Power utilization inspection quality and efficiency evaluation system considering multi-scene indexes

Abstract

The invention discloses a power utilization inspection quality and efficiency evaluation system considering multi-scene indexes, and the system comprises a setting device which is used for setting and modifying inspection indexes, and building and modifying an inspection plan; the inspection data input device is used for automatically verifying actual inspection scenes, inspection items and inspection and assessment processes; an inspector fills in data corresponding to the inspection items through the inspection data input device to serve as inspection data; the inspection data input device combines actual inspection scenes, inspection items, inspection and assessment processes and inspection data into inspection operation data and remotely uploads the inspection operation data to the evaluation data receiving device; the evaluation data receiving device is used for classifying and combining into inspection standard data according to inspection scenes; and the quality and efficiency evaluation system stores an evaluation model, and inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the power utilization inspection quality and efficiency evaluation grade of the inspector. According to the method, power utilization inspection quality-effect evaluation is carried out by considering multi-scene indexes, and the method is objective, standard, normative, fair and effective.

Description

Technical Field

[0001] The present invention relates to the technical field of electricity consumption inspection quality and efficiency evaluation, and in particular to an electricity consumption inspection quality and efficiency evaluation system considering multi-scenario indicators. Background Art

[0002] Power usage inspections include electrical equipment inspections, load monitoring, and leakage protection testing. Electrical equipment encompasses user power receiving devices, metering devices, power usage behavior, and line equipment. Furthermore, regulatory compliance checks, power supply security, locking devices, and grid security maintenance are also required. Power usage inspections are used by industrial and residential users, those with self-supplied power, temporary power applications, high-energy-consuming enterprises, those integrating new energy sources, and renovations of older residential communities, encompassing a wide range of businesses, organizations, and individuals. Because power usage inspections are crucial for both users and power companies, they require quality and efficiency assessments to evaluate inspection quality and measure the performance of inspectors.

[0003] However, the current electricity inspection quality and efficiency evaluation system has poor adaptability. It does not consider the different scenarios of different customers, but simply sets up supervisors to conduct evaluations. Most of the indicators are constructed based on the personal concerns formed by managers' experience. Such indicators are highly personalized, non-standard, non-normalized and unsystematic. The subjective influence of the evaluation is too large and not objective. There is an urgent need for an electricity inspection quality and efficiency evaluation system that considers multi-scenario indicators, which is objective, standard, standardized, fair and effective. Summary of the Invention

[0004] In order to overcome the above-mentioned shortcomings of the prior art, the present invention proposes an electricity inspection quality and efficiency evaluation system that takes into account multiple scenario indicators. The electricity inspection quality and efficiency evaluation is performed by taking into account multiple scenario indicators, which is objective, standard, normative, fair and effective.

[0005] The technical solution adopted by the present invention to solve the technical problem is: a power consumption inspection quality and efficiency evaluation system considering multiple scenario indicators, including:

[0006] Setting means for setting and modifying inspection indicators, and establishing and modifying inspection plans; the inspection plans include inspection scenarios, inspection items, and inspection assessment processes; the inspection assessment processes include the relative time of inspection start, relative time of inspection end, and inspection geographical area of the process of executing the inspection items by the inspector;

[0007] The inspection data input device is used to automatically verify the actual inspection scene, inspection items, and inspection assessment process; the inspector fills in the data corresponding to the inspection item through the inspection data input device as inspection data; the inspection data input device combines the actual inspection scene, inspection items, inspection assessment process and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device;

[0008] An evaluation data receiving device is used to receive inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors' implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios;

[0009] The quality and efficiency evaluation system stores an evaluation model, and inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the quality and efficiency evaluation level of the electricity inspection by the inspector.

[0010] Furthermore, the inspection items include but are not limited to electrical equipment inspection, load monitoring, leakage protection test, and power supply inspection.

[0011] Furthermore, the inspection scenarios include user-side inspection scenarios, grid-side equipment inspection scenarios, and special scenario inspections; the user-side inspection scenarios include electricity consumption by high-energy-consuming enterprises, residential electricity consumption, and distributed energy access electricity consumption; the grid-side equipment inspection scenarios include distribution equipment inspection and power line inspection. The distribution equipment inspection is to check the operating status and insulation performance of transformers, circuit breakers, and distribution cabinets; the power line inspection is to check line aging, damage, and grounding reliability; special scenario inspections include temporary power consumption inspections and new energy consumption assessments.

