Intelligent building comprehensive energy consumption monitoring method and system

Abstract

The invention relates to a smart building comprehensive energy consumption monitoring method and system, and belongs to the field of comprehensive energy consumption monitoring. According to the method, the rule range of the instant consumption is determined according to the data dispersion degree of the instant consumption of the preset number of days, and if the energy consumed on the day is not in the rule range, the energy consumed on the day is marked as abnormal data; otherwise, the data are reasonable data. Whether the energy consumed every day is abnormal or not is judged according to the obtained rule range, and monitoring of the energy consumed by the energy equipment every day is effectively achieved.

Description

Technical Field

[0001] The present invention relates to a method and system for monitoring comprehensive energy consumption of a smart building, and belongs to the field of comprehensive energy consumption monitoring. Background Art

[0002] As the mainstream direction of future building development, smart buildings realize intelligent management and control of building internal equipment by integrating advanced information technologies such as the Internet of Things, big data, and cloud computing, effectively reducing the comprehensive energy consumption of equipment and improving the energy efficiency of buildings. Smart buildings refer to the use of information technology, the Internet of Things technology, and intelligent control technology to integrate and intelligently manage various equipment in buildings, and realize the automation, informatization, and intelligence of building operations. Smart buildings monitor, analyze, and control the operating status of equipment in buildings in real time, optimize the operating strategy of equipment, improve energy efficiency, and reduce energy consumption and operating costs.

[0003] Smart buildings have various energy sources. At present, when monitoring the comprehensive energy consumption of smart buildings, it is basically only used to obtain data and observe whether the data has been tampered with. For example, the published text of the Chinese patent application with publication number CN117193624A does not monitor the daily energy consumption of smart buildings to determine whether the comprehensive energy consumption of the day is abnormal. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for monitoring the comprehensive energy consumption of a smart building, so as to solve the problem of not monitoring whether the comprehensive energy consumption of the smart building on that day is abnormal.

[0005] To achieve the above object, the solution of the present invention includes:

[0006] A method for monitoring comprehensive energy consumption of a smart building according to the present invention comprises the following steps:

[0007] Obtain the real-time consumption of the equipment in the smart building for the preset days. The real-time consumption is the energy consumed by the equipment every day. According to the data discreteness obtained from the real-time consumption of the preset days, determine the regular range of the real-time consumption; if the energy consumed by the equipment on that day is within the regular range, mark the energy consumed on that day as reasonable data; otherwise, mark it as abnormal data.

[0008] Furthermore, the lower limit and the upper limit of the regular range of the instant consumption are obtained according to the minimum value and the maximum value of the instant consumption of the preset days, respectively.

[0009] Furthermore, when determining the lower limit and the upper limit of the regular range, the instantaneous consumption of the preset days is also processed through the following steps:

[0010] The first aggregate evaluation value is obtained by the following formula:

[0011]

[0012] Wherein, H is the first aggregate evaluation value, n is the preset number of days, Li is the instant consumption corresponding to the preset number of days, and P is the average instant consumption of the preset number of days;

[0013] When the first aggregate evaluation value is greater than the first preset value, one instant consumption is selected from the instant consumption of the preset days and deleted, and the first aggregate evaluation value is recalculated until the first aggregate evaluation value is less than or equal to the first preset value. The first deletion ratio is obtained according to the number of deletions. When the first deletion ratio is less than or equal to the second preset value, the range from the minimum to the maximum value of the instant consumption of the preset days that have not been deleted is marked as the lower limit and upper limit of the second regular range.

[0014] Furthermore, the instant consumption of the preset days is sorted from large to small according to the absolute value of the difference between the instant consumption of the preset days and the mean value. When the instant consumption needs to be deleted, it is deleted in descending order.

[0015] Furthermore, when the deletion ratio is greater than a second preset value, the cumulative consumption of the equipment in the smart building for a preset number of months is also obtained. The cumulative consumption is the energy consumed by the equipment each month. According to the data discreteness of the cumulative consumption for the preset number of months, the regular range of the cumulative consumption is determined; if the energy consumed by the equipment in that month is within the regular range, the energy consumed in that month is marked as reasonable data; otherwise, it is marked as abnormal data.

