Intelligent building energy consumption abnormity monitoring method and system

Abstract

The invention relates to the related field of energy consumption monitoring management and control, and discloses an intelligent building energy consumption abnormity monitoring method and system, which is characterized in that electric equipment is grouped by adopting a mode of purposes and spatial positions, the energy consumption of partitions in a building is supervised and controlled, and the energy consumption of the partitions is monitored and controlled in the peak period of power consumption. If not, the power utilization priorities can be judged on the basis of the groups, so that the electronic energy consumption limiting wall is set according to the power utilization priorities of different management groups, the low-priority equipment can distribute certain energy consumption to maintain normal operation of necessary power utilization equipment, and intelligent energy consumption monitoring and power utilization scheduling in the building are realized.

Description

Technical Field

[0001] The present invention relates to the field of energy consumption monitoring and control, and in particular to a method and system for monitoring abnormal energy consumption in an intelligent building. Background Art

[0002] With the increase in a large number of electrical equipment, the demand for power supply has also increased, especially for equipment-intensive places such as office buildings, residences, and shopping malls. Stable energy supply is even more important. For workplaces such as office buildings, the company equipment inside will be constantly replaced as the company changes during their service life, which causes the overall energy supply demand of the building to continue to change. Therefore, when the season enters late summer or late winter, it is easy for energy demand to reach the top of the total energy supply capacity.

[0003] In order to cope with this situation and ensure the stable production of enterprises in the building, effective energy consumption estimation and scheduling management are needed. In the existing technology, most of them adopt manual scheduling. When the energy consumption reaches the peak, the management personnel will shut down some non-essential power facilities for coordination. However, this method cannot respond to the problem of insufficient energy supply in time, and there is a serious lag in processing, which may affect the progress of production. At the same time, the manual prediction method has a large execution error, and the manual shutdown and startup scheduling is cumbersome. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for monitoring abnormal energy consumption of intelligent buildings to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for monitoring abnormal energy consumption of an intelligent building, comprising:

[0007] Obtaining a list of supervised equipment and dividing it into groups and intervals; obtaining a list of electrical equipment in a building and the location tags and category tags corresponding to the electrical equipment, and dividing several of the electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to characterize the categories of electrical equipment, and the intervals are used to characterize the location spaces of the electrical equipment;

[0008] Evaluate the historical data characteristics of group interval equipment; collect statistics on the historical power consumption records of several power-consuming equipment based on a preset cycle period to obtain the periodic power consumption curve of the power-consuming equipment;

[0009] Estimation and judgment of collaborative energy consumption of groups and intervals; divide power-consuming equipment into equipment management groups based on groups and intervals, and estimate the power consumption of equipment management groups at future time points to obtain the energy consumption requirements of management groups corresponding to time nodes;

[0010] Priority inducement determination and grading of group intervals and equipment; when the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of multiple management groups are judged to obtain the energy supply priority order of several management groups;

[0011] Electronic energy consumption restriction scheduling, allocation and management; generating an energy consumption restriction scheme based on the energy supply priority sequence, wherein the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

[0012] As a further solution of the present invention: the group includes a work support group, an environment support group and an infrastructure group, the environment support group includes a temperature adjustment subgroup, and when multiple management groups are characterized as temperature adjustment subgroups, the step of judging the priority induction conditions of multiple management groups and then obtaining the energy supply priority order of the multiple management groups specifically includes:

[0013] Obtaining a building lighting distribution model and marking the locations of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of thermal radiation per unit area of ​​each angle of the building during the daily cycle;

[0014] Obtain the thermal radiation intensity at each time point in the current daily cycle, and calculate the average thermal radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the lighting area, the total thermal radiation is marked as zero;

[0015] An energy supply priority order is established based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority; when the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

[0016] As a further solution of the present invention: the infrastructure group includes a basement facility subgroup and a necessary facility subgroup, the necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation, and the necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the step of judging the priority induction conditions of multiple management groups and then obtaining the energy supply priority order of the multiple management groups specifically includes:

[0017] Based on the daily cycle, historical personnel passage records of several management groups are obtained and counted to obtain the changing relationship between personnel density and time axis within the daily cycle;

[0018] The time axis of the daily cycle is divided into multiple sub-assessment time periods, and the average personnel density of the multiple sub-assessment time periods is calculated and obtained;

[0019] An energy supply priority order is established based on the descending sequence of the average population density; the energy supply priority order is used to indicate that the greater the average population density of the corresponding sub-evaluation time period, the higher the energy supply priority.

