CN117350441B - Efficiency-improving and carbon-reducing operation optimizing system and method for public building - Google Patents
Efficiency-improving and carbon-reducing operation optimizing system and method for public building Download PDFInfo
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Abstract
The invention belongs to the technical field of energy conservation and carbon reduction, and relates to a data analysis technology, in particular to an efficiency-improving carbon reduction operation optimization system and method for a public building. The invention can timely early warn when the carbon emission of the public building is abnormal, and can optimize the carbon reduction of the building, thereby reducing the energy consumption and the total carbon emission.
Description
Technical Field
The invention belongs to the technical field of energy conservation and carbon reduction, relates to a data analysis technology, and particularly relates to an efficiency improvement and carbon reduction operation optimization system and method for public buildings.
Background
The construction industry, which is one of the largest worldwide carbon emission industries, occupies more than 40% of the total worldwide carbon emissions, and there is an urgent need to take effective measures to reduce the adverse effects on climate. Currently, the building community is primarily dependent on various active systems, such as heating, cooling, ventilation, and lighting, which consume a large amount of fossil fuel energy and emit greenhouse gases and pollutants into the atmosphere.
Although some public building efficiency-improving carbon-reducing operation optimizing systems exist in the prior art, the public building efficiency-improving carbon-reducing operation optimizing systems have a problem that abnormal characteristic analysis cannot be performed when carbon emission of the public building exceeds standard. This limitation has resulted in the difficulty in achieving adaptive optimization for public buildings with abnormal carbon emissions due to lack of in-depth knowledge of their carbon emission characteristics. Therefore, there is an urgent need to improve and perfect these systems so that they can more fully analyze and identify carbon emission anomalies, thereby providing a more targeted optimization scheme for public buildings.
Disclosure of Invention
According to the defects in the prior art, the invention provides the public building efficiency-improving carbon-reducing operation optimizing system and method which can timely perform early warning when the carbon emission of the public building is abnormal, and can perform carbon reduction optimization of the building, and reduce the energy consumption and the total carbon emission.
In order to achieve the above purpose, the present invention can be realized by the following technical scheme:
the public building efficiency-improving carbon-reducing operation optimizing system comprises a carbon emission monitoring module, an emission analysis module, an energy consumption analysis module and a carbon-reducing optimizing module, wherein the carbon emission monitoring module, the emission analysis module, the energy consumption analysis module and the carbon-reducing optimizing module are sequentially in communication connection;
the carbon emission monitoring module is used for monitoring and analyzing carbon emission of the public building: generating a monitoring period, acquiring the total carbon emission amount of the public building in the monitoring period, marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, and performing numerical calculation to obtain a carbon emission coefficient TP of the public building in the monitoring period; judging whether carbon emission of the public building in a monitoring period meets the requirement or not through a carbon emission coefficient TP;
the emission analysis module is used for analyzing the abnormal carbon emission characteristics of the public building and marking the public building as a habitual building or a sudden building;
the energy consumption analysis module is used for monitoring and analyzing the energy consumption state of the habitual building, generating an energy optimization signal or a consumption optimization signal and sending the energy optimization signal or the consumption optimization signal to the carbon reduction optimization module;
the carbon reduction optimizing module is used for carrying out optimizing analysis on energy consumption and carbon emission of the habitual building.
As a preferred embodiment of the present invention, the floor data LC is the floor number value of the public building, the area data MJ is the average value of all floor area values of the public building, the energy supply data GN is the energy supply subsystem number value owned by the public building, and the energy supply subsystem comprises an illumination subsystem, a heating subsystem, a refrigeration subsystem, an elevator subsystem and an electric power equipment subsystem.
As a preferred embodiment of the present invention, the specific process of determining whether carbon emissions of a public building meet a requirement in a monitoring period includes: comparing the carbon bank coefficient TP of the public building in the monitoring period with a preset carbon bank threshold value TPmax: if the carbon emission coefficient TP is smaller than the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period meets the requirement; if the carbon emission coefficient TP is greater than or equal to the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period does not meet the requirement, generating an emission analysis signal and sending the emission analysis signal to an emission analysis module.