[0016] Furthermore, the lower limit and the upper limit of the regular range of the cumulative consumption are obtained according to the minimum value and the maximum value of the cumulative consumption of the preset months, respectively.

[0017] When determining the lower and upper limits of the regular range, the accumulated consumption for the preset number of months is also processed in the following steps:

[0018] The second aggregate evaluation value is obtained by the following formula:

[0019]

[0020] Wherein, H1 is the second aggregate evaluation value, n is the preset number of months, Gj is the cumulative consumption corresponding to the preset number of months, and P is the average of the cumulative consumption of the preset number of months;

[0021] When the second aggregate evaluation value is greater than the third preset value, one cumulative consumption is selected from the cumulative consumption of the preset number of months and deleted, and the second aggregate evaluation value is recalculated until the second aggregate evaluation value is less than or equal to the third preset value. The second deletion ratio is obtained according to the number of deletions. When the second deletion ratio is less than or equal to the second preset value, the range from the minimum to the maximum value of the cumulative consumption of the preset number of months that have not been deleted is marked as the lower limit and upper limit of the fourth regular range.

[0022] Furthermore, the accumulated consumption of the preset months is sorted from large to small according to the absolute value of the difference between the accumulated consumption of the preset months and the mean value. When the accumulated consumption needs to be deleted, it is deleted in descending order.

[0023] Furthermore, when the equipment is powered by multiple energy supply methods and each energy supply point is under the corresponding tiered energy consumption billing rules, the energy consumption levels of the tiered energy consumption billing rules for each energy supply point are the same but the unit fees are different. Each energy supply method includes multiple energy supply points that supply energy to the equipment according to the corresponding set power ratio; the energy consumption difference between the current cumulative consumption of the equipment and the next energy consumption level is obtained, and the energy consumption difference is divided by the next energy consumption level to obtain the gear-up ratio. When the gear-up ratio is less than or equal to the fourth preset value, the energy consumption cost before the next energy consumption level is calculated under each energy supply method according to the tiered energy consumption billing rules for each energy supply point, and the energy supply method with the lowest energy consumption cost is selected to power the equipment.

[0024] A smart building comprehensive energy consumption monitoring system comprises a processor, and the processor is used to execute a computer program to implement the steps of a smart building comprehensive energy consumption monitoring method.

[0025] The beneficial effects of the present invention are as follows: the present invention is a pioneering invention. The present invention determines the regular range of instant consumption according to the data discreteness of the instant consumption of preset days. If the energy consumed on that day is not within the regular range, the energy consumed on that day is marked as abnormal data; otherwise, it is reasonable data. The present invention determines whether the energy consumed daily is abnormal through the obtained regular range, and effectively realizes the monitoring of the energy consumed daily. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of the present invention for monitoring whether the energy consumption of the equipment on the day is abnormal;

[0027] Figure 2 It is a flow chart of switching the energy supply point of the equipment according to the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0029] The idea of ​​the present invention is to compare the energy consumption of the day with the energy consumption in the past to determine whether the energy consumption of the day is abnormal.

[0030] Method Example:

[0031] This embodiment provides a comprehensive energy consumption monitoring method for a smart building, where the energy used by the smart building comes from multiple energy supply points, such as electrical energy, light energy, etc. Each energy supply point is used to power the equipment in the smart building, and the equipment that supports multiple energy supply methods is marked as a mixed target, and the equipment that only supports one energy supply method is marked as a single target.

[0032] Monitor the energy consumption of mixed and separate targets. Energy consumption refers to the energy value consumed by the equipment in a set time period. The energy values ​​consumed by the mixed and separate targets on the same day are marked as real-time consumption. The energy values ​​consumed on the same day are obtained at a specified time point every day, generally set to 23:50.

