CN117610699B - Zero-carbon comprehensive energy optimization equipment and method applied to park - Google Patents
Zero-carbon comprehensive energy optimization equipment and method applied to park Download PDFInfo
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Abstract
The invention discloses zero-carbon comprehensive energy optimizing equipment and method applied to a park, relates to the technical field of zero-carbon emission, and aims to solve the problem of poor zero-carbon emission effect in the park. According to the invention, the abnormal data acquisition module acquires the energy data in the abnormal grade, and compares the difference value of the abnormal energy data with the corresponding standard energy data threshold value, the specific value exceeding the emission amount can be more accurately confirmed according to the acquired difference value, the energy optimization efficiency is further improved, the most economical supply proportion of the energy can be found by carrying out energy adjustment according to the numerical data, the energy emission mode of a park is further optimized, and the energy exceeding the zero carbon standard is regulated and controlled to the energy not exceeding the zero carbon emission standard according to the energy complementation, so that the energy reduction optimization complementation is achieved, and the resource waste is effectively reduced.
Description
Technical Field
The invention relates to the technical field of zero carbon emission, in particular to zero carbon comprehensive energy optimization equipment and method applied to a park.
Background
The zero carbon does not emit carbon dioxide, but the design scheme reduces the carbon footprint and the carbon emission by calculating the emission of greenhouse gases (mainly carbon dioxide), so as to achieve zero carbon, namely the zero emission of carbon.
The Chinese patent with publication number CN116258240A discloses a method and a system for optimizing zero-carbon comprehensive energy in a park, which mainly adopts the arrangement of various energy supply modes, can be selected according to actual use conditions and weather conditions, ensures that the energy supply is more reliable and various, and is matched with each other, thereby being capable of adapting to the use requirements in various different use situations; the invention considers the running cost of the system, limits the carbon emission, and obtains a scheme for optimizing the zero-carbon comprehensive energy of the park, and the scheme solves the problem of energy optimization, but has the following problems in actual operation:
1. When the energy data of the park is collected, the data are not subjected to finer comparison and division, so that the later optimizing equipment cannot perform more perfect optimization according to the energy data, and the carbon emission management is poor.
2. No further abnormal confirmation is carried out on the abnormal data, so that when the energy optimization is carried out on the area in the later period, the resource is wasted due to the optimization error.
3. After confirming that the carbon dioxide emission of the park does not reach the zero-carbon standard, the part exceeding the energy is not subjected to more accurate energy optimization, so that the zero-carbon emission effect in the park is poor.
Disclosure of Invention
The invention aims to provide zero-carbon comprehensive energy optimizing equipment and method applied to a park, which are characterized in that an abnormal data acquisition module acquires energy data in abnormal grades, and the threshold value of the abnormal energy data is compared with a corresponding standard energy data threshold value, so that a specific value exceeding the emission amount can be more accurately confirmed according to the acquired difference value, the energy optimizing efficiency is further improved, the most economical supply proportion of the energy can be found by carrying out energy adjustment according to the numerical data, the energy emission mode of the park is further optimized, and the energy exceeding the zero-carbon standard is regulated and controlled to the energy not exceeding the zero-carbon emission standard according to the energy complementation, thereby achieving the optimization complementation of energy reduction, effectively reducing the resource waste and solving the problems in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
The zero-carbon comprehensive energy optimizing device comprises an optimizing monitor and an optimizing management unit, wherein the optimizing monitor monitors and manages energy data of a park through an optimizing management system;
The top end of the optimizing monitor is provided with a signal receiver, the front end of the optimizing monitor is provided with a display screen, and one side of the display screen is provided with a control key;
an optimization management unit comprising:
The monitoring equipment data acquisition module is used for:
Acquiring energy data acquired by each energy collector, wherein each area of each park is provided with energy collectors with different attributes, and the energy collectors acquire the energy data in each park;
The monitoring data judging module is used for:
based on the energy data acquired in the monitoring equipment data acquisition module, distinguishing the energy data according to different attributes, carrying out data comparison on the energy data and standard energy data after distinguishing, and confirming the energy data which are not in the standard energy data in the comparison data according to the comparison result;
The abnormal data processing module is used for:
Based on the energy data which is not in the standard energy data and is acquired in the monitoring data judging module, confirming the difference between the energy data and the standard energy data, judging the energy index threshold value required by the park area according to the confirmed difference, and storing the energy index threshold value;
The energy scheduling and optimizing module is used for:
And based on the energy index threshold value acquired in the abnormal data processing module, the energy index threshold value is corresponding to the park area and the energy attribute, and an energy conversion strategy is prepared according to the corresponding park area and the energy attribute.
Preferably, the energy collector is a water energy collector, an electric energy collector, a gas energy collector and a heat energy collector respectively, wherein the energy collected by the water energy collector, the electric energy collector, the gas energy collector and the heat energy collector is the carbon dioxide emission amount directly or indirectly generated in the park, and the carbon dioxide emission amount data is marked as energy data.
Preferably, the monitoring data judging module includes:
The energy data attribute distinguishing module is used for:
according to different energy data in each area in the park collected by the energy collector, firstly distinguishing the attribute of the different energy data;
Wherein, the attribute of the energy data comprises water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission;
And respectively carrying out data correspondence on the acquired energy data and the attributes of the energy data, and after the data correspondence is finished, carrying out correspondence on the park area information according to the sources of the energy data.
Preferably, the monitoring data judging module further includes:
The standard energy data confirming module is used for:
Confirming standard energy data in a database, and manually setting the standard energy data in the database according to the energy requirement of each park;
the standard energy data comprise water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission of a normal threshold value;
And the carbon dioxide emission thresholds in the areas of each garden are different, and when standard energy data are acquired, the corresponding carbon dioxide emission is corresponding to the carbon dioxide emission threshold of each garden.