As a preferred embodiment of the present invention, the specific process of the emission analysis module for analyzing the abnormal carbon emission characteristics of the public building includes: dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring period as carbon emission values of the monitoring period, forming a carbon emission set by the carbon emission values of all the monitoring periods, calculating variance of the carbon emission set to obtain a concentration coefficient, comparing the concentration coefficient with a preset concentration threshold value, and marking the abnormal carbon emission characteristics of the public building according to the comparison result.
As a preferred embodiment of the present invention, the specific process of comparing the concentration coefficient with a preset concentration threshold value includes: if the concentration coefficient is smaller than the concentration threshold value, marking the abnormal carbon emission characteristic of the public building as habitual abnormality, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module; and if the concentration coefficient is greater than or equal to the concentration threshold, marking the carbon emission abnormality characteristic of the public building as sudden abnormality, marking the corresponding public building as sudden building, and if the public building is marked as sudden building in L1 continuous monitoring periods, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module.
As a preferred embodiment of the present invention, the specific process of the energy consumption analysis module for monitoring and analyzing the energy consumption state of the habitual building includes: the sum value of the energy consumption of all the energy supply subsystems of the habit building in the monitoring period is marked as the energy consumption value of the habit building in the monitoring period, the ratio of the energy consumption value of the habit building to the total carbon value ZT is marked as the energy carbon coefficient of the habit building, the energy carbon coefficient is compared with a preset energy carbon threshold value, and whether the energy consumption state of the habit building meets the requirement or not is judged according to the comparison result.
As a preferred embodiment of the present invention, the specific process of comparing the carbon energy coefficient with a preset carbon energy threshold value includes: if the energy-carbon coefficient is smaller than the energy-carbon threshold, judging that the energy consumption state of the habitual building meets the requirement, generating an energy optimization signal and sending the energy optimization signal to a carbon reduction optimization module; if the energy carbon coefficient is larger than or equal to the energy carbon threshold, judging that the energy consumption state of the habitual building does not meet the requirement, generating a consumption optimization signal and sending the consumption optimization signal to the carbon reduction optimization module.
As a preferred embodiment of the invention, when the carbon reduction optimization module receives the energy optimization signal, the structural optimization scheme data set is called and sent to the mobile phone terminal of the manager, and the structural optimization scheme data set comprises microclimate management, direction optimization, a passive roof, a passive outer wall, an operation type windowing and a passive building structure.
As a preferred embodiment of the present invention, the carbon reduction optimization module performs consumption optimization analysis when receiving the consumption optimization signal: marking the energy consumption of the energy supply subsystems of the habit building in a monitoring period as a consumption supply value, forming a consumption supply set by the consumption supply values of all the energy supply subsystems of the habit building in the monitoring period, calculating the variance of the consumption supply set to obtain a consumption supply coefficient of the habit building, and comparing the consumption supply coefficient with a preset consumption supply threshold value: if the power consumption coefficient is smaller than the power consumption threshold, generating a new energy introduction signal and sending the new energy introduction signal to a mobile phone terminal of a manager; if the power consumption coefficient is greater than or equal to the power consumption threshold, marking the L2 power supply subsystems with the largest power consumption value as an optimizing subsystem, and sending the optimizing subsystem to a mobile phone terminal of a manager.
The optimization method of the public building efficiency-improving carbon-reducing operation optimization system comprises the following steps:
step one: monitoring and analyzing carbon emission of public buildings: generating a monitoring period, acquiring the total carbon emission amount of the public building in the monitoring period, marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, performing numerical calculation to obtain a carbon emission coefficient TP, and judging whether the carbon emission of the public building in the monitoring period meets the requirement or not through the carbon emission coefficient TP;
step two: analyzing the abnormal carbon emission characteristics of the public building: dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring periods as carbon emission values of the monitoring periods, performing variance calculation on the carbon emission values of all the monitoring periods to obtain a concentration coefficient, and marking the public building as a habitual building or a sudden building through the concentration coefficient;
step three: monitoring and analyzing the energy consumption state of the habitual building: marking the sum of the energy consumption of all the energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, carrying out numerical calculation on the energy consumption value and the total carbon value ZT to obtain an energy carbon coefficient, and judging whether the energy consumption state of the habitual building meets the requirement or not through the energy carbon coefficient;
step four: and carrying out optimal analysis on energy consumption and carbon emission of the habitual building.