[0033] Since the analysis methods adopted when performing abnormal analysis on the instant consumption of mixed targets and individual targets are consistent, the monitoring method of the present invention is further described below by taking the mixed target as an example, namely:

[0034] like Figure 1 As shown, firstly select a mixed target and obtain its instant consumption corresponding to each day in the past n days, where n is set according to specific needs, and mark the instant consumption of n days as Li, i = 1, 2, ..., n. According to the discrete degree of data of the n instant consumption, determine the regular range.

[0035] Then calculate the mean value P of the instant consumption Li for n days, that is:

[0036]

[0037] Then, the aggregate evaluation value H of Li is obtained through the mean value P, that is:

[0038]

[0039] Further, determine whether the aggregate evaluation value H is greater than the preset value X1. If it is less than or equal to the preset value X1, the value range from the minimum to the maximum value of Li is marked as the first regular range. At this time, the instant consumption generated by the mixed target on that day will be obtained and marked as real-time consumption. Then, determine whether the real-time consumption is within the first regular range. If it is, the real-time consumption will be marked as reasonable data and no processing will be performed. Otherwise, a suspicion signal will be generated, reminding the management personnel to verify whether the real-time consumption is correct.

[0040] If the aggregate evaluation value H is greater than the preset value X1, sort Li in descending order according to the size of the |Li-P| value. Then delete Li in descending order, and then recalculate the aggregate evaluation value H of Li after deleting the value, until the aggregate evaluation value H is less than or equal to the preset value X1; at this time, obtain the number of deleted Li, and mark the value obtained by dividing it by n as the first deletion ratio. When the first deletion ratio exceeds the preset value X2, a chaotic signal is generated, and then no processing is performed, otherwise a regular signal is generated, where X2 is generally 0.85. When a regular signal is generated, the value range from the minimum value to the maximum value of the deleted Li remaining at this time is marked as the second regular range, and then the instant consumption generated by the mixed target on the day is obtained, marked as real-time consumption, and then it is determined whether the real-time consumption is within the second regular range. If it is, the real-time consumption is marked as reasonable data and no processing is performed, otherwise a suspicious signal is generated, and the management personnel are reminded to verify whether the real-time consumption is correct. Among them, when deleting Li, you can randomly select a Li to delete, but doing so may result in inaccurate aggregate evaluation values; you can also sort from small to large, but in this way, when selecting to delete Li, you will traverse to the last one each time, and the processing time is long. Therefore, as a preferred embodiment, Li is sorted from large to small according to the size of the |Li-P| value, so that when deleting Li, you only need to find the first number each time. The timing of sorting can also be before calculating the aggregate evaluation value, so that when marking the first regular range, you can directly find the first and last digits to reduce the search time.

[0041] As another embodiment, when a chaotic signal is generated, the corresponding cumulative consumption for each of the past m months is also obtained. The cumulative consumption is the energy value consumed by the device each month. m is set according to specific needs, and the cumulative consumption for m months is marked as Gj, j=1, 2, ..., m.

[0042] Then calculate the mean Y of the cumulative consumption Gj for m months, that is:

[0043]

[0044] Then, through the mean Y, we get the aggregate evaluation value H1 of Gj, that is:

[0045]

[0046] Further, determine whether the aggregate evaluation value H1 is greater than the preset value X3. If it is less than or equal to the preset value X3, then mark the value range from the minimum to the maximum value of Gj as the third regular range. At this time, the cumulative consumption of the mixed target at the end of the month will be obtained and marked as the real-time cumulative consumption. Then, determine whether the real-time cumulative consumption is within the third regular range. If it is, mark the real-time cumulative consumption as reasonable data and do not process it. Otherwise, generate a suspicion signal, and remind the management personnel to verify whether the real-time cumulative consumption is correct.