Preferably, the monitoring data judging module further includes:
The energy data comparison module is used for:
respectively acquiring the data threshold values of the energy data and the standard energy data acquired by the energy collector;
integrating the energy data acquired by the energy collector with corresponding attribute data in a data threshold of the standard energy data;
after the integration of the same attribute data is completed, comparing the energy data acquired by the energy acquisition device with the standard energy data by a threshold value;
Confirming the comparison result after the data threshold value comparison is completed, and grading the result after the comparison result confirmation is completed;
the grading comprises a standard grade, an adjacent grade and an abnormal grade;
the abnormal data acquisition module is used for:
And acquiring a difference value of the abnormal comparison data and the standard energy data based on the comparison data in the abnormal grade acquired in the energy data comparison module.
Preferably, the exception data processing module is further configured to:
acquiring abnormal energy data in a park area, and calling historical abnormal data in the park area after the abnormal data are acquired;
after the historical abnormal data is called, confirming an abnormal threshold value in the historical abnormal data;
And judging the historical abnormal threshold value and the threshold value of the obtained abnormal energy data, and judging whether the abnormal energy data is in a normal abnormal range according to a judging result.
Preferably, the abnormal data processing module includes:
The first data extraction module is used for extracting the data quantity corresponding to the abnormal threshold value in the historical abnormal data;
the sample data set acquisition module is used for carrying out sample data segmentation on the historical abnormal data to acquire a sample data set and a data set to be detected; the data proportion range of the sample data set is 18% -23% of all historical abnormal data;
The first comparison module is used for determining that the abnormal energy data in the sample data set is data in a normal abnormal range if the abnormal energy data in the sample data set is in a standard threshold range, and determining that the abnormal energy data is data in an abnormal range if the abnormal energy data in the sample data set is not in the standard threshold range;
The second data extraction module is used for extracting data quantity corresponding to data in an abnormal range in the sample data;
The abnormal factor acquisition module is used for acquiring an abnormal factor by utilizing the data quantity corresponding to the abnormal threshold value in the historical abnormal data and the data quantity corresponding to the data in the abnormal range in the sample data; wherein the anomaly factor is obtained by the following formula:
Wherein R represents the abnormality factor; r 0 represents a preset factor reference value; c s represents the data amount corresponding to the data in the abnormal range in the sample data; m represents the number of data corresponding to data in an abnormal range in the sample data; c z denotes the total data amount of the sample data; n represents the total data number of the sample data; e represents a constant;
And the abnormal energy data initial judgment module is used for judging the abnormal energy initial judgment of the data set to be detected by utilizing the abnormal factors.
Preferably, the abnormal energy data initial judging module is used for
The factor extraction module is used for extracting the abnormal factors;
The initial judgment parameter acquisition module is used for acquiring initial judgment parameters corresponding to the data set to be detected and corresponding to the historical abnormal data in the park area by utilizing the abnormal factors; wherein the initial determination parameter is obtained by the following formula:
Wherein X R represents an initial determination parameter; r represents the abnormality factor; r 0 represents a preset factor reference value; c z denotes the total data amount of the sample data; c represents the corresponding quantity of all historical abnormal data; e represents a constant; x 0 denotes a determination parameter reference value;
The comparison module is used for comparing the initial judgment parameter with a preset initial parameter threshold value to obtain a comparison result;
The early warning module is used for judging that the historical abnormal data in the garden area is excessive corresponding to data and belongs to an abnormal state when the comparison result shows that the initial judgment parameter is larger than the preset initial parameter threshold value, and carrying out early warning;
and the execution judging module is used for judging that the abnormal energy corresponding data in the garden area is normal when the comparison result shows that the initial judging parameter is not more than the preset initial parameter threshold value, executing the judging step of judging whether the abnormal energy data is in a normal abnormal range according to the judging result by judging the historical abnormal threshold value and the acquired threshold value of the abnormal energy data on the data set to be detected.
Preferably, the determination process is as follows:
Detecting a historical abnormal threshold value and a threshold value interval threshold value of the acquired abnormal energy data, wherein if the interval threshold value is within a standard threshold value range, the abnormal energy data is data in a normal abnormal range, and if the interval threshold value is not within the standard threshold value range, the abnormal energy data is data in an abnormal range;
storing abnormal energy data in a standard threshold range, reporting the abnormal energy data which is not in the abnormal range abnormally, and collecting secondary energy after reporting;
and calculating the carbon dioxide emission according to the abnormal energy data in the standard threshold range, and marking the calculated carbon dioxide emission data as energy index data.
Preferably, the energy scheduling and optimizing module includes:
The energy index data attribute dividing module is used for:
The acquired energy index data are corresponding to the attributes of the energy data, and the attributes of the energy index data are confirmed after the corresponding is completed;
Acquiring the emission time and the total emission amount required by the carbon dioxide emission amount of the attribute after the attribute confirmation of the energy index data is completed;
the historical index data acquisition module is used for:
Based on the attribute of the energy index data acquired in the energy index data attribute dividing module, acquiring the emission time required by the carbon dioxide emission quantity of the attribute and the historical data of the total emission quantity;
after the historical data is obtained, carrying out data analysis on the historical data and attribute carbon dioxide emission data aiming at the energy index data;
And acquiring numerical data of the total carbon dioxide emission amount in different time periods according to the analysis result.
