Smart building energy consumption management system for public institutions

Abstract

The present invention discloses a smart management system for building energy consumption applied to public institutions, relates to the technical field of energy management, and improves the accuracy of energy management for public institutions. The present invention obtains the normal use time and normal use section of each power device according to historical operation records and historical equipment operation event records, and obtains the normal total power change curve of each energy detection area according to the historical area operation event record, and sets a pre-stored allocation power for each energy detection area according to the normal total power change curve of each energy detection area, and then obtains the current operation status of each power device in each energy detection area at the beginning of each time section, and obtains the estimated power usage of the corresponding energy detection area according to the normal use time and normal use section of each power device, and adjusts the numerical value of the pre-stored allocation power by comparing the pre-stored allocation power with the estimated power usage.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and in particular to an intelligent building energy consumption management system applied to public institutions. Background Art

[0002] As global energy shortages and environmental problems become increasingly serious, energy management in public institutions has become an important part of promoting sustainable development and energy conservation and emission reduction. Public institutions usually have large building areas and high-intensity energy consumption.

[0003] Existing energy management technologies in public institutions have the following shortcomings:

[0004] High complexity of data processing: A large amount of energy consumption data needs to be processed and analyzed in real time, including data cleaning, calibration, storage and visualization. Existing data processing technologies may experience delays and low processing efficiency when faced with high-frequency and large-scale data, affecting the real-time and accuracy of the system.

[0005] Difficulty in data integration: Since there are several independently operated work areas within public institutions, it is difficult to accurately predict and dispatch energy for each work area within the public institutions;

[0006] Therefore, how to improve the accuracy of energy consumption data processing results while achieving accurate energy forecasting for various work areas within public institutions is a difficulty of the existing technology. For this purpose, an intelligent building energy consumption management system for public institutions is provided. Summary of the invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide a building energy consumption intelligent management system for public institutions.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] A smart building energy consumption management system for public institutions includes a cloud computing platform, wherein the cloud computing platform is communicatively connected to an institution operation record collection module, an energy consumption analysis module, and an energy dispatch management module;

[0010] The institution operation record collection module is used to divide the public institution into several energy detection areas, and then collect the historical personnel interaction records, historical equipment operation event records and historical area operation event records of each power equipment in each energy detection area;

[0011] The energy consumption analysis module is used to establish an equipment operation event tree based on historical operation records and historical equipment operation event records, and obtain the normal use time and normal use section of each power equipment. At the same time, it establishes a regional operation event tree based on historical regional operation event records, and then obtains the normal total power change curve of each energy detection area;

[0012] The energy dispatching management module is used to set a number of time segments, and set a pre-stored allocated power for each energy detection area according to the normal total power change curve of each energy detection area. Then, when a time segment begins, the current operating status of each power equipment in each energy detection area is obtained, and the estimated power usage of the corresponding energy detection area is obtained according to the normal usage time and normal usage segment of each power equipment. By comparing the pre-stored allocated power with the estimated power usage, the numerical value of the pre-stored allocated power is adjusted according to the comparison result.

[0013] Furthermore, the collection process of the historical personnel interaction records, historical equipment operation event records and historical area operation event records includes:

[0014] The institution operation record collection module divides the target public institution into n energy detection areas according to the distribution of houses in the target public institution, where n is a natural number greater than 0;

[0015] Set working state, standby state and shutdown state for each power device, obtain the rated power range of each power device under normal working state through the Internet, and use seven days as a data collection cycle;

[0016] Whenever an electric power equipment is used, historical personnel interaction records, historical equipment operation event records and historical regional operation event records are automatically generated. Whenever a data collection cycle ends, the organization operation record collection module integrates all records generated by the corresponding data collection cycle to generate historical personnel interaction data sets, historical equipment operation event data sets and historical regional operation event data sets.

[0017] Furthermore, the personnel interaction record includes the record generation time, the pedestrian's interaction start time and interaction end time, and the relevant power equipment number;

[0018] The historical equipment operation event record includes the power equipment number, power change curve, and current state name;

[0019] The historical regional operation event record includes a historical total power change curve and a power equipment number associated with a fluctuation position on the historical total power change curve.

