CN116755377A - Energy consumption monitoring and remote control system of alcohol refining unit - Google Patents
Energy consumption monitoring and remote control system of alcohol refining unit Download PDFInfo
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- 238000005265 energy consumption Methods 0.000 title claims abstract description 155
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 title claims abstract description 37
- 238000007670 refining Methods 0.000 title claims abstract description 37
- 238000012544 monitoring process Methods 0.000 title claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 68
- 238000013480 data collection Methods 0.000 claims abstract description 22
- 238000005457 optimization Methods 0.000 claims abstract description 21
- 238000009434 installation Methods 0.000 claims abstract description 9
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- 230000008859 change Effects 0.000 claims description 11
- 238000000034 method Methods 0.000 claims description 10
- 230000001276 controlling effect Effects 0.000 claims description 9
- 230000032683 aging Effects 0.000 claims description 8
- 238000002372 labelling Methods 0.000 claims description 6
- 230000008054 signal transmission Effects 0.000 claims description 6
- 230000001105 regulatory effect Effects 0.000 claims description 4
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention relates to the technical field of energy consumption monitoring. The invention relates to an energy consumption monitoring and remote control system of an alcohol refining unit. It includes a data collection unit; according to the invention, the energy consumption data of the alcohol refining unit is collected in real time, the energy consumption data is predicted, so that the alcohol refining can comprehensively monitor and control the energy consumption condition in real time, remote adjustment and optimization are realized, the energy consumption data is managed and analyzed, an energy consumption report, trend analysis and prediction are generated, decision support and energy consumption optimization suggestions are provided for users, the adjustment and control of the running state of the unit are realized by sending instructions to the unit, intelligent adjustment and optimization can be performed according to the energy consumption report and preset parameters, the energy consumption efficiency of the unit is improved, the bottleneck and potential optimization points of energy consumption can be identified by analyzing and predicting the energy consumption data in combination with the installation environment interference factors, the targeted suggestions and improvement schemes are provided, the energy consumption is helped to optimize for the users, and the production cost is reduced.
Description
Technical Field
The invention relates to the technical field of energy consumption monitoring, in particular to an energy consumption monitoring and remote control system of an alcohol refining unit.
Background
The alcohol refining unit (or rectifying column) is one of important equipment widely applied to industries such as chemical industry, petrochemical industry, medicine, food, alcohol and the like, and in the alcohol refining process, parameters such as reaction temperature, reaction pressure, heat source pressure and the like need to be controlled and regulated in real time so as to ensure the product quality and refining efficiency. Meanwhile, because the energy consumption of the alcohol refining unit is higher, the energy cost is an important component of the operation cost, and when the alcohol refining unit is subjected to energy control, the data acquisition is continuously changed due to the ageing of a machine and the interference of an installation environment, and the energy distribution of the alcohol refining unit is required to be continuously adjusted.
Disclosure of Invention
The invention aims to provide an energy consumption monitoring and remote control system of an alcohol refining unit, so as to solve the problems in the background technology.
In order to achieve the above purpose, the energy consumption monitoring and remote control system of the alcohol refining unit comprises a data collection unit, a data analysis unit, an energy consumption analysis unit, an implementation control unit and a data optimization unit;
the data collection unit is used for collecting energy consumption data of the unit, collecting green energy and introducing energy, and the data analysis unit is used for analyzing according to the unit environment and analyzing the energy consumption data collected by the data collection unit according to the analysis data;
the energy consumption analysis unit is used for predicting the data collected by the data collection unit in combination with the analysis data of the data analysis unit, and manufacturing an energy distribution scheme according to a prediction result;
the implementation control unit is used for controlling the energy consumption of the unit according to the energy distribution scheme manufactured by the energy consumption analysis unit, collecting the running state of the base for evaluation, and performing abnormal analysis according to the energy distribution scheme manufactured by the energy consumption analysis unit;
the data optimization unit is used for marking the abnormal analysis result in the energy distribution scheme, sending the marked abnormal analysis result to the cloud to obtain feedback data, and performing data optimization on the energy distribution scheme according to the feedback data.