[0012] Furthermore, the inspection indicators include inspection coverage rate, hidden danger rectification rate, equipment qualification rate, user satisfaction, safety accident rate, and process specification score; the inspection coverage rate is the percentage of all users and projects covered by the inspection; the hidden danger rectification rate is the percentage of hidden dangers resolved relative to all hidden dangers; the equipment qualification rate is the percentage of qualified power equipment relative to all equipment; user satisfaction is the user's satisfaction with the service effect; the safety accident rate is the proportion of safety accident incidents that occurred after the inspection to all incidents; the process specification score is scored according to the degree of deviation of the process specifications of the inspectors in executing the inspection plan from the standards.

[0013] Furthermore, the setting module adopts a PAD or a mobile phone.

[0014] Furthermore, the inspection data input device includes a Beidou satellite positioning device, a network transmission module, a camera, a control unit, and a memory; the Beidou satellite positioning device, the network transmission module, the camera, and the memory are respectively connected to the control unit.

[0015] Furthermore, the evaluation data receiving device uses a data server to receive inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors' spot checks on inspectors' execution of inspection plans, and operation data of various inspection scenarios of the power grid through the WEB.

[0016] Furthermore, the method for establishing the evaluation model includes the following steps:

[0017] A decision tree model was introduced to classify and evaluate the inspection standard data, obtain the electricity inspection quality and efficiency evaluation results, and input the principal component analysis algorithm to process the data in the electricity inspection quality and efficiency evaluation results to obtain the dimensionality reduction matrix of each leaf node;

[0018] The ABOD algorithm is introduced to calculate the eigenvectors of the dimensionality reduction matrix, obtain the variance value of the angle, and process the repair evaluation results based on the variance value of the angle to obtain the quality and efficiency evaluation level of the inspector's electricity inspection after processing;

[0019] The electricity inspection quality and efficiency evaluation results of each inspection scenario within the preset time are obtained, and a state transition probability matrix is constructed according to the electricity inspection quality and efficiency evaluation results of each inspection plan within the preset time through a Markov chain.

[0020] Among them, introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle, and processing the electricity inspection quality and efficiency evaluation result according to the variance value of the angle to obtain the processed electricity inspection quality and efficiency evaluation result, specifically including: introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle formed between the eigenvectors, and judging whether the variance value is greater than a preset variance threshold;

[0021] When the variance value is greater than the preset variance threshold, obtaining the leaf node where the variance value is greater than the preset variance threshold, and re-split the leaf node;

[0022] When the variance value is no longer greater than the preset variance threshold, a new leaf node is output, and the electricity inspection quality and efficiency evaluation result is corrected according to the new leaf node to obtain a processed evaluation result;

[0023] Obtain the electricity inspection quality and efficiency evaluation results of each inspection scenario within the preset time, and construct a state transition probability matrix according to the electricity inspection quality and efficiency evaluation results of each inspection plan within the preset time through a Markov chain, specifically including: constructing a timestamp, and obtaining the electricity inspection quality and efficiency evaluation results of each inspection scenario in each timestamp, and constructing the electricity inspection quality and efficiency evaluation results of the inspection scenarios within the preset time according to the electricity inspection quality and efficiency evaluation results of the inspection scenarios in each timestamp;

[0024] Calculate the probability value of the electricity inspection quality and efficiency evaluation result transition from one electricity inspection quality and efficiency evaluation result to another inspection scenario at each timestamp through the Markov chain, and transfer the probability matrix based on the electricity inspection quality and efficiency evaluation level of the inspector;

[0025] Among them, the electricity consumption inspection quality and efficiency evaluation results of each inspection scenario within the preset time are the processed evaluation results.

[0026] An evaluation method using the above-mentioned electricity inspection quality and efficiency evaluation system considering multiple scenario indicators includes the following steps:

[0027] Set up equipment and modify inspection indicators, establish and modify inspection plans;

[0028] The evaluation data receiving device automatically verifies the actual inspection scene, inspection items, and inspection assessment process;

[0029] The inspector fills in the data corresponding to the inspection item as inspection data through the inspection data input device;

[0030] The inspection data input device combines the actual inspection scene, inspection items, inspection assessment process and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device;

[0031] The evaluation data receiving device receives inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors’ implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios;

