CN115587857A - Base power supply station key index and level evaluation increasing ratio carry method - Google Patents
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Abstract
The invention relates to a proportion-increasing carry method for key indexes and level evaluation of a base power supply station, which comprises the following steps: step 1, index screening, namely dividing basic units into power supply units with different length ranges according to medium-voltage line management lengths by using a logic tree diagram and an organizational structure model tool, wherein the medium-voltage line length is greater than 100km and is a full-service power supply station, the medium-voltage line length is less than or equal to 100km and is a non-full-service power supply station, and collecting core management indexes of the full-service power supply station and core management indexes of the non-full-service power supply station; step 2, index modeling, index model training and verification are carried out; step 3, index calculation and display are carried out according to the index calculation formula verified in the step 2; aiming at the index evaluation of the basic power supply station, when the index is changed from a single index to a plurality of indexes, the result of an index set becomes rich and complex, the monitoring of single index data and simple multi-index cannot meet the rich monitoring requirement of the whole power supply station, and the like.
Description
Technical Field
The invention belongs to the technical field of power management, and particularly relates to a proportion-increasing carry method for key indexes and level evaluation of a primary power supply station.
Background
At present, comprehensive index evaluation is mainly carried out on a basic power station by an AHP (advanced high performance processor), ANP (artificial intelligence) or entropy method, a specific index value is obtained by data acquisition and data calculation, and then interpretation and application of basic unit service data indexes are realized; in actual work scene business data index interpretation and application, data monitoring is usually needed to be matched, problems are found through a series of actions of business data monitoring, analysis, repeated disk and the like, a solution is sought, prediction and decision are carried out on a next stage target of business, and the function of data index is effectively played; and the data monitoring, namely acquisition and presentation, is to acquire the user full-link behavior data and the service data and present the data by using a visual graph and table. And then the supervision and control are carried out through a data index system. However, when the index changes from a single index to multiple indexes, the result of the index set becomes rich and complex, and the monitoring of single index data and simple multiple indexes cannot meet the rich monitoring requirement of the whole power supply.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method is used for solving the technical problems that the index evaluation of the power supply station in the basic level is changed from a single index into a plurality of indexes, the result of an index set becomes rich and complex, the monitoring of single index data and simple multi-indexes cannot meet the rich monitoring requirement of the whole power supply and the like.
The technical scheme adopted by the invention is as follows:
a base power station key index and level evaluation increasing-ratio carry method comprises the following steps:
step 1, index screening, namely dividing basic units into power supply units with different length ranges according to medium-voltage line management lengths by using a logic tree diagram and an organizational structure model tool, wherein the medium-voltage line length is greater than 100km and is a full-service power supply station, the medium-voltage line length is less than or equal to 100km and is a non-full-service power supply station, and collecting core management indexes of the full-service power supply station and core management indexes of the non-full-service power supply station;
step 2, performing index modeling, index model training and verification;
and 4, calculating and displaying the indexes according to the index calculation formula verified in the step 2.
The core management indexes of the full-service power supply station comprise: medium-voltage line faults, distribution network data quality qualification rate, customer average power failure time, electricity charge recovery rate, electricity charge error rate, 10kV or below damaged line loss rate, line loss abnormity handling completion rate, customer complaint rate, comprehensive automatic meter reading rate and electronic settlement rate.
The core management indexes of the non-full-service power supply station are 7: the system comprises an electric charge recovery rate, an electric charge error rate, a line loss rate with loss of 10kV or below, a line loss abnormity handling completion rate, a customer complaint rate, a comprehensive automatic meter reading rate and an electronic settlement rate.
The index modeling method comprises the following steps:
step 2.1, data acquisition: acquiring and integrating index basic data of a marketing system, a metering automation system, an asset management system and a data quality index monitoring platform 6+1 service system, incrementally acquiring data of an original service system T +1 through an ETL data synchronization tool, and storing the acquired data in a GP database of a data center data operation control platform;
step 2.2, data processing: a scheduling task management and control tool is adopted to perform data cleaning, data analysis and data mining on the previous month data at regular time, refine key data, perform data operation and store a key index result base;
step 2.3, data pushing: the index result set is immediately pushed to MySQL data of a field operation tool package platform through an ETL data synchronization tool;
2.4, dividing the system into a front-end module and a rear-end module according to the functional requirement of increasing carry; the front-end module is a service display layer and comprises a basic function, a date query function and an entity query function; the back-end module is divided into a score statistical layer and a basic data layer; the score statistic layer comprises index score statistics and unit score summary calculation, and the basic data layer comprises data synchronization and index value statistics; and establishing an index calculation model.
