CN119849813A

CN119849813A - Intelligent electricity management method and system based on customer image

Info

Publication number: CN119849813A
Application number: CN202411894985.7A
Authority: CN
Inventors: 汤良杰; 黄腾; 钟文瑜; 张佳森; 施丽亚; 范斯然
Original assignee: Shenzhen Power Supply Bureau Co Ltd
Current assignee: Shenzhen Power Supply Bureau Co Ltd
Priority date: 2024-12-21
Filing date: 2024-12-21
Publication date: 2025-04-18

Abstract

The present invention proposes an intelligent electricity management method based on customer portrait, which includes the following steps: step S1, collecting user electricity data; step S2, analyzing and processing the collected electricity data to construct a customer portrait; step S3, performing intelligent electricity analysis based on the customer portrait and real-time electricity data; step S4, formulating a personalized electricity strategy according to the results of the intelligent electricity analysis; step S5, applying the electricity strategy to actual electricity management and monitoring electricity consumption in real time; step S6, collecting user feedback information on the electricity strategy, and optimizing and adjusting the electricity strategy. The present invention also discloses a corresponding method. The implementation of the present invention can better meet the electricity needs of different user groups and improve the intelligence and personalization level of electricity management.

Description

Intelligent electricity management method and system based on customer image

Technical Field

The invention relates to the technical field of intelligent electricity management, in particular to an intelligent electricity management method and system based on customer images.

Background

In the current society, electric power has become an indispensable part of modern life, and along with development of technology and diversification of user demands, the intellectualization and individualization of an electricity management system have become a problem to be solved urgently. Traditional electricity management systems often employ a standardized, one-time service model that ignores the significant differentiated demands among different user groups.

Commercial users, as an important component of power consumption, often have their power usage behavior closely related to operating efficiency. They not only pay attention to electricity cost, but also hope to optimize operation flow through intelligent control of electric equipment, so that overall efficiency is improved. However, existing electricity management systems often fail to meet their needs for fine management and intelligent control.

Industrial users have extremely high demands on the stability and reliability of the power supply. Their electricity consumption behavior is usually closely connected with the production plan, and electricity needs to be reasonably arranged according to the production requirements to ensure the smooth progress of the production process. However, conventional electricity management systems often lack flexibility and intelligence, and are difficult to personalize electricity management according to actual needs of industrial users.

As another important group of electricity consumption, residential users also have the characteristics of diversity and individuation in electricity demand. They are focusing not only on the convenience of electricity consumption, but also on energy conservation and environmental protection. However, the existing electricity management system can only provide basic electricity information and services, and cannot provide personalized energy conservation suggestions and services according to electricity habits and preferences of residential users.

In summary, the existing electricity management system has obvious defects in meeting the diversified and personalized electricity requirements of users. Therefore, a new method and system for intelligent power management based on customer images are urgently needed to better meet the power requirements of different user groups and improve the level of intelligence and individuation of power management.

Disclosure of Invention

The invention aims to solve the technical problem of providing an intelligent electricity consumption management method and system based on customer images, which can better meet the electricity consumption requirements of different user groups and improve the intelligent and personalized level of electricity consumption management.

The technical scheme adopted by the invention is that as a first aspect of the invention, an intelligent electricity management method based on client images is provided, which comprises the following steps:

Step S1, collecting electricity consumption data of a user, wherein the electricity consumption data comprises electricity consumption amount, electricity consumption time, electric equipment information, user behavior data and environment data;

s2, analyzing and processing the collected electricity consumption data to construct a customer portrait;

s3, intelligent electricity analysis is carried out based on the customer portrait and the real-time electricity data;

step S4, a personalized electricity utilization strategy is formulated according to the intelligent electricity utilization analysis result;

step S5, applying the electricity utilization strategy to actual electricity utilization management, and monitoring electricity utilization conditions in real time;

And S6, collecting feedback information of the user on the electricity utilization strategy, and optimizing and adjusting the electricity utilization strategy.

Preferably, step S2 further comprises:

step S21, data preprocessing, including cleaning, denoising and normalization;

s22, extracting key electricity utilization characteristics and behavior patterns by using data mining and machine learning technologies;

s23, dividing user groups by adopting a cluster analysis and classification algorithm based on the extracted features, and constructing a customer portrait;

Step S24, updating customer portrait regularly.

Preferably, the intelligent electricity analysis of step S3 specifically includes:

s31, predicting the electricity consumption of a user for a period of time in the future by using a prediction model;

Step S32, evaluating and analyzing the energy consumption of the equipment;

and step S33, the electricity utilization behavior of the user is monitored in real time by establishing an abnormal electricity utilization detection model.

