Marketing business scene monitoring and early warning system construction method based on political electricity grid fusion
By introducing clustering algorithms and algorithms that control changes in a single factor in the context of government-power grid integration, and combining the data sharing mechanism of government-power grid, intelligent monitoring and early warning of power users' power consumption status is achieved, data security issues are solved, and the accuracy and timeliness of early warning are improved.
Patent Information
- Application Number
- CN202411805895.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-04-04
AI Technical Summary
In the context of the integration of government-power grids, data security issues in power services are becoming increasingly prominent. How to ensure the security and privacy of electricity-using data and prevent data leakage and abuse has become an important challenge in building a monitoring and early warning system.
By introducing intelligent technical means such as clustering algorithms and algorithms that control changes in single factors, combined with the data sharing and fusion mechanism of the government power grid, intelligent monitoring and early warning of the power consumption status of power users has been achieved, and the timeliness and accuracy of early warnings has been improved.
This method not only improves the accuracy and reliability of monitoring and early warnings, but also enhances the timeliness and effectiveness of early warning signals by dynamically adjusting power consumption data, ensuring the security and privacy of the data.
Smart Images
Figure CN119762277A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the technical field of building a monitoring and early warning system, and specifically relates to a method for building a monitoring and early warning system for marketing business scenarios based on the integration of government and electricity grids. Background Art
[0002] The integration of government and electricity grid refers to the combination of the government's community grid management and the power grid management of the power company, and the improvement of grassroots governance and the quality of power services through information sharing, resource complementarity and collaborative services. This model aims to break down traditional barriers, achieve the deep integration of power services and government governance, and provide residents and enterprises with more convenient and efficient power services. The core of the integration of government and electricity grid is to establish a "grid + power grid" linkage mechanism, and through the close cooperation between power grid members and government grid members, realize the precision, rapidity and intelligence of power services. This model not only improves the response speed of power services, but also enhances the safety and reliability of power facilities, providing residents and enterprises with a better power experience.
[0003] In the context of the integration of government, electricity and grid, the marketing business scenarios of power companies have changed significantly. The traditional electricity marketing model mainly relies on fixed business halls and telephone services, while the integration of government, electricity and grid has promoted the online and intelligentization of electricity services. With the diversification of electricity demand of residents and enterprises, electricity services are also showing a trend of diversification. For example, for elderly people living alone, power companies use electricity intelligent analyzers to monitor the electricity consumption of the elderly in real time, detect abnormal situations in time and notify community grid workers. The integration of government, electricity and grid enables power services to respond to customer needs more quickly. For example, when community grid workers find safety hazards such as damaged meter boxes or privately pulled wires, they can immediately communicate with power grid workers and jointly carry out disposal work. With the help of technical means such as big data and artificial intelligence, power companies can achieve accurate prediction of power loads and intelligent analysis of electricity consumption behaviors. This not only helps to maintain the safe and stable operation of the power grid, but also provides customers with personalized electricity usage suggestions and optimization solutions.
[0004] The construction method of the monitoring and early warning system for marketing business scenarios based on the integration of government and electricity grids mainly follows the following conventional technical ideas: Data collection and integration: Collect electricity consumption data through smart meters, sensors and other equipment, and integrate these data into the power cloud database through the communication network. Data analysis and mining: Use big data technology and artificial intelligence algorithms to analyze and mine electricity consumption data to discover the laws and anomalies of electricity consumption behavior. Construction of monitoring and early warning model: Based on the analysis results of electricity consumption data, a monitoring and early warning model is constructed to achieve real-time monitoring and early warning of electricity consumption behavior. Information push and feedback: The monitoring and early warning results are pushed to power grid members and government grid members in a timely manner so that they can quickly respond to and handle abnormal situations.
[0005] Although the method of building a monitoring and early warning system for marketing business scenarios based on the integration of government and electricity grids has many advantages, there are still some shortcomings: Data security issues: With the collection and integration of electricity consumption data, data security issues have become increasingly prominent. How to ensure the security and privacy of electricity consumption data and prevent data leakage and abuse are issues that need to be focused on when building a monitoring and early warning system. Summary of the invention
[0006] The embodiment of the present application provides a method for constructing a monitoring and early warning system for marketing business scenarios based on the integration of government and electricity grids. The present invention combines the government and electricity grids with marketing business scenarios to achieve data sharing and integration. By introducing intelligent technical means such as clustering algorithms and algorithms for controlling changes in single factors, intelligent monitoring and early warning of power users' electricity consumption status are achieved, thereby improving the timeliness and accuracy of early warnings.
