Implementation Method of Meter Replacement Management in Urban Rail Transit Energy Management System

Abstract

The present invention discloses a method for implementing meter replacement management in an urban rail transit energy management system in the field of rail transit energy management technology, comprising: obtaining historical operating data of an electric meter with the same statistical type as the faulty electric meter as benchmark data; and updating statistical data related to the faulty electric meter based on the obtained benchmark data and according to set rules. The calculation method of the present invention is concise and reliable. Through the meter replacement management calculation method, it can realize meter replacement time period, meter statistical data gap filling and error data correction, station classification and item statistical data gap filling and error data correction, and line-wide statistical data gap filling and error data correction. The calculation results are accurate and reliable, the scheme is simple to operate, and has the advantages of being comprehensive, efficient, complete, safe, intelligent, and flexible.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit energy management, and in particular relates to a method for implementing meter replacement management in an urban rail transit energy management system. Background Art

[0002] With the continuous expansion of urban rail transit networks and the continued growth in passenger volume, total subway energy consumption has also been rising, making urban rail transit a major energy consumer. Energy consumption for urban rail transit typically accounts for over 30% of direct operating costs. Reducing energy costs and reducing pollution emissions while ensuring safe operation has become a key priority for urban rail transit construction and management organizations, necessitating the implementation of sophisticated, efficient, and intelligent energy management. Energy management systems can process massive amounts of energy consumption data in real time, digitizing and visualizing energy consumption. Based on the specific characteristics and operational data of different urban rail lines, they combine big data, artificial intelligence, and other technologies to provide customized energy-saving control solutions and strategies. This can significantly improve users' energy management capabilities and the energy efficiency of energy-using systems, achieving the green goal of energy conservation and efficiency. In actual use, electricity meters often fail, requiring prompt replacement. The inaccurate statistical data generated by energy management systems due to replacement of faulty meters needs to be addressed. Summary of the Invention

[0003] In order to solve the deficiencies in the prior art, the present invention provides a method for implementing meter replacement management in an urban rail transit energy management system, which has the characteristics of accurate and reliable calculation results and simple scheme operation.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] In a first aspect, a method for implementing meter replacement management in an urban rail transit energy management system is provided, comprising: obtaining historical operating data of an electric meter with the same statistical type as the faulty electric meter as benchmark data; and updating statistical data related to the faulty electric meter according to set rules based on the obtained benchmark data.

[0006] Furthermore, the electric meter having the same statistical type as the faulty electric meter refers to an electric meter having the same electricity consumption details as the faulty electric meter.

[0007] Furthermore, the set rules include:

[0008] a. Divide the electricity meters in the urban rail transit energy management system by category, household, item, sub-item and detailed item;

[0009] b. Statistics of individual electricity meters at stations are classified by item, station number, and meter name, and store the 15-minute timetable base value, 15-minute electricity consumption, hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption;

[0010] c. The station classification and sub-item electricity consumption uses tag_name and is stored in the form of station + classification combination, storing the hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption of the sub-items and sub-items respectively;

[0011] d. Based on steps a to c, determine the basic formula configuration for stations, and the configuration of sub-items and detailed formulas for the entire line;

[0012] e. Utilize correlation analysis to parse out the statistical types related to faulty meters based on the station sub-item and detailed statistical classification, station basic formula configuration, and line-wide sub-item and detailed formula configuration;

[0013] Furthermore, the basic formula configuration of the station includes:

[0014] Station dynamic light = electricity used in the station;

[0015] Electricity consumption of other systems in the station = electricity consumption within the station - electricity consumption of the lighting system - electricity consumption of the ventilation and air conditioning system - electricity consumption of the power system - electricity consumption of equipment - electricity consumption of commercial systems - electricity consumption of property management;

[0016] Electricity consumption of station equipment = electricity consumption within the station - electricity consumption of the lighting system - electricity consumption of the ventilation and air-conditioning system - electricity consumption of the power system - electricity consumption of the commercial system - electricity consumption of the property.