[0020] As a further solution of the present invention: it also includes a stable energy supply range and an instantaneous peak energy supply range, the stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time, the control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

[0021] As a further solution of the present invention: it also includes the steps of:

[0022] Based on a daily cycle, historical energy consumption records of several management groups characterized as work support groups are obtained to obtain a relationship between energy consumption of the array and the time axis in the daily cycle, that is, an energy consumption record curve;

[0023] Performing regression analysis on the energy consumption record curves in the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve fitted by the high frequency of the historical energy consumption record is marked as the basic demand curve;

[0024] Based on the basic demand curve, the other energy consumption demand curves are judged. If the other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within the daily cycle, they are marked as characteristic demand curves;

[0025] When determining the total energy consumption demand of a building and the control threshold, an additional determination is made on the total energy consumption demand based on the time period in which the energy consumption peak occurs within the daily cycle.

[0026] The embodiment of the present invention aims to provide a smart building energy consumption abnormality monitoring system, comprising:

[0027] The block splitting module is used to monitor the acquisition of the equipment list and the division of groups and intervals; obtain the list of electrical equipment in the building and the location tags and category tags corresponding to the electrical equipment, and divide the electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to represent the categories of electrical equipment and the intervals are used to represent the location spaces of electrical equipment;

[0028] The feature statistics module is used to evaluate the historical data features of group interval equipment; based on the preset cycle period, the historical power consumption records of several power-consuming equipment are counted to obtain the periodic power consumption curve of the power-consuming equipment;

[0029] Energy consumption assessment module, used for collaborative energy consumption estimation and judgment of groups and intervals; divides power-consuming equipment into equipment management groups based on groups and intervals, and estimates the power consumption of equipment management groups at future time points, and obtains the energy consumption requirements of management groups corresponding to time nodes;

[0030] The priority determination module is used to determine and grade the priority inducements of group intervals and equipment. When the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of multiple management groups are judged to obtain the energy supply priority order of several management groups.

[0031] The energy consumption control module is used for electronic energy consumption restriction scheduling, allocation and management; based on the energy supply priority sequence, an energy consumption restriction scheme is generated, and the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

[0032] As a further solution of the present invention: the group includes a work support group, an environment support group and an infrastructure group, the environment support group includes a temperature adjustment subgroup, and when a plurality of the management groups are characterized as temperature adjustment subgroups, the priority determination module includes:

[0033] A model synchronization unit, used to obtain a building lighting distribution model and mark the positions of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of heat radiation per unit area of ​​each angle of the building during the daily cycle time;

[0034] The radiation evaluation unit is used to obtain the thermal radiation intensity at each time point in the current daily cycle, and calculate the average thermal radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the lighting area, the total thermal radiation is marked as zero;

[0035] The priority determination unit is used to establish an energy supply priority order based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority. When the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

[0036] As a further solution of the present invention: the infrastructure group includes a basement facility subgroup and a necessary facility subgroup, the necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation, and the necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the priority determination module includes:

[0037] The crowd counting unit is used to obtain and count the historical personnel passage records of several management groups based on a daily cycle, and obtain the relationship between the change of personnel density and the time axis within the daily cycle;

[0038] A time splitting unit is used to split the time axis of the daily cycle into multiple sub-evaluation time periods, and calculate and obtain the average personnel density of the multiple sub-evaluation time periods;

[0039] The priority determination unit is used to establish an energy supply priority order based on the descending sequence of the average personnel density; the energy supply priority order is used to indicate that the greater the average personnel density in the corresponding sub-evaluation time period, the higher the energy supply priority.