Preferably, step S4 further comprises:

Step S41, taking the price fluctuation of the electric market and the comfort level of the user into consideration, and formulating a personalized electricity utilization strategy according to the intelligent electricity utilization analysis result and the user demand;

step S42, pushing the formulated electricity utilization strategy to a user through a user interface or a mobile application program;

And step S43, dynamically adjusting and optimizing the power utilization strategy according to feedback and actual execution conditions of the user.

Preferably, step S5 further comprises:

step S51, remotely controlling and automatically adjusting electric equipment through an intelligent control system;

Step S52, a real-time electricity consumption monitoring system is established, and electricity consumption data and equipment operation states are displayed;

step S53, starting an emergency handling mechanism when the abnormal electricity or power system fails.

Accordingly, as another aspect of the present invention, there is also provided an intelligent electricity management system based on a customer image, including:

the data acquisition module is used for collecting power consumption related data of a user;

the client portrait module is used for analyzing and processing the acquired data to construct a client portrait;

the intelligent analysis module is used for carrying out intelligent electricity analysis based on the customer portrait and the real-time electricity data;

the strategy making processing module is used for making a personalized electricity utilization strategy according to the intelligent analysis result;

The control execution module is used for applying the electricity utilization strategy to actual electricity utilization management and controlling electric equipment;

and the monitoring feedback module is used for monitoring the electricity consumption condition in real time, collecting user feedback information and optimizing the electricity consumption strategy.

Preferably, the customer portrait module further comprises:

the data preprocessing unit is used for cleaning, denoising and normalizing the acquired original power consumption data;

The feature extraction unit is used for extracting key electricity utilization features and behavior patterns by using data mining and machine learning technologies;

the user group dividing unit is used for dividing the user group by adopting a cluster analysis and classification algorithm based on the extracted characteristics to construct a customer portrait;

And the portrait updating unit is used for updating the customer portrait regularly.

Preferably, the intelligent analysis module specifically includes:

the power consumption prediction unit is used for predicting the power consumption of a user for a period of time in the future by adopting a prediction model;

The energy consumption evaluation unit is used for evaluating and analyzing the energy consumption of the equipment;

the abnormal electricity utilization detection unit is used for monitoring electricity utilization behaviors of users in real time by establishing an abnormal electricity utilization detection model.

Preferably, the policy formulation processing module further comprises:

The strategy making unit is used for making a personalized electricity utilization strategy according to the intelligent electricity utilization analysis result and the user demand by considering the price fluctuation of the electric power market and the user comfort level;

the strategy pushing unit is used for pushing the formulated electricity utilization strategy to a user through a user interface or a mobile application program;

and the strategy optimization unit is used for dynamically adjusting and optimizing the power utilization strategy according to the feedback and actual execution conditions of the user.

Preferably, the control execution module further includes:

the remote control unit is used for remotely controlling and automatically adjusting the electric equipment through the intelligent control system;

The real-time monitoring unit is used for establishing a real-time electricity consumption monitoring system and displaying electricity consumption data and equipment running states;

and the emergency processing unit is used for starting an emergency processing mechanism when the abnormal electricity utilization or the power system fails.

The embodiment of the invention has the following beneficial effects:

According to the intelligent electricity consumption management method and system based on the customer image, comprehensive and accurate customer image is built by collecting and analyzing the electricity consumption data of the user, intelligent electricity consumption analysis is carried out based on the image, personalized electricity consumption strategies are formulated, intelligent control and real-time monitoring are realized, and finally personalized management of the electricity consumption behavior of the user is realized.

In the invention, the data analysis algorithm and the model are used for carrying out deep mining and analysis on the electricity consumption data of the user, thereby realizing intelligent prediction and decision support on the electricity consumption behavior of the user and improving the intelligent level of electricity consumption management.

According to the invention, a personalized electricity utilization strategy is formulated according to the type of the user, electricity utilization habit, equipment energy consumption characteristics and other dimensional information, and the remote control and automatic operation of the equipment are realized through the intelligent control system, so that the diversified and personalized electricity utilization requirements of the user are met.

According to the invention, through real-time monitoring and analysis of the electricity consumption behavior of the user, abnormal electricity consumption conditions are found and processed in time, electricity consumption time arrangement and equipment control strategies are optimized, electricity consumption efficiency is improved, energy consumption level is reduced, and the aims of energy conservation and emission reduction are achieved.

