Electric quantity monitoring and early warning system and method

Abstract

The invention discloses an electric quantity monitoring and early warning system and method, and the method comprises the steps: obtaining building type information, obtaining target building type information based on the building type information, and selecting a benchmarking building of a to-be-detected building according to the target building purpose type information and the basic parameter information of the to-be-detected building, thereby obtaining a benchmarking building data set; the electricity consumption rule of the to-be-tested building is analyzed by integrating the electricity consumption conditions of the benchmarking building and the to-be-tested building area, and a historical electricity consumption rule result is obtained; the method comprises the following steps: detecting electric quantity use conditions of the whole to-be-detected building and each electric appliance in real time to obtain real-time target electric quantity use information, judging whether the to-be-detected building is over-capacitance in power consumption or not according to the real-time electric quantity use information of the to-be-detected building, if so, outputting a current electric quantity over-capacitance signal, if not, judging whether an electric quantity over-capacitance risk exists or not, and if not, outputting a current electric quantity over-capacitance signal. And if the power over-capacity risk exists, outputting a first power over-capacity early warning signal. The method has the effect of improving the electric quantity monitoring and early warning efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of power monitoring, and in particular to a power monitoring early warning system and method. Background Art

[0002] At present, over-capacity electricity consumption means electricity consumption exceeding the capacity agreed in the contract. The power supply contract signed between the power supply enterprise and each power user has clear clauses stipulating the power consumption capacity, which is one of the duties and obligations jointly performed by the power user and the power supply enterprise. The power supply enterprise can judge whether the power user has over-capacity electricity consumption at any time based on relevant data such as the power meter. Over-capacity electricity consumption is an act that endangers the safety of power supply and disrupts the normal order of power supply and use, and is a breach of contract. Therefore, it is very important to monitor the power consumption.

[0003] The existing power monitoring and early warning system uses the "overcapacity power consumption" audit theme of the marketing audit monitoring system, and uses the value of monthly power consumption greater than the theoretical maximum power consumption as a screening condition to find a list of suspected overcapacity users. However, the existing power monitoring and early warning system cannot automatically learn the user's usage habits of electrical appliances during the use of electricity, and cannot provide intelligent early warnings for users' overcapacity and adjust the power consumption. The efficiency of power monitoring and early warning is low and there is room for improvement. Summary of the invention

[0004] In order to improve the efficiency of power monitoring and early warning, the present application provides a power monitoring and early warning system and method.

[0005] In the first aspect, the power monitoring and early warning method provided by the present application adopts the following technical solutions: The power monitoring and early warning method comprises the following steps: Acquire building type information, determine the type of the building to be tested based on the building type information to obtain target building type information, obtain basic parameter information of the building to be tested, and select a benchmark building of the building to be tested to obtain a benchmark building data set according to the target building use type information and the basic parameter information of the building to be tested; Comprehensively analyze the electricity usage of the benchmark building and the building area to be tested, and analyze the electricity usage pattern of the building to be tested to obtain the historical electricity usage pattern results; Real-time detection of the power usage of the entire building to be tested and each electrical appliance to obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, and determine whether the power usage of the building to be tested is currently over-capacity according to the real-time power usage information of the building to be tested. If the power usage is over-capacity, output a current power over-capacity signal; if the power usage is not over-capacity, determine whether there is a risk of power over-capacity; if there is a risk of power over-capacity, output a first power over-capacity warning signal; Determine whether the power usage of the electrical appliances in the building to be tested is related to the external environment. If so, mark them as characteristic electrical appliances. Based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, determine the influence of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested to obtain a first power usage influence coefficient ATR; According to the external environment and structural design of the building to be tested, the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested is determined to obtain a second power usage influence coefficient BTY; According to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, the influence on the power usage of the characteristic electrical appliances in the tested building is judged to obtain the power usage influence coefficient W; according to the historical power usage law results, the real-time power usage information of the tested building and the power usage influence coefficient W, the power in the tested building is predicted to obtain predicted power usage information; based on the predicted power usage information, it is judged whether there is a risk of power overcapacity in the power in the tested building; if there is a risk of power overcapacity, a second power overcapacity warning signal is output; The current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal are sent to the user terminal and the background monitoring system, and the power consumption of the building to be tested is controlled.

[0006] Preferably, obtaining building type information, wherein the building type information includes industrial buildings, commercial buildings, public buildings and residential buildings; Match the purpose of the building to be tested with the building type information, determine the type of the building to be tested, and obtain the purpose type information of the target building; Obtaining basic parameter information of the building to be tested, wherein the basic parameter information of the building to be tested includes information about the area where the building to be tested is located and information about the building scale of the building to be tested; According to the information of the area where the building to be tested is located, the climate type of the area where the building to be tested is located is determined to obtain the climate type information of the target building; According to the target building climate type information, select all areas that are consistent with the target building climate type and mark them as the benchmark building selection area range; Within the benchmark building selection area, select buildings that have the same use type information as the target building to obtain the preliminary screening results of the benchmark buildings; Based on the preliminary screening results of the benchmark buildings, further screening is performed to select buildings with the same building scale information as the building to be tested, and a benchmark building data set is obtained, wherein the benchmark building data set includes a single benchmark building or multiple benchmark buildings of the building to be tested.

[0007] Preferably, the historical electricity usage of each benchmark building in the benchmark building data set is obtained and analyzed to obtain the benchmark historical electricity usage; Obtain the historical electricity usage of the building to be tested and analyze and process it to obtain the target historical electricity usage; Based on the benchmark historical electricity usage and the target historical electricity usage, the electricity consumption pattern of the historical power use process is analyzed to obtain the historical electricity consumption pattern results of the building to be tested.