As a further improvement of the technical scheme, the data collection unit comprises an energy consumption collection module and an energy source introduction module;
the energy consumption acquisition module is used for monitoring the running state of the engine base in real time and judging and collecting the energy consumption data of the engine base according to the running state of the engine base;
the energy source introducing module is used for judging and collecting green energy sources according to the unit environment and conveying the collected green energy sources to the machine base for energy supply.
As a further improvement of the technical scheme, the data analysis unit comprises an interference analysis module and a data comparison module;
the interference analysis module is used for collecting data of the installation environment of the unit and evaluating the interference degree of the energy consumption data collected by the energy consumption collection module;
the data comparison module is used for comparing different positions of the energy consumption data collected by the energy consumption collection module, and judging the comprehensive value of the collected energy consumption data according to the comparison result.
As a further improvement of the technical scheme, the interference analysis module evaluates the interference degree of the energy consumption collection module for collecting the energy consumption data as follows:
environmental interference assessment: the method comprises the steps of carrying out numerical value acquisition on environmental factors such as environmental noise, air temperature change and humidity change, and judging the accuracy and stability of data acquisition equipment according to the numerical value;
electromagnetic interference assessment: the method comprises the steps of carrying out numerical value acquisition on electromagnetic signal interference from other equipment in a unit installation area, and judging that the transmitted data are abnormal or distorted according to the numerical value;
signal transmission interference assessment: and carrying out numerical value acquisition on interference from the cable line signal transmission line, and judging the influence on the signal quality of the data acquisition equipment according to the numerical value.
As a further improvement of the technical scheme, the data comparison module judges the expression of the comprehensive value of the collected energy consumption data according to the comparison result as follows:
；
wherein the energy consumption data collected by the energy consumption collection module 11 is that，/>Representing the energy consumption data acquired at the ith position of the machine base, < >>Similarly, for two positions +.> and />The energy consumption difference can be defined as: i.e. position->And position->The energy consumption difference between the two is absolute value, which represents the energy consumption distribution difference degree of different positions, and the energy consumption difference expression is as follows:
；
wherein ,the data collection unit represents the position with the largest energy consumption difference in the whole machine base and the difference value is the data collection unit +.>Then the position number corresponding to this position is represented, < +.> and />The value expression defining a location is as follows:
；
wherein ,indicating the number of positions of the stand> and />Respectively express and position->The corresponding difference value maximum position pair and one position in the difference value minimum position pair.
As a further improvement of the technical scheme, the energy consumption analysis unit comprises a prediction analysis module and a scheme making module;
the prediction analysis module is used for predicting the energy consumption data collected by the energy consumption collection module subsequently according to the evaluation result of the interference analysis module and the mechanical aging of the unit;
the scheme making module is used for carrying out energy demand analysis on the prediction result of the prediction analysis module so as to make an energy distribution scheme according to the analysis result.
As a further improvement of the technical scheme, the implementation control unit comprises a scheme implementation module and a state reminding module;
the scheme implementation module is used for uploading the energy distribution scheme manufactured by the scheme manufacturing module to the cloud and controlling the unit;
the state reminding module is used for monitoring the running state of the engine base in real time, analyzing and labeling the abnormal running state and uploading the abnormal running state to the cloud.
As a further improvement of the technical scheme, the scheme implementation module controls the unit as follows:
the power consumption of the alcohol refining unit is controlled by sending an instruction for adjusting the power supply voltage to the unit;
the fuel consumption of the alcohol refining unit is regulated by sending an instruction for controlling the opening and closing of a valve to the unit;
the water resource utilization condition of the alcohol refining unit is optimized by sending a flow adjusting instruction to the unit.