In the invention, the power consumption data and the running state of the equipment are displayed through the visual interface, so that a user can conveniently check and manage the power consumption condition at any time. Meanwhile, the power utilization strategy is dynamically adjusted and optimized according to feedback and actual execution conditions of the user, feasibility and effectiveness of the strategy are guaranteed, and user experience and satisfaction are improved.

In summary, the intelligent electricity management method and system based on the customer image not only improves the intelligent and personalized level of electricity management, but also meets the diversified and personalized electricity requirements of users, and has remarkable social and economic benefits.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the related art, the drawings that are needed in the description of the embodiments of the present invention or the related technologies will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other related drawings may be obtained according to these drawings without inventive effort to those of ordinary skill in the art.

FIG. 1 is a schematic diagram of a main flow of an embodiment of an intelligent power management method based on customer images according to the present invention;

FIG. 2 is a schematic diagram illustrating an embodiment of an intelligent power management system based on customer images according to the present invention;

FIG. 3 is a schematic diagram of the client portrait module of FIG. 2;

FIG. 4 is a schematic diagram of the intelligent analysis module in FIG. 2;

FIG. 5 is a schematic diagram of the strategy formulation processing module in FIG. 2;

Fig. 6 is a schematic structural diagram of the control execution module in fig. 2.

Detailed Description

The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

Referring to fig. 1, a schematic diagram of a main flow of an embodiment of an intelligent power management method based on customer images according to the present invention is shown. In this embodiment, the method at least includes the following steps:

Step S1, collecting electricity consumption data, and collecting electricity consumption related information of a user through various channels, including but not limited to electricity consumption, electricity consumption time, electricity consumption equipment information, user behavior data, environment data and the like, so as to realize multidimensional data collection;

s2, analyzing and processing the collected electricity consumption data, extracting electricity consumption characteristics and behavior modes of a user by using a data analysis algorithm and a model, and constructing a comprehensive and accurate customer portrait, wherein the customer portrait comprises a plurality of dimensional information such as user basic information, electricity consumption habits, equipment energy consumption characteristics, electricity consumption scene preference and the like;

in a specific example, the step S2 includes the following sub-steps:

Step S21, data preprocessing, namely cleaning, denoising and normalizing the acquired original power consumption data, removing abnormal values and error data, and improving the data quality; it can be understood that in the step, the collected original data can be cleaned to remove abnormal electricity consumption data caused by equipment faults;

Step S22, extracting key features capable of reflecting the electricity utilization features and the behavior modes of the user from the preprocessed data by using a data mining and machine learning technology, such as electricity utilization peak time, equipment use frequency, energy consumption change trend and the like, wherein in an actual scene, the peak of electricity utilization of the resident user in a working day is mainly concentrated at 7 to 9 points at night through the data mining technology, and the electricity utilization is relatively uniform all day on weekends;

Step S23, based on the extracted features, dividing users into different groups by adopting a cluster analysis and classification algorithm, and constructing personalized customer portraits for each user, wherein the portraits are presented in a visual mode, so that the users and management staff can conveniently view and understand the portraits; for example, in one practical scenario, a customer representation is built for the resident user, including basic information (e.g., the number of families, the area of the house), electricity usage habits (e.g., the electricity usage patterns on weekdays and weekends), device energy consumption characteristics (e.g., the energy consumption duty cycle of an air conditioner), electricity usage scene preferences (e.g., preference to use an air conditioner in the evening);

and step S24, updating the customer portrait at regular intervals, and timely adjusting and perfecting the customer portrait along with the change of the electricity consumption behavior of the user and the introduction of new data so as to ensure the accuracy and timeliness of the customer portrait. It will be appreciated that as the season changes, the user's electricity usage habits may change, such as increasing frequency of air conditioning in summer, and the system may need to update the user representation periodically to reflect these changes.

Step S3, intelligent electricity analysis is carried out based on customer portrait and real-time electricity consumption data, and the intelligent electricity analysis comprises the functions of electricity consumption prediction, energy consumption evaluation, abnormal electricity consumption detection and the like, so that decision support is provided for electricity consumption management;

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

Step S31, predicting the electricity consumption of a user for a period of time in the future by adopting a prediction model such as time sequence analysis, regression analysis, neural network and the like and combining historical electricity consumption data, weather information and seasonal factors, and providing a basis for power supply planning and scheduling, wherein for example, the electricity consumption of a resident user in the next week can be predicted to be increased by 10% compared with the electricity consumption of the resident user in the next week by combining the historical electricity consumption data and weather forecast (for example, the air temperature of the week in the future is continuously increased);