Preferably, the energy scheduling and optimizing module further includes:
the energy conversion strategy confirming module is used for:
based on the numerical data of the total carbon dioxide emission amount obtained in the historical index data obtaining module, respectively carrying out energy adjustment and energy complementation according to the numerical data;
The energy is adjusted to be according to the attribute corresponding to the numerical data and the park area, the corresponding energy yield and the corresponding energy production proportion in the park area are adjusted, the energy adjustment is converted in a document form, the converted energy is transmitted to the display terminal, and a worker controls the adjustment of the energy yield and the energy production proportion through the terminal;
after the energy adjustment is completed, carrying out energy complementation, wherein the energy complementation is to acquire energy delivery data of each attribute in the area according to the corresponding park interval, and confirm the data of too little carbon dioxide emission and within a normal emission range after the energy delivery data is acquired;
And after the completion of the confirmation, according to attribute data corresponding to the numerical data, comprehensively regulating and controlling the emission of the attribute data and data with the carbon dioxide emission being too small and within a normal emission range, converting energy complementation in a document form, transmitting the converted energy complementation to a display terminal, and comprehensively regulating and controlling the emission of staff through the terminal.
The invention provides another technical scheme, an implementation method applied to zero-carbon comprehensive energy optimization equipment in a park, which comprises the following steps:
The first step: the energy collector collects data with different attributes in the garden area, the energy collector transmits the data to the optimizing monitor 1 through signals after completing the data collection, and the monitored data and the final management scheme are checked through the display screen 3;
And a second step of: the energy collector judges the collected energy data through the monitoring data judging module after the energy data of each park are collected, and abnormal data in the collected energy data can be obtained after the energy data are judged;
and a third step of: after the abnormal data is acquired, acquiring abnormal energy data in the abnormal data within a standard threshold range through an abnormal data processing module, and calculating the carbon dioxide emission amount of the data;
Fourth step: and acquiring the emission time and the emission total amount required by the carbon dioxide emission in the historical data of the energy index data according to the energy scheduling and optimizing module, and performing energy adjustment and energy complementation according to the acquired emission time and emission total amount of the carbon dioxide emission.
Compared with the prior art, the invention has the following beneficial effects:
1. According to the zero-carbon comprehensive energy optimizing equipment and method for the park, the abnormal data acquisition module acquires the energy data in the abnormal level, the threshold value of the abnormal energy data is compared with the corresponding standard energy data threshold value, and the specific value exceeding the emission amount can be more accurately confirmed according to the acquired difference value, so that the energy optimizing efficiency is further improved.
2. According to the zero-carbon comprehensive energy optimizing equipment and method for the park, threshold comparison is carried out on the obtained abnormal energy data and the historical abnormal data, whether the obtained abnormal energy data is in a normal abnormal range or not is judged, accuracy of the abnormal energy data is further improved, if the abnormal energy data is not in the normal abnormal range, reporting and secondary energy acquisition are carried out on the data, and stability of obtaining the abnormal energy data is effectively improved.
3. According to the zero-carbon comprehensive energy optimizing equipment and method for the park, the most economical supply proportion of the energy can be found by adjusting the energy according to the numerical data, the energy emission mode of the park is further optimized, and the energy exceeding the zero-carbon standard is regulated and controlled to the energy not exceeding the zero-carbon emission standard according to the energy complementation, so that the optimization complementation of energy reduction is achieved, and the resource waste is effectively reduced.
Drawings
FIG. 1 is a schematic diagram of an optimized monitor of the present invention;
FIG. 2 is a schematic diagram of the overall optimization flow of the present invention;
FIG. 3 is a schematic diagram of a monitoring data determining module according to the present invention;
fig. 4 is a schematic diagram of an energy scheduling and optimizing module according to the present invention.
In the figure: 1. optimizing a monitor; 2. a signal receiver; 3. a display screen; 4. and controlling the keys.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that in the prior art, when energy data of a park is collected, the data is not subjected to finer comparison and division, so that the optimization equipment at the later stage cannot perform more perfect optimization according to the energy data, and the carbon emission management is poor, please refer to fig. 1-3, the embodiment provides the following technical scheme:
the zero-carbon comprehensive energy optimizing device applied to the park comprises an optimizing monitor 1 and an optimizing management unit, wherein the optimizing monitor 1 monitors and manages park energy data through an optimizing management system; the top end of the optimization monitor 1 is provided with a signal receiver 2, the front end of the optimization monitor 1 is provided with a display screen 3, and one side of the display screen 3 is provided with a control button 4;
an optimization management unit comprising:
The monitoring equipment data acquisition module is used for:
Acquiring energy data acquired by each energy collector, wherein each area of each park is provided with energy collectors with different attributes, and the energy collectors acquire the energy data in each park;
The monitoring data judging module is used for:
based on the energy data acquired in the monitoring equipment data acquisition module, distinguishing the energy data according to different attributes, carrying out data comparison on the energy data and standard energy data after distinguishing, and confirming the energy data which are not in the standard energy data in the comparison data according to the comparison result;
The abnormal data processing module is used for:
Based on the energy data which is not in the standard energy data and is acquired in the monitoring data judging module, confirming the difference between the energy data and the standard energy data, judging the energy index threshold value required by the park area according to the confirmed difference, and storing the energy index threshold value;
The energy scheduling and optimizing module is used for:
And based on the energy index threshold value acquired in the abnormal data processing module, the energy index threshold value is corresponding to the park area and the energy attribute, and an energy conversion strategy is prepared according to the corresponding park area and the energy attribute.