[0040] As a further solution of the present invention: it also includes a stable energy supply range and an instantaneous peak energy supply range, the stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time, the control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

[0041] As a further solution of the present invention: it also includes a redundancy determination module, specifically including:

[0042] A historical synchronization unit, used for acquiring historical energy consumption records of a plurality of management groups characterized as work support groups based on a daily cycle, so as to obtain a relationship between energy consumption of the array and a time axis in a daily cycle, that is, an energy consumption record curve;

[0043] A fitting evaluation unit, used for performing regression analysis on the energy consumption record curves of the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve of the high frequency fitting of the historical energy consumption record is marked as the basic demand curve;

[0044] A characteristic judgment unit, used for judging other energy consumption demand curves based on the basic demand curve, if other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within a daily cycle, then the corresponding ones are marked as characteristic demand curves;

[0045] The redundant judgment unit is used to make an additional judgment on the total energy consumption demand based on the time period of the energy consumption peak in the daily cycle when judging the total energy consumption demand of the building and the control threshold.

[0046] Compared with the prior art, the beneficial effects of the present invention are: by grouping electrical equipment according to purpose and spatial location, zoned energy consumption supervision and control within the building can be achieved; during peak electricity consumption periods, electricity priority can be determined based on the grouping, and electronic energy consumption limit walls can be set according to the electricity priority of different management groups, so that low-priority equipment can be allocated a certain amount of energy consumption to maintain the normal operation of necessary electrical equipment, thereby realizing intelligent energy consumption monitoring and electricity scheduling within the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The present invention is a flowchart of a method for monitoring abnormal energy consumption in intelligent buildings.

[0048] Figure 2 The present invention is a flowchart of the steps of obtaining the energy supply priority order in a method for monitoring abnormal energy consumption in an intelligent building.

[0049] Figure 3 The following is a block diagram of the composition of an intelligent building energy consumption abnormality monitoring system. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0052] like Figure 1 The method for monitoring abnormal energy consumption of a smart building provided by an embodiment of the present invention comprises the following steps:

[0053] S10, obtaining a list of supervised equipment and dividing it into groups and intervals; obtaining a list of electrical equipment in a building and the location tags and category tags corresponding to the electrical equipment, and dividing a number of the electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to characterize the categories of the electrical equipment, and the intervals are used to characterize the location spaces of the electrical equipment;

[0054] S20, evaluating the historical data characteristics of the devices in the group interval; performing statistics on the historical power consumption records of several power-consuming devices based on a preset cycle period to obtain a periodic power consumption curve of the power-consuming devices;

[0055] S30, estimating and judging the collaborative energy consumption of groups and intervals; dividing the electrical equipment into equipment management groups based on the groups and intervals, and estimating the electrical energy consumption of the equipment management groups at future time points, and obtaining the energy consumption requirements of the management groups corresponding to the time nodes;

[0056] S40, determining and grading the priority inducement of group intervals and equipment; when the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of multiple management groups are judged, and then the energy supply priority order of several management groups is obtained;

[0057] S50, electronic energy consumption restriction scheduling, allocation and management; generating an energy consumption restriction scheme based on the energy supply priority sequence, wherein the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