[0007] In order to achieve the above-mentioned purpose, the present invention provides a method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration, comprising the following steps:
[0008] Obtain basic value data samples from the daily basic electricity consumption data or the corrected accurate electricity consumption data of the power users; and calculate the optimal basic value data samples according to the preset clustering algorithm and the basic value data samples; wherein the optimal basic value data samples include: power user stability index parameters, daily floating power index parameters, and abnormal power index probability parameters;
[0009] If the actual deviation value of the power user stability index parameter is greater than the warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the daily floating power index parameter deviation value, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value, then an electricity consumption data adjustment warning signal is issued to the power user.
[0010] In a possible implementation, based on the optimal basic value data sample and a preset algorithm for controlling the change of a single factor, the corresponding relationships among the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user are respectively obtained.
[0011] In one possible implementation, based on the optimal basic value data sample and the pre-stored power user power consumption status deviation data sample corresponding to the optimal basic value data sample, the warning thresholds of the stability index parameters, daily floating power index parameters, and power user performance index parameter deviation values are calculated respectively.
[0012] In a possible implementation, the actual deviation value of the power user stability index parameter is obtained based on the actual operating power user stability index parameter and the predicted data calculated with the corresponding relationship; the actual deviation value of the daily floating power index parameter is obtained based on the actual operating daily floating power index parameter and the predicted data calculated with the corresponding relationship respectively; and the actual deviation value of the power user performance index is obtained based on the corrected power user power consumption and the daily basic power user power consumption.
[0013] In a possible implementation, the stability index parameters include: basic data parameters, power generation data of the power supply plant and equipment status data of the power supply plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power consumption peak time period, daily power consumption trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
[0014] In one possible implementation, the corrected electricity user power consumption is obtained by correcting the operating condition power user power and the weather change data in the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user power consumption classification data.
[0015] In a possible implementation, it includes a data acquisition unit, a corresponding relationship acquisition unit, a warning threshold value construction unit, an actual deviation value acquisition unit and a data processing unit;
[0016] The data acquisition unit acquires a basic value data sample from the daily basic power consumption data or the corrected accurate power consumption data of the power user; and calculates the optimal basic value data sample according to the preset clustering algorithm and the basic value data sample; wherein the optimal basic value data sample includes: a power user stability index parameter, a daily floating power index parameter, and an abnormal power index probability parameter;
[0017] The corresponding relationship acquisition unit acquires the corresponding relationship between the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user according to the optimal basic value data sample and the preset algorithm for controlling the change of a single factor;
[0018] The warning threshold construction unit calculates the warning thresholds of stability index parameters, daily floating power index parameters, and power user performance index parameter deviation values based on the optimal basic value data samples and the pre-stored power user power consumption status deviation data samples corresponding to the optimal basic value data samples.
[0019] In a possible implementation, the actual deviation value acquisition unit acquires the actual deviation value of the power user stability index parameter based on the actual operating power user stability index parameter and the predicted data calculated with the corresponding relationship; acquires the actual deviation value of the daily floating power index parameter based on the actual operating daily floating power index parameter and the predicted data calculated with the corresponding relationship respectively; and acquires the actual deviation value of the power user performance index based on the corrected power user power consumption and the daily basic power user power consumption.
[0020] In one possible implementation, the data processing unit is used to issue an electricity consumption data adjustment warning signal to the power user if the actual deviation value of the power user stability index parameter is greater than the pre-warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the deviation value of the daily floating power index parameter, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value.
[0021] In a possible implementation, the stability index parameters include: basic data parameters, power generation data of the power supply plant and equipment status data of the power supply plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power consumption peak time period, daily power consumption trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
[0022] In one possible implementation, the corrected electricity user power consumption is obtained by correcting the operating condition power user power and the weather change data in the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user power consumption classification data.