Specifically, the energy collector collects the data with different attributes in the round area, the energy collector transmits the data to the optimizing monitor 1 through signals after completing the data collection, the monitored data and the final management scheme are checked through the display screen 3, the signals of the data transmission are received through the signal receiver 2, the monitoring equipment data acquisition module carries out finer collection on the carbon dioxide emission discharged by different energy sources, the accuracy of the energy collection data is further improved, the distinguishing of the energy data is effectively improved through the monitoring data judgment module, the data with different attributes correspond to the checking of the carbon dioxide emission by the staff, the fact that the specific carbon dioxide emission exceeded by the abnormal energy data can be better understood through the abnormal data processing module, the threshold value of the abnormal energy data and the carbon dioxide emission are the same metering unit, the efficiency of optimizing the carbon dioxide emission in the later stage is further enhanced, the energy can be found through the energy scheduling and optimizing module, the data can be subjected to energy adjustment, the most economic energy supply ratio of the energy source can be further improved, the energy waste can be further reduced, and the energy waste can be better and the carbon source can reach zero-saving energy source.
The energy collector is respectively a water energy collector, an electric energy collector, a gas energy collector and a heat energy collector, wherein the energy collected by the water energy collector, the electric energy collector, the gas energy collector and the heat energy collector is the carbon dioxide emission amount directly or indirectly generated in the park, and the carbon dioxide emission amount data is marked as energy data.
Specifically, open in the garden has a plurality of different workshops, and the attribute of operation of every factory building is all different, installs the energy collector respectively in different factory buildings, can effectually improve the efficiency of gathering every factory building energy to the energy attribute that the energy collector gathered is also all different, is hydroenergy collector, electric energy collector, gas energy collector and heat energy collector respectively, through all carrying out finer acquisition to the carbon dioxide emission that different energy discharged, the accuracy of further improvement energy collection data.
The monitoring data judging module comprises:
The energy data attribute distinguishing module is used for:
According to different energy data in each area in the park collected by the energy collector, firstly distinguishing the attribute of the different energy data; wherein, the attribute of the energy data comprises water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission; and respectively carrying out data correspondence on the acquired energy data and the attributes of the energy data, and after the data correspondence is finished, carrying out correspondence on the park area information according to the sources of the energy data.
The monitoring data judging module further comprises:
The standard energy data confirming module is used for:
Confirming standard energy data in a database, and manually setting the standard energy data in the database according to the energy requirement of each park; the standard energy data comprise water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission of a normal threshold value; and the carbon dioxide emission thresholds in the areas of each garden are different, and when standard energy data are acquired, the corresponding carbon dioxide emission is corresponding to the carbon dioxide emission threshold of each garden.
The monitoring data judging module further comprises:
The energy data comparison module is used for:
respectively acquiring the data threshold values of the energy data and the standard energy data acquired by the energy collector; integrating the energy data acquired by the energy collector with corresponding attribute data in a data threshold of the standard energy data; after the integration of the same attribute data is completed, comparing the energy data acquired by the energy acquisition device with the standard energy data by a threshold value; confirming the comparison result after the data threshold value comparison is completed, and grading the result after the comparison result confirmation is completed; the rankings include a standard ranking, an adjacent ranking, and an anomaly ranking.
The abnormal data acquisition module is used for:
And acquiring a difference value of the abnormal comparison data and the standard energy data based on the comparison data in the abnormal grade acquired in the energy data comparison module.
Specifically, the data acquired by the energy collectors in each garden area are firstly acquired, the energy data with different attributes in different areas are distinguished according to the energy data attribute distinguishing module after the acquisition, the attributes of the energy data comprise water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission, the accuracy of acquiring the carbon dioxide emission is effectively improved by distinguishing the energy data, the data with different attributes are respectively corresponding to different carbon dioxide emission, the inspection of the carbon dioxide emission by workers is more convenient, after the distinguishing of the carbon dioxide emission with different attributes is completed, the standard energy data of different energy sources in each garden is confirmed through the standard energy data confirming module, wherein the standard energy data is the normal carbon dioxide emission aiming at the energy of a certain attribute in a certain garden, for example, the normal threshold value of the carbon dioxide emission amount of the water energy collected by the energy collector in the A park, the normal threshold value of the carbon dioxide emission amount of the heat energy collected by the energy collector in the B park can enable the calculated emission amount to be more accurate when the actual energy data is calculated with the standard energy data through the confirmation of the standard energy data, the standard energy data is compared with the actual energy data collected by the energy collector through the energy data comparison module after the confirmation of the standard energy data is completed, the grade division is carried out according to the comparison result after the threshold value comparison is completed, the abnormal carbon dioxide emission of the energy with the attribute in the park can be more quickly known, when the threshold value grade division is in the standard grade, the carbon dioxide emission amount of the corresponding attribute energy in the park is indicated to be the normal emission, when the threshold level is divided into the adjacent levels, the carbon dioxide emission of the corresponding attribute energy source in the park area is about to exceed the normal emission standard, the data are required to be specially observed by staff, countermeasures are not required to be made, when the threshold level is divided into the abnormal levels, the carbon dioxide emission of the corresponding attribute energy source in the park area is abnormal emission, namely exceeds the zero carbon emission standard, finally, the energy source data in the abnormal levels are acquired through an abnormal data acquisition module, the difference value between the threshold value of the abnormal energy source data and the corresponding standard energy source data threshold value is compared, the specific value exceeding the emission amount can be more accurately confirmed according to the acquired difference value, and the energy optimizing efficiency is further improved.
In order to solve the problem that in the prior art, after confirming abnormal data of energy emission in a park, no further abnormal confirmation is performed on abnormal data, so that resource waste caused by optimization errors is caused when the energy optimization is performed on the area in the later period, referring to fig. 2, the embodiment provides the following technical scheme:
the abnormal data processing module is further used for:
Acquiring abnormal energy data in a park area, and calling historical abnormal data in the park area after the abnormal data are acquired; after the historical abnormal data is called, confirming an abnormal threshold value in the historical abnormal data; and judging the historical abnormal threshold value and the threshold value of the obtained abnormal energy data, and judging whether the abnormal energy data is in a normal abnormal range according to a judging result.
