usage strategy through user evaluation and questionnaire survey. The user said that the energy-saving suggestions are useful, but hopes to provide more suggestions on equipment maintenance;

[0097] Step S62: Evaluate the effect of the implementation of the power usage strategy, compare the power consumption, energy consumption level, user satisfaction and other indicators before and after the implementation, and analyze the effectiveness and economic benefits of the strategy; for example, by comparing the power consumption and energy consumption level before and after the implementation of the power usage strategy, it is found that the power consumption has decreased by 5% and the user satisfaction has increased by 20%.

[0098] Step S63: Based on the results of feedback collection and effect evaluation, the intelligent electricity management system is optimized and adjusted, including improving the customer profiling algorithm, optimizing the electricity strategy formulation model, improving system functions, etc., to continuously improve the system performance and user experience; for example, based on user feedback and effect evaluation results, the system has added an equipment maintenance recommendation function and optimized the electricity strategy formulation model to provide recommendations that better meet user needs.

[0099] like Figure 2 As shown, a structural diagram of an embodiment of an intelligent power management system based on customer portrait provided by the present invention is shown. Figures 3 to 6 As shown, in this embodiment, the smart electricity management system 1 based on customer portraits at least includes:

[0100] The data collection module 11 is responsible for collecting the user's electricity consumption related data, including electricity consumption, electricity consumption time, electricity consumption equipment information, user behavior data and environmental data, etc., and collects data through multiple channels such as smart meters, sensors, and user terminal devices;

[0101] The customer portrait module 12 is used to analyze and process the collected data, build a customer portrait, including multiple dimensions of information such as user basic information, electricity usage habits, equipment energy consumption characteristics, electricity usage scenario preferences, etc., and realize the update and management of the customer portrait;

[0102] Intelligent analysis module 13, used to perform intelligent analysis such as power consumption forecasting, energy consumption assessment, abnormal power consumption detection, etc. based on customer portraits and real-time power consumption data, provide decision support for power consumption management, and use data analysis algorithms and models, such as time series analysis, regression analysis, neural network, etc.;

[0103] The strategy formulation processing module 14 is used to formulate personalized power consumption strategies according to the intelligent analysis results and user needs, including power consumption time optimization suggestions, equipment intelligent control solutions, energy saving target setting, etc., and push the strategies to users;

[0104] The control execution module 15 is used to apply the formulated power consumption strategy to the actual power consumption management, control and adjust the power consumption equipment through the intelligent control system, and realize the remote control and automatic operation of the equipment, including equipment switch control, power adjustment and other functions;

[0105] The monitoring and feedback module 16 is used to monitor the user's electricity consumption in real time, collect user feedback information, evaluate the implementation effect of the electricity consumption strategy, ensure the stable operation and continuous optimization of the system, display the electricity consumption data and equipment operation status through a visual interface, and promptly discover and handle abnormal situations.

[0106] like Figure 3 As shown, in a specific example, the customer portrait module 12 further includes:

[0107] The data preprocessing unit 120 is used to clean, denoise and normalize the collected raw power consumption data;

[0108] A feature extraction unit 121, for extracting key power consumption features and behavior patterns using data mining and machine learning techniques;

[0109] A user group division unit 122 is used to divide user groups based on the extracted features and use cluster analysis and classification algorithms to build customer portraits;

[0110] The portrait updating unit 123 is used to regularly update the customer portrait.

[0111] like Figure 4 As shown, in a specific example, the intelligent analysis module 13 specifically includes:

[0112] The power consumption prediction unit 130 is used to predict the power consumption of the user in the future by using a prediction model;

[0113] An energy consumption evaluation unit 131, used to evaluate and analyze the energy consumption of the device;

[0114] The abnormal power usage detection unit 132 is used to monitor the user's power usage behavior in real time by establishing an abnormal power usage detection model.

[0115] like Figure 5 As shown, in a specific example, the policy formulation processing module 14 further includes:

[0116] A strategy formulation unit 140 is used to formulate a personalized power consumption strategy based on the intelligent power consumption analysis results and user needs, taking into account power market price fluctuations and user comfort;

[0117] The policy push unit 141 is used to push the formulated power usage policy to the user through the user interface or the mobile application;

[0118] The strategy optimization unit 142 is used to dynamically adjust and optimize the power usage strategy according to user feedback and actual execution status.

[0119] like Figure 6 As shown, in a specific example, the control execution module 15 further includes:

[0120] A remote control unit 150, for remotely controlling and automatically adjusting electrical equipment through an intelligent control system;

[0121] A real-time monitoring unit 151 is used to establish a real-time power consumption monitoring system to display power consumption data and equipment operation status;

[0122] The emergency processing unit 152 is used to start the emergency processing mechanism when abnormal power consumption or power system failure occurs.

[0123] For more details, please refer to and combine the above Figure 1 The description of is not repeated here.

[0124] The implementation of the embodiments of the present invention has the following beneficial effects:

[0125] The present invention provides an intelligent electricity management method and system based on customer portrait, which builds a comprehensive and accurate customer portrait by collecting and analyzing the user's electricity consumption data, and performs intelligent electricity consumption analysis based on the portrait, formulates personalized electricity consumption strategies, realizes intelligent control and real-time monitoring, and finally realizes personalized management of the user's electricity consumption behavior.

[0126] In the present invention, by using data analysis algorithms and models, the user's electricity consumption data is deeply mined and analyzed, thereby realizing intelligent prediction and decision support for the user's electricity consumption behavior, and improving the intelligence level of electricity management.

[0127] In the present invention, a personalized electricity usage strategy is formulated based on multiple dimensions of information such as user type, electricity usage habits, and equipment energy consumption characteristics, and remote control and automated operation of equipment are achieved through an intelligent control system to meet users' diverse and personalized electricity needs.

[0128] In the present invention, through real-time monitoring and analysis of users' electricity usage behavior, abnormal electricity usage is discovered and handled in a timely manner, electricity usage schedules and equipment control strategies are optimized, electricity efficiency is improved, energy consumption levels are reduced, and the goal of energy conservation and emission reduction is achieved.

[0129] In the present invention, power consumption data and equipment operation status are displayed through a visual interface, which is convenient for users to view and manage their power consumption at any time. At the same time, according to user feedback and actual implementation, the power consumption strategy is dynamically adjusted and optimized to ensure the feasibility and effectiveness of the strategy and improve user experience and satisfaction.

[0130] To sum up, the intelligent electricity management method and system based on customer portrait provided by the present invention not only improve the intelligence and personalization level of electricity management, but also meet the diversified and personalized electricity needs of users, and have significant social and economic benefits.

[0131] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0132] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] The above disclosure is only a preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. An intelligent electricity management method based on customer portrait, characterized in that: The following steps are involved: Step S1, collecting the user's electricity consumption data, including electricity consumption, electricity consumption time, electricity consumption equipment information, user behavior data and environmental data; Step S2, analyzing and processing the collected electricity consumption data to construct a customer profile; Step S3, performing intelligent power consumption analysis based on customer portraits and real-time power consumption data; Step S4, formulating a personalized electricity consumption strategy according to the intelligent electricity consumption analysis results; Step S5, applying the power consumption strategy to actual power consumption management and monitoring power consumption in real time; Step S6, collecting user feedback on the power usage strategy, and optimizing and adjusting the power usage strategy.

2. The method according to claim 1, characterized in that Step S2 further comprises: Step S21: data preprocessing, including cleaning, denoising and normalization; Step S22: extracting key electricity consumption characteristics and behavior patterns using data mining and machine learning techniques; Step S23: Based on the extracted features, cluster analysis and classification algorithms are used to divide user groups and construct customer portraits; Step S24: Update customer profile regularly.

3. The method according to claim 2, characterized in that The intelligent power consumption analysis in step S3 specifically includes: Step S31: using the prediction model to predict the user's electricity consumption in the future; Step S32: Evaluate and analyze the energy consumption of the equipment; Step S33: Monitor the user's electricity usage behavior in real time by establishing an abnormal electricity usage detection model.

4. The method according to claim 3, characterized in that Step S4 further comprises: Step S41: Considering the price fluctuations in the electricity market and user comfort, formulate a personalized electricity consumption strategy according to the intelligent electricity consumption analysis results and user needs; Step S42: Pushing the formulated power usage strategy to the user through the user interface or mobile application; Step S43: Dynamically adjust and optimize the power usage strategy based on user feedback and actual implementation status.

5. The method according to claim 4, characterized in that Step S5 further comprises: Step S51, remotely controlling and automatically adjusting electrical equipment through an intelligent control system; Step S52, establishing a real-time power consumption monitoring system to display power consumption data and equipment operation status; Step S53, starting the emergency processing mechanism when abnormal power consumption or power system failure occurs.

6. An intelligent electricity management system based on customer portrait, characterized in that: include: Data collection module, used to collect users' electricity consumption related data; Customer portrait module, used to analyze and process the collected data and build customer portraits; Intelligent analysis module, used for intelligent power consumption analysis based on customer portraits and real-time power consumption data; A strategy formulation processing module is used to formulate personalized power consumption strategies based on intelligent analysis results; A control execution module is used to apply the power consumption strategy to actual power consumption management and control power consumption equipment; The monitoring and feedback module is used to monitor power usage in real time, collect user feedback information, and optimize power usage strategies.

7. The system of claim 6, characterized in that The customer portrait module further includes: A data preprocessing unit is used to clean, denoise and normalize the collected raw power consumption data; Feature extraction unit, used to extract key power consumption features and behavior patterns using data mining and machine learning techniques; A user group division unit is used to divide user groups based on the extracted features and use cluster analysis and classification algorithms to build customer portraits; The portrait updating unit is used to regularly update the customer portrait.

8. The system according to claim 7, characterized in that The intelligent analysis module specifically includes: The power consumption prediction unit is used to predict the power consumption of the user in the future by using a prediction model; Energy consumption evaluation unit, used to evaluate and analyze the energy consumption of equipment; The abnormal power consumption detection unit is used to monitor the user's power consumption behavior in real time by establishing an abnormal power consumption detection model.

9. The system according to claim 8, characterized in that The policy formulation processing module further includes: The strategy formulation unit is used to formulate personalized electricity consumption strategies based on the results of intelligent electricity consumption analysis and user needs, taking into account electricity market price fluctuations and user comfort; A policy push unit, used to push the formulated power consumption policy to the user through the user interface or mobile application; The strategy optimization unit is used to dynamically adjust and optimize the power consumption strategy based on user feedback and actual execution status.

10. The system according to claim 9, characterized in that The control execution module further includes: Remote control unit, used for remote control and automatic regulation of electrical equipment through intelligent control system; Real-time monitoring unit, used to establish a real-time power consumption monitoring system to display power consumption data and equipment operating status; The emergency processing unit is used to activate the emergency processing mechanism in case of abnormal power consumption or power system failure.

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