Power grid intelligent service scene matching and task distribution method and device and computer program product

Abstract

The invention discloses a power grid intelligent service scene matching and task distribution method and device and a computer program product, and the method comprises the steps: S1, carrying out the dynamic updating of a verbal skill library based on a power grid business scene classification system through the verbal skill use frequency, the customer response rate and the satisfaction score; s2, performing intelligent verbal skill matching through an electricity consumption association rule, a fault record association rule, a scene-time linkage rule and a dynamic adjustment mechanism based on the electricity consumption behavior characteristics of the customer; and S3, based on the power grid service monitoring index, performing task intelligent distribution in combination with the employee capability label, the workload dynamic evaluation, the task emergency degree and the regional suitability. According to the method, the accuracy, the efficiency and the quality of power grid service are improved, the service cost is remarkably reduced, a standardized, intelligent and dynamically optimized service solution is provided for power grid enterprises, and key pain points in traditional power grid service are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, specifically to a method, apparatus, and computer program product for matching and assigning smart grid service scenarios. Background Technology

[0002] Currently, power grid companies primarily rely on human customer service and static script libraries for services. This leads to problems such as a lack of scenario-based categorization in the script libraries, static and fixed content, reliance on manual scheduling for task assignment, and insufficient service quality monitoring. Traditional script libraries only provide basic question-and-answer templates and cannot be dynamically updated based on customer electricity consumption behavior and power grid operating status, resulting in low service efficiency and low customer satisfaction. During peak electricity consumption periods or extreme weather conditions, manual dispatch struggles to respond quickly to customer needs, causing long waiting times, low fault handling efficiency, and poor service experience. Furthermore, different employees provide inconsistent answers to the same questions, lacking standardized service processes and affecting the consistency of service quality. While existing technologies include enterprise WeChat marketing script libraries and intelligent order dispatch systems, neither is specifically designed for the characteristics of power grid business and cannot effectively adapt to the unique features of power grid business scenarios. Summary of the Invention

[0003] The technical problem to be solved by the embodiments of the present invention is to provide a method, device and computer program product for matching and assigning smart grid service scenarios, so as to realize the standardization, intelligence and dynamic optimization of power grid business services.

[0004] To address the aforementioned technical problems, this invention provides a method for matching and dispatching smart grid service scenarios, comprising: Step S1: Based on the power grid business scenario classification system, the script library is dynamically updated by the frequency of script usage, customer response rate and satisfaction score. Step S2: Based on customer electricity consumption behavior characteristics, intelligent script matching is performed through electricity consumption association rules, fault record association rules, scenario-time linkage rules, and dynamic adjustment mechanisms. Step S3: Based on power grid business monitoring indicators, combined with employee capability tags, dynamic workload assessment, task urgency and regional adaptability, intelligent task assignment is carried out.

[0005] Preferably, the power grid business scenario classification system includes fault reporting scenarios, electricity consultation scenarios, safety promotion scenarios, and marketing activity scenarios. The fault reporting scenarios include line faults, equipment faults, power outage reporting, and power restoration consultation. The electricity consultation scenarios include electricity bill inquiries, electricity price consultations, account opening and transfer, electricity capacity adjustments, and seasonal electricity usage. The safety promotion scenarios include residential electricity safety, enterprise electricity safety, high-voltage area warnings, and thunderstorm protection. The marketing activity scenarios include electricity price package recommendations, energy-saving product promotions, points redemption, and holiday discounts.

[0006] Preferably, the construction of the script library specifically includes: Synchronize historical power grid service data through the service management platform interface, including customer inquiry records, fault handling work orders, service evaluation feedback, and electricity consumption behavior data, and remove invalid data; For each specific scenario, natural language processing technology is used to extract high-frequency and effective expressions. In the fault reporting scenario, standardized script templates are built based on historical fault types, processing procedures and customer feedback. In the electricity consultation scenario, script templates are customized based on customer electricity usage behavior, electricity pricing policies and business processing procedures.