[0008] Preferably, the power usage of each electrical appliance in the building to be tested is detected in real time to obtain individual real-time power usage information of each electrical appliance; Conduct real-time detection of the overall power usage data of the building to be tested to obtain overall real-time power usage information; The individual real-time power usage information and the overall real-time power usage information are combined to form real-time target power usage information; Creating an electricity usage time series graph data set, wherein the electricity usage time series graph data set includes a main electricity usage time series graph and multiple sub-electricity usage time series graphs, wherein the main electricity usage time series graph corresponds to the overall real-time electricity usage information, and the sub-electricity usage time series graphs correspond one-to-one to the individual real-time electricity usage information; Draw the main power usage time series diagram based on the overall real-time power usage information, and draw the corresponding sub-power usage time series diagram based on the real-time power usage information of each individual; Compare the overall real-time power usage information of the building to be tested with the preset theoretical maximum power usage information to obtain the current power usage comparison result; Based on the comparison result of the current power usage, if the overall real-time power usage information of the building to be tested is greater than or equal to the preset theoretical maximum power usage information, the current power usage of the building to be tested exceeds the capacity, and a current power excess capacity signal is output; Based on the current power usage comparison result, if the overall real-time power usage information of the building to be tested is less than the preset theoretical maximum power usage information, the difference between the overall real-time power usage information and the theoretical maximum power usage information is calculated to obtain the current power difference, and the current power difference is compared with the preset current power difference threshold. If the current power difference is less than or equal to the preset current power difference threshold, it means that the building to be tested currently has a risk of over-capacity power consumption, and the first over-capacity warning signal is output.

[0009] Preferably, it is determined whether the power consumption of each electrical appliance in the building to be tested will be affected by the external environment, and the electrical appliances affected by the external environment are marked as characteristic electrical appliances; Detecting the number of characteristic electrical appliances to obtain characteristic electrical appliance number information AQ; According to the type of each characteristic electrical appliance, the degree to which each characteristic electrical appliance is affected by the external environment is determined to obtain the electrical appliance environment correlation coefficient AE; According to the characteristic electrical appliance number information AQ and the electrical appliance environment correlation coefficient AE, based on the characteristic electrical appliance relationship function Calculation is performed to determine the influence of characteristic electrical appliances in the building to be tested on the electricity usage in the building to be tested, and a first electricity usage influence coefficient ATR is obtained, wherein a1 and a2 are proportional factors and are both greater than 0.

[0010] Preferably, the environment type in which the characteristic electrical appliance is affected by the outside world is marked as relevant environment type information; Detecting environmental parameters based on relevant environmental type information to obtain relevant environmental parameter information; Compare the relevant environmental parameter information with the preset relevant environmental parameter standard range. If the relevant environmental parameter information is within the preset relevant environmental parameter standard range, the environmental impact coefficient is 0. If the relevant environmental parameter information is not within the preset relevant environmental parameter standard range, select the middle value of the relevant environmental parameter standard range as the environmental standard parameter, calculate the difference between the relevant environmental parameter information and the environmental standard parameter to obtain the environmental difference, and obtain the environmental impact coefficient of the relevant environmental parameter information based on the environmental difference; Among the environmental impact coefficients of each environmental related parameter information, the environmental impact coefficients of the environmental related parameters whose environmental impact coefficients are not 0 are selected and marked as characteristic environmental impact coefficients; A characteristic environment correlation coefficient BH is obtained based on the characteristic environment impact coefficient. If there is only one characteristic environment impact coefficient, the characteristic environment impact coefficient is the characteristic environment correlation coefficient BH. If there are multiple values ​​of the characteristic environment impact coefficient, the characteristic environment correlation coefficient BH is obtained by averaging the characteristic environment impact coefficients. The building enclosure coefficient BR is obtained by judging the enclosure of the building to be tested according to the structural design of the building to be tested; According to the characteristic environment correlation coefficient BH and the building enclosure coefficient BR, based on the environment correlation function Calculation is performed to determine the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested, and a second power usage influence coefficient BTY is obtained, wherein b1 and b2 are proportional factors and are both greater than 0.

[0011] Preferably, according to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, based on the external influence relationship function Calculate and determine the impact on the power usage of the characteristic electrical appliances in the building to be tested, and obtain the power usage impact coefficient W, where: , is the proportional factor and is greater than 0; According to the historical electricity consumption pattern results and the real-time electricity usage information of the building to be tested, the overall electricity usage of the building to be tested is predicted, and the preliminary prediction results of electricity usage are output; According to the power usage influence coefficient W, the power usage of the characteristic electrical appliances in the tested building affected by the external environment is determined to obtain the environmental impact power deviation value; The preliminary power usage prediction result is adjusted based on the environmental impact power deviation value to obtain the predicted power usage information; Displaying the predicted power usage information in real time on the mother power usage time series graph; The predicted electricity usage information is compared with the preset theoretical maximum electricity usage information. If the predicted electricity usage information is greater than or equal to the preset theoretical maximum electricity usage information, it is predicted that the building under test has an overcapacity risk, and a second electricity overcapacity warning signal is output.

[0012] Preferably, a signal connection link is established between the wireless communication module and the building to be tested; Based on the wireless communication module, the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal are sent to the user terminal and the background monitoring system; When receiving the current power over-capacity signal, the power supply to the building to be tested is interrupted and a power supply interruption signal is output, and the power supply interruption signal is sent to the user terminal and the background monitoring system based on wireless communication technology; When the first power over-capacity warning signal or the second power over-capacity warning signal is received, the power consumption of the electrical appliance with the highest power consumption is cut off based on the time series diagram of each sub-power consumption, and the electrical appliance power cut-off signal is output, and the electrical appliance power cut-off signal is sent to the user terminal and the background monitoring system based on wireless communication technology.