[0047] If the aggregate evaluation value H1 is greater than the preset value X3, and Gj is sorted in order from large to small according to the size of the |Gj-P| value, then Gj is deleted in order from large to small, and then the aggregate evaluation value H1 of Gj after the value is deleted is recalculated until the aggregate evaluation value H1 is less than or equal to the preset value X3; at this time, the number of deleted Gj is obtained, and the value obtained by dividing it by n is marked as the second deletion ratio. When the second deletion ratio exceeds the preset value X2, a chaotic signal is generated, and then no processing is performed, otherwise a regular signal is generated. When a regular signal is generated, the value range from the minimum value to the maximum value of the Gj that remains to be deleted is marked as the fourth regular range, and then the cumulative consumption generated by the mixed target at the end of the month is obtained, and it is marked as the real-time cumulative consumption, and then it is determined whether the real-time cumulative consumption is within the fourth regular range. If it is, the real-time cumulative consumption is marked as reasonable data and no processing is performed, otherwise a suspicious signal is generated, and the management personnel are reminded to verify whether the real-time consumption is correct.

[0048] The present invention also switches the energy supply mode used by the device supporting multiple energy supply modes, and specifically switches through the following method:

[0049] like Figure 2 As shown, any mixed target is selected, all its energy supply modes are obtained, and all energy supply modes supported by the mixed target are marked as supply points, and the billing rules for each supply point are obtained; wherein the energy supply mode is the power proportion occupied by multiple energy supply points when the equipment functions, for example, one energy supply mode is 30% photovoltaic discharge, 30% wind discharge, 30% grid discharge and 10% energy storage discharge, and the other is 0% photovoltaic discharge, 30% wind discharge, 40% grid discharge and 30% energy storage discharge; since the energy supply points occupy different proportions when supplying energy, even if the energy unit price of a certain energy supply point is the lowest at this time, but its proportion is the highest, it will result in high costs; therefore, it is necessary to calculate the cost required for each energy supply mode to reach the next energy level.

[0050] The supply point currently in use is marked as an instant supply point, the difference between the cumulative consumption of the mixed label and the energy consumption level under the next tiered billing rule is obtained, and the value obtained by dividing the difference by the next energy consumption level is marked as the gear-up ratio.

[0051] When the upshift ratio is less than the preset value B1, no processing is performed; otherwise, the difference is multiplied by the billing rules of the energy supply method currently being used by the equipment at the current gear to obtain the immediate bidding fee; and the difference is multiplied by the billing rules of the remaining supply point methods of the equipment at the current gear to obtain the bidding fee.

[0052] A corresponding supply point with the lowest cost is selected from the instant bidding fee and the bidding fee. At this time, the supply point will be switched to the energy supply method used by the mixed target next to provide energy for the mixed target. At the same time, the supply point will be marked as an instant supply point and monitored in the same way.

[0053] System Example:

[0054] This embodiment provides a smart building comprehensive energy consumption monitoring system. When the system detects the comprehensive energy consumption of the smart building, the processor in the system executes a computer program implemented by the method introduced in the method embodiment. Since the introduction of the method is clear enough, it will not be repeated here.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for monitoring comprehensive energy consumption of smart buildings, characterized in that: The steps include: Obtaining the instantaneous consumption of the equipment in the smart building for a preset number of days, where the instantaneous consumption is the energy consumed by the equipment every day, and determining the regular range of the instantaneous consumption according to the data discreteness of the instantaneous consumption for the preset number of days; If the energy consumed by the equipment on that day is within the regular range, the energy consumed on that day is marked as reasonable data; otherwise, it is marked as abnormal data.

2. The method for monitoring comprehensive energy consumption of smart buildings according to claim 1, characterized in that: The lower limit and the upper limit of the regular range of the instant consumption are obtained according to the minimum value and the maximum value of the instant consumption of the preset days, respectively.