[0007] Preferably, in step S1, the dynamic update mechanism of the script library includes: retaining scripts with high usage frequency, high response rate, and high satisfaction rating; optimizing scripts with low usage frequency, low response rate, and low satisfaction rating; and adding scripts based on new business needs or customer feedback.

[0008] Preferably, in step S2, the customer's electricity consumption behavior characteristics include: electricity consumption trend over the past 6 months, fault records, payment habits, and types of electrical equipment.

[0009] Preferably, in step S2, the electricity consumption association rule is as follows: for customers with high electricity consumption, energy-saving advice and peak-valley electricity pricing packages are recommended; for customers with a sudden increase in electricity consumption, an electricity anomaly investigation script is recommended; the fault record association rule is as follows: for customers with a fault frequency of ≥3 times / year, preventive maintenance script is pushed; the scenario-time linkage rule is as follows: during peak electricity consumption periods, off-peak usage script and overload protection script are pushed; during typhoon / rainstorm weather, emergency fault reporting script is pushed. The dynamic adjustment mechanism is as follows: based on the customer's response to the recommended scripts, the weight of subsequent script recommendations is optimized in real time.

[0010] Preferably, in step S3, the power grid business monitoring indicators include: customer waiting time, service satisfaction, task completion rate, script usage rate, and customer re-inquiry rate.

[0011] Preferably, in step S3, the employee competency tags include: fault repair expert, marketing package recommendation expert, and high-voltage electricity consultation specialist; the dynamic workload assessment is: by real-time statistics of the number of tasks currently pending and the processing time of employees, new tasks are prioritized to be assigned to employees with ≤3 pending tasks; the task urgency ranking is: fault reporting > safety hazard consultation > marketing activities > routine electricity consultation; the regional adaptability is: in combination with the power grid power supply zoning, tasks are assigned to employees responsible for the corresponding regions.

[0012] The present invention also provides a power grid smart service scenario matching and task dispatching device, comprising: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to perform the smart grid service scenario matching and task dispatching method.

[0013] The present invention also provides a computer program product, including computer instructions, which instruct a computer device to perform the operation corresponding to the method.

[0014] Implementing this invention offers the following advantages: By constructing a refined classification system for power grid business scenarios and a dynamic script library, this invention standardizes service scripts for all positions, effectively avoiding uneven service quality caused by differences in personnel experience. The intelligent script matching algorithm, based on customer electricity consumption behavior characteristics, achieves precise linkage between "customer profile - scenario needs - script recommendation" through electricity consumption association rules, fault record association rules, scenario-time linkage rules, and a dynamic adjustment mechanism. This significantly reduces script selection time, greatly shortening consultation and fault reporting response times. The intelligent task dispatch mechanism, based on a power grid business-specific monitoring indicator system, combined with employee capability tags, dynamic workload assessment, task urgency, and regional adaptability, avoids delays in manual dispatch and improves service response speed. Simultaneously, through a dynamic script update mechanism and task monitoring system, it effectively reduces customer re-inquiry rates and ineffective communication time, improves marketing activity conversion rates, and reduces manual promotion costs. This invention not only improves the accuracy, efficiency, and quality of power grid services, but also significantly reduces service costs, providing power grid companies with standardized, intelligent, and dynamically optimized service solutions, effectively addressing key pain points in traditional power grid services. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating a method for matching and dispatching smart grid service scenarios according to an embodiment of the present invention. Detailed Implementation

[0017] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.

[0018] Please refer to Figure 1 As shown, Embodiment 1 of the present invention provides a method for matching and dispatching smart grid service scenarios, including: Step S1: Based on the power grid business scenario classification system, the script library is dynamically updated by the frequency of script usage, customer response rate and satisfaction score. Step S2: Based on customer electricity consumption behavior characteristics, intelligent script matching is performed through electricity consumption association rules, fault record association rules, scenario-time linkage rules, and dynamic adjustment mechanisms. Step S3: Based on power grid business monitoring indicators, combined with employee capability tags, dynamic workload assessment, task urgency and regional adaptability, intelligent task assignment is carried out.