The index calculation formula of the index calculation model comprises:
index 1: medium voltage line failure rate
Medium voltage line fault rate = Σ (number of medium voltage line faults)/Σ (statistical medium voltage line kilometers) × 100 × 12/n, n = the number of months from the beginning of the year till now, statistical month value n =1;
index 2: distribution network data quality qualification rate
Distribution network data quality qualification rate { [ 0.1+ GIS and production station line consistency (public line) 0.2+ GIS and marketing station line consistency (public line) 0.1+ GIS and marketing station line consistency 0.2+ GIS and marketing user consistency 0.4} 0.6+ low-voltage user belonging area and concentrator belonging area consistency 0.4} + 100%.
Index 3: average power off time of customer
The customer power failure time (medium voltage) = Σ power failure duration per time × the number of medium voltage customers affected by power failure per time;
index 4: recovery rate of electric charge
The recovery rate of the electric charge = the actual electric charge in the statistical period (the current year)/the electric charge to be charged in the current year 100%;
index 5: error rate of electricity charge
The electricity charge error rate = (number of electricity charge error pens in the statistical period/total number of electricity charge bills in the statistical period) 100%;
index 6: loss rate of 10kV or less
A loss line loss rate of 10kV and below = (power supply amount-sales electricity amount)/(power supply amount-lossless electricity amount) × 100%;
index 7: completion rate of line loss exception handling
A line loss abnormality disposal completion rate = [ (number of disposed normal lines/number of abnormal lines) × 0.3+ (number of disposed normal lands/number of abnormal lands) × 0.7] × 100%;
index 8: customer complaint rate
Customer complaint rate = 95598 actual complaint number of the year/total number of electric power users (ten thousands of users) in the statistical region
Index 9: comprehensive automatic meter reading rate
The comprehensive automatic meter reading rate = [ (the automatic meter reading rate of a specific transformer user × (0.3) + the automatic meter reading rate of a public transformer user × (0.3) + the automatic meter reading rate of a low-voltage user × (0.4) ] × 100%;
index 10: electronic settlement rate
Electronic settlement rate = (number of automatic meter reading settlement users in maintenance range/total number of users in maintenance range) × 100%.
The index model training method comprises the following steps:
(1) Substituting the service parameters into an index model calculation formula to obtain a calculation result;
(2) And comparing and analyzing the calculation result with the real data, and repeatedly correcting the index model formula.
The index model verification method comprises the following steps:
introducing the standard operation data into the trained model formula to obtain a prediction result;
performing inverse normalization compilation on the prediction result to restore the data into an original data type;
comparing and analyzing the inverse normalization result and the real data, and calculating the accuracy of the model;
and performing service verification aiming at the model accuracy until the model is optimal.
The method also comprises an index model test, and comprises the following steps:
(1) Bringing the index operation data into the trained model to obtain a predicted value;
(2) And performing inverse normalization compilation on the predicted values, converting the data into an original data type, calculating the accuracy of the model by using the inverse normalization data and the true value of the standard operation data, and evaluating the effectiveness of the model.
Step 3, the method for calculating and displaying the indexes according to the index calculation formula verified in step 2 comprises the following steps: setting a ranking period, and developing evaluation according to a mode of monthly notification, quarterly statistics and annual assessment; secondly, setting a ranking level: dividing the indexes into a city bureau level, a county and district bureau level and a power supply station level, and ranking according to the index score ranking from high to low after the index is calculated; and finally displaying the ranking result.