[0013] In the second aspect, the present application provides a power monitoring and early warning system, which adopts the following technical solutions: The power monitoring and early warning system includes: The benchmark building analysis module is configured to obtain building type information, determine the type of the building to be tested based on the building type information to obtain target building type information, obtain basic parameter information of the building to be tested, and select a benchmark building of the building to be tested according to the target building use type information and the basic parameter information of the building to be tested to obtain a benchmark building data set; The historical electricity consumption pattern analysis module is configured to comprehensively analyze the electricity usage of the benchmark building and the building area to be tested, and analyze the electricity consumption pattern of the building to be tested to obtain the historical electricity consumption pattern results; The power overcapacity detection module is configured to detect the power usage of the entire building to be tested and each electrical appliance in real time, obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, and judge whether the power usage of the building to be tested is currently overcapacity according to the real-time power usage information of the building to be tested. If the power usage is overcapacity, output a current power overcapacity signal; if the power usage is not overcapacity, judge whether there is a risk of power overcapacity, and if there is a risk of power overcapacity, output a first power overcapacity warning signal; The electrical appliance self-impact analysis module is configured to determine whether the power usage of the electrical appliances in the building to be tested is related to the external environment. If so, it is marked as a characteristic electrical appliance. Based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, the influence of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested is determined to obtain a first power usage influence coefficient ATR; The environmental impact analysis module is configured to determine the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested according to the external environment and structural design of the building to be tested, and obtain a second power usage influence coefficient BTY; The power overcapacity prediction module is configured to determine the influence on the power usage of the characteristic electrical appliances in the tested building according to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, and obtain the power usage influence coefficient W; predict the power in the tested building according to the historical power usage law results, the real-time power usage information of the tested building, and the power usage influence coefficient W to obtain the predicted power usage information; determine whether there is a risk of power overcapacity in the power in the tested building based on the predicted power usage information; and output a second power overcapacity warning signal if there is a risk of power overcapacity; The wireless communication module is configured to send the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal to the user terminal and the background monitoring system, and control the power consumption of the building to be tested.

[0014] In summary, the present application includes at least one of the following beneficial technical effects: The benchmark building to be tested is determined by the target building type information and the basic parameter information of the building to be tested to obtain the benchmark building data set. The power usage pattern of the building to be tested is analyzed by combining the power usage of the benchmark building and the building to be tested to obtain the historical power usage pattern of the building to be tested, which provides data support for the subsequent power monitoring and early warning of the building to be tested. By means of real-time detection of the power usage of each electrical appliance in the building to be tested and the power usage data of the building to be tested as a whole, the individual real-time power usage information of each electrical appliance and the overall real-time power usage information are obtained respectively, and a power usage time series graph data set is created, which includes a main power usage time series graph and multiple sub-power usage time series graphs. The main power usage time series graph is drawn based on the overall real-time power usage information, and the corresponding sub-power usage time series graph is drawn based on the individual real-time power usage information of each electrical appliance, so that users and the background can intuitively and in detail understand the power usage of the building to be tested, and the efficiency of power monitoring and early warning is improved. According to the overall real-time power usage information, it is judged whether the power usage of the building to be tested is currently over-capacity and whether there is a risk of over-capacity. If the power usage is over-capacity, the current power over-capacity signal is output, and if there is a risk of over-capacity, the first power over-capacity early warning signal is output, which improves the efficiency of power over-capacity monitoring and early warning; By using the information to determine whether the power usage of electrical appliances in the building to be tested is related to the external environment, if so, they are marked as characteristic appliances. The first power usage influence coefficient ATR is obtained according to the number of characteristic appliances and the correlation between the characteristic appliances and the external environment. The second power usage influence coefficient BTY is obtained according to the external environment and structural design of the building to be tested. The power usage influence coefficient W is obtained by combining the first power usage influence coefficient ATR and the second power usage influence coefficient BTY. According to the historical power usage pattern results, the real-time power usage information of the building to be tested and the power usage influence coefficient W, it is determined whether there is a risk of over-capacity of power consumption in the building to be tested, thereby further improving the efficiency of power monitoring and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of the power monitoring and early warning method mainly embodied in this embodiment; Figure 2 This is a schematic diagram of the modules of the power monitoring and early warning system mainly embodied in this embodiment.

[0016] Figure numerals: 1. Benchmarking building analysis module; 2. Historical electricity consumption pattern analysis module; 3. Overcapacity detection module; 4. Electrical appliance impact analysis module; 5. Environmental impact analysis module; 6. Overcapacity prediction module; 7. Wireless communication module. DETAILED DESCRIPTION

[0017] The present application is further described in detail below in conjunction with the accompanying drawings.

[0018] The embodiment of the present application discloses a power monitoring and early warning method.

[0019] The power monitoring and early warning method comprises the following steps: Reference Figure 1, step S1, obtain building type information, determine the type of the building to be tested based on the building type information to obtain the target building type information, obtain basic parameter information of the building to be tested, and select the benchmark building of the building to be tested according to the target building use type information and the basic parameter information of the building to be tested to obtain the benchmark building data set. Step S1 specifically includes the following sub-steps: Step S11, obtaining building type information, which includes industrial buildings, commercial buildings, public buildings and residential buildings. For example, factories are industrial buildings, shopping malls and commercial streets are commercial buildings, subway stations and stations are public buildings, and residential areas where people live in their daily lives are residential buildings.

[0020] Step S12, matching the purpose of the building where the building to be tested is located with the building type information, determining the type of the building where the building to be tested is located, and obtaining the target building purpose type information.

[0021] Step S13, obtaining basic parameter information of the building to be tested, where the basic parameter information of the building to be tested includes information about the area where the building to be tested is located and information about the building scale of the building to be tested.

[0022] Step S14, determining the climate type of the area where the building to be tested is located according to the area information where the building to be tested is located to obtain the climate type information of the target building.

[0023] Step S15, according to the climate type information of the target building, select all areas that are consistent with the climate type of the target building and mark them as the benchmark building selection area range.

[0024] Step S16, within the benchmark building selection area, select buildings with the same use type information as the target building to obtain a preliminary screening result of the benchmark buildings.