[0058] In this embodiment, a method for monitoring abnormal energy consumption in a smart building is provided. By grouping electrical equipment according to purpose and spatial location, energy consumption supervision and control of partitions in the building are implemented. During peak power consumption periods, power priority can be determined based on the grouping, and electronic energy consumption limit walls can be set according to the power priority of different management groups, so that low-priority equipment can be allocated a certain amount of energy consumption to maintain the normal operation of necessary electrical equipment, thereby realizing intelligent energy consumption monitoring and power scheduling in the building. With the rapid iteration and update of mechanical equipment products related to life and production, more and more electronic and electrical equipment are used in various scene functions, such as computers or related professional equipment for work, air-conditioning equipment for maintaining indoor temperature in hot and cold weather, etc. With the increase of electrical equipment, the demand for power supply also increases, especially for equipment-intensive places such as office buildings, residences, and shopping malls, stable energy supply is even more important. For workplaces such as office buildings, the company equipment inside will be constantly replaced with changes in the company during their service life, which leads to the continuous change of the overall energy supply demand of the building. Therefore, when the season enters late summer or late winter, it is easy for the energy demand to reach the top of the total energy supply capacity. Therefore, in order to ensure the stable production of enterprises in the building, effective energy consumption estimation and scheduling management are required. In the existing technology, most of them adopt manual scheduling. When the energy consumption reaches the top, the management personnel will shut down some non-essential power facilities, but this method has no effect. It is impossible to deal with the problem of reaching the ceiling in time. At the same time, the manual prediction method has a large execution error, and the manual shutdown and startup scheduling is relatively cumbersome. The solution in this embodiment is: classify the electrical equipment, and the classification includes two parts. One is the purpose classification, that is, the category label. For different purpose classifications, it corresponds to the priority level of electricity use. For example, the priority of office electricity use is higher than the priority of environmental electricity use such as refrigeration, and the priority of electricity use in idle time and unmanned places such as basements; the second is location classification. According to the location classification, two effects can be achieved. The first effect is that the electrical equipment of the same enterprise in the same office space can be concentrated and divided (for example, there are 50 computers on a certain floor of a building, belonging to three offices of two enterprises respectively). The second effect is that for the same electrical equipment under the same purpose classification, its usage priority will be different in different location environments. For example, the air conditioner in the office on the sunny side needs to work at a higher energy consumption if it wants to achieve a good cooling effect. On the contrary, the office in the shade does not need a higher working energy consumption, so its priority is lower. Through such classification management method and prediction based on the historical electricity consumption habits of these electrical equipment, if the total energy consumption supply of the building is about to reach its peak at a certain point in time or time period in the future, the energy consumption of low-priority electrical equipment will be restricted according to the priority, so that part of the energy consumption can be allocated to higher-priority electrical equipment, thereby ensuring the normal progress of major work needs.

[0059] like Figure 2 As shown, as another preferred embodiment of the present invention, the group includes a work support group, an environment support group and an infrastructure group, the environment support group includes a temperature adjustment subgroup, and when multiple management groups are characterized as temperature adjustment subgroups, the step of judging the priority induction conditions of multiple management groups and then obtaining the energy supply priority order of the multiple management groups specifically includes:

[0060] S41, obtaining a building lighting distribution model and marking the positions of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of heat radiation per unit area of ​​each angle of the building during the daily cycle time;

[0061] S42, obtaining the heat radiation intensity at each time point in the current daily cycle, and calculating the average heat radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the illumination area, the total heat radiation is marked as zero;

[0062] S43, establishing an energy supply priority order based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority order is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority; when the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

[0063] In this embodiment, the work support group is used to characterize the main equipment required for work, such as computers and production equipment. The temperature adjustment subgroup here specifically characterizes cooling and heating equipment such as air conditioners. Specifically, because different facades of the building will be affected by solar radiation during a day, the overall temperature of the office rooms connected to the facades will be higher than that of other rooms. Therefore, in the process of cooling and heating, its energy consumption demand and efficiency will also change. Therefore, energy consumption electronic walls can be set for rooms with higher cooling and heating efficiency to allocate part of the energy consumption for other operations. Among them, the embodiment is specifically based on summer cooling conditions. Therefore, the greater the unit volume of thermal radiation, the higher the energy supply priority. If it is under the premise of winter heating conditions, the greater the unit volume of thermal radiation, the lower the energy supply priority.