As a further improvement of the technical scheme, the data optimization unit comprises an evaluation feedback module and a scheme updating module;
the evaluation feedback module is used for collecting feedback information of the energy allocation scheme modified by the user after the state reminding module is uploaded to the cloud;
the scheme updating module is used for updating the energy distribution scheme according to the feedback information collected by the evaluation feedback module, predicting the updated scheme and judging implementation of the scheme according to a prediction result.
Compared with the prior art, the invention has the beneficial effects that:
in the energy consumption monitoring and remote control system of the alcohol refining unit, the energy consumption data of the alcohol refining unit are collected in real time and predicted through the energy consumption data, so that alcohol refining can comprehensively monitor and control the energy consumption condition in real time, remote adjustment and optimization are realized, an energy consumption report, trend analysis and prediction are generated through management and analysis of the energy consumption data, decision support and energy consumption optimization suggestion are provided for a user, adjustment and control of the running state of the unit are realized through sending instructions to the unit, intelligent adjustment and optimization can be performed according to the energy consumption report and preset parameters, the energy consumption efficiency of the unit is improved, bottleneck and potential optimization points of energy consumption can be identified through analysis and prediction of the energy consumption data combined with installation environment interference factors, a targeted suggestion and improvement scheme is provided, the user is helped to optimize energy consumption, and the production cost is reduced.
Drawings
FIG. 1 is an overall flow diagram of the present invention;
FIG. 2 is a block diagram of a flow of collecting green energy for incoming energy supply in accordance with the present invention;
FIG. 3 is a block flow diagram of the present invention for analysis according to the crew environment;
FIG. 4 is a block flow diagram of an energy distribution scheme of the present invention;
FIG. 5 is a block flow diagram of anomaly analysis for an energy distribution scheme of the present invention;
fig. 6 is a block flow diagram of data optimization for an energy distribution scheme in accordance with the present invention.
The meaning of each reference sign in the figure is:
10. a data collection unit; 11. an energy consumption acquisition module; 12. an energy source introduction module;
20. a data analysis unit; 21. an interference analysis module; 22. a data comparison module;
30. an energy consumption analysis unit; 31. a predictive analysis module; 32. a scheme making module;
40. an implementation control unit; 41. a scheme implementation module; 42. a state reminding module;
50. a data optimizing unit; 51. an evaluation feedback module; 52. and a scheme updating module.
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.
Examples:
referring to fig. 1-6, the present embodiment is directed to an energy consumption monitoring and remote control system of an alcohol refining unit, which includes a data collecting unit 10, a data analyzing unit 20, an energy consumption analyzing unit 30, an implementation control unit 40 and a data optimizing unit 50;
the data collection unit 10 is used for collecting energy consumption data of the unit, collecting green energy and introducing energy, and the data analysis unit 20 is used for analyzing according to the unit environment and analyzing the energy consumption data collected by the data collection unit 10 according to the analysis data;
the data collection unit 10 comprises an energy consumption acquisition module 11 and an energy introduction module 12;
the energy consumption acquisition module 11 is used for monitoring the running state of the engine base in real time and judging and collecting the energy consumption data of the engine base according to the running state of the engine base; the data acquisition is carried out according to the working state of the engine base, so that the waste of sensor energy sources is avoided, the engine base data are acquired by adopting the sensor when the engine base works, and the sensor part comprises a temperature sensor, a pressure sensor and a flow sensor which are respectively arranged in the alcohol refining unit and used for acquiring energy consumption data such as temperature, pressure, flow and the like in real time;
the energy source introducing module 12 is used for judging and collecting green energy sources according to the unit environment, and conveying the collected green energy sources to the stand for energy supply. The energy supply system of the unit is used for introducing green energy sources such as solar energy, wind energy and the like into the energy supply system of the unit, so that the energy consumption of the unit is reduced, the operation cost is reduced, and meanwhile, the energy supply system also accords with the concept of environmental protection, and the steps are as follows:
judging the required energy: the selected green energy type and characteristics are derived from the type of energy required by the housing, such as dc, ac or other forms of energy.