[0020] Furthermore, the process of establishing the device operation event tree includes:

[0021] Overlap and splice the historical power change curves contained in the historical equipment operation event data segments from the same historical equipment operation event data set and corresponding to the same day in sequence, and set an operation event node at the splicing point;

[0022] At the same time, according to the recorded pedestrian interaction start time and interaction end time of each historical personnel interaction record in the historical personnel interaction data segment, a number of personnel start interaction nodes and personnel end interaction nodes are set on the overlapping and spliced ​​historical power change curve, and the same label is set for the personnel start interaction nodes and personnel end interaction nodes from the same historical personnel interaction record;

[0023] Then, the overlapping and spliced ​​historical power change curves from the same historical personnel interaction record are connected in sequence to obtain the equipment operation event tree of the corresponding power equipment in the corresponding data collection period.

[0024] Furthermore, the process of obtaining the normal use time and normal use section of each power equipment includes:

[0025] Through the personnel start interaction node and the personnel end interaction node on the operation event tree of each device, the usage duration and usage time segment of the corresponding power equipment are obtained, and the usage duration and usage time segment are normally distributed. The central value of the normal distribution is selected to obtain the normal usage duration and normal usage segment of each power equipment.

[0026] Furthermore, the process of establishing the regional operation event tree includes:

[0027] By adopting the process of establishing the equipment operation event tree, the historical total power change curves contained in the historical regional operation event data segments corresponding to the same day from the same historical regional operation event data set are overlapped and spliced ​​in sequence, and at the same time, a number of time segments are set on the overlapping and spliced ​​historical total power change curves, so as to obtain the regional operation event tree under the corresponding data collection period;

[0028] A two-dimensional coordinate system is established, and the overlapping and spliced ​​historical total power change curves corresponding to the same energy detection area but different data collection periods are mapped onto the same two-dimensional coordinate system, and a number of equal-length time segments are divided on the coordinate axis associated with time in the two-dimensional coordinate system;

[0029] Obtain the area value between each time segment and the coordinate axis of the associated time of each overlapping and spliced ​​historical total power change curve, and record it as the total power value in the corresponding time segment;

[0030] Then, the total power values ​​of the historical total power change curves after different overlaps and splicing in the same time segment are normally distributed, and the normal area total value at the normal distribution center position is selected, and the historical total power change curve segment corresponding to the normal total power value is selected, which is recorded as the normal power change segment in the corresponding time segment;

[0031] The normal power change sections of each time section are connected in sequence to obtain the normal total power change curve of each energy detection area.

[0032] Furthermore, the process of obtaining the estimated power usage of the energy detection area includes:

[0033] According to the normal power change section of each energy detection area in each time section, set the pre-stored allocation power for each energy detection area;

[0034] Whenever a time period begins, the running time of the power equipment currently in working state in each energy detection area is obtained, and according to the normal use time of the corresponding power equipment, the estimated use time of the corresponding power equipment in the time period is obtained, and then the estimated power consumption of the corresponding power equipment in the time period is obtained. At the same time, whenever a power equipment is started, the estimated power consumption of the corresponding power equipment in the time period is obtained according to the normal use time of the corresponding power equipment;

[0035] For the power equipment in standby state in each energy detection area, the pending power usage of the corresponding energy detection area is obtained according to the proportion of the normal use period of each power equipment in the current time period, and no operation is performed on the power equipment in the off state;

[0036] The predicted power usage and pending power usage of each energy detection area in the current time segment are added together to obtain the estimated power usage value of the corresponding energy detection area in the current time segment.