[0064] As another preferred embodiment of the present invention, the infrastructure group includes a basement facility subgroup and a necessary facility subgroup, the necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation, and the necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the step of judging the priority induction conditions of multiple management groups and then obtaining the energy supply priority order of several management groups specifically includes:

[0065] Based on the daily cycle, historical personnel passage records of several management groups are obtained and counted to obtain the changing relationship between personnel density and time axis within the daily cycle;

[0066] The time axis of the daily cycle is divided into multiple sub-assessment time periods, and the average personnel density of the multiple sub-assessment time periods is calculated and obtained;

[0067] An energy supply priority order is established based on the descending sequence of the average population density; the energy supply priority order is used to indicate that the greater the average population density of the corresponding sub-evaluation time period, the higher the energy supply priority.

[0068] In this embodiment, the infrastructure group is specifically described, wherein the necessary infrastructure may include the elevator group equipment of the building, the gas circulation equipment in the building, etc.; for places such as basements where no one exists for a long time, their priority can be determined by judging the flow of people, that is, in time periods with a large number of people, such as the morning, noon and evening time periods at the workplace, there are many people driving to the workplace, and a certain amount of energy consumption is required to ensure the coverage and operation of basic equipment such as lighting, while in other time periods there may be few people passing by, and energy consumption can be limited. Taking lighting as an example, this can be achieved by, for example, reducing the lighting density and the lighting brightness of a single device.

[0069] As another preferred embodiment of the present invention, it also includes a stable energy supply range and an instantaneous peak energy supply range, the stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time, the control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

[0070] In this embodiment, the stable energy supply range is the range within which the building power supply equipment can maintain a stable output for a long time. However, in actual use, in order to ensure the occurrence of extra long-term power consumption, it is necessary to reserve a certain amount of redundant power supply to achieve the purpose of responding to emergencies. Although the peak energy supply range is larger, it cannot be used as a conventional functional capability judgment standard, because it is the instantaneous overclocking capability of the functional equipment, which is designed to cope with the high energy consumption requirements generated when the equipment group is instantly started or damaged, and cannot be maintained for a long time. Therefore, it is not used as the basis for setting the control threshold.

[0071] As another preferred embodiment of the present invention, the steps are also included:

[0072] Based on a daily cycle, historical energy consumption records of several management groups characterized as work support groups are obtained to obtain a relationship between energy consumption of the array and the time axis in the daily cycle, that is, an energy consumption record curve;

[0073] Performing regression analysis on the energy consumption record curves in the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve fitted by the high frequency of the historical energy consumption record is marked as the basic demand curve;

[0074] Based on the basic demand curve, the other energy consumption demand curves are judged. If the other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within the daily cycle, they are marked as characteristic demand curves;

[0075] When determining the total energy consumption demand of a building and the control threshold, an additional determination is made on the total energy consumption demand based on the time period in which the energy consumption peak occurs within the daily cycle.

[0076] In this embodiment, for some management groups, if judged by cycles, there may be several cycles of excess energy consumption demands under uncertain specific rules within multiple cycles. For example, within 20 working days, a company's energy consumption in 15 working days is based on a relatively flat basic demand curve, while in the other 5 working days, its energy consumption demand increases significantly between 14:00 and 16:00 (possibly due to unconventional situations such as equipment testing), so the corresponding characteristic demand curve, and the specific dates of these 5 working days are also uncertain. Therefore, when making a judgment on the total energy consumption demand, it is necessary to set additional judgment reservations from 14:00 to 16:00 in each daily cycle on the basis of the basic demand curve to ensure that sufficient redundant energy supply can be dispatched when unconventional situations occur.