The invention has the beneficial effects that:
the invention solves the technical problems that the service development state of a power supply station cannot be mastered in time by basic staff of the branch county bureau and the power supply station, when indexes are changed from single indexes to multiple indexes, the result of an index set becomes rich and complex, the monitoring of single index data and simple multiple indexes cannot meet the rich monitoring requirements of the whole power supply station, and the like. "the index source data is firstly indexed, and then multi-index automatic comprehensive calculation is carried out according to the business needs, including: the method comprises the steps of establishing an information index data aggregation and pushing platform which takes a basic-level power supply station service as a center for each power supply station organization in the whole province through weighted summation, weighted geometric average, linear weighting and geometric comprehensive combination, calculating the value of the rank of each power supply station, providing dynamic rank of the basic-level power supply station in the whole province for users in real time through a field tool APP, accelerating internal and external communication between the power supply stations, improving working efficiency, achieving data integration, index transparence, query visualization, improvement precision and benchmarking visualization of the power supply station management, comprehensively creating a good atmosphere of 'help-driving-over-learning', and accumulating successful experience for digital transformation of a company and assisting the power company to fall on the ground 'three-base construction strategy'.
Detailed Description
The invention is further described below with reference to specific embodiments.
Step 1, index screening:
in order to realize management, implementation and guarantee efficient linkage of three levels, tools such as a logic tree diagram, organizational structure model management and the like are used for dividing the medium-voltage line management length in a basic unit into power supply units with different length ranges, the medium-voltage line length is greater than 100km and is a full-service power supply station, the medium-voltage line length is less than or equal to 100km and is a non-full-service power supply station, wherein the core management indexes of the full-service power supply station are 10: medium-voltage line faults, distribution network data quality qualification rate, customer average power failure time, electricity charge recovery rate, electricity charge error rate, 10kV or below damaged line loss rate, line loss abnormity handling completion rate, customer complaint rate, comprehensive automatic meter reading rate and electronic settlement rate. The core management indexes of the non-full service power supply station are 7: the system comprises an electric charge recovery rate, an electric charge error rate, a line loss rate with loss of 10kV or below, a line loss abnormity handling completion rate, a customer complaint rate, a comprehensive automatic meter reading rate and an electronic settlement rate.
The method comprises the following steps:
(1) Professional fusion and establishment of efficient linkage mechanism
A logic tree diagram, an organizational structure model management tool and other tools are used for constructing a one-leading, three-level and multi-subject cooperative propulsion organization, the advantages of all levels are effectively exerted, and management, implementation and high-efficiency linkage of three levels are achieved.
(2) Data management tool for finding core elements and developing' Guizhou characteristics
The method focuses on indexes in the field of safe production and power utilization service, takes key assessment indexes of a five-star power supply station as a basis, takes load reduction and direct system acquisition and transmission as basic criteria, screens evaluation indexes, makes a scheme, designs system module functions, and develops an increasing ratio carry data management tool with Guizhou characteristics on the basis of an on-site tool APP.
(3) Elaborately screening data service and scientifically establishing mode
(1) The evaluation range is determined, and the comprehensive coverage of power supply station management is realized
According to the principle of 'full coverage and full range', the key target of 'pushing the creation of star-level power supply stations and comprehensively improving the management level of the power supply stations of companies' is centered, all power supply stations belonging to Guizhou power grid companies are selected as 'increasing-ratio carry' core index evaluation objects, and the range covers the whole province.
(2) Subdividing service types and establishing reasonable and fair evaluation foundation
According to different business organization modes, power supply stations are divided into two types: the system comprises a full-service power supply station, a power distribution station and a power distribution system, wherein the full-service power supply station is mainly responsible for customer service, metering, electric charge recovery, and 10kV or below distribution line operation and maintenance; and the second is a non-full-service power supply station, namely a 'marketing + low-voltage operation and maintenance service' power supply station, which is mainly responsible for customer service, metering, electric charge recovery, and low-voltage (0.4 kV) distribution line operation and maintenance. According to the division result, the total province has 227 total service power stations and 436 non-total service power stations.
(3) Screening business indexes and elaborately designing an evaluation system
Based on 'core indexes evaluated by south network star class stations', management tools such as an expert scoring method and key performance management are used, experts at all levels of an organization company are used for conducting research and study, and key indexes are screened from two dimensions of 'distribution network operation and maintenance and business service' according to the principles of 'index objective, data real, direct acquisition and direct delivery' and the like to serve as rating indexes.
Step 2, index calculation:
basic data of key indexes come from all business systems, and after the data are synchronized, according to business requirements, the data are acquired according to different business logic data, processed, modeled by indexes, trained and tested.