3. The method for monitoring comprehensive energy consumption of smart buildings according to claim 2, characterized in that: When determining the lower limit and the upper limit of the regular range, the instantaneous consumption of the preset days is also processed through the following steps: The first aggregate evaluation value is obtained by the following formula: Wherein, H is the first aggregate evaluation value, n is the preset number of days, Li is the instant consumption corresponding to the preset number of days, and P is the average of the instant consumption of the preset number of days; When the first aggregate evaluation value is greater than a first preset value, one instant consumption is selected from the instant consumption of the preset days and deleted, and the first aggregate evaluation value is recalculated until the first aggregate evaluation value is less than or equal to the first preset value. A first deletion ratio is obtained according to the number of deletions, and when the first deletion ratio is less than or equal to a second preset value, the range from the minimum to the maximum value of the instant consumption of the preset days that have not been deleted is marked as the lower limit and upper limit of the second regular range.

4. The method for monitoring comprehensive energy consumption of smart buildings according to claim 3, characterized in that: The instant consumption of the preset days is sorted from large to small according to the absolute value of the difference between the instant consumption of the preset days and the mean value. When the instant consumption needs to be deleted, it is deleted in descending order.

5. The method for monitoring comprehensive energy consumption of smart buildings according to claim 3, characterized in that: When the deletion ratio is greater than a second preset value, the cumulative consumption of the equipment in the smart building for a preset number of months is also obtained, where the cumulative consumption is the energy consumed by the equipment each month, and the regular range of the cumulative consumption is determined according to the data discreteness of the cumulative consumption for the preset number of months; If the energy consumed by the equipment in the current month is within the regular range, the energy consumed in the current month is marked as reasonable data; otherwise, it is marked as abnormal data.

6. The method for monitoring comprehensive energy consumption of smart buildings according to claim 5, characterized in that: The lower limit and the upper limit of the regular range of the cumulative consumption are obtained according to the minimum value and the maximum value of the cumulative consumption of the preset number of months.

7. The method for monitoring comprehensive energy consumption of smart buildings according to claim 6, characterized in that: When determining the lower limit and the upper limit of the regular range, the accumulated consumption of the preset number of months is also processed through the following steps: The second aggregate evaluation value is obtained by the following formula: Wherein, H1 is the second aggregate evaluation value, n is the preset number of months, Gj is the cumulative consumption corresponding to the preset number of months, and P is the average of the cumulative consumption of the preset number of months; When the second aggregate evaluation value is greater than the third preset value, one cumulative consumption is selected from the cumulative consumption of the preset number of months and deleted, and the second aggregate evaluation value is recalculated until the second aggregate evaluation value is less than or equal to the third preset value. The second deletion ratio is obtained according to the number of deletions. When the second deletion ratio is less than or equal to the second preset value, the range from the minimum to the maximum value of the cumulative consumption of the preset number of months that have not been deleted is marked as the lower limit and upper limit of the fourth regular range.

8. The method for monitoring comprehensive energy consumption of smart buildings according to claim 7, characterized in that: The accumulated consumption of the preset months is sorted from large to small according to the absolute value of the difference between the accumulated consumption of the preset months and the mean value. When the accumulated consumption needs to be deleted, it is deleted in descending order.

9. The method for monitoring comprehensive energy consumption of smart buildings according to claim 5, characterized in that: When the equipment is powered by multiple energy supply methods, and each energy supply point is under the corresponding tiered energy consumption billing rules, the energy consumption levels of the tiered energy consumption billing rules of each energy supply point are the same but the unit fees are different, and each energy supply method includes multiple energy supply points that supply energy to the equipment according to the corresponding set power ratio; the energy consumption difference between the current cumulative consumption of the equipment and the next energy consumption level is obtained, and the energy consumption difference is divided by the next energy consumption level to obtain the gear-up ratio; when the gear-up ratio is less than or equal to the fourth preset value, the energy consumption cost before the next energy consumption level is calculated under each energy supply method according to the tiered energy consumption billing rules of each energy supply point, and the energy supply method with the lowest energy consumption cost is selected to power the equipment.

10. A smart building comprehensive energy consumption monitoring system, comprising a processor, characterized in that: The processor is used to execute a computer program to implement the steps of the smart building comprehensive energy consumption monitoring method according to any one of claims 1 to 9.

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