[0077] like Figure 3 As shown, the present invention also provides an intelligent building energy consumption abnormality monitoring system, which comprises:

[0078] The block splitting module 100 is used to obtain the list of supervised equipment and divide it into groups and intervals; obtain the list of electrical equipment in the building and the location tags and category tags corresponding to the electrical equipment, and divide the plurality of electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to represent the categories of electrical equipment and the intervals are used to represent the location spaces of the electrical equipment;

[0079] The feature statistics module 200 is used for evaluating the historical data features of the group interval devices; based on a preset cycle period, the historical power consumption records of several power-consuming devices are counted to obtain the periodic power consumption curve of the power-consuming devices;

[0080] The energy consumption evaluation module 300 is used for estimating and judging the collaborative energy consumption of groups and intervals; dividing the electrical equipment into equipment management groups based on groups and intervals, and estimating the electrical energy consumption of the equipment management groups at future time points, and obtaining the energy consumption requirements of the management groups corresponding to the time nodes;

[0081] The priority determination module 400 is used for determining and grading the priority inducements of group intervals and equipment; when the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of the multiple management groups are determined, and then the energy supply priority order of the several management groups is obtained;

[0082] The energy consumption control module 500 is used for electronic energy consumption restriction scheduling, allocation and management; an energy consumption restriction scheme is generated based on the energy supply priority sequence, and the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

[0083] As another preferred embodiment of the present invention, the group includes a work support group, an environment support group and an infrastructure group, the environment support group includes a temperature regulation subgroup, and when a plurality of the management groups are characterized as temperature regulation subgroups, the priority determination module includes:

[0084] A model synchronization unit, used to obtain a building lighting distribution model and mark the positions of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of heat radiation per unit area of ​​each angle of the building during the daily cycle time;

[0085] The radiation evaluation unit is used to obtain the thermal radiation intensity at each time point in the current daily cycle, and calculate the average thermal radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the lighting area, the total thermal radiation is marked as zero;

[0086] The priority determination unit is used to establish an energy supply priority order based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority. When the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

[0087] As another preferred embodiment of the present invention, the infrastructure group includes a basement facility subgroup and a necessary facility subgroup, the necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation, and the necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the priority determination module includes:

[0088] The crowd counting unit is used to obtain and count the historical personnel passage records of several management groups based on a daily cycle, and obtain the relationship between the change of personnel density and the time axis within the daily cycle;

[0089] A time splitting unit is used to split the time axis of the daily cycle into multiple sub-evaluation time periods, and calculate and obtain the average personnel density of the multiple sub-evaluation time periods;

[0090] The priority determination unit is used to establish an energy supply priority order based on the descending sequence of the average personnel density; the energy supply priority order is used to indicate that the greater the average personnel density in the corresponding sub-evaluation time period, the higher the energy supply priority.

[0091] As another preferred embodiment of the present invention, it also includes a stable energy supply range and an instantaneous peak energy supply range, the stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time, the control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

[0092] As another preferred embodiment of the present invention, it also includes a redundancy determination module, specifically including:

[0093] A historical synchronization unit, used for acquiring historical energy consumption records of a plurality of management groups characterized as work support groups based on a daily cycle, so as to obtain a relationship between energy consumption of the array and a time axis in a daily cycle, that is, an energy consumption record curve;

[0094] A fitting evaluation unit, used for performing regression analysis on the energy consumption record curves of the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve of the high frequency fitting of the historical energy consumption record is marked as the basic demand curve;

[0095] A characteristic judgment unit, used for judging other energy consumption demand curves based on the basic demand curve, if other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within a daily cycle, then the corresponding ones are marked as characteristic demand curves;

[0096] The redundant judgment unit is used to make an additional judgment on the total energy consumption demand based on the time period of the energy consumption peak in the daily cycle when judging the total energy consumption demand of the building and the control threshold.

[0097] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0098] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0099] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for monitoring abnormal energy consumption of intelligent buildings, characterized in that: Include: Obtaining a list of supervised equipment and dividing it into groups and intervals; obtaining a list of electrical equipment in a building and the location tags and category tags corresponding to the electrical equipment, and dividing several of the electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to characterize the categories of electrical equipment, and the intervals are used to characterize the location spaces of the electrical equipment; Evaluation of historical data characteristics of equipment in group intervals; Based on a preset cycle, historical power consumption records of several power-consuming devices are counted to obtain a cycle power consumption curve of the power-consuming devices; Estimation and judgment of collaborative energy consumption of groups and intervals; divide power-consuming equipment into equipment management groups based on groups and intervals, and estimate the power consumption of equipment management groups at future time points to obtain the energy consumption requirements of management groups corresponding to time nodes; Priority inducement determination and grading of group intervals and equipment; when the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of multiple management groups are judged to obtain the energy supply priority order of several management groups; Electronic energy consumption restriction scheduling, allocation and management; generating an energy consumption restriction scheme based on the energy supply priority sequence, wherein the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