[0037] Furthermore, the adjustment process of the pre-stored allocated power includes:

[0038] Set the estimated power difference interval, and then determine whether the difference between the estimated power usage value of each energy detection area and the corresponding pre-stored allocated power in the current time period is less than or equal to the estimated power difference threshold;

[0039] If the difference is within the estimated power difference range, no action is taken;

[0040] If the difference is less than the estimated power difference range, the energy scheduling management module supplements the estimated power usage value according to the difference until the difference is within the estimated power difference range;

[0041] If the difference is greater than the estimated power difference range, the energy scheduling management module reduces the estimated power usage value according to the size of the difference until the difference is within the estimated power difference range.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention establishes an equipment operation event tree according to historical operation records and historical equipment operation event records, and obtains the normal use time and normal use section of each electric equipment. At the same time, a regional operation event tree is established according to historical regional operation event records, and then the normal total power change curve of each energy detection area is obtained. A number of time sections are set, and a pre-stored allocation power is set for each energy detection area according to the normal total power change curve of each energy detection area. Then, whenever a time section begins, the current operation status of each electric equipment in each energy detection area is obtained, and according to the normal use time and normal use section of each electric equipment, the estimated usage power of the corresponding energy detection area is obtained. By comparing the pre-stored allocation power with the estimated usage power, the numerical value of the pre-stored allocation power is adjusted according to the comparison result, thereby achieving accurate energy prediction and allocation for each work area in a public institution while improving the accuracy of the processing results of the energy consumption data. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0045] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0046] like Figure 1 As shown, the building energy consumption intelligent management system applied to public institutions includes a cloud computing platform, and the cloud computing platform is communicatively connected with an institution operation record collection module, an energy consumption analysis module, and an energy dispatch management module;

[0047] The institution operation record collection module is used to divide the public institution into several energy detection areas, and then collect the historical personnel interaction records, historical equipment operation event records and historical area operation event records of each power equipment in each energy detection area;

[0048] The energy consumption analysis module is used to establish an equipment operation event tree based on historical operation records and historical equipment operation event records, and obtain the normal use time and normal use section of each power equipment. At the same time, it establishes a regional operation event tree based on historical regional operation event records, and then obtains the normal total power change curve of each energy detection area;

[0049] The energy dispatching management module is used to set a number of time segments, and set a pre-stored allocated power for each energy detection area according to the normal total power change curve of each energy detection area. Then, when a time segment begins, the current operating status of each power equipment in each energy detection area is obtained, and the estimated power usage of the corresponding energy detection area is obtained according to the normal usage time and normal usage segment of each power equipment. By comparing the pre-stored allocated power with the estimated power usage, the numerical value of the pre-stored allocated power is adjusted according to the comparison result.

[0050] Further, the working principle of the present invention is described below by way of examples:

[0051] The institution operation record collection module divides the target public institution into n energy detection areas according to the distribution of houses in the target public institution, and then marks the power equipment in each energy detection area with a number. 1，1 、a 1，2 、a 1，3 ,……,a n，m , where a n，m represents the mth power equipment in the nth energy detection area, where n and m are natural numbers greater than 0;

[0052] Each power device in the energy detection area is connected in parallel through a line, and a sub-power sensor is installed at the connection between each line and the power device. At the same time, a total power sensor is installed in each energy detection area, and the power equipment is equipped with a face recognition device;

[0053] The mechanism operation record collection module communicates with all sub-power sensors, face recognition devices and various power sensors, and sets the working state, standby state and shutdown state for each power equipment;

[0054] The rated power range of each power equipment under normal working conditions is obtained through the Internet, and a data collection cycle is seven days. It should be noted that there are additional data collection cycles for special periods, such as holidays, such as the Spring Festival and National Day;

[0055] Furthermore, whenever a facial recognition device detects that a pedestrian uses its associated power equipment, the facial recognition device and the related sub-power sensors and total power sensors respectively generate historical personnel interaction records, historical equipment operation event records, and historical area operation event records, and upload the historical personnel interaction records, historical equipment operation event records, and historical area operation event records to the organization operation record collection module;

[0056] Whenever a data collection cycle ends, the organization operation record collection module integrates all records generated by the corresponding data collection cycle to generate a historical personnel interaction data set, a historical equipment operation event data set, and a historical regional operation event data set;

[0057] The personnel interaction record includes the record generation time, the pedestrian interaction start time and interaction end time and the relevant power equipment number;

[0058] The historical equipment operation event record includes the power equipment number, power change curve, and current state name;

[0059] The historical regional operation event record includes a historical total power change curve and a power equipment number associated with a fluctuation position on the historical total power change curve.