Specifically, the abnormal data processing module includes:
The first data extraction module is used for extracting the data quantity corresponding to the abnormal threshold value in the historical abnormal data;
the sample data set acquisition module is used for carrying out sample data segmentation on the historical abnormal data to acquire a sample data set and a data set to be detected; the data proportion range of the sample data set is 18% -23% of all historical abnormal data;
The first comparison module is used for determining that the abnormal energy data in the sample data set is data in a normal abnormal range if the abnormal energy data in the sample data set is in a standard threshold range, and determining that the abnormal energy data is data in an abnormal range if the abnormal energy data in the sample data set is not in the standard threshold range;
The second data extraction module is used for extracting data quantity corresponding to data in an abnormal range in the sample data;
The abnormal factor acquisition module is used for acquiring an abnormal factor by utilizing the data quantity corresponding to the abnormal threshold value in the historical abnormal data and the data quantity corresponding to the data in the abnormal range in the sample data; wherein the anomaly factor is obtained by the following formula:
Wherein R represents the abnormality factor; r 0 represents a preset factor reference value; c s represents the data amount corresponding to the data in the abnormal range in the sample data; m represents the number of data corresponding to data in an abnormal range in the sample data; c z denotes the total data amount of the sample data; n represents the total data number of the sample data; e represents a constant;
And the abnormal energy data initial judgment module is used for judging the abnormal energy initial judgment of the data set to be detected by utilizing the abnormal factors.
The technical effects of the technical scheme are as follows: and detecting abnormal energy data, namely extracting data quantity corresponding to an abnormal threshold value in the historical abnormal data by the first data extraction module. This helps to determine a standard threshold for abnormal energy data.
Sample data segmentation, namely a sample data set acquisition module is responsible for dividing historical abnormal data into a sample data set and a data set to be detected. The sample dataset represents 18% -23% of the total historical anomaly data, which ensures that enough sample data is used to train and evaluate the anomaly detection model.
Abnormal energy data classification, namely, through a primary comparison module, the system can divide abnormal energy data in a sample data set into data in a normal abnormal range and data in an abnormal range. This helps identify those outlier data that do not meet the standard threshold.
And calculating an abnormality factor by using the data amount corresponding to the abnormality threshold value in the historical abnormality data and the data amount corresponding to the data in the abnormal abnormality range in the sample data. This anomaly factor can be used to quantify the degree of anomaly of the anomaly data.
And the abnormal data judgment, namely the abnormal energy data initial judgment module judges the abnormal energy data in the data set to be detected by using the calculated abnormal factors. This facilitates automated identification and marking of the abnormal energy data for further processing or analysis.
In general, the technical effect of this technical solution is to achieve efficient detection, classification and quantification of abnormal energy data in historical abnormal data, and to enable automated abnormal data determination in the data set to be detected. This helps to increase the efficiency of the exception data handling, enabling the system to better cope with the exception situation.
Specifically, an abnormal energy data initial determination module is used for
The factor extraction module is used for extracting the abnormal factors;
The initial judgment parameter acquisition module is used for acquiring initial judgment parameters corresponding to the data set to be detected and corresponding to the historical abnormal data in the park area by utilizing the abnormal factors; wherein the initial determination parameter is obtained by the following formula:
Wherein X R represents an initial determination parameter; r represents the abnormality factor; r 0 represents a preset factor reference value; c z denotes the total data amount of the sample data; c represents the corresponding quantity of all historical abnormal data; e represents a constant; x 0 denotes a determination parameter reference value;
The comparison module is used for comparing the initial judgment parameter with a preset initial parameter threshold value to obtain a comparison result;
The early warning module is used for judging that the historical abnormal data in the garden area is excessive corresponding to data and belongs to an abnormal state when the comparison result shows that the initial judgment parameter is larger than the preset initial parameter threshold value, and carrying out early warning;
and the execution judging module is used for judging that the abnormal energy corresponding data in the garden area is normal when the comparison result shows that the initial judging parameter is not more than the preset initial parameter threshold value, executing the judging step of judging whether the abnormal energy data is in a normal abnormal range according to the judging result by judging the historical abnormal threshold value and the acquired threshold value of the abnormal energy data on the data set to be detected.
The technical effects of the technical scheme are as follows: the factor extraction module is used for extracting an abnormality factor, and the factor is obtained through calculation of the data quantity corresponding to the abnormality threshold value in the historical abnormality data. This factor is used in the subsequent decision process.
And calculating initial judgment parameters by an initial judgment parameter acquisition module according to the abnormal factors and other parameters. This parameter is used to evaluate whether the historical anomaly data is excessive, i.e., whether it is in an abnormal state.
And comparing and early warning, namely comparing the calculated initial judgment parameter with a preset initial parameter threshold value by a comparison module. If the initial judgment parameter is larger than a preset initial parameter threshold, the early warning module judges that the data corresponding to the historical abnormal data in the garden area are excessive, belongs to an abnormal state and carries out early warning. This helps to find anomalies early and take necessary action.
And executing judgment, namely if the initial judgment parameter is not greater than a preset initial parameter threshold value, judging that the abnormal energy corresponding data in the garden area is in a normal state by the execution judgment module. Then, it performs a decision step of comparing the history abnormality threshold with the threshold of the obtained abnormal energy data to further determine whether the abnormal energy data belongs to the range of normal abnormality. This helps to accurately judge the state of the abnormal data.
In general, the technical effect of the technical scheme is to realize multi-level judgment of the historical abnormal data, including judgment of whether the historical abnormal data are excessive and in a normal state and accurate threshold judgment of abnormal energy data in a data set to be detected. This helps to improve the identification and management of abnormal situations, ensuring that abnormal data in the rural areas are handled and controlled in a timely manner.