[0017] Furthermore, the full-line sub-items and detailed item formula configurations include:

[0018] The electricity consumption of the entire line by item = the sum of the electricity consumption of each station by item;

[0019] The detailed electricity consumption of the entire line = the sum of the detailed electricity consumption of each station.

[0020] Furthermore, the statistical data related to the faulty electric meter includes the faulty electric meter itself, and station, classification, and sub-item data related to the faulty electric meter.

[0021] Furthermore, the fault types of the faulty electric meter include meter value regression, meter value jump, meter value recovery, meter value non-update and abnormal daily power consumption.

[0022] On the second aspect, a system for implementing meter replacement management in an urban rail transit energy management system is provided, including: a data acquisition module for acquiring historical operating data of meters with the same statistical type as the faulty meter as benchmark data; a data processing module for updating statistical data related to the faulty meter based on the acquired benchmark data and in accordance with set rules.

[0023] Furthermore, the data acquisition module and the data processing module are deployed on the server of the control center; the data acquisition system installed at each station sends the collected data to the server of the control center through the communication network.

[0024] Furthermore, the data acquisition system installed at each station includes a smart electricity meter, a smart water meter, a smart gas meter, a serial port server and a station switch installed at each station.

[0025] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention obtains historical operating data of meters with the same statistical type as the faulty meter as benchmark data; based on the obtained benchmark data, the statistical data related to the faulty meter is updated according to the set rules; the calculation method is concise and reliable, and the meter replacement management calculation method can be used to realize the meter replacement time period, the filling of meter statistical data and the correction of erroneous data, the filling of station classification and item statistical data and the filling of line-wide statistical data and the correction of erroneous data, the calculation results are accurate and reliable, the scheme is simple to operate, and has the advantages of being comprehensive, efficient, complete, safe, intelligent and flexible; the energy consumption data obtained according to the demand analysis and energy plan management and tracking are carried out, thereby providing technical guidance for the optimal economic operation of the equipment, realizing energy conservation and improving energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention provides a flow chart of a method for implementing meter replacement management in an urban rail transit energy management system. DETAILED DESCRIPTION

[0027] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0028] Example 1:

[0029] like Figure 1 As shown, a method for implementing meter replacement management in an urban rail transit energy management system includes: obtaining historical operating data of a meter with the same statistical type as the faulty meter as benchmark data; based on the obtained benchmark data, updating the statistical data related to the faulty meter according to the set rules.

[0030] In this embodiment, the urban rail transit energy management system includes control center-level equipment, backbone network, station-level equipment, and field-level equipment; among them, the control center-level equipment consists of energy management workstations, central control room switches, central equipment room switches, energy management servers, large-screen systems, etc.

[0031] Station-level equipment consists of energy management workstations, station switches, PLCs, serial port servers, etc.; the workstations are used to display the energy management system of the current station.

[0032] Field-level equipment consists of wind system, water system, smart electricity meter, smart water meter, integrated measurement and control device, etc.

[0033] The control center includes a server and a workstation; the server is used to collect, store, and calculate the meter data sent from each station, and the workstation and large-screen display system are used to display the energy management system interface; the station switches, PLCs, and serial port servers of each station are used to collect meter data from various systems at the field level and transmit the data to the center. The collection system includes electricity meters, water meters, gas meters, serial port servers, and station switches; the communication network connects the collection systems of each station and the control center, and is used to transmit the collected real-time data.

[0034] This embodiment utilizes the above-mentioned system to implement missing and incorrect data correction for electricity meter statistics, missing and incorrect data correction for station-level, sub-item, and detailed statistical data, and missing and incorrect data correction for line-wide statistics during the meter replacement period. This embodiment first categorizes the devices in the above-mentioned system to facilitate meter replacement management.

[0035] Classification method for household-based and item-based electricity meters in urban rail transit energy management system.

[0036] Classification: According to the type of energy consumed, it is divided into electricity consumption, water consumption, etc.

[0037] Household division: Electricity consumption is divided into households according to different energy consumption entities, such as stations, vehicle depots, parking lots, control centers and main depots. Mainline traction electricity consumption is regarded as a virtual large household, and yard traction electricity consumption is included in the yard's dynamic lighting electricity consumption.

[0038] Sub-item ①. The electricity consumption of stations and control centers is divided into: ventilation and air-conditioning electricity, power electricity, equipment electricity, lighting electricity, commercial electricity, and property electricity.

[0039] Sub-item ②. The electricity consumption items of the yard and section are divided into: ventilation and air-conditioning electricity, power electricity, equipment electricity, lighting electricity, commercial electricity, property electricity, and yard and section traction electricity.

[0040] Sub-item ③. The main station’s electricity consumption is divided into: electricity consumption within the station, electricity consumption of lines, and electricity consumption of other lines.

[0041] Sub-items: The electricity consumption sub-items are divided into detailed electricity consumption items, such as ventilation and air conditioning are further divided into: ventilation (first and second level loads of ventilation and air conditioning electrical control cabinets), ventilation (interval jet fans), refrigeration (third level loads of ventilation and air conditioning electrical control cabinets), refrigeration (chillers), refrigeration (multi-split outdoor units).

[0042] (1) Table 1 shows a classification method for electric meter classification and sub-items in an urban rail transit energy management system (for the purpose of illustrating the algorithm only);

[0043] Table 1

[0044] Electricity consumption subcategory number Electricity consumption category Electricity consumption category number Electricity Classification 100 Traction electricity -- -- -- -- 101 traction 200 Lighting electricity -- -- 300 Electricity for ventilation and air conditioning -- -- -- -- 301 Ventilation (first and second level loads of ventilation and air conditioning electric control cabinet) -- -- 302 Ventilation (interval jet fan) -- -- 303 Refrigeration (ventilation and air conditioning electrical control cabinet level 3 load) -- -- 304 Refrigeration (chiller) -- -- 305 Refrigeration (multi-split outdoor unit) 400 Power electricity -- -- 500 Equipment power consumption-original -- -- 600 Commercial electricity -- -- 700 Environmental control cabinet BAS -- -- 800 Property electricity -- -- 900 Station electricity -- -- 995 Animation photos -- -- 999 Total power consumption of the line -- -- -- -- 1200 other

[0045] (2) Intelligent alarm for meter failure

[0046] Alarms are issued for various fault conditions of the electricity meter: meter value regression, meter value jump, meter value recovery, meter value not updating, abnormal daily power consumption; based on the above abnormal conditions, owners are promptly notified to check and replace the abnormal meter.

[0047] The energy management system monitors all meter data in real time on the central server.

[0048] If the meter value regresses, the system will display a prominent alarm in real time: the meter reading is abnormal, the current value (how much) is less than the previous value (how much).

[0049] If the meter value jumps, the system will display a prominent alarm in real time: the meter reading is abnormal, the current value (how much) increases (how much) compared to the previous value.

[0050] If the meter value is restored, the system will display a prominent alarm in real time: the meter reading (value) has been restored and updated, and how many days have passed since the last update.

[0051] If the meter value is not updated, the system will display a prominent alarm in real time: the meter reading (value) has not been updated for more than a certain number of days.

[0052] Daily scheduled monitoring of daily electricity consumption: If the daily electricity consumption is abnormal, the system will display a prominent alarm in real time: the daily increase (value) of the meter's electricity consumption exceeds the set threshold (value).

[0053] Administrators can select the meter that has issued an alarm based on the meter's intelligent alarm information and replace the faulty meter in a targeted manner.

[0054] (3) Statistical function of a single meter at a station

[0055] Statistics of individual electricity meters at stations are classified by electricity consumption item (category), station number, and meter name (tag_name), storing the 15-minute timetable base value, 15-minute electricity consumption, hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption.

[0056] The data is collected by the smart meters installed at each station and transmitted to the energy management system control center server through the network. The server stores the 15-minute meter bottom value of the meter; the 15-minute power consumption is stored using Ehi_x (key), where hi represents the 15th minute of the hour, hi represents (0, 2, 3, ... 23), x represents (0, 15, 30, 45), and key = meter_name + location_id + cabetory_id represents the meter name. At the same time, the hourly power consumption E is stored. hi(key) , i represents the hour (0-23); daily electricity consumption E di(key) , i represents the day (0-31); monthly electricity consumption E mi(key) , i represents month (1-12); annual electricity consumption E yi(key) , i represents a year;

[0057] in:

[0058]

[0059]

[0060]

[0061]

[0062] (4) Statistical functions for station sub-items and electricity consumption details

[0063] The station's classified and itemized electricity consumption is stored using the tag_name in the form of a station + classification combination (such as 1.101, 1.201...), storing the hourly, daily, monthly, and annual electricity consumption of the item and sub-item respectively. The hourly electricity consumption is taken from the hourly values of all meters for the corresponding sub-item of the station, the daily electricity consumption is taken from the 24-hour sum of the classified and sub-item sub-items, the monthly electricity consumption is taken from the daily sum of the classified and sub-item sub-items, and the annual electricity consumption is taken from the monthly sum of the corresponding classified and sub-item sub-items.

[0064] The naming rules of station sub-items and sub-items are stored in the form of key = location_id + category; the hourly electricity consumption Ehi is the sum of the hourly electricity consumption of the same sub-item of the station within the hour, and the meter data is taken from the electricity consumption of the same sub-item of the same station in (2); the daily electricity consumption E di 、Monthly electricity consumption E mi , annual electricity consumption E yi ; The electricity consumption of each item = the sum of the electricity consumption of each item;

[0065] E hi(location_id+category) =∑E h_i(meter_name+location_id+category_id) (5)

[0066]

[0067]

[0068]

[0069] (5) Station and line-wide formula configuration and statistical functions

[0070] The basic configuration of the station is mainly divided into:

[0071] Station power supply = electricity consumption within the station, i.e.:

[0072] E li .995 = E li .900 (9)

[0073] Electricity consumption of other systems in the station = electricity consumption within the station - electricity consumption of the lighting system - electricity consumption of the ventilation and air conditioning system - electricity consumption of the power system - electricity consumption of equipment - electricity consumption of commercial systems - electricity consumption of property management, that is:

[0074] E li .1200=E li .900-E li .200-E li .300-E li .400-E li .500-E li .600-E li .800 (10)

[0075] Station equipment electricity consumption = station electricity consumption - lighting system electricity consumption - ventilation and air conditioning system electricity consumption - power electricity consumption - commercial system electricity consumption - property electricity consumption, that is:

[0076] E li .1200=E li .900-E li .200-E li .300-E li .400-E li .600-E li .800 (11)

[0077] The full-line formula configuration is mainly divided into sub-item and detailed formula configuration:

[0078] The electricity consumption of the entire line by item = the sum of the electricity consumption of each station by item, that is:

[0079]

[0080]

[0081] …

[0082]

[0083] The detailed electricity consumption of the entire line = the sum of the detailed electricity consumption of each station, that is;

[0084]

[0085]

[0086]

[0087] …

[0088]

[0089] (6) According to steps (4) and (5), the statistical types related to the replaced electric meter sub-category are parsed.

[0090] Based on correlation analysis, find out the statistical categories that need to be filled and the erroneous data corrected.

[0091] For example, if the meter with location_id 6, category_id 301, and meter name "xmhcz.P105-10" is replaced, correlation analysis can be used to identify the statistical categories that need to be filled and the incorrect data corrected: the direct and indirect classification statistics with 301 are: {direct_correlation_[6.301(999.301)], indirect_correlation_[6.300(6.1200 6.1700 999.300 999.1200 999.1700)]}.

[0092] (7) Calculation of statistical values of categories and items during the table change period

[0093] Taking the incoming line "xmhcz.P105-10" of station No. 6 of a certain line as an example, the meter alarm fault was found at 20210910 10:20:30 [start_time], and the human-machine interface displayed "The meter value is not updated. The meter reading (325590) has not been updated for more than 10 days" and the meter needs to be replaced; the meter was manually confirmed to be damaged and replaced. The meter was restored at 20210920 12:00:00 [end_time], and the reading was 21222 when it was restored. The electricity consumption for nearly 10 days could not be measured, resulting in errors in the meter data statistics and itemized statistical data involving the meter, and the erroneous data needs to be corrected; the location_id of this meter is 6, the category_id is 301; the ten-day average value of this meter is E 平均10 =200.

[0094] ① Decompose [start_time, end_time] into hours (T1, T2, T3...T n ).

[0095] ② From the data stored in the database, find the data that matches (T1, T2, T3...T n ) corresponds to the statistical value E of (6.301) ti_old =[(E t1_old, E t2_old, E t3_old ,.....E t4_old )].

[0096] ③Calculate the hourly electricity consumption of the meter from the average electricity consumption over 10 days, E 平均 =E 平均10 / twenty four.

[0097] ④Calculate the value of (T1, T2, T3...T n ) corresponds to the hour difference [E d_value(t1), E d_value(t2), E d_value(t3) ...E d_value(tn) ], where E d_value(ti) =E 平均 -E ti_old , the difference is the value that needs to be filled and the error data correction value.

[0098] ⑤Calculate the new (T1, T2, T3...T n ) corresponds to the new statistical value E of (location_id+category_id)(6.301) ti_new =[(E t1_old, E t2_old, E t3_old ,.....E t4_old )],E t1_old E ti_new =E d_value(ti) +E ti_old .

[0099] ⑥E ti_new Update the corresponding storage columns according to the time series (T1, T2, T3...Tn).

[0100] ⑦ Execute steps ②③④⑤⑥ to calculate the statistical value sequence corresponding to (999.301) directly corresponding to (6.301) in step ⑥ and update it to the corresponding storage column; similarly, follow steps ②③④⑤⑥ to calculate the statistical value sequence corresponding to (6.300,999.300) indirectly corresponding to (6.301) in step ⑥ and update it to the corresponding storage column.

[0101] ⑧ In particular, for the indirect corresponding [6.1200 6.1700 999.1200 999.1700] in step ⑥, use E when calculating step ⑤. ti_new =[(E t1_old, E t2_old, E t3_old,..... E t4_old )],E t1_old E ti_new =E ti_old -E d_value(ti) , the rest of steps ②③④⑥ are the same.

[0102] ⑨Decompose [start_time, end_time] into day j =[day j ,day j+1 ,day j+3 ...day j+n ].

[0103] According to day j Sequence, use the following formula (19) to calculate the daily power statistics of the direct and indirect related types [6.301, 999.301, 6.300, 6.1200, 6.1700, 999.300, 999.1200, 999.1700] in step ⑥ and update them to the corresponding storage sequence,

[0104]

[0105] Similarly, decompose [start_time, end_time] into months, Month j =[month j ,month i+j ,month j+3 ... month j+n ], use the following formula (20) to calculate the monthly electricity statistics of the direct and indirect related types [6.301, 999.301, 6.300, 6.1200, 6.1700, 999.300, 999.1200, 999.1700] in step ⑥ and update them to the corresponding storage sequence,

[0106]

[0107] Similarly, decompose [start_time, end_time] into years, year j =[month j ,month j+1 ,month j+3 ... monthj+n ], use the following formula (21) to calculate the monthly electricity statistics of the direct and indirect related types [6.301, 999.301, 6.300, 6.1200, 6.1700, 999.300, 999.1200, 999.1700] in step ⑥ and update them to the corresponding storage sequence,

[0108]

[0109] ⑩Statistical calculation for a single meter

[0110] According to steps ① and ③, E 平均 =E / 24, respectively updated to (T1, T2, T3...T n ) can be stored in the sequence;

[0111] Decompose [start_time, end_time] into day i =[day i ,day i+1 ,day i+3 ...day i+n ] Use the following formula (22) to calculate the daily statistics and update them to the corresponding daily storage sequence.

[0112]

[0113] Similarly, decompose [start_time, end_time] into months, Month j =[month j ,month j+1 ,month j+3 ...month j+n ], use the following formula (23) to calculate the monthly statistics and update them to the corresponding monthly storage sequence,

[0114]

[0115] Similarly, decompose [start_time, end_time] into years,

[0116] year j =[year j ,year j+1 ,year j+3 ...year j+n ], use the following formula (24) to calculate the annual statistics and update them to the corresponding annual storage sequence,

[0117]

[0118] At this point, by executing steps ①②③④⑤⑥⑦⑧⑨⑩, the meter replacement management function is completed, and the meter replacement time period, meter statistical data gap filling and error data correction, station classification and item statistical data gap filling and error data correction, and line-wide statistical data gap filling and error data correction are realized.

[0119] This embodiment obtains historical operating data of meters with the same statistical type as the faulty meter as benchmark data; based on the obtained benchmark data, the statistical data related to the faulty meter is updated according to the set rules; the calculation method is concise and reliable, and the meter replacement management calculation method can be used to realize the meter replacement time period, the filling of meter statistical data and the correction of erroneous data, the filling of station classification and item statistical data and the filling of line-wide statistical data and the correction of erroneous data, and the calculation results are accurate and reliable. The solution is simple to operate and has the advantages of being comprehensive, efficient, complete, safe, intelligent and flexible; the energy consumption data obtained according to the demand analysis is used, and energy plan management and tracking are carried out, thereby providing technical guidance for the optimal economic operation of the equipment, achieving energy conservation and improving energy utilization efficiency.

[0120] Example 2:

[0121] Based on the implementation method of meter replacement management in an urban rail transit energy management system described in Example 1, this embodiment provides an implementation system for meter replacement management in an urban rail transit energy management system, including: a data acquisition module, used to obtain historical operating data of meters with the same statistical type as the faulty meter as benchmark data; a data processing module, used to update statistical data related to the faulty meter based on the acquired benchmark data and according to set rules.

[0122] The data acquisition module and data processing module are deployed on the server of the control center; the data acquisition system installed in each station sends the collected data to the server of the control center through the communication network.

[0123] The data collection system installed at each station includes smart electricity meters, smart water meters, smart gas meters, serial port servers and station switches.

[0124] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for implementing meter replacement management in an urban rail transit energy management system, characterized in that: include: Obtain historical operating data of an electric meter with the same statistical type as the faulty electric meter as the benchmark data; Based on the acquired baseline data and in accordance with the set rules, the statistical data related to the faulty electricity meter is updated; The electric meter with the same statistical type as the faulty electric meter refers to an electric meter with the same electricity consumption details as the faulty electric meter; The statistical types of electricity meters are obtained by classifying, dividing electricity meters in the urban rail transit energy management system by household and item: First, it is divided into several categories based on the type of energy consumed, including electricity and water; Each category is divided into several sub-households according to different energy consumption entities, including stations, vehicle depots, parking lots, control centers and main stations; Different households are divided into items, and each item has a sub-item of electricity consumption, including ventilation and air conditioning electricity, power electricity, equipment electricity, lighting electricity, commercial electricity and property electricity; The small items of electricity consumption are divided into detailed items of electricity consumption; Among them, a faulty meter refers to an electric meter that issues an alarm for meter value regression, meter value jump, meter value recovery, meter value non-update and / or abnormal daily power consumption; The set rules include: a. Divide the electricity meters in the urban rail transit energy management system by category, household, item, sub-item and detailed item; b. Statistics of individual electricity meters at stations are classified by item, station number, and meter name, and store the 15-minute timetable base value, 15-minute electricity consumption, hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption; c. The station classification and sub-item electricity consumption uses tag_name and is stored in the form of station + classification combination, storing the hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption of the sub-items and sub-items respectively; d. Based on steps a to c, determine the basic formula configuration for stations, and the configuration of sub-items and detailed formulas for the entire line; e. Utilize correlation analysis to parse out the statistical types related to faulty meters based on the station sub-item and detailed statistical classification, station basic formula configuration, and line-wide sub-item and detailed formula configuration.

2. The method for implementing meter replacement management in an urban rail transit energy management system according to claim 1, characterized in that: The basic formula configuration of the station includes: Station dynamic photo = electricity consumption within the station; Electricity consumption of other systems in the station = electricity consumption within the station - electricity consumption of the lighting system - electricity consumption of the ventilation and air-conditioning system - electricity consumption of the power system - electricity consumption of equipment - electricity consumption of commercial systems - electricity consumption of property management; Electricity consumption of station equipment = electricity consumption within the station - electricity consumption of the lighting system - electricity consumption of the ventilation and air-conditioning system - electricity consumption of the power system - electricity consumption of the commercial system - electricity consumption of the property.

3. The method for implementing meter replacement management in an urban rail transit energy management system according to claim 1, characterized in that: The full-line sub-items and detailed item formula configurations include: The electricity consumption of the entire line is the sum of the electricity consumption of each station; The detailed electricity consumption of the entire line = the sum of the detailed electricity consumption of each station.

4. The method for implementing meter replacement management in an urban rail transit energy management system according to claim 1, characterized in that: The statistical data related to the faulty electric meter include the faulty electric meter itself, and the station, classification, and sub-item data related to the faulty electric meter.

5. The method for implementing meter replacement management in an urban rail transit energy management system according to claim 1, characterized in that: The fault types of the faulty electric meter include meter value regression, meter value jump, meter value recovery, meter value non-update and abnormal daily power consumption.

6. A system for implementing meter replacement management in an urban rail transit energy management system, characterized in that: include: A data acquisition module, used to acquire historical operating data of an electric meter of the same statistical type as the faulty electric meter as benchmark data; A data processing module is used to update statistical data related to the faulty electric meter based on the acquired baseline data and in accordance with set rules; The electric meter with the same statistical type as the faulty electric meter refers to an electric meter with the same electricity consumption details as the faulty electric meter; The statistical types of electricity meters are obtained by classifying, dividing electricity meters in the urban rail transit energy management system by household and item: First, it is divided into several categories based on the type of energy consumed, including electricity and water; Each category is divided into several sub-households according to different energy consumption entities, including stations, vehicle depots, parking lots, control centers and main stations; Different households are divided into items, and each item has a sub-item of electricity consumption, including ventilation and air conditioning electricity, power electricity, equipment electricity, lighting electricity, commercial electricity and property electricity; The small items of electricity consumption are divided into detailed items of electricity consumption; Among them, a faulty meter refers to an electric meter that issues an alarm for meter value regression, meter value jump, meter value recovery, meter value non-update and / or abnormal daily power consumption; The set rules include: a. Divide the electricity meters in the urban rail transit energy management system by category, household, item, sub-item and detailed item; b. Statistics of individual electricity meters at stations are classified by item, station number, and meter name, and store the 15-minute timetable base value, 15-minute electricity consumption, hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption; c. The station classification and sub-item electricity consumption uses tag_name and is stored in the form of station + classification combination, storing the hourly electricity consumption, daily electricity consumption, monthly electricity consumption, and annual electricity consumption of the sub-items and sub-items respectively; d. Based on steps a to c, determine the basic formula configuration for stations, and the configuration of sub-items and detailed formulas for the entire line; e. Utilize correlation analysis to parse out the statistical types related to faulty meters based on the station sub-item and detailed statistical classification, station basic formula configuration, and line-wide sub-item and detailed formula configuration.

7. The system for implementing meter replacement management in the urban rail transit energy management system according to claim 6, characterized in that: The data acquisition module and the data processing module are deployed on the server of the control center; the data acquisition system installed in each station sends the collected data to the server of the control center through the communication network.

8. The system for implementing meter replacement management in the urban rail transit energy management system according to claim 7, characterized in that: The data acquisition system installed at each station includes a smart electricity meter, a smart water meter, a smart gas meter, a serial port server and a station switch installed at each station.

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