And (3) collecting green energy: and selecting corresponding collecting tools and equipment according to the green energy types and the environmental conditions to obtain the collected green energy E.
And (3) conveying green energy: and determining a proper conveying mode and conveying equipment according to the collected green energy types. Assuming that the impedance of a power transmission line or pipeline for transmitting green energy is R, the distance of power transmission or transmission is L, the flow of power transmission current or transmission energy is I or Q, and the power of power transmission or water is P, the loss in the transmission process can be calculated by using the following formula:
a power transmission line:；
conveying pipeline:；
energy supply: the green energy delivered to the housing is converted to the energy required by the housing or directly powers the housing, which can be calculated using the following formula:
the green energy is converted into electric energy: p=eta;
directly supply energy to the stand: p=e;
wherein eta represents the conversion efficiency of converting green energy into electric energy, and P is the electric energy received by the engine base;
the data analysis unit 20 includes an interference analysis module 21 and a data comparison module 22;
the interference analysis module 21 is used for collecting data of the installation environment of the unit and evaluating the interference degree of the energy consumption data collected by the energy consumption collection module 11; for these factors, corresponding measures can be taken, such as increasing the number of sensors, improving the equipment protection, etc., to improve the stability and accuracy of the data acquisition equipment, thereby reducing the influence of interference factors;
the data comparison module 22 is used for comparing different positions of the energy consumption data collected by the energy consumption collection module 11, and judging the comprehensive value of the collected energy consumption data according to the comparison result.
The interference analysis module 21 evaluates the interference degree of the energy consumption data collected by the energy consumption collection module 11 as follows:
environmental interference assessment: the method comprises the steps of carrying out numerical value acquisition on environmental factors such as environmental noise, air temperature change and humidity change, and judging the accuracy and stability of data acquisition equipment according to the numerical value; the acquisition was performed using a sensor, expressed as follows:
influence of environmental noise on the accuracy of data acquisition devices:
error=ASSNR；
wherein A represents the amplitude of environmental noise, S represents the amplitude of the measured signal, SNR represents the signal-to-noise ratio, and the larger the error value is, the larger the influence is;
influence of temperature or humidity changes on the stability of the data acquisition device:
De%=Deltax（x0）x100%；
wherein Deltax represents a measured value deviation caused by environmental change, x0 represents a measured value before environmental change, de% is an influence value, and the smaller the De% influence value is, the larger the influence on the acquisition equipment is.
Electromagnetic interference assessment: the method comprises the steps of carrying out numerical value acquisition on electromagnetic signal interference from other equipment in a unit installation area, and judging that the transmitted data are abnormal or distorted according to the numerical value; first, a suitable test apparatus needs to be selected. The equipment is provided with an electromagnetic field intensity tester, a spectrum analyzer and an oscilloscope, and the electromagnetic field intensity tester, the spectrum analyzer and the oscilloscope need to be selected according to specific conditions; the expression is:
relationship between electromagnetic field strength and voltage amplitude:
V=Ed；
where V represents the voltage amplitude, E represents the electromagnetic field strength, and d represents the distance from the measured point to the power supply.
Degree of fundamental frequency distortion:
；
where V1 represents the fundamental frequency voltage amplitude, vk represents the k-multiplied voltage amplitude, and THD is the degree of influence.
Degree of loss of fundamental frequency effective value:
V=X,Z-1；
wherein X and Z respectively represent the peak value and the effective value of the interfered voltage;
signal transmission interference assessment: and carrying out numerical value acquisition on interference in signal transmission lines such as a cable line, a communication line and the like, and judging the influence on the signal quality of the data acquisition equipment according to the numerical value. The acquisition of interference signals, including the demand signals and interference noise signals from other signal sources, is generally carried out by adopting test instruments such as oscilloscopes, spectrum analyzers and the like; the expression is as follows:
signal-to-noise ratio SNR:
SNR=QE；
wherein, Q is signal power, E is noise power, which can be obtained by time domain and frequency domain analysis of the signal.