[0019] Specifically, in step S1, the constructed power grid business scenario classification system divides power grid business into four major categories of core scenarios according to service purpose, and each core scenario is further subdivided into two sub-scenarios, as follows: Fault reporting scenarios include secondary sub-scenarios such as line faults, equipment faults, power outage reporting, and power restoration consultation; Electricity usage consultation scenarios include secondary sub-scenarios such as electricity bill inquiry, electricity price consultation, account opening and transfer, electricity capacity adjustment, and seasonal electricity usage. Safety awareness campaign scenarios include secondary sub-scenarios such as home electrical safety, business electrical safety, high-voltage area warnings, and thunderstorm protection; Marketing campaign scenarios include secondary sub-scenarios such as electricity price package recommendations, energy-saving product promotions, points redemption, and holiday discounts.

[0020] Based on the above scenario classification system, the construction of the script library includes the following specific steps: Data Acquisition and Preprocessing: Synchronize historical power grid service data through the service management platform interface, including customer inquiry records, fault handling work orders, service evaluation feedback, electricity consumption behavior data (electricity consumption, payment records, fault frequency), etc., remove invalid data (duplicate records, data with incorrect format), and retain valid service data for the construction of the script library.

[0021] Contextualized Script Template Extraction: For each specific scenario, natural language processing techniques are used to extract high-frequency and effective expressions. Fault reporting scenarios: Based on historical fault types (such as line short circuit, transformer overload), processing flow (dispatch - inspection - power restoration - follow-up visit), and customer feedback (common questions: "How long will it take to repair?" "Do I need to pay?"), we will build standardized script templates, such as: "Hello! The line fault you reported in [XX area] has been registered. We will arrange for a repairman to come to your site within [XX minutes]. Please stay away from the fault area during the inspection. We will notify you as soon as the repair is completed." Electricity consultation scenario: Based on customer electricity consumption behavior (such as high-consumption customers, customers with seasonal surges), electricity pricing policies, and business processing procedures, customized script templates are created, such as: "Hello! Based on your electricity consumption over the past 3 months (average monthly [XX kWh]), we recommend you apply for the 'Peak-Valley Electricity Price Package'. The off-peak electricity price is only 0.35 yuan / kWh, and you are expected to save [XX yuan] in electricity bills per month. Application path: Service Management Platform - My Services - Package Change."

[0022] The dynamic update mechanism of the script library is implemented through the service data statistics module. This module collects data such as script usage frequency, customer response rate, and satisfaction score in real time, and iterates and updates the script templates every quarter: retaining effective scripts (scripts with high usage frequency, high response rate, and high satisfaction score), optimizing inefficient scripts (scripts with low usage frequency, low response rate, and low satisfaction score), and adding scenario-based scripts (scripts added based on new business needs or customer feedback).

[0023] Understandably, the script library could specifically be the WeChat Work script library.

[0024] Step S2 involves intelligent dialogue matching based on customer electricity consumption behavior characteristics. The intelligent dialogue matching of this invention is based on customer electricity consumption behavior characteristics, specifically including the following dimensions: Customer electricity consumption data: electricity consumption trend in the past 6 months (surge / decrease / stable), fault records (fault type, frequency, repair satisfaction), payment habits (on time / overdue / prepayment), and type of electrical equipment (residential / commercial / industrial). Business scenario data: current service scenario (fault reporting / consultation, etc.), time dimension (season, holidays, extreme weather), power grid operation status (peak / off-peak electricity consumption, heavy equipment load areas); Historical interaction data: past customer inquiries and responses to past dialogue (whether follow-up questions were asked, satisfaction rating).