The invention has the following beneficial effects:
1. according to the invention, the carbon emission of the public building can be monitored and analyzed through the carbon emission monitoring module, the carbon emission coefficient is obtained through statistics and analysis of various emission parameters of the public building in a monitoring period, and the carbon emission normal degree of the public building is fed back through the carbon emission coefficient, so that early warning is timely carried out when the carbon emission of the public building is abnormal;
2. according to the invention, the abnormal carbon emission characteristics of the public building can be analyzed through the emission analysis module, the concentration coefficient of the public building is obtained through a time-division analysis mode, and the uniformity of the carbon emission of the public building on a time line is fed back through the concentration coefficient, so that the abnormal carbon emission characteristics of the public building are marked according to the concentration coefficient, and a data support is provided for a carbon reduction optimization process;
3. according to the invention, the energy consumption state of the habitual building can be monitored and analyzed through the energy consumption analysis module, the energy consumption and the total carbon value are calculated to obtain the energy-carbon coefficient, the positive correlation degree of the energy consumption and the carbon emission of the habitual building is fed back through the energy-carbon coefficient, and different optimization modes are adopted for reducing carbon optimization for the habitual building in different energy consumption states;
4. according to the invention, the optimization analysis of energy consumption and carbon emission can be carried out on the habitual building through the carbon reduction optimization module, and the carbon reduction optimization analysis is carried out by combining the structural optimization scheme and the consumption optimization analysis, so that the energy consumption and the total carbon emission of the habitual building are reduced in a targeted manner.
Drawings
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical scheme of the present invention will be clearly and completely described in the following examples.
Example 1
As shown in fig. 1, the public building efficiency-improving carbon-reducing operation optimizing system comprises a carbon emission monitoring module, an emission analysis module, an energy consumption analysis module and a carbon-reducing optimizing module, wherein the carbon emission monitoring module, the emission analysis module, the energy consumption analysis module and the carbon-reducing optimizing module are sequentially in communication connection.
The carbon emission monitoring module is used for monitoring and analyzing carbon emission of the public building: generating a monitoring period, acquiring the total carbon emission amount of a public building in the monitoring period and marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, wherein the floor data LC is the floor number value of the public building, the area data MJ is the average value of all floor area values of the public building, the energy supply data GN is the energy supply subsystem number value owned by the public building, and the energy supply subsystem comprises an illumination subsystem, a heating subsystem, a refrigeration subsystem, an elevator subsystem and an electric power equipment subsystem; the carbon emission coefficient TP of the public building in the monitoring period is obtained by the formula tp= (α1×zt)/(α2×lc+α3×mj+α4×gn), wherein α1, α2, α3 and α4 are all proportional coefficients, and α4 > α3 > α2 > α1 > 1.
Comparing the carbon bank coefficient TP of the public building in the monitoring period with a preset carbon bank threshold value TPmax: if the carbon emission coefficient TP is smaller than the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period meets the requirement; if the carbon emission coefficient TP is larger than or equal to the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period does not meet the requirement, generating an emission analysis signal and sending the emission analysis signal to an emission analysis module; the carbon emission of the public building is monitored and analyzed, the carbon emission coefficient is obtained by counting and analyzing various emission parameters of the public building in a monitoring period, and the carbon emission normal degree of the public building is fed back through the carbon emission coefficient, so that early warning is timely carried out when the carbon emission of the public building is abnormal.
The emission analysis module is used for analyzing abnormal carbon emission characteristics of the public building: dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring period as the carbon emission value of the monitoring period, forming a carbon emission set by the carbon emission values of all the monitoring periods, performing variance calculation on the carbon emission set to obtain a concentration coefficient, and comparing the concentration coefficient with a preset concentration threshold value:
if the concentration coefficient is smaller than the concentration threshold value, marking the abnormal carbon emission characteristic of the public building as habitual abnormality, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module; and if the concentration coefficient is greater than or equal to the concentration threshold, marking the carbon emission abnormality characteristic of the public building as sudden abnormality, marking the corresponding public building as sudden building, and if the public building is marked as sudden building in L1 continuous monitoring periods, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module.