[0060] Further, the organization operation record collection module sends all historical personnel interaction data sets, historical equipment operation event data sets, and historical regional operation event data sets to the energy consumption analysis module;

[0061] Establishing the equipment operation event tree and the regional operation event tree in the corresponding data collection period according to the historical personnel interaction data set, the historical equipment operation event data set and the historical regional operation event data set;

[0062] The process of establishing the equipment operation event tree includes: dividing the historical personnel interaction data set and the historical equipment operation event data set into seven historical personnel interaction data segments and historical equipment operation event data segments on a daily basis;

[0063] Overlap and splice the historical power change curves contained in the historical equipment operation event data segments from the same historical equipment operation event data set and corresponding to the same day in sequence, and set an operation event node at the splicing point;

[0064] At the same time, according to the recorded pedestrian interaction start time and interaction end time of each historical personnel interaction record in the historical personnel interaction data segment, a number of personnel start interaction nodes and personnel end interaction nodes are set on the overlapping and spliced ​​historical power change curve, and the same label is set for the personnel start interaction nodes and personnel end interaction nodes from the same historical personnel interaction record;

[0065] Then, the overlapping and spliced ​​historical power change curves from the same historical personnel interaction record are connected in sequence to obtain the equipment operation event tree of the corresponding power equipment in the corresponding data collection period;

[0066] At the same time, through the personnel start interaction node and the personnel end interaction node on the operation event tree of each device, the usage time and usage time segment of the corresponding power equipment are obtained, and the usage time and usage time segment are normally distributed, and the center value of the normal distribution is selected to obtain the normal usage time and normal usage segment of each power equipment;

[0067] It should be noted that whenever a historical personnel interaction dataset and a historical equipment operation event dataset are generated in a data collection cycle, the normal usage duration and normal usage segment are automatically updated, and the historical personnel interaction dataset and the historical equipment operation event dataset with the longest generation time are deleted at the same time.

[0068] Furthermore, by adopting the process of establishing the equipment operation event tree, the historical total power change curves contained in the historical regional operation event data segments corresponding to the same day from the same historical regional operation event data set are overlapped and spliced ​​in sequence, and at the same time, a number of time segments are set on the historical total power change curves after overlapped and spliced;

[0069] According to the historical equipment operation event records contained in the historical equipment operation event data set corresponding to each historical area operation event data set, the total power change values ​​of each power equipment in the corresponding energy detection area at each time node in each time segment are summarized, and the occurrence nodes of each total power change value are marked on the historical total power change curve after overlapping and splicing;

[0070] Then, the overlapping and spliced ​​historical total power change curves corresponding to each energy detection area in the same data collection period are spliced ​​in chronological order, so as to obtain the regional operation event tree in the corresponding data collection period;

[0071] A two-dimensional coordinate system is established, and the overlapping and spliced ​​historical total power change curves corresponding to the same energy detection area but different data collection periods are mapped onto the same two-dimensional coordinate system, and a number of equal-length time segments are divided on the coordinate axis associated with time in the two-dimensional coordinate system;

[0072] Obtain the area value between each time segment and the coordinate axis of the associated time of each overlapping and spliced ​​historical total power change curve, and record it as the total power value in the corresponding time segment;

[0073] Then, the total power values ​​of the historical total power change curves after different overlaps and splicing in the same time segment are normally distributed, and the normal area total value at the normal distribution center position is selected, and the historical total power change curve segment corresponding to the normal total power value is selected, which is recorded as the normal power change segment in the corresponding time segment;

[0074] The normal power change sections of each time section are connected in sequence to obtain the normal power change curve of the corresponding energy detection area, and the normal power change curve is repeatedly established to obtain the normal total power change curve of each energy detection area.