2. The method for monitoring abnormal energy consumption of a smart building according to claim 1, characterized in that: The groups include a work support group, an environment support group, and an infrastructure group. The environment support group includes a temperature adjustment subgroup. When a plurality of the management groups are characterized as temperature adjustment subgroups, the step of judging the priority induction conditions of the plurality of management groups and then obtaining the energy supply priority order of the plurality of management groups specifically includes: Obtaining a building lighting distribution model and marking the locations of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of thermal radiation per unit area of ​​each angle of the building during the daily cycle; Obtain the thermal radiation intensity at each time point in the current daily cycle, and calculate the average thermal radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the lighting area, the total thermal radiation is marked as zero; An energy supply priority order is established based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority; when the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

3. The method for monitoring abnormal energy consumption of intelligent buildings according to claim 2, characterized in that: The infrastructure group includes a basement facility subgroup and a necessary facility subgroup. The necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation. The necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the step of judging the priority induction conditions of multiple management groups and then obtaining the energy supply priority order of the multiple management groups specifically includes: Based on the daily cycle, historical personnel passage records of several management groups are obtained and counted to obtain the changing relationship between personnel density and time axis within the daily cycle; The time axis of the daily cycle is divided into multiple sub-assessment time periods, and the average personnel density of the multiple sub-assessment time periods is calculated and obtained; An energy supply priority order is established based on the descending sequence of the average population density; the energy supply priority order is used to indicate that the greater the average population density of the corresponding sub-evaluation time period, the higher the energy supply priority.

4. The method for monitoring abnormal energy consumption of a smart building according to claim 1, characterized in that: It also includes a stable energy supply range and an instantaneous peak energy supply range. The stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time. The control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

5. The method for monitoring abnormal energy consumption of intelligent buildings according to claim 4, characterized in that: Also includes the steps: Based on a daily cycle, historical energy consumption records of several management groups characterized as work support groups are obtained to obtain a relationship between energy consumption of the array and the time axis in the daily cycle, that is, an energy consumption record curve; Performing regression analysis on the energy consumption record curves in the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve fitted by the high frequency of the historical energy consumption record is marked as the basic demand curve; Based on the basic demand curve, the other energy consumption demand curves are judged. If the other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within the daily cycle, they are marked as characteristic demand curves; When determining the total energy consumption demand of a building and the control threshold, an additional determination is made on the total energy consumption demand based on the time period in which the energy consumption peak occurs within the daily cycle.

6. An intelligent building energy consumption abnormality monitoring system, characterized in that: Include: The block splitting module is used to monitor the acquisition of the equipment list and the division of groups and intervals; obtain the list of electrical equipment in the building and the location tags and category tags corresponding to the electrical equipment, and divide the electrical equipment into groups and intervals based on the location tags and category tags, wherein the groups are used to represent the categories of electrical equipment and the intervals are used to represent the location spaces of electrical equipment; Feature statistics module, used for historical data feature evaluation of devices in group intervals; Based on a preset cycle, historical power consumption records of several power-consuming devices are counted to obtain a cycle power consumption curve of the power-consuming devices; Energy consumption assessment module, used for collaborative energy consumption estimation and judgment of groups and intervals; divides power-consuming equipment into equipment management groups based on groups and intervals, and estimates the power consumption of equipment management groups at future time points, and obtains the energy consumption requirements of management groups corresponding to time nodes; The priority determination module is used to determine and grade the priority inducements of group intervals and equipment. When the total energy consumption demand of several management groups in the building reaches the preset control threshold, the priority inducement conditions of multiple management groups are judged to obtain the energy supply priority order of several management groups. The energy consumption control module is used for electronic energy consumption restriction scheduling, allocation and management; based on the energy supply priority sequence, an energy consumption restriction scheme is generated, and the energy consumption restriction scheme is used to perform electronic energy consumption wall restriction on the management group with low energy supply priority.