[0025] Step S17, further screening is performed based on the preliminary screening results of the benchmark buildings, and buildings with building scale information consistent with the building to be tested are selected to obtain a benchmark building data set, which includes a single benchmark building or multiple benchmark buildings of the building to be tested.

[0026] Reference Figure 1 Step S2, comprehensively analyzing the electricity usage of the benchmark building and the building area to be tested, and analyzing the electricity usage pattern of the building to be tested to obtain the historical electricity usage pattern results. Step S2 specifically includes the following sub-steps: Step S21, obtaining the historical electricity usage of each benchmark building in the benchmark building data set and analyzing and processing it to obtain the benchmark historical electricity usage.

[0027] Step S22, obtaining the historical electricity usage of the building to be tested and analyzing and processing to obtain the target historical electricity usage.

[0028] Step S23, comprehensively comparing the historical power usage and the target historical power usage, analyzing the power consumption pattern during the historical power usage process, and obtaining the historical power consumption pattern results of the building to be tested.

[0029] In specific applications, the electricity consumption of the building to be tested is accidental, so the historical electricity consumption pattern cannot be summarized based solely on the electricity consumption of the building to be tested. The benchmark building to be tested is determined through the target building type information and the basic parameter information of the building to be tested to obtain the benchmark building data set. By combining the electricity usage of the benchmark building and the building to be tested, the electricity consumption pattern of the building to be tested is analyzed to obtain the historical electricity consumption pattern results of the building to be tested, which provides data support for subsequent electricity monitoring and early warning of the building to be tested.

[0030] Reference Figure 1 , step S3, real-time detection of the power usage of the entire building to be tested and each electrical appliance, obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, and determine whether the building to be tested is currently over-capacity according to the real-time power usage information of the building to be tested. If the power usage is over-capacity, output the current power over-capacity signal. If the power usage is not over-capacity, determine whether there is a risk of power over-capacity. If there is a risk of power over-capacity, output the first power over-capacity warning signal. Step S3 specifically includes the following sub-steps: Step S31 , real-time detection of the power usage of each electrical appliance in the building to be tested is performed to obtain individual real-time power usage information of each electrical appliance.

[0031] Step S32, real-time detection of the overall power usage data of the building to be tested is performed to obtain overall real-time power usage information.

[0032] Step S33: The individual real-time power usage information and the overall real-time power usage information are combined to form real-time target power usage information.

[0033] Step S34, create a power usage time series graph data set, the power usage time series graph data set includes a main power usage time series graph and multiple sub-power usage time series graphs, the main power usage time series graph corresponds to the overall real-time power usage information, and the sub-power usage time series graphs correspond one-to-one to the individual real-time power usage information.

[0034] Step S35, drawing a main power usage time series diagram based on the overall real-time power usage information, and drawing a corresponding sub-power usage time series diagram based on the real-time power usage information of each individual.

[0035] Step S36, comparing the overall real-time power usage information of the building to be tested with the preset theoretical maximum power usage information to obtain a current power usage comparison result.

[0036] Step S37, based on the comparison result of the current power usage, if the overall real-time power usage information of the building to be tested is greater than or equal to the preset theoretical maximum power usage information, the current power usage of the building to be tested exceeds the capacity, and a current power excess capacity signal is output.

[0037] Step S38, based on the current power usage comparison result, if the overall real-time power usage information of the building to be tested is less than the preset theoretical maximum power usage information, then the difference between the overall real-time power usage information and the theoretical maximum power usage information is calculated to obtain the current power difference, and the current power difference is compared with the preset current power difference threshold. If the current power difference is less than or equal to the preset current power difference threshold, it indicates that the building to be tested currently has a risk of over-capacity power consumption, and a first over-capacity warning signal is output.

[0038] In specific applications, by real-time detection of the power usage of each electrical appliance in the building to be tested and the power usage data of the building to be tested as a whole, the individual real-time power usage information of each electrical appliance and the overall real-time power usage information are obtained respectively, and a power usage time series graph data set is created, which includes a main power usage time series graph and multiple sub-power usage time series graphs. The main power usage time series graph is drawn based on the overall real-time power usage information, and the corresponding sub-power usage time series graph is drawn based on the individual real-time power usage information of each electrical appliance. This allows users and the background to intuitively and in detail understand the power usage of the building to be tested, thereby improving the efficiency of power monitoring and early warning. According to the overall real-time power usage information, it is determined whether the power usage of the building to be tested is currently over-capacity and whether there is a risk of over-capacity. If the power usage is over-capacity, the current power over-capacity signal is output; if there is a risk of over-capacity, the first power over-capacity warning signal is output, thereby improving the efficiency of power over-capacity monitoring and early warning.

[0039] Reference Figure 1 , step S4, determining whether the power usage of the electrical appliances in the building to be tested is related to the external environment, if so, marking them as characteristic electrical appliances, and determining the influence of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, and obtaining a first power usage influence coefficient ATR. Step S4 specifically includes the following sub-steps: Step S41, determining whether the power consumption of each electrical appliance in the building to be tested will be affected by the external environment, and marking the electrical appliances affected by the external environment as characteristic electrical appliances.

[0040] Step S42, detecting the number of characteristic electrical appliances to obtain characteristic electrical appliance number information AQ.

[0041] Step S43, determining the degree to which each characteristic electrical appliance is affected by the external environment according to the type of each characteristic electrical appliance to obtain an electrical appliance environment correlation coefficient AE.

[0042] For example, among electrical appliances, air conditioners are greatly affected by the external environment, while appliances with insulation functions such as health kettles and rice cookers are also affected by the external environment, while lamps and the like are not affected by the external environment. Therefore, the ranking relationship of the electrical environment correlation coefficients AE of air conditioners, health kettles, and lamps is: the air conditioner has the largest electrical environment correlation coefficient AE, the health kettle comes second, and the lamp has the smallest electrical environment correlation coefficient AE.