[0023] The present invention also provides a computer terminal device, comprising:
[0024] one or more processors;
[0025] A memory, coupled to the processor, for storing one or more programs;
[0026] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration.
[0027] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for constructing a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids is implemented.
[0028] Compared with the prior art, the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration in the embodiment of the present invention has the following beneficial effects:
[0029] Improve the accuracy of monitoring and early warning: This method extracts basic value data samples from the daily basic electricity consumption data of power users or the corrected accurate electricity consumption data, and calculates the optimal basic value data samples based on the preset clustering algorithm, including power user stability index parameters, daily floating power index parameters, abnormal power index probability parameters, etc., so as to more accurately reflect the power consumption behavior characteristics of power users and improve the accuracy and reliability of monitoring and early warning.
[0030] Realize dynamic adjustment of electricity consumption data: This method can dynamically adjust the correspondence between the stability index parameters of electricity users, daily floating power index parameters and the electricity consumption status of electricity users according to the changes in the electricity consumption status of electricity users through a preset algorithm for controlling the changes in a single factor, thereby ensuring that the monitoring and early warning system can reflect the changes in the electricity consumption status of electricity users in real time.
[0031] Enhance the timeliness and effectiveness of early warning signals: This method sets an early warning threshold. When the actual deviation value of the power user's power consumption data exceeds the early warning threshold, it can promptly send a power data adjustment early warning signal to the power user, helping the power user to promptly discover and adjust power consumption behavior and avoid potential safety risks and economic losses.
[0032] Introducing clustering algorithm to optimize basic value data samples: Traditional methods often directly use the original electricity consumption data of power users as the basis for monitoring and early warning. This method optimizes the basic value data samples by introducing clustering algorithm to obtain the optimal basic value data samples, thereby improving the representativeness and accuracy of the data.
[0033] Establish a multi-parameter early warning mechanism: This method not only takes into account the stability index parameters and daily floating power index parameters of power users, but also introduces the probability parameters of abnormal power indicators, forming a multi-parameter early warning mechanism that can more comprehensively and accurately reflect the changes in power consumption status of power users.
[0034] Realize fine-grained correction of electricity consumption data: This method makes fine corrections to electricity consumption of electricity users through multi-dimensional information such as operating power of electricity users and weather change data in the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user electricity consumption classification data, thereby improving the accuracy and reliability of the data.
[0035] Government-electricity grid integration: This method combines the government-electricity grid with marketing business scenarios to achieve data sharing and integration, providing a richer and more comprehensive data source for the monitoring and early warning system and improving the overall efficiency of the system.
[0036] Intelligent early warning: This method realizes intelligent monitoring and early warning of power users' power consumption status by introducing intelligent technical means such as clustering algorithms and algorithms for controlling changes in single factors, thereby improving the timeliness and accuracy of early warning.
[0037] User-friendliness: This method helps power users to timely discover and adjust their power usage behaviors by sending them early warning signals for adjusting power consumption data. This not only improves users’ safety awareness and energy-saving awareness, but also enhances their satisfaction and trust in power services.
[0038] In summary, the method of constructing a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids can provide strong support for the intelligent management and services of the power industry. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] 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.
[0040] Figure 1 A flow chart of a method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration provided by the present invention. DETAILED DESCRIPTION
[0041] 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.
[0042] 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.
[0043] like Figure 1 As shown, the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration provided by an embodiment of the present invention, the first embodiment of the present invention:
[0044] The embodiment of the present invention provides a method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration, which at least includes the following steps:
[0045] S101. Obtain basic value data samples from the daily basic power consumption data or the corrected accurate power consumption data of the power user; and calculate the optimal basic value data samples according to the preset clustering algorithm and the basic value data samples; wherein the optimal basic value data samples include: power user stability index parameters, daily floating power index parameters, and abnormal power index probability parameters;
[0046] S102, according to the optimal basic value data sample and the preset algorithm for controlling the change of a single factor, respectively obtaining the corresponding relationship between the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user;
[0047] S103, according to the optimal basic value data sample and the pre-stored power user power consumption state deviation data sample corresponding to the optimal basic value data sample, respectively calculate the early warning threshold value of the stability index parameter, the daily floating power index parameter, and the power user performance index parameter deviation value;
[0048] S104, obtaining the actual deviation value of the stability index parameter of the power user according to the actual operation of the stability index parameter of the power user and the predicted data calculated with the corresponding relationship; obtaining the actual deviation value of the daily floating power index parameter according to the actual operation of the daily floating power index parameter and the predicted data calculated with the corresponding relationship respectively; and obtaining the actual deviation value of the power user performance index according to the corrected power user power consumption and the daily basic power user power consumption;
[0049] For step S104, in the present invention, the power of the power user under operating conditions is corrected by factors such as weather change data in the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor, and power user rotation speed to obtain the power user's standard operating condition power.