7. The intelligent building energy consumption abnormality monitoring system according to claim 6 is characterized in that: The groups include a work support group, an environment support group, and an infrastructure group. The environment support group includes a temperature regulation subgroup. When a plurality of the management groups are characterized as temperature regulation subgroups, the priority determination module includes: A model synchronization unit, used to obtain a building lighting distribution model and mark the positions of several management groups in the building, wherein the lighting distribution model is set based on a daily cycle and is used to characterize the proportion of heat radiation per unit area of ​​each angle of the building during the daily cycle time; The radiation evaluation unit is used to obtain the thermal radiation intensity at each time point in the current daily cycle, and calculate the average thermal radiation per unit volume of the space where the management group is located at the estimated time node based on the location mark of the management group in the building. If the management group is not covered by the lighting area, the total thermal radiation is marked as zero; The priority determination unit is used to establish an energy supply priority order based on the descending order of the average thermal radiation per unit volume of several of the management groups; the energy supply priority is used to indicate that the larger the thermal radiation per unit volume, the higher the energy supply priority. When the total schedulable energy consumption of the temperature regulation subgroup is insufficient, an electronic energy consumption wall is set for the management group with low thermal radiation per unit volume.

8. The intelligent building energy consumption abnormality monitoring system according to claim 7 is characterized in that: The infrastructure group includes a basement facility subgroup and a necessary facility subgroup. The necessary facility subgroup is used to represent a collection of basic equipment necessary for building operation. The necessary facility subgroup has the highest energy supply priority. When multiple management groups are represented as basement facility subgroups, the priority determination module includes: The crowd counting unit is used to obtain and count the historical personnel passage records of several management groups based on a daily cycle, and obtain the relationship between the change of personnel density and the time axis within the daily cycle; A time splitting unit is used to split the time axis of the daily cycle into multiple sub-evaluation time periods, and calculate and obtain the average personnel density of the multiple sub-evaluation time periods; The priority determination unit is used to establish an energy supply priority order based on the descending sequence of the average personnel density; the energy supply priority order is used to indicate that the greater the average personnel density in the corresponding sub-evaluation time period, the higher the energy supply priority.

9. The intelligent building energy consumption abnormality monitoring system according to claim 6, characterized in that: It also includes a stable energy supply range and an instantaneous peak energy supply range. The stable energy supply range is used to characterize the maximum energy supply intensity that the building can maintain for a long time. The control threshold is smaller than the stable energy supply range, and the difference between the stable functional range and the control threshold is the redundant energy supply.

10. The intelligent building energy consumption abnormality monitoring system according to claim 9, characterized in that: It also includes a redundancy determination module, specifically including: A historical synchronization unit, used for acquiring historical energy consumption records of a plurality of management groups characterized as work support groups based on a daily cycle, so as to obtain a relationship between energy consumption of the array and a time axis in a daily cycle, that is, an energy consumption record curve; A fitting evaluation unit, used for performing regression analysis on the energy consumption record curves of the array to obtain the energy consumption demand curve by fitting. If the number of the energy consumption demand curves fitted is not unique, the energy consumption demand curve of the high frequency fitting of the historical energy consumption record is marked as the basic demand curve; A characteristic judgment unit, used for judging other energy consumption demand curves based on the basic demand curve, if other energy consumption demand curves have energy consumption peaks higher than the basic demand curve within a daily cycle, then the corresponding ones are marked as characteristic demand curves; The redundant judgment unit is used to make an additional judgment on the total energy consumption demand based on the time period of the energy consumption peak in the daily cycle when judging the total energy consumption demand of the building and the control threshold.

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