[0075] Furthermore, the energy dispatch management module communicates with various power equipment, sub-power sensors and total power sensors in the public institution, and sets a pre-stored allocation power for each energy detection area according to the normal power change section of each energy detection area in each time section;

[0076] Whenever a time period begins, the running time of the power equipment currently in working state in each energy detection area is obtained, and according to the normal use time of the corresponding power equipment, the estimated use time of the corresponding power equipment in the time period is obtained, and then the estimated power consumption of the corresponding power equipment in the time period is obtained. At the same time, whenever a power equipment is started, the estimated power consumption of the corresponding power equipment in the time period is obtained according to the normal use time of the corresponding power equipment;

[0077] For the power equipment in standby state in each energy detection area, the pending power usage of the corresponding energy detection area is obtained according to the proportion of the normal use period of each power equipment in the current time period, and no operation is performed on the power equipment in the off state;

[0078] It should be noted that, whenever a power device in standby state is started, the estimated power usage value of the corresponding power device is automatically deleted from the pending power usage of the corresponding energy detection area;

[0079] The estimated power usage and pending power usage of each energy detection area in the current time segment are added together to obtain the estimated power usage value of the corresponding energy detection area in the current time segment;

[0080] Set the estimated power difference interval, and then determine whether the difference between the estimated power usage value of each energy detection area and the corresponding pre-stored allocated power in the current time period is less than or equal to the estimated power difference threshold;

[0081] If the difference is within the estimated power difference range, no action is taken;

[0082] If the difference is less than the estimated power difference range, the energy scheduling management module supplements the estimated power usage value according to the difference until the difference is within the estimated power difference range;

[0083] If the difference is greater than the estimated power difference range, the energy scheduling management module reduces the estimated power usage value according to the size of the difference until the difference is within the estimated power difference range.