Analyzing the abnormal carbon emission characteristics of the public building, acquiring a concentration coefficient of the public building in a time-division analysis mode, and feeding back the uniformity of the carbon emission of the public building on a time line through the concentration coefficient, so that the abnormal carbon emission characteristics of the public building are marked according to the concentration coefficient, and data support is provided for a carbon reduction optimization process.
The energy consumption analysis module is used for monitoring and analyzing the energy consumption state of the habitual building: marking the sum of the energy consumption of all energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, marking the ratio of the energy consumption value of the habitual building to the total carbon value ZT as the energy carbon coefficient of the habitual building, and comparing the energy carbon coefficient with a preset energy carbon threshold value:
if the energy-carbon coefficient is smaller than the energy-carbon threshold, judging that the energy consumption state of the habitual building meets the requirement, generating an energy optimization signal and sending the energy optimization signal to a carbon reduction optimization module; if the energy carbon coefficient is larger than or equal to the energy carbon threshold, judging that the energy consumption state of the habitual building does not meet the requirement, generating a consumption optimization signal and sending the consumption optimization signal to the carbon reduction optimization module.
The energy consumption state of the habitual building is monitored and analyzed, the energy consumption and the total carbon value are calculated to obtain an energy-carbon coefficient, the positive correlation degree of the energy consumption and the carbon emission of the habitual building is fed back through the energy-carbon coefficient, and different optimization modes are adopted for carrying out carbon reduction optimization on the habitual building in different energy consumption states.
The carbon reduction optimizing module is used for carrying out optimizing analysis on energy consumption and carbon emission of the habitual building: and when the carbon reduction optimization module receives the energy optimization signal, the structural optimization scheme data set is called and sent to a mobile phone terminal of a manager, wherein the structural optimization scheme data set comprises microclimate management, direction optimization, a passive roof, a passive outer wall, an operation type windowing and a passive building structure.
And the carbon reduction optimization module performs consumption optimization analysis when receiving the consumption optimization signal: marking the energy consumption of the energy supply subsystems of the habit building in a monitoring period as a consumption supply value, forming a consumption supply set by the consumption supply values of all the energy supply subsystems of the habit building in the monitoring period, calculating the variance of the consumption supply set to obtain a consumption supply coefficient of the habit building, and comparing the consumption supply coefficient with a preset consumption supply threshold value: if the power consumption coefficient is smaller than the power consumption threshold, generating a new energy introduction signal and sending the new energy introduction signal to a mobile phone terminal of a manager; if the power consumption coefficient is greater than or equal to the power consumption threshold, marking the L2 power supply subsystems with the largest power consumption value as an optimization subsystem, wherein L1 and L2 are both constant values, and specific values of L1 and L2 are set by a manager; the optimization subsystem is sent to a mobile phone terminal of a manager; and (3) carrying out energy consumption and carbon emission optimization analysis on the habitual building, and carrying out carbon reduction optimization analysis by combining a structural optimization scheme and the consumption optimization analysis, so as to reduce the energy consumption and the total carbon emission of the habitual building in a targeted manner.
Example two
As shown in fig. 2, the public building efficiency-improving and carbon-reducing operation optimization method comprises the following steps:
step one: monitoring and analyzing carbon emission of public buildings: generating a monitoring period, acquiring the total carbon emission amount of the public building in the monitoring period, marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, performing numerical calculation to obtain a carbon emission coefficient TP, and judging whether the carbon emission of the public building in the monitoring period meets the requirement or not through the carbon emission coefficient TP;
step two: analyzing the abnormal carbon emission characteristics of the public building: dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring periods as carbon emission values of the monitoring periods, performing variance calculation on the carbon emission values of all the monitoring periods to obtain a concentration coefficient, and marking the public building as a habitual building or a sudden building through the concentration coefficient;
step three: monitoring and analyzing the energy consumption state of the habitual building: marking the sum of the energy consumption of all the energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, carrying out numerical calculation on the energy consumption value and the total carbon value ZT to obtain an energy carbon coefficient, and judging whether the energy consumption state of the habitual building meets the requirement or not through the energy carbon coefficient;
step four: and carrying out optimal analysis on energy consumption and carbon emission of the habitual building.