The judging mode is to detect a historical abnormal threshold value and a threshold value interval threshold value of the acquired abnormal energy source data, if the interval threshold value is within a standard threshold value range, the abnormal energy source data is data in a normal abnormal range, and if the interval threshold value is not within the standard threshold value range, the abnormal energy source data is data in an abnormal range; storing abnormal energy data in a standard threshold range, reporting the abnormal energy data which is not in the abnormal range abnormally, and collecting secondary energy after reporting; and calculating the carbon dioxide emission according to the abnormal energy data in the standard threshold range, and marking the calculated carbon dioxide emission data as energy index data.
Specifically, the energy data in the abnormal level is firstly acquired, then the historical abnormal data of the attribute is confirmed after the acquisition, the acquired abnormal energy data is compared with the historical abnormal data in terms of threshold value, whether the acquired abnormal energy data is in a normal abnormal range or not is judged, the accuracy of the abnormal energy data is further improved, if the abnormal energy data is not in the normal abnormal range, the data is reported and acquired for the second time, the acquisition stability of the abnormal energy data is effectively improved, the carbon dioxide emission amount is calculated for the energy data threshold value in the normal abnormal range, the purpose of calculation is to better know the specific carbon dioxide emission amount exceeded by the abnormal energy data, the threshold value of the abnormal energy data and the carbon dioxide emission amount are the same metering unit, and the efficiency of optimizing the carbon dioxide emission amount in the later period is further enhanced.
In order to solve the problem that in the prior art, after confirming that the carbon dioxide emission of the campus does not reach the zero carbon standard, the part exceeding the energy is not subjected to more accurate energy optimization, so that the zero carbon emission effect in the campus is poor, please refer to fig. 4, and the embodiment provides the following technical scheme:
An energy scheduling and optimizing module, comprising:
The energy index data attribute dividing module is used for:
The acquired energy index data are corresponding to the attributes of the energy data, and the attributes of the energy index data are confirmed after the corresponding is completed; and after the attribute confirmation of the energy index data is completed, acquiring the emission time and the total emission amount required by the carbon dioxide emission amount of the attribute.
The historical index data acquisition module is used for:
Based on the attribute of the energy index data acquired in the energy index data attribute dividing module, acquiring the emission time required by the carbon dioxide emission quantity of the attribute and the historical data of the total emission quantity; after the historical data is obtained, carrying out data analysis on the historical data and attribute carbon dioxide emission data aiming at the energy index data; and acquiring numerical data of the total carbon dioxide emission amount in different time periods according to the analysis result.
The energy scheduling and optimizing module further comprises:
the energy conversion strategy confirming module is used for:
Based on the numerical data of the total carbon dioxide emission amount obtained in the historical index data obtaining module, respectively carrying out energy adjustment and energy complementation according to the numerical data; the energy is adjusted to be according to the attribute corresponding to the numerical data and the park area, the corresponding energy yield and the corresponding energy production proportion in the park area are adjusted, the energy adjustment is converted in a document form, the converted energy is transmitted to the display terminal, and a worker controls the adjustment of the energy yield and the energy production proportion through the terminal; after the energy adjustment is completed, carrying out energy complementation, wherein the energy complementation is to acquire energy delivery data of each attribute in the area according to the corresponding park interval, and confirm the data of too little carbon dioxide emission and within a normal emission range after the energy delivery data is acquired; and after the completion of the confirmation, according to attribute data corresponding to the numerical data, comprehensively regulating and controlling the emission of the attribute data and data with the carbon dioxide emission being too small and within a normal emission range, converting energy complementation in a document form, transmitting the converted energy complementation to a display terminal, and comprehensively regulating and controlling the emission of staff through the terminal.
Specifically, the energy index data attribute dividing module is used for acquiring the energy data which is not in the zero carbon emission standard, after the data are acquired, the data of the park area and the energy attribute to which the energy data belong are confirmed, and then the emission time and the emission total amount required by the carbon dioxide emission in the area are acquired according to the confirmed park area and the confirmed energy attribute, so that the detailed condition of the carbon dioxide emission of the energy data can be acquired more accurately, a worker can pay special attention according to the moment that the carbon dioxide emission is higher, the stability of energy optimization is further improved, the most economical supply proportion of the energy can be found by carrying out energy adjustment according to the numerical data, the energy emission mode of the park area is further optimized, and the energy exceeding the zero carbon standard is regulated and controlled to the energy not exceeding the zero carbon emission standard according to the energy complementation, thereby achieving the optimization complementation of energy reduction and effectively reducing the resource waste.