[0043] Step S44: based on the characteristic electrical appliance relationship function, the characteristic electrical appliance number information AQ and the electrical appliance environment correlation coefficient AE are calculated. Calculation is performed to determine the influence of characteristic electrical appliances in the building to be tested on the electricity usage in the building to be tested, and a first electricity usage influence coefficient ATR is obtained, wherein a1 and a2 are proportional factors and are both greater than 0.

[0044] Reference Figure 1 Step S5, according to the external environment and structural design of the building to be tested, determine the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested to obtain a second power usage influence coefficient BTY. Step S5 specifically includes the following sub-steps: Step S51, marking the environment type in which the characteristic electrical appliance is affected by the outside world as relevant environment type information.

[0045] Let's take an example to illustrate: for example, the characteristic appliance is an air conditioner, and the air conditioner is affected by the temperature and wind of the external environment, so the relevant environment type information is temperature and wind speed.

[0046] Step S52: detecting environmental parameters based on relevant environmental type information to obtain relevant environmental parameter information.

[0047] Let's take an example to illustrate: for example, if the characteristic appliance is an air conditioner, the relevant environment type information is temperature and wind speed, then the relevant environment parameter information is the environment temperature value and the environment wind speed value.

[0048] Step S53, compare the relevant environmental parameter information with the preset relevant environmental parameter standard range. If the relevant environmental parameter information is within the preset relevant environmental parameter standard range, the environmental impact coefficient is 0. If the relevant environmental parameter information is not within the preset relevant environmental parameter standard range, the middle value of the relevant environmental parameter standard range is selected as the environmental standard parameter, and the difference between the relevant environmental parameter information and the environmental standard parameter is calculated to obtain the environmental difference value, and the environmental impact coefficient of the relevant environmental parameter information is obtained based on the environmental difference value. The larger the environmental difference value, the larger the environmental impact coefficient.

[0049] Now let's take an example to illustrate: if the relevant environmental parameter information is the ambient temperature value, the ambient temperature value is compared with the ambient temperature standard range in the preset relevant environmental parameter standard range. If the ambient temperature value is within the ambient temperature standard range, the environmental impact coefficient is 0. If the ambient temperature value is not within the ambient temperature standard range, the middle value of the ambient temperature standard range is selected as the ambient standard temperature. The difference between the ambient temperature value and the ambient standard temperature is calculated to obtain the ambient temperature difference, and then the environmental impact coefficient is obtained. The larger the ambient temperature difference, the larger the environmental impact coefficient.

[0050] Step S54 , selecting the environmental impact coefficients of the environmental related parameters whose environmental impact coefficients are not 0 from among the environmental impact coefficients of the environmental related parameter information and marking them as characteristic environmental impact coefficients.

[0051] Step S55, obtaining a characteristic environment correlation coefficient BH based on the characteristic environment impact coefficient. If there is only one characteristic environment impact coefficient, the characteristic environment impact coefficient is the characteristic environment correlation coefficient BH. If there are multiple values ​​of the characteristic environment impact coefficient, the characteristic environment correlation coefficient BH is obtained by calculating the average of the characteristic environment impact coefficients.

[0052] Step S56, judging the sealing property of the building to be tested according to the structural design of the building to be tested to obtain the building sealing coefficient BR.

[0053] Step S57, based on the characteristic environment correlation coefficient BH and the building enclosure coefficient BR, based on the environment correlation function Calculation is performed to determine the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested, and a second power usage influence coefficient BTY is obtained, wherein b1 and b2 are proportional factors and are both greater than 0.

[0054] Reference Figure 1 , step S6, according to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, determine the influence on the power usage of the characteristic electrical appliances in the building to be tested, and obtain the power usage influence coefficient W, and according to the historical power usage law results, the real-time power usage information of the building to be tested, and the power usage influence coefficient W, predict the power usage in the building to be tested to obtain the predicted power usage information, and determine whether there is a risk of power overcapacity in the power usage in the building to be tested based on the predicted power usage information, and if there is a risk of power overcapacity, output a second power overcapacity warning signal. Step S6 specifically includes the following sub-steps: Step S61: Based on the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, based on the external influence relationship function Calculate and determine the impact on the power usage of the characteristic electrical appliances in the building to be tested, and obtain the power usage impact coefficient W, where: , are scaling factors and are all greater than 0.

[0055] Step S62, predicting the overall power usage of the building to be tested based on the historical power usage pattern results and the real-time power usage information of the building to be tested, and outputting a preliminary power usage prediction result.

[0056] Step S63, determining the power usage of characteristic electrical appliances in the building to be tested affected by the external environment according to the power usage impact coefficient W to obtain an environmental impact power deviation value.

[0057] Step S64, adjusting the preliminary power usage prediction result based on the environmental impact power usage deviation value to obtain predicted power usage information.

[0058] Step S65, displaying the predicted power usage information in real time on the parent power usage time series graph.

[0059] Step S66, compare the predicted power usage information with the preset theoretical maximum power usage information. If the predicted power usage information is greater than or equal to the preset theoretical maximum power usage information, it is predicted that the building under test has an overcapacity risk, and a second power overcapacity warning signal is output.

[0060] In specific applications, electrical appliances in a building may be affected by the external environment, which in turn affects the power consumption of the appliances. In the embodiment of the present application, it is determined whether the power consumption of the electrical appliances in the building to be tested is related to the external environment. If so, they are marked as characteristic appliances. A first power consumption influence coefficient ATR is obtained based on the number of characteristic appliances and the correlation between the characteristic appliances and the external environment. A second power consumption influence coefficient BTY is obtained based on the external environment and structural design of the building to be tested. The power consumption influence coefficient W is obtained by combining the first power consumption influence coefficient ATR and the second power consumption influence coefficient BTY. Based on the historical power consumption pattern results, the real-time power consumption information of the building to be tested and the power consumption influence coefficient W, it is determined whether there is a risk of over-capacity of power consumption in the building to be tested, thereby improving the efficiency of power monitoring and early warning.