[0032] The quality and efficiency evaluation system inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the quality and efficiency evaluation level of the inspector's electricity inspection.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention employs a setting device for setting and modifying inspection indicators and establishing and modifying inspection plans; an inspection data input device for automatically verifying actual inspection scenarios, inspection items, and inspection assessment processes; inspectors use the inspection data input device to enter data corresponding to the inspection items as inspection data; the inspection data input device combines the actual inspection scenarios, inspection items, inspection assessment processes, and inspection data into inspection operation data and remotely uploads it to an evaluation data receiving device. The evaluation data receiving device receives inspection operation data, user satisfaction evaluation data on inspectors, inspection indicator data from supervisors spot-checking inspectors' implementation of inspection plans, and operational data from various power grid inspection scenarios, which are classified and combined into inspection standard data based on the inspection scenarios; a quality and efficiency evaluation system stores an evaluation model, and inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the inspector's electricity inspection quality and efficiency evaluation grade. Furthermore, the present invention utilizes a decision tree, which can rapidly process large amounts of data, enabling intelligent monitoring of the quality and efficiency of electricity inspections. Furthermore, the present invention integrates principal component analysis and the ABOD algorithm to optimize the decision tree model, which can improve the accuracy of batch data processing, ensuring objectivity, standardization, and compliance, as well as fairness and effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments.

[0036] Figure 1 This is an overall structural diagram of an electricity consumption inspection quality and efficiency evaluation system that considers multiple scenario indicators in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0038] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the present invention.

[0039] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, 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 indirectly connected through an intermediate medium, or it can be internal communication between two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] like Figure 1 As shown, an embodiment of the present invention provides a system for evaluating the quality and efficiency of electricity consumption that considers multiple scenario indicators, including:

[0041] The configuration device is used to set and modify inspection indicators and establish and modify inspection plans. The inspection plan includes inspection scenarios, inspection items, and inspection assessment processes. The inspection assessment process includes the relative inspection start time, relative inspection end time, and inspection geographical area of the process for inspectors to perform inspection items.

[0042] The inspection data input device is used to automatically verify the actual inspection scenario, inspection items, and inspection assessment process. Inspectors use the inspection data input device to enter the data corresponding to the inspection items as inspection data. The inspection data input device combines the actual inspection scenario, inspection items, inspection assessment process, and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device.

[0043] The evaluation data receiving device is used to receive inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors' implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios.

[0044] , an evaluation model is stored, and all data obtained by the evaluation data receiving device are input into the evaluation model to obtain the quality and efficiency evaluation level of the inspector's electricity inspection.

[0045] Inspection items include but are not limited to electrical equipment inspection, load monitoring, leakage protection testing, and power supply inspection.

[0046] Inspection scenarios include user-side inspections, grid-side equipment inspections, and special inspection scenarios. User-side inspections cover electricity consumption by high-energy-consuming enterprises, residential electricity consumption, and distributed energy access. Grid-side equipment inspections include distribution equipment inspections and power line inspections. Distribution equipment inspections include checking the operating status and insulation performance of transformers, circuit breakers, and distribution cabinets; power line inspections include checking for line aging, damage, and grounding reliability. Special inspection scenarios include temporary power use inspections and new energy consumption assessments.

[0047] Inspection indicators include inspection coverage rate, hidden danger rectification rate, equipment qualification rate, user satisfaction, safety accident rate, and process specification score; inspection coverage rate is the percentage of all users and projects covered by the inspection; hidden danger rectification rate is the percentage of hidden dangers resolved relative to all hidden dangers; equipment qualification rate is the percentage of qualified power equipment relative to all equipment; user satisfaction is the user's satisfaction with the service effect; safety accident rate is the proportion of safety accident incidents that occurred after the inspection to all incidents; process specification score is the score based on the degree of deviation of the process specifications of the inspectors in executing the inspection plan from the standards.

[0048] The setting module uses a PAD or mobile phone.

[0049] The inspection data input device includes a Beidou satellite positioning device, a network transmission module, a camera, a control unit, and a memory. The Beidou satellite positioning device, the network transmission module, the camera, and the memory are connected to the control unit respectively.

[0050] The evaluation data receiving device uses a data server to receive inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors' implementation of inspection plans, and operation data of various inspection scenarios of the power grid through the WEB.

[0051] The method for establishing the evaluation model includes the following steps:

[0052] A decision tree model was introduced to classify and evaluate the inspection standard data, obtain the electricity inspection quality and efficiency evaluation results, and input the principal component analysis algorithm to process the data in the electricity inspection quality and efficiency evaluation results to obtain the dimensionality reduction matrix of each leaf node;

[0053] The ABOD algorithm is introduced to calculate the eigenvectors of the dimensionality reduction matrix, obtain the variance value of the angle, and process the repair evaluation results based on the variance value of the angle to obtain the quality and efficiency evaluation level of the inspector's electricity inspection after processing;

[0054] The electricity inspection quality and efficiency evaluation results of each inspection scenario within the preset time are obtained, and a state transition probability matrix is constructed according to the electricity inspection quality and efficiency evaluation results of each inspection plan within the preset time through a Markov chain.