The invention provides another technical scheme, an implementation method applied to zero-carbon comprehensive energy optimization equipment in a park, which comprises the following steps:
The first step: the energy collector collects data with different attributes in the garden area, the energy collector transmits the data to the optimizing monitor 1 through signals after completing the data collection, and the monitored data and the final management scheme are checked through the display screen 3;
Wherein,
And a second step of: the energy collector judges the collected energy data through the monitoring data judging module after the energy data of each park are collected, and abnormal data in the collected energy data can be obtained after the energy data are judged;
The threshold value of the abnormal energy data is compared with the corresponding threshold value of the standard energy data, and a specific value exceeding the emission amount can be more accurately confirmed according to the obtained difference value, so that the energy optimization efficiency is further improved;
and a third step of: after the abnormal data is acquired, acquiring abnormal energy data in the abnormal data within a standard threshold range through an abnormal data processing module, and calculating the carbon dioxide emission amount of the data;
The acquired abnormal energy data is compared with the historical abnormal data in a threshold value, and whether the acquired abnormal energy data is in a normal abnormal range or not is judged, so that the accuracy of the abnormal energy data is further improved;
Fourth step: acquiring the emission time and the emission total amount required by the carbon dioxide emission in the historical data of the energy index data according to the energy scheduling and optimizing module, and performing energy adjustment and energy complementation according to the acquired emission time and emission total amount of the carbon dioxide emission;
The most economical supply proportion of the energy can be found by adjusting the energy according to the numerical data, the energy emission mode of a park is further optimized, and the energy exceeding the zero carbon standard is regulated and controlled to the energy not exceeding the zero carbon emission standard according to the energy complementation, so that the optimization complementation of energy reduction is achieved, and the resource waste is effectively reduced.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. Be applied to garden zero carbon comprehensive energy optimizing equipment, including optimizing monitor (1) and optimizing management unit, its characterized in that: the optimization monitor (1) monitors and manages the energy data of the park through an optimization management system;
The top end of the optimizing monitor (1) is provided with a signal receiver (2), the front end of the optimizing monitor (1) is provided with a display screen (3), and one side of the display screen (3) is provided with a control key (4);
an optimization management unit comprising:
The monitoring equipment data acquisition module is used for:
Acquiring energy data acquired by each energy collector, wherein each area of each park is provided with energy collectors with different attributes, and the energy collectors acquire the energy data in each park;
The monitoring data judging module is used for:
based on the energy data acquired in the monitoring equipment data acquisition module, distinguishing the energy data according to different attributes, carrying out data comparison on the energy data and standard energy data after distinguishing, and confirming the energy data which are not in the standard energy data in the comparison data according to the comparison result;
The abnormal data processing module is used for:
Based on the energy data which is not in the standard energy data and is acquired in the monitoring data judging module, confirming the difference between the energy data and the standard energy data, judging the energy index threshold value required by the park area according to the confirmed difference, and storing the energy index threshold value;
The energy scheduling and optimizing module is used for:
Based on the energy index threshold value obtained from the abnormal data processing module, the energy index threshold value is corresponding to the park area and the energy attribute, and an energy conversion strategy is prepared according to the corresponding park area and the energy attribute;
The abnormal data processing module is further configured to:
acquiring abnormal energy data in a park area, and calling historical abnormal data in the park area after the abnormal data are acquired;
after the historical abnormal data is called, confirming an abnormal threshold value in the historical abnormal data;
judging the historical abnormal threshold value and the threshold value of the obtained abnormal energy data, and judging whether the abnormal energy data is in a normal abnormal range according to a judging result;
the abnormal data processing module comprises:
The first data extraction module is used for extracting the data quantity corresponding to the abnormal threshold value in the historical abnormal data;
the sample data set acquisition module is used for carrying out sample data segmentation on the historical abnormal data to acquire a sample data set and a data set to be detected; the data proportion range of the sample data set is 18% -23% of all historical abnormal data;
The first comparison module is used for determining that the abnormal energy data in the sample data set is data in a normal abnormal range if the abnormal energy data in the sample data set is in a standard threshold range, and determining that the abnormal energy data is data in an abnormal range if the abnormal energy data in the sample data set is not in the standard threshold range;
The second data extraction module is used for extracting data quantity corresponding to data in an abnormal range in the sample data;
The abnormal factor acquisition module is used for acquiring an abnormal factor by utilizing the data quantity corresponding to the abnormal threshold value in the historical abnormal data and the data quantity corresponding to the data in the abnormal range in the sample data; wherein the anomaly factor is obtained by the following formula:
Wherein R represents the abnormality factor; r 0 represents a preset factor reference value; c s represents the data amount corresponding to the data in the abnormal range in the sample data; m represents the number of data corresponding to data in an abnormal range in the sample data; c z denotes the total data amount of the sample data; n represents the total data number of the sample data; e represents a constant;
The abnormal energy data initial judging module is used for judging abnormal energy initial judgment of the data set to be detected by utilizing the abnormal factors;
Abnormal energy data initial judging module for
The factor extraction module is used for extracting the abnormal factors;
The initial judgment parameter acquisition module is used for acquiring initial judgment parameters corresponding to the data set to be detected and corresponding to the historical abnormal data in the park area by utilizing the abnormal factors; wherein the initial determination parameter is obtained by the following formula:
Wherein X R represents an initial determination parameter; r represents the abnormality factor; r 0 represents a preset factor reference value; c z denotes the total data amount of the sample data; c represents the corresponding quantity of all historical abnormal data; e represents a constant; x 0 denotes a determination parameter reference value;
The comparison module is used for comparing the initial judgment parameter with a preset initial parameter threshold value to obtain a comparison result;
The early warning module is used for judging that the historical abnormal data in the garden area is excessive corresponding to data and belongs to an abnormal state when the comparison result shows that the initial judgment parameter is larger than the preset initial parameter threshold value, and carrying out early warning;
And the execution judging module is used for judging that the abnormal energy corresponding data in the garden area is normal when the comparison result shows that the initial judging parameter is not more than the preset initial parameter threshold value, executing the judging step of judging whether the abnormal energy data is in a normal abnormal range according to the judging result by judging the historical abnormal threshold value and the acquired threshold value of the abnormal energy data on the data set to be detected.
2. The zero-carbon comprehensive energy optimization device applied to a park according to claim 1, wherein: the energy collector is respectively a water energy collector, an electric energy collector, a gas energy collector and a heat energy collector, wherein the energy collected by the water energy collector, the electric energy collector, the gas energy collector and the heat energy collector is the carbon dioxide emission amount directly or indirectly generated in the park, and the carbon dioxide emission amount data is marked as energy data.