[0061] Reference Figure 1 , step S7, sending the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal to the user terminal and the background monitoring system, and controlling the power consumption of the building to be tested. Step S7 specifically includes the following sub-steps: Step S71: Establish a signal connection link between the wireless communication module 7 and the building to be tested. It should be noted that the wireless communication module 7 in the embodiment of the present application refers to a wireless communication module 7 based on Bluetooth technology.

[0062] Step S72 , based on the wireless communication module 7 , the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal are sent to the user terminal and the background monitoring system.

[0063] Step S73, when receiving the current power over-capacity signal, interrupt the power supply to the building to be tested and output a power supply interruption signal, and send the power supply interruption signal to the user terminal and the background monitoring system based on wireless communication technology.

[0064] Step S74, when the first power over-capacity warning signal or the second power over-capacity warning signal is received, based on the time series diagram of each sub-power usage, the power consumption of the electrical appliance with the highest power consumption is cut off, and an electrical appliance power cut-off signal is output, and the electrical appliance power cut-off signal is sent to the user terminal and the background monitoring system based on wireless communication technology.

[0065] The embodiment of the present application also discloses a power monitoring and early warning system.

[0066] Reference Figure 2 , power monitoring and early warning system, including: The benchmark building analysis module 1 is configured to obtain building type information, determine the type of the building to be tested based on the building type information to obtain the target building type information, obtain basic parameter information of the building to be tested, and select the benchmark building of the building to be tested according to the target building use type information and the basic parameter information of the building to be tested to obtain the benchmark building data set.

[0067] The historical electricity consumption pattern analysis module 2 is configured to comprehensively analyze the electricity usage of the benchmark building and the building area to be tested, and to obtain the historical electricity consumption pattern results by analyzing the electricity consumption pattern of the building to be tested.

[0068] The power overcapacity detection module 3 is configured to detect the power usage of the entire building to be tested and each electrical appliance in real time, obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, and judge whether the power usage of the building to be tested is currently overcapacity according to the real-time power usage information of the building to be tested. If the power usage is overcapacity, output the current power overcapacity signal; if the power usage is not overcapacity, judge whether there is a risk of power overcapacity; if there is a risk of power overcapacity, output the first power overcapacity warning signal.

[0069] The electrical appliance self-impact analysis module 4 is configured to determine whether the power usage of the electrical appliances in the building to be tested is related to the external environment. If so, it is marked as a characteristic electrical appliance. Based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, the impact of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested is determined to obtain a first power usage impact coefficient ATR.

[0070] The environmental impact analysis module 5 is configured to determine the impact of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested according to the external environment and structural design of the building to be tested, and obtain a second power usage impact coefficient BTY.

[0071] The power overcapacity prediction module 6 is configured to determine the impact on the power usage of characteristic electrical appliances in the building to be tested based on the first power usage impact coefficient ATR and the second power usage impact coefficient BTY, and obtain the power usage impact coefficient W; predict the power in the building to be tested based on the historical power usage pattern results, the real-time power usage information of the building to be tested, and the power usage impact coefficient W to obtain predicted power usage information; based on the predicted power usage information, determine whether there is a risk of power overcapacity in the building to be tested; if there is a risk of power overcapacity, output a second power overcapacity warning signal.

[0072] The wireless communication module 7 is configured to send the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal to the user terminal and the background monitoring system, and control the power consumption of the building to be tested.

[0073] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. The power monitoring and early warning method is characterized by: The following steps are involved: Acquire building type information, determine the type of the building to be tested based on the building type information to obtain target building type information, obtain basic parameter information of the building to be tested, and select a benchmark building of the building to be tested to obtain a benchmark building data set according to the target building use type information and the basic parameter information of the building to be tested; Comprehensively analyze the electricity usage of the benchmark building and the building area to be tested, and analyze the electricity usage pattern of the building to be tested to obtain the historical electricity usage pattern results; Real-time detection of the power usage of the entire building to be tested and each electrical appliance to obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, and determine whether the power usage of the building to be tested is currently over-capacity according to the real-time power usage information of the building to be tested. If the power usage is over-capacity, output a current power over-capacity signal; if the power usage is not over-capacity, determine whether there is a risk of power over-capacity; if there is a risk of power over-capacity, output a first power over-capacity warning signal; Determine whether the power usage of the electrical appliances in the building to be tested is related to the external environment. If so, mark them as characteristic electrical appliances. Based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, determine the influence of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested to obtain a first power usage influence coefficient ATR; According to the external environment and structural design of the building to be tested, the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested is determined to obtain a second power usage influence coefficient BTY; According to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, the influence on the power usage of the characteristic electrical appliances in the tested building is judged to obtain the power usage influence coefficient W; according to the historical power usage law results, the real-time power usage information of the tested building and the power usage influence coefficient W, the power in the tested building is predicted to obtain predicted power usage information; based on the predicted power usage information, it is judged whether there is a risk of power overcapacity in the power in the tested building; if there is a risk of power overcapacity, a second power overcapacity warning signal is output; The current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal are sent to the user terminal and the background monitoring system, and the power consumption of the building to be tested is controlled.