(1) Data acquisition
The method comprises the steps of firstly, acquiring data, comprehensively integrating index basic data of a marketing system, a metering automation system, an asset management system, a data quality index monitoring platform 6+1 service system and the like, incrementally acquiring data of an original service system T +1 through ETL data synchronization tool software, and storing the acquired data in a GP database of a data center data operation control platform;
(2) data processing
Secondly, data extraction, namely performing data cleaning, data analysis and data mining on the data of the previous month at a fixed time of 1 point 12 days per month by adopting a scheduling task management and control tool, extracting key data, and storing a key index result base after carrying out data operation; and thirdly, data pushing, namely instantly pushing the key index result set to MySQL data of the field operation toolkit platform through ETL data synchronization tool software.
(3) Index modeling
By using management tools such as team co-creation and questionnaire survey, the system collects the functional requirements of each level of managers and users on 'increasing and carrying', and combines the functions of the requirement planning module: the whole body is divided into a front-end module and a rear-end module. The system comprises a front-end module, a service display layer, a data query module and a data query module, wherein the front-end module is mainly a service display layer and comprises three major parts, namely a basic function, a date query function and a unit query function, and specifically comprises 14 small functions such as index details, monthly ranking, quarterly ranking and annual ranking; the back-end module is mainly divided into a score statistic layer and a basic data layer, wherein the score statistic layer mainly comprises two functions of index score statistics and unit score summary calculation, and the basic data layer mainly comprises two functions of data synchronization and index value statistics. And the following index calculation model formula is completed.
Index 1: medium voltage line failure rate
Medium voltage line fault rate = Σ (number of medium voltage line faults)/Σ (statistical medium voltage line kilometers) × 100 × 12/n, n = number of months from the beginning of the year to the present, statistical current month value n =1;
index 2: distribution network data quality qualification rate
The formula: distribution network data quality qualification rate { [ 0.1+ GIS and production station line consistency (public line) 0.2+ GIS and marketing station line consistency (public line) 0.1+ GIS and marketing station line consistency 0.2+ GIS and marketing user consistency 0.4} 0.6+ low-voltage user belonging area and concentrator belonging area consistency 0.4} + 100%.
Index 3: average power off time of customer
Customer power failure time (medium voltage) = duration of each power failure multiplied by the number of medium voltage customers affected by each power failure;
index 4: recovery rate of electric charge
The recovery rate of the electric charge = the actual electric charge in the statistical period (the current year)/the electric charge to be charged in the current year 100%;
index 5: error rate of electricity charge
The electricity charge error rate = (number of electricity charge error pens in the statistical period/total number of electricity charge bills in the statistical period) 100%;
index 6: loss rate of 10kV or less
A loss line loss rate of 10kV and below = (power supply amount-sales electricity amount)/(power supply amount-lossless electricity amount) × 100%;
index 7: completion rate of line loss exception handling
A line loss abnormality disposal completion rate = [ (number of disposed normal lines/number of abnormal lines) = 0.3+ (number of disposed normal lands/number of abnormal lands) × 0.7] × 100%;
index 8: customer complaint rate
Customer complaint rate = 95598 actual complaint number of the company/total number of the electric power consumers (ten thousands of customers) in the statistical region
Index 9: comprehensive automatic meter reading rate
The comprehensive automatic meter reading rate = [ (the automatic meter reading rate of a specific transformer user × (0.3) + the automatic meter reading rate of a public transformer user × (0.3) + the automatic meter reading rate of a low-voltage user × (0.4) ] × 100%;
index 10: electronic settlement rate
Electronic settlement rate = (number of automatic meter reading settlement users in maintenance range/total number of users in maintenance range) × 100%;
(4) training and validating models
The index verification method comprises the following steps:
(1) Substituting the service parameters into a calculation formula to obtain a calculation result;
(2) Comparing and analyzing the calculation result with the real data to ensure the accuracy of the calculation index value;
the model verification method comprises the following steps:
A. carrying the standard operation data into the trained model to obtain a prediction result;
B. performing inverse normalization compilation on the prediction result to restore the data into an original data type;
C. comparing and analyzing the anti-normalization result with the real data, and calculating the accuracy of the model;
D. and performing service verification aiming at the model accuracy until the model is optimal.
The model test method is as follows:
(1) The index operation data is brought into the trained model to obtain a predicted value;
(2) And performing inverse normalization compilation on the predicted values, converting the data into an original data type, calculating the accuracy of the model by using the inverse normalization data and the true value of the standard operation data, and evaluating the effectiveness of the model.