3. The zero-carbon comprehensive energy optimization device applied to a park according to claim 1, wherein: the monitoring data judging module comprises:
The energy data attribute distinguishing module is used for:
according to different energy data in each area in the park collected by the energy collector, firstly distinguishing the attribute of the different energy data;
Wherein, the attribute of the energy data comprises water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission;
And respectively carrying out data correspondence on the acquired energy data and the attributes of the energy data, and after the data correspondence is finished, carrying out correspondence on the park area information according to the sources of the energy data.
4. A zero carbon comprehensive energy optimization device for a campus according to claim 3, wherein: the monitoring data judging module further comprises:
The standard energy data confirming module is used for:
Confirming standard energy data in a database, and manually setting the standard energy data in the database according to the energy requirement of each park;
the standard energy data comprise water energy carbon dioxide emission, electric energy carbon dioxide emission, gas energy carbon dioxide emission and heat energy carbon dioxide emission of a normal threshold value;
And the carbon dioxide emission thresholds in the areas of each garden are different, and when standard energy data are acquired, the corresponding carbon dioxide emission is corresponding to the carbon dioxide emission threshold of each garden.
5. The zero-carbon comprehensive energy optimization device applied to a park according to claim 4, wherein: the monitoring data judging module further comprises:
The energy data comparison module is used for:
respectively acquiring the data threshold values of the energy data and the standard energy data acquired by the energy collector;
integrating the energy data acquired by the energy collector with corresponding attribute data in a data threshold of the standard energy data;
after the integration of the same attribute data is completed, comparing the energy data acquired by the energy acquisition device with the standard energy data by a threshold value;
Confirming the comparison result after the data threshold value comparison is completed, and grading the result after the comparison result confirmation is completed;
the grading comprises a standard grade, an adjacent grade and an abnormal grade;
the abnormal data acquisition module is used for:
And acquiring a difference value of the abnormal comparison data and the standard energy data based on the comparison data in the abnormal grade acquired in the energy data comparison module.
6. The zero-carbon comprehensive energy optimization device applied to a park according to claim 1, wherein: the judging process is as follows:
Detecting a historical abnormal threshold value and a threshold value interval threshold value of the acquired abnormal energy data, wherein if the interval threshold value is within a standard threshold value range, the abnormal energy data is data in a normal abnormal range, and if the interval threshold value is not within the standard threshold value range, the abnormal energy data is data in an abnormal range;
storing abnormal energy data in a standard threshold range, reporting the abnormal energy data which is not in the abnormal range abnormally, and collecting secondary energy after reporting;
and calculating the carbon dioxide emission according to the abnormal energy data in the standard threshold range, and marking the calculated carbon dioxide emission data as energy index data.
7. The zero-carbon comprehensive energy optimization device applied to a park according to claim 1, wherein: the energy scheduling and optimizing module comprises:
The energy index data attribute dividing module is used for:
The acquired energy index data are corresponding to the attributes of the energy data, and the attributes of the energy index data are confirmed after the corresponding is completed;
Acquiring the emission time and the total emission amount required by the carbon dioxide emission amount of the attribute after the attribute confirmation of the energy index data is completed;
the historical index data acquisition module is used for:
Based on the attribute of the energy index data acquired in the energy index data attribute dividing module, acquiring the emission time required by the carbon dioxide emission quantity of the attribute and the historical data of the total emission quantity;
after the historical data is obtained, carrying out data analysis on the historical data and attribute carbon dioxide emission data aiming at the energy index data;
And acquiring numerical data of the total carbon dioxide emission amount in different time periods according to the analysis result.
8. The zero-carbon comprehensive energy optimization device applied to a park according to claim 7, wherein: the energy scheduling and optimizing module further comprises:
the energy conversion strategy confirming module is used for:
based on the numerical data of the total carbon dioxide emission amount obtained in the historical index data obtaining module, respectively carrying out energy adjustment and energy complementation according to the numerical data;
The energy is adjusted to be according to the attribute corresponding to the numerical data and the park area, the corresponding energy yield and the corresponding energy production proportion in the park area are adjusted, the energy adjustment is converted in a document form, the converted energy is transmitted to the display terminal, and a worker controls the adjustment of the energy yield and the energy production proportion through the terminal;
after the energy adjustment is completed, carrying out energy complementation, wherein the energy complementation is to acquire energy delivery data of each attribute in the area according to the corresponding park interval, and confirm the data of too little carbon dioxide emission and within a normal emission range after the energy delivery data is acquired;
And after the completion of the confirmation, according to attribute data corresponding to the numerical data, comprehensively regulating and controlling the emission of the attribute data and data with the carbon dioxide emission being too small and within a normal emission range, converting energy complementation in a document form, transmitting the converted energy complementation to a display terminal, and comprehensively regulating and controlling the emission of staff through the terminal.
9. A method of implementing a zero carbon integrated energy optimization plant for a campus as claimed in any one of claims 1 to 8, comprising the steps of:
The first step: the energy collector collects data with different attributes in the garden area, the energy collector transmits the data to the optimizing monitor (1) through signals after completing the data collection, and the monitored data and the final management scheme are checked through the display screen (3);
And a second step of: the energy collector judges the collected energy data through the monitoring data judging module after the energy data of each park are collected, and abnormal data in the collected energy data can be obtained after the energy data are judged;
and a third step of: after the abnormal data is acquired, acquiring abnormal energy data in the abnormal data within a standard threshold range through an abnormal data processing module, and calculating the carbon dioxide emission amount of the data;
Fourth step: and acquiring the emission time and the emission total amount required by the carbon dioxide emission in the historical data of the energy index data according to the energy scheduling and optimizing module, and performing energy adjustment and energy complementation according to the acquired emission time and emission total amount of the carbon dioxide emission.
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