[0055] Among them, introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle, and processing the electricity inspection quality and efficiency evaluation result according to the variance value of the angle to obtain the processed electricity inspection quality and efficiency evaluation result, specifically including: introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle formed between the eigenvectors, and judging whether the variance value is greater than a preset variance threshold;

[0056] When the variance value is greater than the preset variance threshold, obtaining the leaf node where the variance value is greater than the preset variance threshold, and re-split the leaf node;

[0057] When the variance value is no longer greater than the preset variance threshold, a new leaf node is output, and the electricity inspection quality and efficiency evaluation result is corrected according to the new leaf node to obtain a processed evaluation result;

[0058] Obtain the electricity inspection quality and efficiency evaluation results of each inspection scenario within the preset time, and construct a state transition probability matrix according to the electricity inspection quality and efficiency evaluation results of each inspection plan within the preset time through a Markov chain, specifically including: constructing a timestamp, and obtaining the electricity inspection quality and efficiency evaluation results of each inspection scenario in each timestamp, and constructing the electricity inspection quality and efficiency evaluation results of the inspection scenarios within the preset time according to the electricity inspection quality and efficiency evaluation results of the inspection scenarios in each timestamp;

[0059] Calculate the probability value of the electricity inspection quality and efficiency evaluation result transition from one electricity inspection quality and efficiency evaluation result to another inspection scenario at each timestamp through the Markov chain, and transfer the probability matrix based on the electricity inspection quality and efficiency evaluation level of the inspector;

[0060] Among them, the electricity consumption inspection quality and efficiency evaluation results of each inspection scenario within the preset time are the processed evaluation results.

[0061] An evaluation method using the above-mentioned electricity inspection quality and efficiency evaluation system considering multiple scenario indicators includes the following steps:

[0062] Set up equipment and modify inspection indicators, establish and modify inspection plans;

[0063] The evaluation data receiving device automatically verifies the actual inspection scene, inspection items, and inspection assessment process;

[0064] The inspector fills in the data corresponding to the inspection item as inspection data through the inspection data input device;

[0065] The inspection data input device combines the actual inspection scene, inspection items, inspection assessment process and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device;

[0066] The evaluation data receiving device receives inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors’ implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios;

[0067] The quality and efficiency evaluation system inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the quality and efficiency evaluation level of the inspector's electricity inspection.

[0068] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A system for evaluating the quality and efficiency of electricity consumption inspections taking into account multiple scenario indicators, characterized in that: include: Setting means for setting and modifying inspection indicators, and establishing and modifying inspection plans; the inspection plans include inspection scenarios, inspection items, and inspection assessment processes; the inspection assessment processes include the relative time of inspection start, relative time of inspection end, and inspection geographical area of the process of executing the inspection items by the inspector; The inspection data input device is used to automatically verify the actual inspection scene, inspection items, and inspection assessment process; the inspector fills in the data corresponding to the inspection item through the inspection data input device as inspection data; the inspection data input device combines the actual inspection scene, inspection items, inspection assessment process and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device; An evaluation data receiving device is used to receive inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors' implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios; The quality and efficiency evaluation system stores an evaluation model, and inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the quality and efficiency evaluation level of the electricity inspection by the inspector.

2. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The inspection items include but are not limited to electrical equipment inspection, load monitoring, leakage protection testing, and power supply inspection.

3. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The inspection scenarios include user-side inspection scenarios, grid-side equipment inspection scenarios, and special scenario inspections; the user-side inspection scenarios include electricity consumption by high-energy-consuming enterprises, residential electricity consumption, and distributed energy access electricity consumption; the grid-side equipment inspection scenarios include distribution equipment inspection and power line inspection. The distribution equipment inspection includes checking the operating status and insulation performance of transformers, circuit breakers, and distribution cabinets; the power line inspection includes checking line aging, damage, and grounding reliability; Special scenario inspections include temporary electricity usage inspections and new energy consumption assessments.

4. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The inspection indicators include inspection coverage rate, hidden danger rectification rate, equipment qualification rate, user satisfaction, safety accident rate, and process specification score; inspection coverage rate is the percentage of all users and projects covered by the inspection; hidden danger rectification rate is the percentage of hidden dangers resolved relative to all hidden dangers; equipment qualification rate is the percentage of qualified power equipment relative to all equipment; and user satisfaction is the user's satisfaction with the service effect; The safety accident rate is the proportion of safety accident events that occurred after the inspection to all events; The process specification score is based on the degree to which the inspector deviates from the standard in executing the process specification of the inspection plan.

5. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The setting module adopts a PAD or a mobile phone.

6. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The inspection data input device includes a Beidou satellite positioning device, a network transmission module, a camera, a control unit, and a memory; the Beidou satellite positioning device, the network transmission module, the camera, and the memory are respectively connected to the control unit.

7. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The evaluation data receiving device adopts a data server to receive inspection operation data, user satisfaction evaluation data of inspectors, inspection index data of supervisors' spot checks on inspectors' execution of inspection plans, and operation data of various inspection scenarios of the power grid through the WEB.

8. The electricity inspection quality and efficiency evaluation system considering multiple scenario indicators according to claim 1 is characterized in that: The method for establishing the evaluation model comprises the following steps: A decision tree model was introduced to classify and evaluate the inspection standard data, obtain the electricity inspection quality and efficiency evaluation results, and input the principal component analysis algorithm to process the data in the electricity inspection quality and efficiency evaluation results to obtain the dimensionality reduction matrix of each leaf node; The ABOD algorithm is introduced to calculate the eigenvectors of the dimensionality reduction matrix, obtain the variance value of the angle, and process the repair evaluation results based on the variance value of the angle to obtain the quality and efficiency evaluation level of the inspector's electricity inspection after processing; Obtain the electricity inspection quality and efficiency evaluation results for each inspection scenario within the preset time, and construct a state transition probability matrix based on the electricity inspection quality and efficiency evaluation results for each inspection plan within the preset time through a Markov chain; Among them, introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle, and processing the electricity inspection quality and efficiency evaluation result according to the variance value of the angle to obtain the processed electricity inspection quality and efficiency evaluation result, specifically including: introducing the ABOD algorithm, calculating the eigenvectors of the dimensionality reduction matrix by the ABOD algorithm, obtaining the variance value of the angle formed between the eigenvectors, and judging whether the variance value is greater than a preset variance threshold; When the variance value is greater than the preset variance threshold, obtaining the leaf node where the variance value is greater than the preset variance threshold, and re-split the leaf node; When the variance value is no longer greater than the preset variance threshold, a new leaf node is output, and the electricity inspection quality and efficiency evaluation result is corrected according to the new leaf node to obtain a processed evaluation result; Obtain the electricity inspection quality and efficiency evaluation results of each inspection scenario within the preset time, and construct a state transition probability matrix according to the electricity inspection quality and efficiency evaluation results of each inspection plan within the preset time through a Markov chain, specifically including: constructing a timestamp, and obtaining the electricity inspection quality and efficiency evaluation results of each inspection scenario in each timestamp, and constructing the electricity inspection quality and efficiency evaluation results of the inspection scenarios within the preset time according to the electricity inspection quality and efficiency evaluation results of the inspection scenarios in each timestamp; Calculate the probability value of the electricity inspection quality and efficiency evaluation result transition from one electricity inspection quality and efficiency evaluation result to another inspection scenario at each timestamp through the Markov chain, and transfer the probability matrix based on the electricity inspection quality and efficiency evaluation level of the inspector; Among them, the electricity consumption inspection quality and efficiency evaluation results of each inspection scenario within the preset time are the processed evaluation results.

9. An evaluation method using the above-mentioned electricity inspection quality and efficiency evaluation system considering multiple scenario indicators includes the following steps: Set up equipment and modify inspection indicators, establish and modify inspection plans; The evaluation data receiving device automatically verifies the actual inspection scene, inspection items, and inspection assessment process; The inspector fills in the data corresponding to the inspection item as inspection data through the inspection data input device; The inspection data input device combines the actual inspection scene, inspection items, inspection assessment process and inspection data into inspection operation data and remotely uploads it to the evaluation data receiving device; The evaluation data receiving device receives inspection operation data, user satisfaction evaluation data on inspectors, inspection index data of supervisors on inspectors’ implementation of inspection plans, and operation data of various inspection scenarios of the power grid, which are classified and combined into inspection standard data according to the inspection scenarios; The quality and efficiency evaluation system inputs all data obtained by the evaluation data receiving device into the evaluation model to obtain the quality and efficiency evaluation level of the inspector's electricity inspection.

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