In summary, the public building efficiency-improving carbon-reducing operation optimizing system and method, during operation, a monitoring period is generated, the total carbon emission amount of the public building in the monitoring period is obtained and marked as a total carbon value ZT, floor data LC, area data MJ and energy supply data GN of the public building are obtained, a carbon emission coefficient TP is obtained through numerical calculation, and whether the carbon emission of the public building in the monitoring period meets the requirement is judged through the carbon emission coefficient TP; dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring periods as carbon emission values of the monitoring periods, performing variance calculation on the carbon emission values of all the monitoring periods to obtain a concentration coefficient, and marking the public building as a habitual building or a sudden building through the concentration coefficient; marking the sum of the energy consumption of all the energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, carrying out numerical calculation on the energy consumption value and the total carbon value ZT to obtain an energy carbon coefficient, and judging whether the energy consumption state of the habitual building meets the requirement or not through the energy carbon coefficient; and carrying out optimal analysis on energy consumption and carbon emission of the habitual building.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula tp= (α1×zt)/(α2×lc+α3×mj+α4×gn); collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding carbon number coefficient for each group of sample data; substituting the set carbon array coefficient and the acquired sample data into a formula, forming a quaternary one-time equation set by any four formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2, alpha 3 and alpha 4 which are respectively 4.48, 3.65, 2.83 and 2.65;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding carbon-row coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the carbon number coefficient is proportional to the value of the total carbon value.
Claims (3)
1. The public building efficiency-improving carbon-reducing operation optimizing system is characterized by comprising a carbon emission monitoring module, an emission analysis module, an energy consumption analysis module and a carbon-reducing optimizing module, wherein the carbon emission monitoring module, the emission analysis module, the energy consumption analysis module and the carbon-reducing optimizing module are sequentially in communication connection;
the carbon emission monitoring module is used for monitoring and analyzing carbon emission of the public building: generating a monitoring period, acquiring the total carbon emission amount of the public building in the monitoring period, marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, and performing numerical calculation to obtain a carbon emission coefficient TP of the public building in the monitoring period; judging whether carbon emission of the public building in a monitoring period meets the requirement or not through a carbon emission coefficient TP;
the emission analysis module is used for analyzing the abnormal carbon emission characteristics of the public building and marking the public building as a habitual building or a sudden building;
the energy consumption analysis module is used for monitoring and analyzing the energy consumption state of the habitual building, generating an energy optimization signal or a consumption optimization signal and sending the energy optimization signal or the consumption optimization signal to the carbon reduction optimization module;
the carbon reduction optimizing module is used for carrying out optimizing analysis on energy consumption and carbon emission of the habitual building;
the calculation formula of the carbon emission coefficient TP of the public building in the monitoring period is as follows: tp= (α1×zt)/(α2×lc+α3×mj+α4×gn), wherein α1, α2, α3, and α4 are all scaling factors, and α4 > α3 > α2 > α1 > 1;
the specific process for judging whether the carbon emission of the public building in the monitoring period meets the requirement comprises the following steps: comparing the carbon bank coefficient TP of the public building in the monitoring period with a preset carbon bank threshold value TPmax: if the carbon emission coefficient TP is smaller than the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period meets the requirement; if the carbon emission coefficient TP is larger than or equal to the carbon emission threshold value TPmax, judging that the carbon emission of the public building in the monitoring period does not meet the requirement, generating an emission analysis signal and sending the emission analysis signal to an emission analysis module;
the specific process of the emission analysis module for analyzing the abnormal carbon emission characteristics of the public building comprises the following steps: dividing a monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring period as carbon emission values of the monitoring period, forming a carbon emission set by the carbon emission values of all the monitoring periods, performing variance calculation on the carbon emission set to obtain a concentration coefficient, comparing the concentration coefficient with a preset concentration threshold value, and marking the abnormal carbon emission characteristics of the public building according to a comparison result;