Signal distortion ratio THD:
；
where V1 represents the fundamental voltage in the spectrum and Vk represents the kth harmonic voltage in the spectrum.
The data comparison module 22 judges the expression of the comprehensive value of the collected energy consumption data according to the comparison result as follows:
Eij=Ei-Ej；
the energy consumption data collected by the energy consumption collection module 11 is E, ei represents the energy consumption data collected at the ith position of the stand, ej is the same, in order to determine the value of each position, we can use the energy consumption difference between different positions of the stand, and for two positions i and j, the energy consumption difference can be defined as: that is, the energy consumption difference between the position i and the position j takes an absolute value, and the larger the value is, the larger the energy consumption difference between the two positions is represented, the energy consumption distribution difference degree of different positions is represented, and the energy consumption difference expression is as follows:
DE=DE&(IMI,JMI),{IMIJMI}；
where de=data collection unit 10, the position pair difference value representing the greatest difference in energy consumption in the whole engine base is the data collection unit 10, and (IMA, JMA) represents the position number corresponding to the position, and DL and (IMI, JMI) are similarly defined, and the value expression defining a position is as follows:
Vi={DE}{1,2,n}&1-i{min}；
where n represents the number of positions of the housing, i { max } and i { min } represent one position of the maximum difference value position pair and the minimum difference value position pair corresponding to position i, respectively, and this definition represents the relative value of position i in the position comparison with the maximum difference value and the position comparison with the minimum difference value, and in this definition, the evaluation is performed according to the Vi value, and the smaller the difference value, the higher the value.
The energy consumption analysis unit 30 is used for predicting the data collected by the data collection unit 10 and the analysis data of the data analysis unit 20, and making an energy distribution scheme according to the prediction result;
the energy consumption analysis unit 30 includes a prediction analysis module 31 and a scenario making module 32;
the prediction analysis module 31 is configured to predict the energy consumption data collected by the energy consumption collection module 11 according to the evaluation result of the interference analysis module 21 and the mechanical aging of the unit; the expression is as follows:
energy consumption = α+β1×temperature+β2×humidity+β3×wind speed direction+β4×barometric pressure+β5×mechanical ageing;
wherein, the energy consumption: the energy consumption of a unit is generally expressed in units of measurement such as kilowatt-hours kWh and the like, alpha: the intercept term in the model indicates that when the factors such as temperature, humidity, wind speed, air pressure and mechanical aging are all 0, certain energy consumption still exists, and the factors include beta 1, beta 2, beta 3, beta 4 and beta 5: regression coefficients, representing the degree of influence of the corresponding change of each predictor on energy consumption, for example, β1 represents the influence of temperature change on energy consumption, β2 represents the influence of humidity change on energy consumption, and so on, temperature, humidity, wind speed, air pressure, mechanical aging: the independent variables in the model represent the influence of environmental factors and the degree of mechanical ageing on the energy consumption.
The scheme making module 32 is configured to perform energy demand analysis on the prediction result of the prediction analysis module 31, so as to make an energy distribution scheme according to the analysis result. The method comprises the following steps:
predicting energy consumption: and the energy consumption of the unit in a future period is predicted through the data acquired by the energy consumption acquisition module 11, so as to obtain a predicted value of the energy consumption data.
Determining service requirements: and determining the required energy consumption and quality according to the application or occasion of the unit.
Analyzing the predicted data: and comparing the predicted result with the service demand, analyzing the deviation condition between the energy consumption and the demand, and analyzing the cause and influence of the deviation. And also analyze the main reasons affecting the energy consumption to determine the need for reinforcement or improvement.