And 3, performing index calculation and display according to the index calculation formula verified in the step 2:
in the past, the power supply service completion condition of a primary power supply unit is only known by one mu and three thirds of the land, and the invention realizes the full-coverage dynamic ranking management of a primary power supply station of the province, wherein the ranking period is set: carrying out evaluation according to the modes of monthly notification, seasonal statistics and annual assessment on the whole; secondly, setting a ranking level: the whole system is divided into a city bureau level, a county and district bureau level and a power supply station level, and the index score ranking is ranked from high to low according to the three levels; thirdly, displaying the ranking result: and the increasing ratio carry ranking module automatically displays the ranking condition of each level of each power supply station of the province.
Collecting the function requirements of each level of managers and users on 'increasing ratio carry' on increasing ratio carry application, and combining the functions of the requirement planning module: the whole body is divided into a front-end module and a rear-end module. The system comprises a front-end module, a service display layer, a data query module and a data query module, wherein the front-end module is mainly a service display layer and comprises three major parts, namely a basic function, a date query function and a unit query function, and specifically comprises 14 small functions such as index details, monthly ranking, quarterly ranking and annual ranking; the back-end module is mainly divided into a score statistic layer and a basic data layer, wherein the score statistic layer mainly comprises two functions of index score statistics and unit score summary calculation, and the basic data layer mainly comprises two functions of data synchronization and index value statistics. The platform energization is realized, and the service management digitization is driven.
Claims (9)
1. A base power supply station key index and level evaluation increasing ratio carry method is characterized in that: the method comprises the following steps:
step 1, selecting indexes, namely dividing basic units into power supply units with different length ranges according to medium-voltage line management lengths by using a logic tree diagram and an organizational structure model tool, wherein the medium-voltage line length is more than 100km and is a full-service power supply station, the medium-voltage line length is less than or equal to 100km and is a non-full-service power supply station, and collecting core management indexes of the full-service power supply station and core management indexes of the non-full-service power supply station;
step 2, index modeling, index model training and verification are carried out;
and 3, performing index calculation and display according to the index calculation formula verified in the step 2.
2. The proportion-increasing carry method for the key indexes and the level evaluation of the base power supply station as claimed in claim 1, wherein: the core management indexes of the full-service power supply station comprise: medium-voltage line faults, distribution network data quality qualification rate, customer average power failure time, electricity charge recovery rate, electricity charge error rate, 10kV or below damaged line loss rate, line loss abnormity handling completion rate, customer complaint rate, comprehensive automatic meter reading rate and electronic settlement rate.
3. The proportion-increasing carry method for the key indexes and the level evaluation of the base power supply station as claimed in claim 1, wherein: the core management indexes of the non-full service power supply station are 7: the system comprises an electric charge recovery rate, an electric charge error rate, a line loss rate with loss of 10kV or below, a line loss abnormity handling completion rate, a customer complaint rate, a comprehensive automatic meter reading rate and an electronic settlement rate.
4. The proportion-increasing carry method for the key indexes and the level evaluation of the base power supply station as claimed in claim 1, wherein: the index modeling method comprises the following steps:
step 2.1, data acquisition: acquiring and integrating index basic data of a marketing system, a metering automation system, an asset management system and a data quality index monitoring platform 6+1 service system, incrementally acquiring data of an original service system T +1 through an ETL data synchronization tool, and storing the acquired data in a GP database of a data center data operation control platform;
step 2.2, data processing: a scheduling task management and control tool is adopted to perform data cleaning, data analysis and data mining on the previous month data at regular time, refine key data, perform data operation and store a key index result base;
step 2.3, data pushing: the index result set is instantly pushed to MySQL data of a field operation tool kit platform through an ETL data synchronization tool;
2.4, dividing the system into a front-end module and a rear-end module according to the functional requirement of increasing carry; the front-end module is a service display layer and comprises a basic function, a date query function and an entity query function; the back-end module is divided into a score statistical layer and a basic data layer; the score statistic layer comprises index score statistics and unit score summary calculation, and the basic data layer comprises data synchronization and index value statistics; and establishing an index calculation model.
5. The carry-over method for the key index and the level evaluation of the base power supply station according to claim 4, characterized in that: the index calculation formula of the index calculation model comprises:
index 1: medium voltage line failure rate
Medium voltage line fault rate = Σ (number of medium voltage line faults)/Σ (statistical medium voltage line kilometers) × 100 × 12/n, n = number of months from the beginning of the year to the present, statistical current month value n =1;
index 2: distribution network data quality qualification rate
Distribution network data quality qualification rate { [ consistency of GIS and production station line (public line) 0.1+ GIS and production public line variation consistency 0.2+ GIS and marketing station line consistency (public line) 0.1+ GIS and marketing public line variation consistency 0.2+ GIS and marketing user consistency 0.4] } 0.6+ consistency of the station area to which the low-voltage user belongs and the station area to which the concentrator belongs 0.4} 100%;
index 3: average power off time of customer
Customer power failure time (medium voltage) = duration of each power failure multiplied by the number of medium voltage customers affected by each power failure;
index 4: recovery rate of electric charge
The recovery rate of the electric charge = the actual electric charge in the statistical period (the current year)/the electric charge to be charged in the current year 100%;
index 5: error rate of electricity charge
The electricity charge error rate = (number of electricity charge error pens in the statistical period/total number of electricity charge bills in the statistical period) 100%;
index 6: loss rate of 10kV or less
A loss line loss rate of 10kV and below = (power supply amount-sales electricity amount)/(power supply amount-lossless electricity amount) × 100%;
index 7: completion rate of line loss exception handling
A line loss abnormality disposal completion rate = [ (number of disposed normal lines/number of abnormal lines) = 0.3+ (number of disposed normal lands/number of abnormal lands) × 0.7] × 100%;
index 8: customer complaint rate
Customer complaint rate = 95598 actual complaint number of the company/total number of the electric power consumers (ten thousands of customers) in the statistical region
Index 9: comprehensive automatic meter reading rate
The comprehensive automatic meter reading rate = [ (the automatic meter reading rate of a specific transformer user × (0.3) + the automatic meter reading rate of a public transformer user × (0.3) + the automatic meter reading rate of a low-voltage user × (0.4) ] × 100%;
index 10: electronic settlement rate
Electronic settlement rate = (number of automatic meter reading settlement users in maintenance range/total number of users in maintenance range) × 100%.
6. The proportion-increasing carry method for the key indexes and the level evaluation of the base power supply station as claimed in claim 1, wherein: the index model training method comprises the following steps:
(1) Substituting the service parameters into an index model calculation formula to obtain a calculation result;
and comparing and analyzing the calculation result with the real data, and repeatedly correcting the index model formula.
7. The proportion-increasing carry method for the key indexes and the level evaluation of the base power supply station as claimed in claim 1, wherein: the index model verification method comprises the following steps:
the standard operation data is brought into a trained model formula to obtain a prediction result;
performing inverse normalization compilation on the prediction result to restore the data into an original data type;
comparing and analyzing the inverse normalization result and the real data, and calculating the accuracy of the model;
and performing service verification aiming at the model accuracy until the model is optimal.
8. The carry-over method for the key index and the level evaluation of the base power supply station according to claim 7, wherein: the method also comprises an index model test, and comprises the following steps:
bringing the index operation data into the trained model to obtain a predicted value;
(2) And performing inverse normalization compilation on the predicted values, converting the data into an original data type, calculating the accuracy of the model by using the inverse normalization data and the true value of the standard operation data, and evaluating the effectiveness of the model.
9. The base power station key index and level evaluation carry-over method according to claim 1, characterized in that: step 3, the method for calculating and displaying the indexes according to the index calculation formula verified in step 2 comprises the following steps: setting a ranking period, and developing evaluation according to a mode of monthly notification, quarterly statistics and annual assessment; secondly, setting a ranking level: dividing the indexes into a city bureau level, a county and district bureau level and a power supply station level, and ranking according to the index score ranking from high to low after the index is calculated; and finally displaying the ranking result.
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| CN112348701A (en) * | 2020-11-06 | 2021-02-09 | 贵州电网有限责任公司 | Method, device and system for processing power supply station line-to-user data and electronic equipment |
| CN117474395A (en) * | 2023-11-01 | 2024-01-30 | 海南电网有限责任公司 | Monitoring methods and systems for measuring business indicators |
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