[0050] S105. If the actual deviation value of the power user stability index parameter is greater than the pre-warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the deviation value of the daily floating power index parameter, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value, then a power consumption data adjustment warning signal is issued to the power user.
[0051] In one embodiment of the present invention, the stability index parameters include: basic data parameters, power generation data of the power plant and equipment status data of the power plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power peak time period, daily power trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
[0052] It should be added that the daily peak electricity consumption time period of electricity users is mainly adjusted based on the power of electricity users. The daily voltage fluctuation range, daily current fluctuation range, and daily power fluctuation range will affect the electricity consumption status of electricity users. Electricity users use the daily electricity consumption trough time period and the daily electricity consumption range to change the electricity consumption status, thereby affecting the monthly average electricity consumption peak time period, the monthly average electricity consumption trough time period, and the power generation data parameters of the power supply plant, the equipment status data of the power supply plant, the daytime electricity consumption parameters, and the nighttime electricity consumption parameters.
[0053] In one embodiment of the present invention, the corrected electricity consumption of the electricity user is obtained by correcting the operating condition electricity user power and the weather change data of the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user electricity consumption classification data.
[0054] The second embodiment of the present invention:
[0055] A system for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to an embodiment of the present invention comprises: a data acquisition unit, a corresponding relationship acquisition unit, an early warning threshold construction unit, an actual deviation value acquisition unit and a data processing unit; wherein,
[0056] The data acquisition unit acquires a basic value data sample from the daily basic power consumption data or the corrected accurate power consumption data of the power user; and calculates the optimal basic value data sample according to the preset clustering algorithm and the basic value data sample; wherein the optimal basic value data sample includes: a power user stability index parameter, a daily floating power index parameter, and an abnormal power index probability parameter;
[0057] The corresponding relationship acquisition unit acquires the corresponding relationship between the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user according to the optimal basic value data sample and the preset algorithm for controlling the change of a single factor;
[0058] The warning threshold value construction unit calculates the warning threshold values of the stability index parameter, the daily floating power index parameter, and the deviation value of the power user performance index parameter according to the optimal basic value data sample and the pre-stored power user power consumption state deviation data sample corresponding to the optimal basic value data sample;
[0059] The actual deviation value acquisition unit acquires the actual deviation value of the power user stability index parameter according to the actual running power user stability index parameter and the predicted data calculated with the corresponding relationship; acquires the actual deviation value of the daily floating power index parameter according to the actual running daily floating power index parameter and the predicted data calculated with the corresponding relationship respectively; and acquires the actual deviation value of the power user performance index according to the corrected power user power consumption and the daily basic power user power consumption;
[0060] The data processing unit is used to issue an electricity consumption data adjustment warning signal to the power user if the actual deviation value of the power user stability index parameter is greater than the pre-warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the deviation value of the daily floating power index parameter, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value.
[0061] In one embodiment of the present invention, the stability index parameters include: basic data parameters, power generation data of the power plant and equipment status data of the power plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power peak time period, daily power trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
[0062] It should be added that the daily peak electricity consumption time period of electricity users is mainly adjusted based on the power of electricity users. During the electricity consumption process, the daily voltage fluctuation range, daily current fluctuation range, and daily power fluctuation range will affect the electricity consumption status of electricity users. Electricity users use the daily electricity consumption trough time period and the daily electricity consumption range to change the electricity consumption status, thereby affecting the monthly average electricity consumption peak time period and the monthly average electricity consumption trough time period. At the same time, the joint effect of the power user's rotation speed affects the power generation data, equipment status data and night power consumption parameters of the power supply plant.
[0063] In one embodiment of the present invention, the corrected electricity consumption of the electricity user is obtained by correcting the operating condition electricity user power and the weather change data of the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user electricity consumption classification data.
[0064] The third embodiment of the present invention:
[0065] A computer terminal device provided in an embodiment of the present invention includes one or more processors; a memory coupled to the processor and used to store one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method for constructing a comprehensive early warning system for power user status as described above.
[0066] The fourth embodiment of the present invention:
[0067] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for constructing a comprehensive early warning system for power user status as described above is implemented as claimed in claim 1.
[0068] The beneficial effects of the method for constructing a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids in the present invention are mainly reflected in the following aspects:
[0069] Improve the accuracy of monitoring and early warning: This method extracts basic value data samples from the daily basic electricity consumption data of power users or the corrected accurate electricity consumption data, and calculates the optimal basic value data samples based on the preset clustering algorithm, including power user stability index parameters, daily floating power index parameters, abnormal power index probability parameters, etc., so as to more accurately reflect the power consumption behavior characteristics of power users and improve the accuracy and reliability of monitoring and early warning.
[0070] Realize dynamic adjustment of electricity consumption data: This method can dynamically adjust the correspondence between the stability index parameters of electricity users, daily floating power index parameters and the electricity consumption status of electricity users according to the changes in the electricity consumption status of electricity users through a preset algorithm for controlling the changes in a single factor, thereby ensuring that the monitoring and early warning system can reflect the changes in the electricity consumption status of electricity users in real time.
[0071] Enhance the timeliness and effectiveness of early warning signals: This method sets an early warning threshold. When the actual deviation value of the power user's power consumption data exceeds the early warning threshold, it can promptly send a power data adjustment early warning signal to the power user, helping the power user to promptly discover and adjust power consumption behavior and avoid potential safety risks and economic losses.
[0072] Introducing clustering algorithm to optimize basic value data samples: Traditional methods often directly use the original electricity consumption data of power users as the basis for monitoring and early warning. This method optimizes the basic value data samples by introducing clustering algorithm to obtain the optimal basic value data samples, thereby improving the representativeness and accuracy of the data.
[0073] Establish a multi-parameter early warning mechanism: This method not only takes into account the stability index parameters and daily floating power index parameters of power users, but also introduces the probability parameters of abnormal power indicators, forming a multi-parameter early warning mechanism that can more comprehensively and accurately reflect the changes in power consumption status of power users.
[0074] Realize fine-grained correction of electricity consumption data: This method makes fine corrections to electricity consumption of electricity users through multi-dimensional information such as operating power of electricity users and weather change data in the user's area, daily voltage fluctuation range, working day data, daily power fluctuation range, generator power factor and user electricity consumption classification data, thereby improving the accuracy and reliability of the data.
[0075] Government-electricity grid integration: This method combines the government-electricity grid with marketing business scenarios to achieve data sharing and integration, providing a richer and more comprehensive data source for the monitoring and early warning system and improving the overall efficiency of the system.
[0076] Intelligent early warning: This method realizes intelligent monitoring and early warning of power users' power consumption status by introducing intelligent technical means such as clustering algorithms and algorithms for controlling changes in single factors, thereby improving the timeliness and accuracy of early warning.
[0077] User-friendliness: This method helps power users to timely discover and adjust their power usage behaviors by sending them early warning signals for adjusting power consumption data. This not only improves users’ safety awareness and energy-saving awareness, but also enhances their satisfaction and trust in power services.
[0078] In summary, the method of constructing a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids can provide strong support for the intelligent management and services of the power industry.
[0079] 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 method for constructing a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids, characterized in that: The following steps are involved: Obtain basic value data samples from the daily basic electricity consumption data or corrected accurate electricity consumption data of power users; And according to the preset clustering algorithm and the basic value data sample, the optimal basic value data sample is calculated; wherein the optimal basic value data sample includes: power user stability index parameter, daily floating power index parameter, abnormal power index probability parameter; If the actual deviation value of the power user stability index parameter is greater than the warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the daily floating power index parameter deviation value, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value, then an electricity consumption data adjustment warning signal is issued to the power user.