Step S32, according to the information of the electric equipment of the user and the actual electricity consumption situation, the energy consumption of the equipment is estimated and analyzed, high-energy-consumption equipment and energy consumption abnormal points are identified, and references are provided for the establishment of energy-saving measures;

and step S33, the abnormal electricity consumption behavior of the user is monitored in real time by establishing an abnormal electricity consumption detection model, abnormal electricity consumption conditions such as sudden increase and decrease of electricity consumption, long-time running abnormality of equipment and the like are found in time, an early warning signal is sent out, electricity consumption safety and stable running of an electric power system are guaranteed, for example, the system monitors sudden increase of electricity consumption in the user' S home in the evening, and the system sends out an early warning signal in time due to abnormal energy consumption caused by air conditioner faults through intelligent analysis.

Step S4, a power consumption strategy is formulated, and according to intelligent power consumption analysis results, a personalized power consumption strategy is formulated by combining user demands and power supply conditions, such as optimizing power consumption time schedule, intelligent equipment control strategy, energy saving advice and the like;

further, the step S4 includes the following substeps:

Step S41, according to intelligent electricity analysis results and user demands, a personalized electricity utilization strategy is formulated, wherein the personalized electricity utilization strategy comprises electricity utilization time optimization suggestions, equipment intelligent control schemes, energy-saving target setting and the like, and the strategy formulation considers factors such as price fluctuation of an electric power market, user comfort and the like;

Step S42, pushing the formulated electricity utilization strategy to a user through a user interface or a mobile application program, and explaining the advantages and expected effects of the strategy to the user to encourage the user to adopt and execute;

Step S43, dynamically adjusting and optimizing the power utilization strategy according to the feedback and actual execution conditions of the user to ensure the feasibility and effectiveness of the strategy, for example, according to the feedback of the user (for example, the user indicates that the washing machine is inconvenient to use at night), the system adjusts the power utilization strategy and provides suggestions more suitable for the user.

S5, applying the formulated electricity utilization strategy to actual electricity utilization management, controlling and adjusting the electric equipment through an intelligent control system, and monitoring the electricity utilization condition in real time to ensure effective execution of the strategy;

in a specific example, the step S5 includes the following sub-steps:

Step S51, connecting and communicating with electric equipment through an intelligent control system to realize remote control and automatic adjustment of the equipment, and controlling parameters such as switching time, running power and the like of the equipment according to an electricity utilization strategy;

Step S52, a real-time electricity consumption monitoring system is established, the electricity consumption condition of a user is collected and monitored in real time, the parameters comprise current, voltage, power and the like, and electricity consumption data and equipment operation states are displayed through a visual interface, so that the user and management personnel can conveniently check at any time;

And step S53, when abnormal electricity consumption or power system faults occur, the intelligent electricity consumption management system can automatically start an emergency treatment mechanism, and corresponding measures such as cutting off the power supply of fault equipment, starting a standby power supply and the like are adopted to ensure the electricity consumption safety of a user and the stability of the power system.

And S6, collecting feedback information of a user on the electricity utilization strategy and actual electricity utilization effect data, optimizing and adjusting the electricity utilization strategy, and continuously perfecting the intelligent electricity utilization management system.

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

Step S61, collecting feedback information of the user on the electricity utilization strategy in a user evaluation, questionnaire survey, system log and other modes, and knowing satisfaction degree and opinion suggestion of the user;

Step S62, the implementation effect of the electricity utilization strategy is evaluated, indexes such as electricity consumption, energy consumption level, user satisfaction and the like before and after implementation are compared, and the effectiveness and economic benefit of the strategy are analyzed, for example, the electricity consumption and the energy consumption level before and after implementation of the electricity utilization strategy are compared, the electricity consumption is found to be reduced by 5%, and the user satisfaction is improved by 20%.

Step S63, optimizing and adjusting the intelligent electricity management system according to feedback collection and effect evaluation results, including improving customer portrait algorithm, optimizing electricity strategy making model, perfecting system function, etc., continuously improving system performance and user experience, for example, according to user feedback and effect evaluation results, the system increases equipment maintenance suggestion function and optimizes electricity strategy making model to provide suggestions more in line with user demand.