[0084] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A smart building energy consumption management system for public institutions, including a cloud computing platform, characterized in that: The cloud computing platform is communicatively connected to an organization operation record collection module, an energy consumption analysis module, and an energy dispatch management module; The institution operation record collection module is used to divide the public institution into several energy detection areas, and then collect the historical personnel interaction records, historical equipment operation event records and historical area operation event records of each power equipment in each energy detection area; The collection process of the historical personnel interaction records, historical equipment operation event records and historical area operation event records includes: According to the distribution of houses in the target public institution, the target public institution is divided into n energy detection areas, where n is a natural number greater than 0. The working state, standby state and shutdown state are set for each power equipment. The rated power range of each power equipment in the normal working state is obtained through the Internet, and a data collection cycle is seven days; Whenever an electric power equipment is used, historical personnel interaction records, historical equipment operation event records and historical regional operation event records are automatically generated. Whenever a data collection cycle ends, the organization operation record collection module integrates all records generated by the corresponding data collection cycle to generate historical personnel interaction data sets, historical equipment operation event data sets and historical regional operation event data sets respectively; The personnel interaction record includes the record generation time, the pedestrian interaction start time and interaction end time and the relevant power equipment number; The historical equipment operation event record includes the power equipment number, power change curve, and current state name; The historical regional operation event record includes a historical total power change curve and a power equipment number associated with a fluctuation position on the historical total power change curve; The energy consumption analysis module is used to establish an equipment operation event tree based on historical operation records and historical equipment operation event records, and obtain the normal use time and normal use section of each power equipment. At the same time, it establishes a regional operation event tree based on historical regional operation event records, and then obtains the normal total power change curve of each energy detection area; The process of establishing the equipment operation event tree includes: The historical personnel interaction data set and the historical equipment operation event data set are divided into seven historical personnel interaction data segments and historical equipment operation event data segments on a daily basis. The historical power change curves contained in the historical equipment operation event records corresponding to the same day from the same historical equipment operation event data set are overlapped and spliced ​​in sequence, and operation event nodes are set at the splicing locations. According to the interaction start time and interaction end time of the pedestrians recorded in each historical personnel interaction record in the historical personnel interaction data segment, a plurality of personnel start interaction nodes and personnel end interaction nodes are set on the overlapping and spliced ​​historical power change curve, and the same label is set for the personnel start interaction nodes and personnel end interaction nodes from the same historical personnel interaction record; Then, the overlapping and spliced ​​historical power change curves from the same historical personnel interaction record are connected in sequence to obtain the equipment operation event tree of the power equipment in the corresponding data collection period; The process of obtaining the normal use time and normal use section of each power equipment includes: Through the personnel start interaction node and the personnel end interaction node on the operation event tree of each device, the usage time and usage time segment of the corresponding power equipment are obtained, and each usage time and usage time segment are normally distributed, and the center value of the normal distribution is selected to obtain the normal usage time and normal usage segment of each power equipment; The process of establishing the regional operation event tree includes: By adopting the process of establishing the equipment operation event tree, the historical total power change curves contained in the historical regional operation event data segments corresponding to the same historical regional operation event data set and on the same day are overlapped and spliced ​​in sequence to obtain the regional operation event tree under the corresponding data collection period; A two-dimensional coordinate system is established, and the overlapping and spliced ​​historical total power change curves corresponding to the same energy detection area but different data collection periods are mapped onto the same two-dimensional coordinate system, and a number of equal-length time segments are divided on the coordinate axis associated with time in the two-dimensional coordinate system; Obtain the area value between each time segment and the coordinate axis of the associated time of each overlapping and spliced ​​historical total power change curve, and record it as the total power value in the corresponding time segment; Then, the total power values ​​of the historical total power change curves after different overlaps and splicing in the same time segment are normally distributed, and the normal area total value at the normal distribution center position is selected, and the historical total power change curve segment corresponding to the normal total power value is selected and recorded as the normal power change segment in the corresponding time segment. The normal power change segments of each time segment are connected in sequence to obtain the normal total power change curve of each energy detection area; The energy dispatching management module is used to set a number of time segments, and set a pre-stored allocated power for each energy detection area according to the normal total power change curve of each energy detection area. Then, when a time segment begins, the current operating status of each power equipment in each energy detection area is obtained, and the estimated power usage of the corresponding energy detection area is obtained according to the normal usage time and normal usage segment of each power equipment. By comparing the pre-stored allocated power with the estimated power usage, the numerical value of the pre-stored allocated power is adjusted according to the comparison result.

2. The intelligent building energy consumption management system for public institutions according to claim 1 is characterized in that: The process of obtaining the estimated power usage of the energy detection area includes: According to the normal power change section of each energy detection area in each time section, set the pre-stored allocation power for each energy detection area; Whenever a time period begins, the running time of the power equipment currently in working state in each energy detection area is obtained, and according to the normal use time of the corresponding power equipment, the estimated use time of the corresponding power equipment in the time period is obtained, and then the estimated power consumption of the corresponding power equipment in the time period is obtained, and whenever a power equipment is started, the estimated power consumption of the corresponding power equipment in the time period is obtained according to the normal use time of the corresponding power equipment; For the power equipment in standby state in each energy detection area, the pending power usage of the corresponding energy detection area is obtained according to the proportion of the normal use period of each power equipment in the current time period, and no operation is performed on the power equipment in the off state; The predicted power usage and pending power usage of each energy detection area in the current time segment are added together to obtain the estimated power usage value of the corresponding energy detection area in the current time segment.

3. The intelligent building energy consumption management system for public institutions according to claim 2 is characterized in that: The adjustment process of the pre-stored allocated power includes: Set the estimated power difference interval, and then determine whether the difference between the estimated power usage value of each energy detection area and the corresponding pre-stored allocated power in the current time period is less than or equal to the estimated power difference threshold; If the difference is within the estimated power difference range, no action is taken; If the difference is less than the estimated power difference range, the energy scheduling management module supplements the estimated power usage value according to the difference until the difference is within the estimated power difference range; If the difference is greater than the estimated power difference range, the energy scheduling management module reduces the estimated power usage value according to the size of the difference until the difference is within the estimated power difference range.

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