[0025] Intelligent script matching is achieved through four types of rules: Electricity consumption association rules: For customers with high electricity consumption (monthly average electricity consumption > 150% of the regional average), we recommend energy-saving advice and peak-valley electricity pricing packages; for customers with a sudden increase in electricity consumption, we recommend an electricity anomaly investigation script. Fault record association rules: For customers with a fault frequency of ≥3 times / year, preventative maintenance scripts will be pushed to them; Scene-time linkage rules: During the summer peak electricity consumption period (June-August), push out off-peak usage call scripts + overload protection scripts; During typhoon / rainstorm weather, push out emergency fault reporting scripts; Dynamic adjustment mechanism: Based on the customer's response to the recommended scripts (such as clicking the package application link or replying to follow-up questions), the weight of subsequent script recommendations is optimized in real time (if the customer does not respond to the energy-saving scripts, the frequency of similar script recommendations is reduced).

[0026] In practical applications, based on the customer's current electricity consumption behavior characteristics, business scenario data, and historical interaction data, the above four types of rules are comprehensively applied to generate the most suitable recommended script, achieving precise linkage between "customer profile - scenario needs - script recommendation".

[0027] Step S3 involves intelligent task assignment based on power grid business monitoring indicators. The intelligent task assignment of this invention is based on a power grid business-specific monitoring indicator system, which includes: Key Indicator 1: Customer Waiting Time (Thresholds are set according to scenarios: fault reporting ≤ 5 minutes, electricity consultation ≤ 2 minutes, triggering an alert if the timeout is exceeded). Key Indicator 2: Service Satisfaction (collected through the "Service Evaluation" portal on WeChat Work, with scores ranging from 1 to 5; work orders scoring below 3 are automatically marked as "requires review"). Key Indicator 3: Task Completion Rate (Statistics by business type: fault repair completion rate ≥ 98%, consultation and answer completion rate ≥ 95%, uncompleted tasks trigger secondary dispatch). Supporting metrics: script usage rate (the percentage of scripts called from the WeChat Work script library is ≥85%), customer re-inquiry rate (the re-inquiry rate for the same question is ≤10%).

[0028] Intelligent task dispatch is based on the following dimensions: Employee competency tags: Based on historical work order data, assign competency tags to employees (such as "fault repair expert", "marketing package recommendation expert", "high voltage electricity consultant"). Workload dynamic assessment: Real-time statistics of employees' current number of pending tasks and processing time are collected through the WeChat Work backend, and new tasks are assigned to idle employees (≤3 pending tasks) in a priority manner; Task urgency ranking: set according to power grid business priority, fault reporting (especially involving large-scale power outages and high-risk areas) > safety hazard consultation > marketing activities > routine electricity use consultation; Regional adaptability: Based on the power grid power supply zones, tasks are assigned to the employees responsible for the corresponding areas (e.g., a line fault in area XX is assigned to the emergency repair personnel in that area).

[0029] In practical applications, after collecting task information, the system comprehensively evaluates employee competency tags, workload, task urgency, and regional suitability to generate a task assignment plan. The plan automatically pushes tasks (including customer information, recommended scripts, and processing time limits) through WeChat Work. Once the employee confirms the task, a customer notification is triggered, enabling intelligent task assignment and real-time customer feedback.

[0030] The following section will introduce specific application examples of the power grid smart service scenario matching and task dispatching method of the present invention.

[0031] During peak summer electricity consumption periods, intelligent script matching is used to push "off-peak electricity usage suggestions + overload emergency handling scripts" to customers in high-load areas (e.g., "Currently, it is peak electricity consumption. It is recommended to avoid using high-power equipment simultaneously between 10:00-12:00 and 18:00-20:00. If a circuit breaker trips, please turn off air conditioners, electric water heaters, etc. If the fault persists after restarting the circuit breaker, you can report the problem at any time"). Furthermore, intelligent task assignment prioritizes dispatching work orders to employees tagged with "Peak Electricity Consumption Consultation." Work orders that do not respond within the specified time are automatically transferred to backup personnel. This reduces the average consultation and response time from 3.5 minutes to 1.2 minutes, the fault reporting response time from 10 minutes to 4 minutes, and increases customer satisfaction from 82% to 96%.

[0032] In typhoon weather fault reporting scenarios, the system pushes "Typhoon Weather Fault Emergency Script" (including safety tips, required information for reporting faults, and explanation of repair priorities), and assigns tasks to employees with outdoor emergency repair qualifications by fault area clustering (faults in the same area are grouped together for dispatch). At the same time, the repair progress is updated in real time and synchronized with customers, which increases the fault repair completion rate from 85% to 98%, reduces the customer inquiry rate from 18% to 5%, and improves the work efficiency of emergency repair personnel by 40%.

[0033] During holiday marketing campaigns, the system pushes customized marketing messages to residential users (e.g., "Exclusive National Day benefits! Prepay your electricity bill and enjoy great gifts. You can get up to ** yuan in electricity bill redemption and redeem an energy-saving desk lamp. Click the link to apply now!"). By monitoring the click-through rate of the marketing messages, the system automatically optimizes inefficient messages, increasing the marketing campaign conversion rate from 12% to 28%, improving the accuracy of message matching by 35%, and reducing manual promotion costs by 50%.

[0034] This invention achieves standardization, intelligence, and dynamic optimization of power grid services by intelligently matching power grid business scenario classification with customer electricity consumption behavior. It effectively solves technical problems in traditional power grid services such as static script library, poor service scenario adaptability, low task dispatch efficiency, and insufficient service quality monitoring, and significantly improves the quality and efficiency of power grid services.

[0035] Corresponding to the power grid smart service scenario matching and task dispatching method described in Embodiment 1 of the present invention, Embodiment 2 of the present invention also provides a power grid smart service scenario matching and task dispatching device, comprising: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to perform the power grid smart service scenario matching and task dispatching method described in Embodiment 1 of the present invention.

[0036] Corresponding to the power grid smart service scenario matching and task dispatching method described in Embodiment 1 of the present invention, Embodiment 3 of the present invention also provides a computer program product, including computer instructions, which instruct computer equipment to perform the operations corresponding to the power grid smart service scenario matching and task dispatching method described in Embodiment 1 of the present invention.

[0037] Preferably, the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or the processor can be any conventional processor. The processor is the control center of the device, connecting various parts of the device through various interfaces and lines.

[0038] The memory mainly includes a program storage area and a data storage area. The program storage area can store the operating system, applications required for at least one function, etc., while the data storage area can store related data, etc. Furthermore, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard drive, a SmartMedia Card (SMC), a Secure Digital (SD) card, and a Flash Card, or other volatile solid-state storage devices.

[0039] It should be noted that the above-mentioned devices may include, but are not limited to, processors and memory, as will be understood by those skilled in the art.

[0040] As explained above, compared with existing technologies, the beneficial effects of this invention are as follows: By constructing a refined power grid business scenario classification system and a dynamic script library, this invention achieves standardization of service scripts for all positions, effectively avoiding uneven service quality caused by differences in personnel experience. The intelligent script matching algorithm, based on customer electricity consumption behavior characteristics, achieves precise linkage between "customer profile - scenario needs - script recommendation" through electricity consumption association rules, fault record association rules, scenario-time linkage rules, and a dynamic adjustment mechanism. This significantly reduces script selection time, greatly shortening consultation and fault reporting response times. The intelligent task dispatch mechanism, based on the power grid business's unique monitoring indicator system, combined with employee capability tags, dynamic workload assessment, task urgency, and regional adaptability, avoids delays in manual dispatch and improves service response speed. Simultaneously, through a dynamic script update mechanism and task monitoring system, it effectively reduces customer re-inquiry rates and ineffective communication time, improves marketing activity conversion rates, and reduces manual promotion costs. This invention not only improves the accuracy, efficiency, and quality of power grid services, but also significantly reduces service costs, providing power grid companies with standardized, intelligent, and dynamically optimized service solutions, effectively addressing key pain points in traditional power grid services.

[0041] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for matching and dispatching smart grid service scenarios, characterized in that, include: Step S1: Based on the power grid business scenario classification system, the script library is dynamically updated by the frequency of script usage, customer response rate and satisfaction score. Step S2: Based on customer electricity consumption behavior characteristics, intelligent script matching is performed through electricity consumption association rules, fault record association rules, scenario-time linkage rules, and dynamic adjustment mechanisms. Step S3: Based on power grid business monitoring indicators, combined with employee capability tags, dynamic workload assessment, task urgency and regional adaptability, intelligent task assignment is carried out.

2. The method according to claim 1, characterized in that, The power grid business scenario classification system includes fault reporting scenarios, electricity consultation scenarios, safety promotion scenarios, and marketing activity scenarios. Among them, the fault reporting scenarios include line faults, equipment faults, power outage reporting, and power restoration consultation; the electricity consultation scenarios include electricity bill inquiries, electricity price consultations, account opening and transfer, electricity capacity adjustments, and seasonal electricity usage; the safety promotion scenarios include residential electricity safety, enterprise electricity safety, high-voltage area warnings, and thunderstorm protection; and the marketing activity scenarios include electricity price package recommendations, energy-saving product promotions, points redemption, and holiday discounts.

3. The method according to claim 2, characterized in that, The construction of the script library specifically includes: Synchronize historical power grid service data through the service management platform interface, including customer inquiry records, fault handling work orders, service evaluation feedback, and electricity consumption behavior data, and remove invalid data; For each specific scenario, natural language processing technology is used to extract high-frequency and effective expressions. In the fault reporting scenario, standardized script templates are built based on historical fault types, processing procedures and customer feedback. In the electricity consultation scenario, script templates are customized based on customer electricity usage behavior, electricity pricing policies and business processing procedures.

4. The method according to claim 1, characterized in that, In step S1, the dynamic update mechanism of the script library includes: retaining scripts with high usage frequency, high response rate, and high satisfaction rating; optimizing scripts with low usage frequency, low response rate, and low satisfaction rating; and adding scripts based on new business needs or customer feedback.

5. The method according to claim 1, characterized in that, In step S2, the customer's electricity consumption behavior characteristics include: electricity consumption trend over the past 6 months, fault records, payment habits, and types of electrical equipment.

6. The method according to claim 1, characterized in that, In step S2, the electricity consumption association rule is as follows: for customers with high electricity consumption, energy-saving advice and peak-valley electricity pricing packages are recommended; for customers with a sudden increase in electricity consumption, an electricity anomaly investigation script is recommended; the fault record association rule is as follows: for customers with a fault frequency of ≥3 times / year, preventive maintenance script is pushed; the scenario-time linkage rule is as follows: during peak electricity consumption periods, off-peak usage script and overload protection script are pushed; during typhoon / rainstorm weather, emergency fault reporting script is pushed. The dynamic adjustment mechanism is as follows: based on the customer's response to the recommended scripts, the weight of subsequent script recommendations is optimized in real time.

7. The method according to claim 1, characterized in that, In step S3, the power grid business monitoring indicators include: customer waiting time, service satisfaction, task completion rate, script usage rate, and customer re-inquiry rate.

8. The method according to claim 1, characterized in that, In step S3, the employee competency tags include: fault repair expert, marketing package recommendation expert, and high-voltage electricity consultation specialist; the dynamic workload assessment is: by real-time statistics of the number of tasks currently pending and the processing time of employees, new tasks are prioritized to be assigned to employees with ≤3 pending tasks; the task urgency ranking is: fault reporting > safety hazard consultation > marketing activities > routine electricity consultation; the regional adaptability is: in combination with the power grid power supply zoning, tasks are assigned to employees responsible for the corresponding regions.

9. A smart grid service scenario matching and task dispatching device, characterized in that, include: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to perform the smart grid service scenario matching and task dispatching method as described in any one of claims 1 to 8.

10. A computer program product, characterized in that, Includes computer instructions that instruct a computer device to perform an operation corresponding to the method as described in any one of claims 1 to 8.

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