Referring now to FIG. 2, a schematic diagram illustrating one embodiment of a customer image-based intelligent power management system is shown. As shown in fig. 3 to 6, in this embodiment, the intelligent electricity management system 1 based on the client image at least includes:

the data acquisition module 11 is used for collecting power consumption related data of a user, including power consumption, power consumption time, power consumption equipment information, user behavior data, environment data and the like, and acquiring data through a plurality of channels such as a smart meter, a sensor, user terminal equipment and the like;

A customer portrait module 12 for analyzing and processing the collected data, constructing a customer portrait, including a plurality of dimension information such as user basic information, electricity consumption habit, equipment energy consumption characteristics, electricity consumption scene preference, etc., and realizing the update and management of the customer portrait;

the intelligent analysis module 13 is used for performing intelligent analysis such as electricity prediction, energy consumption assessment, abnormal electricity detection and the like based on customer portrait and real-time electricity consumption data, providing decision support for electricity management, and applying a data analysis algorithm and a model such as time sequence analysis, regression analysis, neural network and the like;

The policy making processing module 14 is configured to make a personalized power consumption policy according to the intelligent analysis result and the user requirement, including power consumption time optimization suggestion, equipment intelligent control scheme, energy saving target setting, etc., and push the policy to the user;

The control execution module 15 is used for applying the formulated electricity utilization strategy to actual electricity utilization management, controlling and adjusting the electric equipment through the intelligent control system, and realizing remote control and automatic operation of the equipment, wherein the functions comprise equipment switch control, power adjustment and the like;

the monitoring feedback module 16 is used for monitoring the electricity consumption condition of the user in real time, collecting user feedback information, evaluating the implementation effect of the electricity consumption strategy, guaranteeing the stable operation and continuous optimization of the system, displaying the electricity consumption data and the equipment operation state through a visual interface, and finding and processing abnormal conditions in time.

As shown in fig. 3, in a specific example, the client portrait module 12 further includes:

the data preprocessing unit 120 is used for cleaning, denoising and normalizing the collected original power consumption data;

A feature extraction unit 121 for extracting key electricity utilization features and behavior patterns using data mining and machine learning techniques;

a user group dividing unit 122 for dividing the user group by using a cluster analysis and classification algorithm based on the extracted features, and constructing a customer portrait;

and a portrait update unit 123 for periodically updating the customer portrait.

As shown in fig. 4, in a specific example, the intelligent analysis module 13 specifically includes:

The electricity consumption prediction unit 130 is configured to predict electricity consumption of a period of time in the future for a user by using a prediction model;

an energy consumption evaluation unit 131 for evaluating and analyzing the device energy consumption;

the abnormal electricity consumption detection unit 132 is configured to monitor the electricity consumption behavior of the user in real time by establishing an abnormal electricity consumption detection model.

As shown in fig. 5, in a specific example, the policy making processing module 14 further includes:

The policy making unit 140 is configured to make a personalized electricity consumption policy in consideration of price fluctuation of the electric power market and user comfort according to the intelligent electricity consumption analysis result and user requirements;

The policy pushing unit 141 is configured to push the formulated power consumption policy to a user through a user interface or a mobile application program;

The policy optimization unit 142 is configured to dynamically adjust and optimize the power consumption policy according to feedback and actual execution conditions of the user.

As shown in fig. 6, in a specific example, the control execution module 15 further includes:

a remote control unit 150 for remotely controlling and automatically adjusting the electric equipment through the intelligent control system;

the real-time monitoring unit 151 is configured to establish a real-time electricity consumption monitoring system, and display electricity consumption data and an operating state of equipment;

an emergency handling unit 152 for initiating an emergency handling mechanism in case of abnormal power usage or power system failure.

For more details, reference is made to and the description of fig. 1 is incorporated in the foregoing, and details are not repeated here.

The embodiment of the invention has the following beneficial effects:

It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above disclosure is only a preferred embodiment of the present invention, and it is needless to say that the scope of the invention is not limited thereto, and therefore, the equivalent changes according to the claims of the present invention still fall within the scope of the present invention.

Claims

1. An intelligent electricity management method based on customer images is characterized by comprising the following steps:

2. The method of claim 1, wherein step S2 further comprises:

step S21, data preprocessing, including cleaning, denoising and normalization;

Step S24, updating customer portrait regularly.

3. The method of claim 2, wherein the intelligent electricity analysis of step S3 specifically comprises:

Step S32, evaluating and analyzing the energy consumption of the equipment;

4. The method of claim 3, wherein step S4 further comprises:

5. The method of claim 4, wherein step S5 further comprises:

6. An intelligent electricity management system based on customer image, which is characterized by comprising:

7. The system of claim 6, wherein the customer representation module further comprises:

8. The system of claim 7, wherein the intelligent analysis module comprises:

9. The system of claim 8, wherein the policy-making processing module further comprises:

10. The system of claim 9, wherein the control execution module further comprises: