Urban building energy consumption monitoring system based on intelligent electric meter

Abstract

The invention discloses an urban building energy consumption monitoring system based on an intelligent electric meter, relates to the technical field of energy consumption monitoring, and solves the problem that the energy consumption condition between buildings is difficult to monitor and know in real time. Reactive power of users in different buildings is standardized, so that the different buildings can compare respective energy consumption conditions, energy consumption differences among the different buildings can be displayed more intuitively, an automatic processing flow is provided to feed back abnormal reactive power conditions to workers in time, and the working efficiency is improved. Meanwhile, the abnormally consumed reactive power in the self-adaptive compensation circuit of the reactive power compensation device is allocated, so that a user and a worker can conveniently know the specific power utilization condition; and improvement measures are formulated by comparing power utilization differences of different buildings, so that the power utilization energy efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy consumption monitoring, and in particular, relates to an urban building energy consumption monitoring system based on smart electric meters. Background Art

[0002] With the rapid development of science and technology and the continuous advancement of urbanization, the energy consumption problem of urban buildings has become increasingly prominent. As a major component of urban energy consumption, the efficient energy management of buildings is not only related to the sustainable use of energy, but also directly affects the green development of the city and the quality of life of residents. Traditional building energy consumption monitoring methods have problems such as low monitoring accuracy, data lag, and low degree of automation, which are difficult to meet the needs of modern cities for energy conservation and emission reduction.

[0003] The popularization of smart meters provides a new technical means for monitoring building energy consumption. Smart meters can collect users' electricity consumption data in real time and transmit the data to the central server through the communication network. This provides a data basis for realizing refined management of building energy consumption. Urban building energy consumption monitoring systems based on smart meters have emerged. The present invention proposes an urban building energy consumption monitoring system based on smart meters, which aims to obtain users' electricity consumption data in real time through the monitoring capabilities of smart meters, analyze and calculate users' active and reactive electricity consumption data to find out abnormal reactive power, and dynamically adjust the switching of capacitor groups according to abnormal needs to achieve precise compensation. At the same time, the scale differences between buildings are eliminated through standardized processing, so that the energy efficiency levels of different buildings can be objectively compared, and targeted energy efficiency improvement plans can be formulated. Summary of the invention

[0004] The purpose of the present invention is to provide an urban building energy consumption monitoring system based on smart meters. By real-time monitoring of the active power data of the total electricity users in the building, abnormal power consumption can be discovered in time, and abnormal situations can be promptly notified to staff and users through communication with the central server to reduce losses caused by failures. At the same time, by quantitatively comparing the reactive power between buildings, the energy efficiency of different buildings can be effectively monitored. By taking buildings with excellent energy efficiency as benchmark buildings and adopting the management method of promoting benchmark buildings, the energy efficiency of electricity consumption in various buildings in the city can be effectively improved.

[0005] The purpose of the present invention can be achieved through the following technical solutions: The urban building energy consumption monitoring system based on smart meters includes: Smart meters collect users’ energy consumption data, including active power, reactive power, reactive power, voltage, and frequency. The database module receives and stores the energy consumption data processed by the central server; User terminal module, through which users can view energy consumption reports and energy consumption warning reminders sent by the central server, and through which users can set power consumption warning lines; The central server coordinates the communication and data transmission of each module, monitors the abnormal active power consumption of users, promptly notifies the staff of abnormal circuit energy consumption, analyzes the reactive power, deploys reactive compensation devices to compensate for the abnormal reactive power consumption in the circuit, calculates and analyzes the standardized scores of unit users and the differences in energy efficiency management measures between different buildings, and formulates improvement measures; Reactive power compensation device, combined with built-in capacitor bank, connected to the circuit to balance abnormal reactive power.

[0006] As a further solution of the present invention, the smart meter uploads the collected energy consumption data to the central server via a wireless network, and the central server processes the data into a form that can be stored by a database module, which then stores the energy consumption data persistently.

[0007] As a further solution of the present invention, the method for the central server to monitor abnormal active power consumption of the user comprises the following steps: A periodic time period t is preset to monitor a set of continuous active power consumption of any user in a city building within the time period t; Divide the time period t into b time periods evenly, expressed as , , ..., ;in is any time period in the b time periods, c is a positive integer counting index, starting from 1, with a maximum value of b. The active power corresponding to each of the b time periods is averaged and recorded as: , , ..., , sort the averaged active power from small to large, and get the sorted result: , , ..., ; Take the first quartile and record it as , and then take the third quartile and record it as , calculate the interquartile range IQR according to the formula: Set the minimum threshold of active power to , calculated according to the formula: Set the maximum threshold of active power as , calculated according to the formula: If the user's active power consumption in any of the b time periods exceeds the preset or less than All of them will be regarded as abnormal energy consumption status; Users can set their own energy consumption warning line, that is, and , the threshold set by yourself must be within the threshold range calculated by the quartile method. When the user's active power exceeds the threshold range, the current power consumption state is regarded as an abnormal energy consumption state; The central server obtains abnormal energy consumption status, generates energy consumption warning reminders to notify users and staff, and generates energy consumption reports for users to refer to.

[0008] As a further solution of the present invention, the method for the central server to analyze reactive power is: In the time period t, if the reactive power of the current building does not exceed the reactive power threshold, it indicates that the circuit of the current building is working well, and a normal energy consumption reminder is generated; If the reactive power of the current building exceeds the reactive power threshold, it indicates that the current building has abnormal energy consumption, and the current power consumption state is regarded as an abnormal energy consumption state, and an energy consumption warning reminder is generated; The generated normal energy consumption reminder and energy consumption warning reminder of the current building are transmitted to the staff.

[0009] As a further solution of the present invention, the method for analyzing reactive power further includes the following steps: Obtain the reactive power of the user in time period t; The reactive power of all users in the entire building in time period t is summarized to obtain the total reactive power I of the corresponding building; If the total reactive power I of the corresponding building in time period t is greater than the preset total reactive power threshold , the total reactive power of the current building is considered abnormal.

[0010] As a further solution of the present invention, the central server promptly notifies the staff of the abnormal energy consumption of the circuit, and at the same time deploys the reactive power compensation device to compensate for the abnormal reactive power consumption in the circuit.

[0011] As a further solution of the present invention, the reactive power compensation device compensates for the abnormal reactive power consumption in the circuit by: Obtain the reactive power of all users in the current building within time period t, and obtain the total reactive power P of the entire building by summing up; Get the voltage of the current building users and average it to get the building average voltage V. Get the frequency of the AC power used by the current building users and average it to get the building average frequency f. Combine the total reactive power P and the target reactive power Calculate the required reactive power compensation capacity , according to the formula: Determine the required reactive power compensation capacity After that, adjust the appropriate capacitor bank to compensate for the required reactive power compensation capacity. ; The capacitor groups in the reactive power compensation device are sorted in ascending order, and the sorting result is recorded as: , ,..., , where o represents the total number of capacitor groups, The largest capacitor group is selected and the sorted capacitor groups are stored in the database module; When a capacitor bank is needed, first check whether the database module has stored the data related to the reactive power compensation capacity. Capacitor banks of the same capacity , x is a counting index starting from 1, the maximum value is o, if it exists = , then the capacitor group put into use; If there is no reactive power compensation capacity For capacitor banks with the same capacity, the first reactive power compensation capacity is obtained backwards. Large capacitor bank , the capacitor group Put into use, where y is a counting index starting from 1 and the maximum value is o; If there is no reactive power compensation capacity greater than the current If there is a large capacitor group, take the largest capacitor group first. , then from Start to use, continue to acquire capacitors and accumulate until the accumulated result reaches the reactive power compensation capacity .

[0012] As a further solution of the present invention, the central server calculates and analyzes the standardized scores of unit users and the differences in energy efficiency management measures between different buildings, and formulates improvement measures as follows: Obtain the reactive power of all users in any building within a preset time period T1 and accumulate it, then divide the accumulated result by the total number of users in the current building to obtain the reactive power per user in the current building; Get the reactive power of unit users in different buildings at the same time and in the same preset time period T1, recorded as , where K represents the number of buildings, and the average reactive power per user is obtained by averaging the reactive power of users in all buildings. ; Calculate the standardized score of a unit user according to the formula : in, is the standard deviation of reactive power of all building unit users; A low unit user standardization score indicates that the reactive power of the unit user in the current building is low, and the energy efficiency management of the current building is relatively good; conversely, a high unit user standardization score indicates that the energy efficiency management of the current building is relatively poor; The building with the lowest unit user standardization score is taken as the benchmark building. The differences in energy efficiency management measures between the benchmark building and other buildings are analyzed, and improvement measures are formulated.

[0013] As a further solution of the present invention, the formulation of the improvement measures also includes the following steps: Normalize the score by unit user And the corresponding building unit area lamp power And the proportion of energy-saving lamps in the corresponding buildings There is a linear relationship, and a multiple linear regression model is established: in, is the intercept term, representing the initial value coefficient, and They are the lamp power per unit area of ​​the corresponding buildings The coefficient and the proportion of energy-saving lamps in the corresponding building The coefficient of is the error term, indicating the error value; Combined with the multivariate linear regression model, the standardized score of the user unit that achieves the set target in the corresponding building is calculated The proportion of energy-saving lamps , the calculation formula is: in, , and All are coefficients, which are considered as known values, combined with the unit area lamp power of the corresponding building. , Standardized score of target unit users , calculate the proportion of energy-saving lamps in the corresponding building when the target unit user standardized score is achieved ; If there is a proportion of energy-saving lamps in any building The value is lower than the normalized score of the unit user that meets the set target in the current building The proportion of energy-saving lamps calculated at , it means that the proportion of energy-saving lamps in the current building does not meet the preset standard; Existing lamps need to be replaced to increase the proportion of energy-saving lamps in the current building until the corresponding building = .

[0014] Beneficial effects of the present invention: The present invention monitors the active power of users in urban buildings in real time and sets a safety threshold for the active power, so as to timely discover abnormal energy consumption and timely remind users and staff in both directions, thereby helping staff to timely discover abnormal energy consumption and prevent energy waste. By real-time monitoring of the reactive power status, the reactive power situation of the entire building can be accurately grasped. When the reactive power is abnormal, timely compensation measures can be taken to reduce energy loss during transmission and distribution, which can also help maintain the stable operation of the power grid and reduce power failures caused by abnormal reactive power. Automated process processing reduces the need for manual intervention and can achieve intelligent management of abnormal energy consumption in buildings. By standardizing the reactive power per unit user between buildings, the standardized score per unit user is obtained. , so that the total reactive power between different buildings is comparable, by standardizing the scores of unit users in different buildings By making comparisons, we can identify buildings with poor and excellent energy efficiency management. By learning from and adopting the management measures of excellent buildings to poorer buildings, we can promote the improvement of overall energy efficiency and promote sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a structural diagram of the urban building energy consumption monitoring system based on smart meters of the present invention; Figure 2 This is a flow chart of calculating the standardized score of a unit user in embodiment 3 of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example 1 Urban building energy consumption monitoring system based on smart meters, such as Figure 1 As shown, the system includes: Smart meters are installed in every household in urban buildings to ensure full coverage and to collect and upload the energy consumption data of every electricity user in real time. The collected energy consumption data includes active power, reactive power, reactive power, voltage, and frequency; The database module receives the user energy consumption data processed by the central server: active power, reactive power, reactive power, voltage, frequency, and the information of the corresponding home user, and stores it as a record; User terminal module: a module that interacts with users. Electricity users can view their own electricity consumption and energy consumption reports through mobile devices, and receive energy consumption warning reminders. Users can set the energy consumption warning line for household electricity through the user terminal module. When the energy consumption of household electricity exceeds the energy consumption warning line, the user will be reminded. It should be noted that the energy consumption warning line is not set arbitrarily, but needs to be within a certain safety threshold. The central server coordinates and processes the communication and data transmission between the modules, analyzes and preprocesses the energy consumption data, stores the preprocessed energy consumption data in the database module, displays the generated energy consumption report and energy consumption warning reminder to the user terminal module, and promptly notifies the staff of abnormal energy consumption; If there is abnormal reactive power consumption in the current building's circuit, the reactive power compensation device will be automatically deployed to compensate for the abnormal reactive power consumption in the circuit to ensure the stability of the power supply line; The reactive power compensation device connects the appropriate capacitor group into the circuit after calculation and combination, quickly responds to abnormal reactive power consumption and ensures stable operation of the power grid.

[0019] Example 2 This embodiment discloses a method for abnormal monitoring of active power consumption of a user, which is specifically as follows: Active power is the part of electric energy that is effectively utilized. In household electricity consumption, the electricity bill is usually calculated according to the active power consumed. Therefore, analyzing the active power can help us understand the specific electricity consumption of the household. When abnormal active power consumption occurs, the problem can be discovered in time by monitoring the active power. First, the active power recorded by the smart meter of any user in the city building within the periodic preset time period t is obtained. The active power is not a single value, but a continuous set of values; Then the preset time period t is subdivided into b small time periods, and the time of each small time period in these b time periods is the same. These b time periods are expressed as: , ,..., , is any time period, c is a positive integer counting index, starting from 1, and the maximum value does not exceed b; The active power corresponding to each of the b time periods is obtained. The active power in each small time period should also be a set of continuous values. The active power in each time period is averaged and the averaged active power is recorded in chronological order as: , ,..., , and then sort the averaged active power from small to large, recorded as: , ,..., ; Take the first quartile of the sorted results , and The value at , and then take the third quartile , and The value at , calculate the interquartile range IQR: ; set up , as the minimum threshold of active power, is calculated according to the formula: set up , as the highest threshold of active power, is calculated according to the formula: If the active power in any of the b time periods exceeds the preset maximum threshold or below the minimum threshold All of them will be regarded as abnormal energy consumption status; When abnormal energy consumption occurs in a user's electricity consumption, the central server will first send an energy consumption warning to the staff. The central server will then upload the user's electricity consumption data to the user terminal module for the user to review and understand his or her own electricity consumption.

[0020] Exemplarily, the electricity consumption of user A within 24 hours a day is monitored, and the 24 hours are evenly divided into 24 small time periods, each of which is 1 hour.

[0021] The active power consumption of each hour is obtained from the smart meter, and then the minimum and maximum thresholds of the active power consumption are calculated through the specific active power consumption values ​​(this value can be obtained through historical data, and the thresholds for each household should be different). For example, the calculated minimum threshold is 0.5 kWh and the maximum threshold is 3.5 kWh. Check whether the average active power consumption in each time period exceeds the maximum or minimum threshold. It is found that the average active power consumption in the time period from 23:00 to 24:00 is 5 kWh, which exceeds the maximum threshold of 3.5 kWh. Then the power consumption corresponding to this time period is regarded as an abnormal energy consumption state. After the central server detects the abnormal energy consumption, it will immediately send an energy consumption warning to remind the staff, informing user A that the power consumption in the time period from 23:00 to 24:00 is abnormal. At the same time, the power consumption of user A is uploaded to the user terminal module. Users can view detailed power consumption data and abnormal prompts through mobile phone APP or computer web pages, so as to timely understand and adjust their power consumption behavior and avoid unnecessary energy waste.

[0022] Example 3 This embodiment discloses a method for selecting benchmark buildings by comparing the standardized unit user scores of different buildings. Figure 2 As shown, the specific steps include: Within the preset time T1, the reactive power of each user in the current building is recorded through the smart meter, and the reactive power of each user is accumulated and summed to obtain the total reactive power of the entire building. Then, the number of users in the entire building is counted, and the total reactive power of the entire building is divided by the total number of users in the entire building to obtain the reactive power per user. For other buildings, the reactive power per user of each building is obtained in the same way, and the reactive power per user of each building is recorded as: , where K represents the total number of buildings. The total reactive power of all buildings in the corresponding city is accumulated and then divided by the total number of all users in the corresponding city to obtain the average reactive power per user, recorded as ; In order to eliminate the scale differences between buildings, it is necessary to standardize the reactive power per user of each building so that the reactive power per user of different buildings can be compared on a common scale. The calculation formula is as follows: in, is the standard deviation of the reactive power per user in all buildings, which is used to measure the discreteness of a group of reactive power values ​​per user. The calculation formula is as follows: Normalized score of unit users in the entire building The lower the score, the lower the reactive power per unit user in the current building, which means the energy efficiency management of the current building is better; conversely, the higher the standardized score per unit user in the building, the worse the energy efficiency management of the current building is. The building with the lowest unit user standardization score is taken as the benchmark building. The differences in energy efficiency management measures between the benchmark building and other buildings are analyzed, and improvement measures are formulated.

[0023] Example 4 This embodiment discloses a method for formulating improvement measures by analyzing the differences in energy efficiency management measures between a benchmark building and other buildings, which specifically includes the following steps: Get the lamp power per unit area of ​​each of the K buildings: ,..., ,in Represents any one of the lamp power per unit area of ​​K buildings; obtain the proportion of energy-saving lamps in each of the K buildings: ,..., ,in represents any one of the proportions of energy-saving lamps in K buildings; keeping other conditions unchanged, we can know the standardized score of the unit user And the lamp power per unit area and energy-saving lamps There is a linear relationship, based on which a multiple linear regression model is established: in, is the intercept term, representing the initial value coefficient, and They are the coefficient of lamp power per unit area and the coefficient of energy-saving lamp proportion, is the error term, which represents the error value.

[0024] From the actual electricity consumption, we can know that the greater the power of the lamp per unit area, the more electricity the building consumes per unit time, the greater the power consumption per user, and the higher the reactive power per user (the greater the power of the lamp per unit area, the greater the power consumption, the more reactive power, and the higher the reactive power). Therefore, the standardized score per user The higher the energy efficiency of the building, the lower the energy efficiency of the building. is positive, indicating that the influence of the lamp power per unit area on the standardized score of the unit user is positive; The higher the proportion of energy-saving lamps, the lower the total power of the corresponding building lamps. Therefore, it can be known that the building power consumption will decrease with the increase of the proportion of energy-saving lamps, the smaller the power consumption per user, and the lower the reactive power per user (energy-saving lamps usually have a higher power factor, which means that the proportion of active power is higher under the same apparent power, so the proportion of reactive power is correspondingly reduced). Therefore, the standardized score per user The lower the energy consumption of the building, the more efficient it is; so It is negative, indicating that the proportion of energy-saving lamps has a negative impact on the standardized score of unit users.

[0025] Combined with Example 3, the calculated The values ​​and the statistical calculations of this embodiment The value can be combined with the multiple linear regression model to find a Value makes Minimization, which is a way to improve energy efficiency; To minimize , which needs to be minimized , so we can get: Set target unit user standardized score , which is used to represent the expected standardized score per unit user of the current building. It should be noted that the target standardized score per unit user It needs to be set according to the actual situation of the current building to make it more in line with the actual energy efficiency improvement expectations. becomes the value to be calculated under the current conditions and is recorded again as , the calculation formula is: Because the multiple linear regression model , and All are coefficients, which are considered as known values, combined with the lamp power per unit area , Standardized score of target unit users , the proportion of energy-saving lamps in the corresponding building can be calculated ,and =min(100%,max(0%, )),make sure The specific value of the percentage is between 0% and 100%. If the calculated percentage of energy-saving lamps is If it exceeds the preset range, the target unit user standardized score should be adjusted and recalculate Until the proportion of energy-saving lamps within a reasonable range.

[0026] For example, assuming the coefficients are known =5, =2, =-5, the current building's unit area lighting power =2 (W / m2), the set target unit user standardized score =5, then after calculation, it can be known that when the target unit user standardized score set for the current building is reached, the proportion of energy-saving lamps It is 80%.

[0027] By comparing the differences in energy efficiency management measures between buildings with different energy consumption, the following steps can be summarized to improve the energy efficiency of building electricity use: Carry out energy-saving transformation on the lighting system and count the lamp power per unit area in K buildings: ,..., , according to the opinions of experts, the maximum lamp power per unit area of ​​each building is determined , compare the lamp power per unit area of ​​each K building with the highest lamp power per unit area For comparison, if ,..., There are lamps with power higher than the highest lamp power per unit area Then adjust the lamp power per unit area of ​​the corresponding building until the highest lamp power per unit area is reached. standards; Count the proportion of energy-saving lamps in each building's lighting fixtures, and calculate the proportion of energy-saving lamps in the corresponding building when the target unit user standardized score is achieved based on the multivariate linear regression model. ; Count the number of energy-saving lamps in K buildings respectively and record them as , ,..., , calculate the proportion of energy-saving lamps in each building according to the formula: Where k represents a positive integer count index, starting from 1, with a maximum value of K. represents the proportion of energy-saving lamps in the kth building; If any The value is lower than the percentage of energy-saving lamps calculated when the current building reaches the set target unit user standardized score , it means that the proportion of energy-saving lamps in the current building has not reached the preset standard, and the existing lamps need to be replaced to increase the proportion of energy-saving lamps in the current building until the corresponding building reaches = .

[0028] For example, assuming K=3, the total power of the lamps in the three buildings is 1000W, 1500W and 2000W respectively, and the corresponding areas are 500 square meters, 750 square meters and 400 square meters respectively. First, calculate the lamp power per unit area of ​​each building, Building 1: 1000 / 500=2 (W / square meter), Building 2: 1500 / 750=2 (W / square meter), Building 3: 2000 / 400=5 (W / square meter), and preset the highest lamp power per unit area =2 (W / m2), that is, the maximum total power of lamps per square meter is 2W. By comparison, it can be seen that building 3 is higher than the maximum lamp power per unit area. , it is necessary to reduce the lamp power per unit area of ​​Building 3 until the maximum lamp power per unit area is reached. standards; If the number of lamps in three buildings is 100, 150 and 200 respectively, and the number of energy-saving lamps is 50, 75 and 160 respectively, the proportion of energy-saving lamps in each building can be calculated according to the formula is 50%, is 50%, is 80%. If the proportion of energy-saving lamps in each building when reaching the target unit user standardized score is calculated through the multivariate linear regression model, If both are 80%, the energy-saving lamps in Building 1 and Building 2 do not meet the preset standard, and the existing lamps need to be replaced until the proportion of energy-saving lamps in the existing lamps reaches the calculated proportion of energy-saving lamps. .

[0029] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0030] It should be stated that all user data collected in this application is collected with the user's consent and authorization. The use of user data is legal and compliant, and the use and processing of user data complies with the relevant laws, regulations and standards of the relevant regions.

Claims

1. The urban building energy consumption monitoring system based on smart meters is characterized by: The system includes: Smart meters collect users’ energy consumption data, including active power, reactive power, reactive power, voltage, and frequency. The database module receives and stores the energy consumption data processed by the central server; User terminal module, through which users can view energy consumption reports and energy consumption warning reminders sent by the central server, and through which users can set power consumption warning lines; The central server coordinates the communication and data transmission of each module, monitors the abnormal active power consumption of users, promptly notifies the staff of abnormal circuit energy consumption, analyzes the reactive power, deploys reactive compensation devices to compensate for the abnormal reactive power consumption in the circuit, calculates and analyzes the standardized scores of unit users and the differences in energy efficiency management measures between different buildings, and formulates improvement measures; Reactive power compensation device, combined with built-in capacitor bank, connected to the circuit to balance abnormal reactive power.

2. The urban building energy consumption monitoring system based on smart meters according to claim 1 is characterized in that: The smart meter uploads the collected energy consumption data to the central server via the wireless network, which processes it into a form that can be stored by the database module, and then the database module stores the energy consumption data persistently.

3. The urban building energy consumption monitoring system based on smart meters according to claim 1 is characterized in that: The method for the central server to monitor abnormal active power consumption of users comprises the following steps: A periodic time period t is preset to monitor a set of continuous active power consumption of any user in a city building within the time period t; Divide the time period t into b time periods evenly, expressed as , , ..., ;in is any time period in the b time periods, c is a positive integer counting index, starting from 1, with a maximum value of b. The active power corresponding to each of the b time periods is averaged and recorded as: , , ..., , sort the averaged active power from small to large, and get the sorted result: , , ..., ; Take the first quartile and record it as , and then take the third quartile as , calculate the interquartile range IQR according to the formula: The minimum threshold value of active power is set as , calculated according to the formula: Set the maximum threshold of active power as , calculated according to the formula: If the user's active power consumption in any of the b time periods exceeds the preset or less than All of them will be regarded as abnormal energy consumption status; Users can set their own energy consumption warning line, that is, and , the threshold set by yourself must be within the threshold range calculated by the quartile method. When the user's active power exceeds the threshold range, the current power consumption state is regarded as an abnormal energy consumption state; The central server obtains abnormal energy consumption status, generates energy consumption warning reminders to notify users and staff, and generates energy consumption reports for users to refer to.

4. The urban building energy consumption monitoring system based on smart meters according to claim 3 is characterized in that: The method for the central server to analyze reactive power is: In the time period t, if the reactive power of the current building does not exceed the reactive power threshold, it indicates that the circuit of the current building is working well, and a normal energy consumption reminder is generated; If the reactive power of the current building exceeds the reactive power threshold, it indicates that the current building has abnormal energy consumption, and the current power consumption state is regarded as an abnormal energy consumption state, and an energy consumption warning reminder is generated; The generated normal energy consumption reminder and energy consumption warning reminder of the current building are transmitted to the staff.

5. The urban building energy consumption monitoring system based on smart meters according to claim 4 is characterized in that: The method for analyzing reactive power also includes the following steps: Obtain the reactive power of the user in time period t; The reactive power of all users in the entire building in time period t is summarized to obtain the total reactive power I of the corresponding building; If the total reactive power I of the corresponding building in time period t is greater than the preset total reactive power threshold , the total reactive power of the current building is considered abnormal.

6. The urban building energy consumption monitoring system based on smart meters according to claim 5 is characterized in that: The central server will promptly notify staff of abnormal circuit energy consumption and deploy reactive power compensation devices to compensate for the abnormal reactive power consumption in the circuit.

7. The urban building energy consumption monitoring system based on smart meters according to claim 6 is characterized in that: The reactive power compensation device compensates for the abnormal reactive power consumption in the circuit in the following way: Obtain the reactive power of all users in the current building within time period t, and obtain the total reactive power P of the entire building by summing up; Get the voltage of the current building users and average it to get the building average voltage V. Get the frequency of the AC power used by the current building users and average it to get the building average frequency f. Combine the total reactive power P and the target reactive power Calculate the required reactive power compensation capacity , according to the formula: Determine the required reactive power compensation capacity After that, adjust the appropriate capacitor bank to compensate for the required reactive power compensation capacity. ; The capacitor groups in the reactive power compensation device are sorted in ascending order, and the sorting result is recorded as: , ,..., , where o represents the total number of capacitor groups, The largest capacitor group is selected and the sorted capacitor groups are stored in the database module; When a capacitor bank is needed, first check whether the database module has stored the data related to the reactive power compensation capacity. Capacitor banks of the same capacity , x is a counting index starting from 1, the maximum value is o, if it exists = , then the capacitor group put into use; If there is no reactive power compensation capacity For capacitor banks with the same capacity, the first reactive power compensation capacity is obtained backwards. Large capacitor bank , the capacitor group Put into use, where y is a counting index starting from 1 and the maximum value is o; If there is no reactive power compensation capacity greater than the current If there is a large capacitor group, take the largest capacitor group first. , then from Start to use, continue to acquire capacitors and accumulate until the accumulated result reaches the reactive power compensation capacity .

8. The urban building energy consumption monitoring system based on smart meters according to claim 7 is characterized in that: The central server calculates and analyzes the standardized scores of unit users and the differences in energy efficiency management measures between different buildings, and formulates improvement measures as follows: Obtain the reactive power of all users in any building within a preset time period T1 and accumulate it, then divide the accumulated result by the total number of users in the current building to obtain the reactive power per user in the current building; Get the reactive power of unit users in different buildings at the same time and in the same preset time period T1, recorded as , where K represents the number of buildings, and the average reactive power per user is obtained by averaging the reactive power of users in all buildings. ; Calculate the standardized score of a unit user according to the formula : in, is the standard deviation of reactive power of all building unit users; A low unit user standardization score indicates that the reactive power of the unit user in the current building is low, and the energy efficiency management of the current building is relatively good; conversely, a high unit user standardization score indicates that the energy efficiency management of the current building is relatively poor; The building with the lowest unit user standardization score is taken as the benchmark building. The differences in energy efficiency management measures between the benchmark building and other buildings are analyzed, and improvement measures are formulated.

9. The urban building energy consumption monitoring system based on smart meters according to claim 8 is characterized in that: The formulation of the improvement measures also includes the following steps: Normalize the score by unit user And the corresponding building unit area lamp power And the proportion of energy-saving lamps in the corresponding buildings There is a linear relationship, and a multiple linear regression model is established: in, is the intercept term, representing the initial value coefficient, and They are the lamp power per unit area of ​​the corresponding buildings The coefficient and the proportion of energy-saving lamps in the corresponding building The coefficient of is the error term, indicating the error value; Combined with the multivariate linear regression model, the standardized score of the user unit that achieves the set target in the corresponding building is calculated The proportion of energy-saving lamps , the calculation formula is: in, , and All are coefficients, which are considered as known values, combined with the unit area lamp power of the corresponding building. , Standardized score of target unit users , calculate the proportion of energy-saving lamps in the corresponding building when the target unit user standardized score is achieved ; If the proportion of energy-saving lamps in any building The value is lower than the normalized score of the unit user that meets the set target in the current building The proportion of energy-saving lamps calculated at , it means that the proportion of energy-saving lamps in the current building does not meet the preset standard; Existing lamps need to be replaced to increase the proportion of energy-saving lamps in the current building until the corresponding building = .

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