2. The power monitoring and early warning method according to claim 1 is characterized in that: The steps of obtaining building type information, obtaining building type information, determining the type of the building to be tested based on the building type information to obtain target building type information, obtaining basic parameter information of the building to be tested, and selecting a benchmark building of the building to be tested to obtain a benchmark building data set according to the target building use type information and the basic parameter information of the building to be tested, specifically include: Acquire building type information, where the building type information includes industrial buildings, commercial buildings, public buildings, and residential buildings; Match the purpose of the building to be tested with the building type information, determine the type of the building to be tested, and obtain the purpose type information of the target building; Obtaining basic parameter information of the building to be tested, wherein the basic parameter information of the building to be tested includes information about the area where the building to be tested is located and information about the building scale of the building to be tested; According to the information of the area where the building to be tested is located, the climate type of the area where the building to be tested is located is determined to obtain the climate type information of the target building; According to the target building climate type information, select all areas that are consistent with the target building climate type and mark them as the benchmark building selection area range; Within the benchmark building selection area, select buildings that have the same use type information as the target building to obtain the preliminary screening results of the benchmark buildings; Based on the preliminary screening results of the benchmark buildings, further screening is performed to select buildings with the same building scale information as the building to be tested, and a benchmark building data set is obtained, wherein the benchmark building data set includes a single benchmark building or multiple benchmark buildings of the building to be tested.

3. The power monitoring and early warning method according to claim 2 is characterized in that: The steps of analyzing the electricity usage of the benchmark building and the building area to be tested and obtaining the historical electricity usage results of the building to be tested include: Obtain the historical electricity usage of each benchmark building in the benchmark building data set and analyze and process it to obtain the benchmark historical electricity usage; Obtain the historical electricity usage of the building to be tested and analyze and process it to obtain the target historical electricity usage; Based on the benchmark historical electricity usage and the target historical electricity usage, the electricity consumption pattern of the historical power use process is analyzed to obtain the historical electricity consumption pattern results of the building to be tested.

4. The power monitoring and early warning method according to claim 3 is characterized in that: The steps of detecting the power usage of the entire building to be tested and each electrical appliance in real time, obtaining real-time target power usage information, drawing a power usage time series diagram based on the real-time target power usage information and updating it in real time, judging whether the power usage of the building to be tested is currently over-capacity according to the real-time power usage information of the building to be tested, outputting a current power over-capacity signal if the power usage is over-capacity, judging whether there is a risk of power over-capacity if the power usage is not over-capacity, and outputting a first power over-capacity warning signal if there is a risk of power over-capacity, specifically include: Conduct real-time detection of the power usage of each electrical appliance in the building to be tested, and obtain the individual real-time power usage information of each electrical appliance; Conduct real-time detection of the overall power usage data of the building to be tested to obtain overall real-time power usage information; The individual real-time power usage information and the overall real-time power usage information are combined to form real-time target power usage information; Creating an electricity usage time series graph data set, wherein the electricity usage time series graph data set includes a main electricity usage time series graph and multiple sub-electricity usage time series graphs, wherein the main electricity usage time series graph corresponds to the overall real-time electricity usage information, and the sub-electricity usage time series graphs correspond one-to-one to the individual real-time electricity usage information; Draw the main power usage time series diagram based on the overall real-time power usage information, and draw the corresponding sub-power usage time series diagram based on the real-time power usage information of each individual; Compare the overall real-time power usage information of the building to be tested with the preset theoretical maximum power usage information to obtain the current power usage comparison result; Based on the comparison result of the current power usage, if the overall real-time power usage information of the building to be tested is greater than or equal to the preset theoretical maximum power usage information, the current power usage of the building to be tested exceeds the capacity, and a current power excess capacity signal is output; Based on the current power usage comparison result, if the overall real-time power usage information of the building to be tested is less than the preset theoretical maximum power usage information, the difference between the overall real-time power usage information and the theoretical maximum power usage information is calculated to obtain the current power difference, and the current power difference is compared with the preset current power difference threshold. If the current power difference is less than or equal to the preset current power difference threshold, it means that the building to be tested currently has a risk of over-capacity power consumption, and the first over-capacity warning signal is output.

5. The power monitoring and early warning method according to claim 4 is characterized in that: The steps of determining whether the power usage of the electrical appliances in the building to be tested is related to the external environment, marking them as characteristic electrical appliances if relevant, and determining the influence of the characteristic electrical appliances on the power usage in the building to be tested based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment to obtain a first power usage influence coefficient ATR specifically include: Determine whether the power consumption of each electrical appliance in the building to be tested will be affected by the external environment, and mark the appliances affected by the external environment as characteristic appliances; Detecting the number of characteristic electrical appliances to obtain characteristic electrical appliance number information AQ; According to the type of each characteristic electrical appliance, the degree to which each characteristic electrical appliance is affected by the external environment is determined to obtain the electrical appliance environment correlation coefficient AE; According to the characteristic electrical appliance number information AQ and the electrical appliance environment correlation coefficient AE, based on the characteristic electrical appliance relationship function Calculation is performed to determine the influence of characteristic electrical appliances in the building to be tested on the electricity usage in the building to be tested, and a first electricity usage influence coefficient ATR is obtained, wherein a1 and a2 are proportional factors and are both greater than 0.

6. The power monitoring and early warning method according to claim 5 is characterized in that: The step of determining the influence of the external environment around the building to be tested on the power usage of characteristic electrical appliances in the building to be tested according to the external environment and structural design of the building to be tested to obtain a second power usage influence coefficient BTY specifically includes: Marking the environment type of the characteristic electrical appliance affected by the outside world as relevant environment type information; Detecting environmental parameters based on relevant environmental type information to obtain relevant environmental parameter information; Compare the relevant environmental parameter information with the preset relevant environmental parameter standard range. If the relevant environmental parameter information is within the preset relevant environmental parameter standard range, the environmental impact coefficient is 0. If the relevant environmental parameter information is not within the preset relevant environmental parameter standard range, select the middle value of the relevant environmental parameter standard range as the environmental standard parameter, calculate the difference between the relevant environmental parameter information and the environmental standard parameter to obtain the environmental difference, and obtain the environmental impact coefficient of the relevant environmental parameter information based on the environmental difference; Among the environmental impact coefficients of each environmental related parameter information, the environmental impact coefficients of the environmental related parameters whose environmental impact coefficients are not 0 are selected and marked as characteristic environmental impact coefficients; A characteristic environment correlation coefficient BH is obtained based on the characteristic environment impact coefficient. If there is only one characteristic environment impact coefficient, the characteristic environment impact coefficient is the characteristic environment correlation coefficient BH. If there are multiple values ​​of the characteristic environment impact coefficient, the characteristic environment correlation coefficient BH is obtained by averaging the characteristic environment impact coefficients. The building enclosure coefficient BR is obtained by judging the enclosure of the building to be tested according to the structural design of the building to be tested; According to the characteristic environment correlation coefficient BH and the building enclosure coefficient BR, based on the environment correlation function Calculation is performed to determine the influence of the external environment around the building to be tested on the power usage of the characteristic electrical appliances in the building to be tested, and a second power usage influence coefficient BTY is obtained, wherein b1 and b2 are proportional factors and are both greater than 0.