2. According to the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 1, it is characterized in that: According to the optimal basic value data sample and the preset algorithm for controlling the change of a single factor, the corresponding relationship between the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user is obtained respectively.
3. According to the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 2, it is characterized in that: According to the optimal basic value data sample and the pre-stored power user power consumption status deviation data sample corresponding to the optimal basic value data sample, the warning thresholds of the stability index parameter, the daily floating power index parameter and the power user performance index parameter deviation value are calculated respectively.
4. The method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 3 is characterized in that: Obtaining an actual deviation value of the power user stability index parameter according to the power user stability index parameter actually in operation and the prediction data calculated with the corresponding relationship; Acquire the actual deviation value of the daily floating power index parameter according to the actual running daily floating power index parameter and the prediction data calculated respectively with the corresponding relationship; And obtain the actual deviation value of the power user performance index based on the corrected power user power consumption and the daily basic power user power consumption.
5. According to the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 4, it is characterized in that: The stability index parameters include: basic data parameters, power generation data of the power supply plant and equipment status data of the power supply plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power consumption peak time period, daily power consumption trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
6. The method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 5 is characterized in that: The corrected power consumption of the power user is obtained by correcting the power of the power user under operating conditions and the weather change data of the user's area, the daily voltage fluctuation range, the working day data, the daily power fluctuation range, the generator power factor and the user's power consumption classification data.
7. A system for building a marketing business scenario monitoring and early warning system based on the integration of government and electricity grids, characterized in that: It includes a data acquisition unit, a corresponding relationship acquisition unit, a warning threshold value construction unit, an actual deviation value acquisition unit and a data processing unit; The data acquisition unit acquires a basic value data sample from the daily basic power consumption data or the corrected accurate power consumption data of the power user; and calculates the optimal basic value data sample according to the preset clustering algorithm and the basic value data sample; wherein the optimal basic value data sample includes: a power user stability index parameter, a daily floating power index parameter, and an abnormal power index probability parameter; The corresponding relationship acquisition unit acquires the corresponding relationship between the power user stability index parameter, the daily floating power index parameter and the power consumption status of the power user according to the optimal basic value data sample and the preset algorithm for controlling the change of a single factor; The warning threshold value construction unit calculates the warning threshold values of the stability index parameter, the daily floating power index parameter, and the deviation value of the power user performance index parameter according to the optimal basic value data sample and the pre-stored power user power consumption state deviation data sample corresponding to the optimal basic value data sample; The actual deviation value acquisition unit acquires the actual deviation value of the power user stability index parameter according to the actual running power user stability index parameter and the predicted data calculated with the corresponding relationship; acquires the actual deviation value of the daily floating power index parameter according to the actual running daily floating power index parameter and the predicted data calculated with the corresponding relationship respectively; and acquires the actual deviation value of the power user performance index according to the corrected power user power consumption and the daily basic power user power consumption; The data processing unit is used to send a power consumption data adjustment warning signal to the power user if the actual deviation value of the power user stability index parameter is greater than the pre-warning threshold of the power user stability index parameter deviation value, or the actual deviation value of the daily floating power index parameter is greater than the warning threshold of the deviation value of the daily floating power index parameter, or the actual deviation value of the power user performance index parameter is greater than the warning threshold of the power user performance index deviation value; The stability index parameters include: basic data parameters, power generation data of the power supply plant and equipment status data of the power supply plant; the daily floating power index parameters include: basic data parameters, daytime power consumption parameters and nighttime power consumption parameters; the power user performance index parameters include: corrected power user power consumption; wherein, the basic data parameters include: daily voltage floating range, daily current floating range, daily power floating range, daily power consumption peak time period, daily power consumption trough time period, daily power consumption range, monthly average power consumption peak time period and monthly average power consumption trough time period.
8. The system for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration according to claim 7 is characterized in that: The corrected power consumption of the power user is obtained by correcting the power of the power user under operating conditions and the weather change data of the user's area, the daily voltage fluctuation range, the working day data, the daily power fluctuation range, the generator power factor and the user's power consumption classification data.
9. A computer terminal device, characterized in that: include: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration as described in any one of claims 1 to 6.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the method for constructing a marketing business scenario monitoring and early warning system based on government-electricity grid integration as described in any one of claims 1 to 6.