the specific process of comparing the concentration coefficient with a preset concentration threshold value comprises the following steps: if the concentration coefficient is smaller than the concentration threshold value, marking the abnormal carbon emission characteristic of the public building as habitual abnormality, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module; if the concentration coefficient is greater than or equal to the concentration threshold, marking the carbon emission abnormal characteristic of the public building as sudden abnormal, marking the corresponding public building as sudden building, and if the public building is marked as sudden building in L1 continuous monitoring periods, marking the corresponding public building as habitual building, and sending the habitual building to the energy consumption analysis module;
the specific process of the energy consumption analysis module for monitoring and analyzing the energy consumption state of the habitual building comprises the following steps: marking the sum of the energy consumption of all the energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, marking the ratio of the energy consumption value of the habitual building to the total carbon value ZT as the energy carbon coefficient of the habitual building, comparing the energy carbon coefficient with a preset energy carbon threshold value, and judging whether the energy consumption state of the habitual building meets the requirement or not according to the comparison result;
the specific process for comparing the energy-carbon coefficient with the preset energy-carbon threshold value comprises the following steps: if the energy-carbon coefficient is smaller than the energy-carbon threshold, judging that the energy consumption state of the habitual building meets the requirement, generating an energy optimization signal and sending the energy optimization signal to a carbon reduction optimization module; if the energy carbon coefficient is larger than or equal to the energy carbon threshold, judging that the energy consumption state of the habitual building does not meet the requirement, generating a consumption optimization signal and sending the consumption optimization signal to a carbon reduction optimization module;
when the carbon reduction optimizing module receives the energy optimizing signal, the structural optimizing scheme data set is called and sent to a mobile phone terminal of a manager, and the structural optimizing scheme data set comprises microclimate management, direction optimization, a passive roof, a passive outer wall, an operation type windowing and a passive building structure;
and the carbon reduction optimization module performs consumption optimization analysis when receiving the consumption optimization signal: marking the energy consumption of the energy supply subsystems of the habit building in a monitoring period as a consumption supply value, forming a consumption supply set by the consumption supply values of all the energy supply subsystems of the habit building in the monitoring period, calculating the variance of the consumption supply set to obtain a consumption supply coefficient of the habit building, and comparing the consumption supply coefficient with a preset consumption supply threshold value: if the power consumption coefficient is smaller than the power consumption threshold, generating a new energy introduction signal and sending the new energy introduction signal to a mobile phone terminal of a manager; if the power consumption coefficient is greater than or equal to the power consumption threshold, marking the L2 power supply subsystems with the largest power consumption value as an optimizing subsystem, and sending the optimizing subsystem to a mobile phone terminal of a manager.
2. The utility model as claimed in claim 1, wherein the floor data LC is the floor number value of the utility, the area data MJ is the average value of all floor area values of the utility, the energy data GN is the energy subsystem number value owned by the utility, and the energy subsystem comprises a lighting subsystem, a heating subsystem, a cooling subsystem, an elevator subsystem and an electric power equipment subsystem.
3. The optimization method of the public building efficiency-improving carbon-reducing operation optimization system according to claim 2, comprising the following steps:
step one: monitoring and analyzing carbon emission of public buildings: generating a monitoring period, acquiring the total carbon emission amount of the public building in the monitoring period, marking the total carbon emission amount as a total carbon value ZT, acquiring floor data LC, area data MJ and energy supply data GN of the public building, performing numerical calculation to obtain a carbon emission coefficient TP, and judging whether the carbon emission of the public building in the monitoring period meets the requirement or not through the carbon emission coefficient TP;
step two: analyzing the abnormal carbon emission characteristics of the public building: dividing the monitoring period into a plurality of monitoring periods, marking the total carbon emission amount of the public building in the monitoring periods as carbon emission values of the monitoring periods, performing variance calculation on the carbon emission values of all the monitoring periods to obtain a concentration coefficient, and marking the public building as a habitual building or a sudden building through the concentration coefficient;
step three: monitoring and analyzing the energy consumption state of the habitual building: marking the sum of the energy consumption of all the energy supply subsystems of the habitual building in the monitoring period as the energy consumption value of the habitual building in the monitoring period, carrying out numerical calculation on the energy consumption value and the total carbon value ZT to obtain an energy carbon coefficient, and judging whether the energy consumption state of the habitual building meets the requirement or not through the energy carbon coefficient;
step four: and carrying out optimal analysis on energy consumption and carbon emission of the habitual building.
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