7. The power monitoring and early warning method according to claim 6 is characterized in that: According to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, the influence on the power usage of the characteristic electrical appliances in the tested building is judged to obtain the power usage influence coefficient W; according to the historical power usage law results, the real-time power usage information of the tested building and the power usage influence coefficient W, the power in the tested building is predicted to obtain predicted power usage information; based on the predicted power usage information, whether there is a risk of power overcapacity in the power in the tested building is judged; if there is a risk of power overcapacity, a second power overcapacity warning signal is output, specifically comprising: According to the first power usage influence coefficient ATR and the second power usage influence coefficient BTY, based on the external influence relationship function Calculate and determine the impact on the power usage of the characteristic electrical appliances in the building to be tested, and obtain the power usage impact coefficient W, where: , is the proportional factor and is greater than 0; According to the historical electricity consumption pattern results and the real-time electricity usage information of the building to be tested, the overall electricity usage of the building to be tested is predicted, and the preliminary prediction results of electricity usage are output; According to the power usage influence coefficient W, the power usage of the characteristic electrical appliances in the tested building affected by the external environment is determined to obtain the environmental impact power deviation value; The preliminary power usage prediction result is adjusted based on the environmental impact power deviation value to obtain the predicted power usage information; Displaying the predicted power usage information in real time on the mother power usage time series graph; The predicted electricity usage information is compared with the preset theoretical maximum electricity usage information. If the predicted electricity usage information is greater than or equal to the preset theoretical maximum electricity usage information, it is predicted that the building under test has an overcapacity risk, and a second electricity overcapacity warning signal is output.

8. The power monitoring and early warning method according to claim 7 is characterized in that: The steps of sending the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal to the user terminal and the background monitoring system, and controlling and adjusting the power consumption of the building to be tested specifically include: Establishing a signal connection link between the wireless communication module (7) and the building to be tested; Based on the wireless communication module (7), the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal are sent to the user terminal and the background monitoring system; When receiving the current power over-capacity signal, the power supply to the building to be tested is interrupted and a power supply interruption signal is output, and the power supply interruption signal is sent to the user terminal and the background monitoring system based on wireless communication technology; When the first power over-capacity warning signal or the second power over-capacity warning signal is received, the power consumption of the electrical appliance with the highest power consumption is cut off based on the time series diagram of each sub-power consumption, and the electrical appliance power cut-off signal is output, and the electrical appliance power cut-off signal is sent to the user terminal and the background monitoring system based on wireless communication technology.

9. The power monitoring and early warning system is characterized by: The power monitoring and early warning system is used to implement the power monitoring and early warning method described in any one of claims 1 to 8, including: The benchmark building analysis module (1) is configured to obtain building type information, determine the type of the building to be tested based on the building type information to obtain target building type information, obtain basic parameter information of the building to be tested, and select a benchmark building of the building to be tested according to the target building use type information and the basic parameter information of the building to be tested to obtain a benchmark building data set; The historical electricity consumption pattern analysis module (2) is configured to comprehensively analyze the electricity consumption of the benchmark building and the building area to be tested, and analyze the electricity consumption pattern of the building to be tested to obtain the historical electricity consumption pattern result; The power overcapacity detection module (3) is configured to detect the power usage of the entire building to be tested and each electrical appliance in real time, obtain real-time target power usage information, draw a power usage time series diagram based on the real-time target power usage information and update it in real time, determine whether the power usage of the building to be tested is currently overcapacity based on the real-time power usage information of the building to be tested, output a current power overcapacity signal if the power usage is overcapacity, determine whether there is a risk of power overcapacity if the power usage is not overcapacity, and output a first power overcapacity warning signal if there is a risk of power overcapacity; The electrical appliance self-impact analysis module (4) is configured to determine whether the power usage of the electrical appliances in the building to be tested is related to the external environment, and if so, mark it as a characteristic electrical appliance, and based on the number of characteristic electrical appliances and the correlation between the characteristic electrical appliances and the external environment, determine the influence of the characteristic electrical appliances in the building to be tested on the power usage in the building to be tested to obtain a first power usage influence coefficient ATR; An environmental impact analysis module (5) is configured to determine the impact of the external environment surrounding the building under test on the power usage of characteristic electrical appliances in the building under test based on the external environment and structural design of the building under test, and obtain a second power usage impact coefficient BTY; The power overcapacity prediction module (6) is configured to determine the impact on the power usage of the characteristic electrical appliances in the building to be tested based on the first power usage impact coefficient ATR and the second power usage impact coefficient BTY, and obtain the power usage impact coefficient W; predict the power in the building to be tested based on the historical power usage pattern results, the real-time power usage information of the building to be tested, and the power usage impact coefficient W to obtain predicted power usage information; determine whether there is a risk of power overcapacity in the power in the building to be tested based on the predicted power usage information; and output a second power overcapacity warning signal if there is a risk of power overcapacity; The wireless communication module (7) is configured to send the current power over-capacity signal, the first power over-capacity warning signal and the second power over-capacity warning signal to the user terminal and the background monitoring system, and to control the power consumption of the building to be tested.

Images