And (3) preparing an energy distribution scheme: based on the analysis results of energy demand and consumption, a corresponding energy distribution scheme is formulated to ensure the stability and safety of energy supply;
the implementation control unit 40 is used for controlling the energy consumption of the unit according to the energy distribution scheme manufactured by the energy consumption analysis unit 30, collecting the running state of the base for evaluation, and performing anomaly analysis according to the energy distribution scheme manufactured by the energy consumption analysis unit 30;
the implementation control unit 40 includes a scenario implementation module 41 and a status alert module 42;
the scheme implementation module 41 is used for uploading the energy allocation scheme manufactured by the scheme manufacturing module 32 to the cloud and controlling the unit; the cloud platform is communicated with the unit and sends an instruction to the unit;
the state reminding module 42 is configured to monitor the running state of the stand in real time, and analyze and annotate the abnormal running state and upload the abnormal running state to the cloud. The method comprises the following steps:
and (3) data acquisition: and installing a sensor, and collecting real-time data of the engine base, including relevant data such as temperature, running speed, current, vibration, engine base state and the like.
Uploading data: and uploading the acquired frame data to the cloud, and selecting a local storage system to facilitate further analysis.
Data analysis: and analyzing the uploaded engine base data by using a data analysis tool, and identifying an abnormal operation state. Machine learning analysis data may be employed.
And (3) anomaly labeling: labeling the detected abnormality by a labeling system, wherein the labeling system comprises an abnormality type, an abnormality occurrence time, a data state of an abnormality moment and the like;
the scheme implementation module 41 controls the unit as follows:
the power consumption of the alcohol refining unit is controlled by sending an instruction for adjusting the power supply voltage to the unit;
the fuel consumption of the alcohol refining unit is regulated by sending an instruction for controlling the opening and closing of a valve to the unit;
the water resource utilization condition of the alcohol refining unit is optimized by sending a flow adjusting instruction to the unit.
The data optimization unit 50 is configured to mark the abnormal analysis result in the energy distribution scheme, send the marked abnormal analysis result to the cloud to obtain feedback data, and perform data optimization on the energy distribution scheme according to the feedback data.
The data optimization unit 50 includes an evaluation feedback module 51 and a scheme update module 52;
the evaluation feedback module 51 is used for collecting feedback information of the energy allocation scheme modified by the user after the state reminding module 42 is uploaded to the cloud; and sending an energy consumption report and running state reminding information to a user through the cloud platform, and providing a real-time energy consumption monitoring visualization and warning function. A user can inquire and analyze historical energy consumption data through the cloud platform, so that energy consumption optimization and decision support can be realized;
the scheme updating module 52 is configured to update the energy allocation scheme according to the feedback information collected by the evaluation feedback module 51, predict the updated scheme, and determine implementation of the scheme according to the prediction result. The method comprises the following steps:
and (3) establishing a prediction model to predict the updated energy distribution scheme to obtain the energy use condition in a future period of time. The predictive model may employ a neural network model.
Judging the energy distribution scheme according to the prediction result, guiding an energy manager to adjust, improving the energy utilization efficiency and reducing the energy consumption cost, and making energy-saving control and management work;
the foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. Energy consumption monitoring and remote control system of alcohol refining unit, its characterized in that: comprises a data collection unit (10), a data analysis unit (20), an energy consumption analysis unit (30), an implementation control unit (40) and a data optimization unit (50);
the data collection unit (10) is used for collecting energy consumption data of the unit, collecting green energy and introducing energy, and the data analysis unit (20) is used for analyzing according to the unit environment and analyzing the energy consumption data collected by the data collection unit (10) according to the analysis data;
the energy consumption analysis unit (30) is used for predicting the data acquired by the data collection unit (10) in combination with the analysis data of the data analysis unit (20), and manufacturing an energy distribution scheme according to a prediction result;
the implementation control unit (40) is used for controlling the energy consumption of the unit according to the energy distribution scheme manufactured by the energy consumption analysis unit (30), collecting the running state of the base for evaluation, and performing abnormal analysis according to the energy distribution scheme manufactured by the energy consumption analysis unit (30);
the data optimization unit (50) is used for marking the abnormal analysis result in the energy distribution scheme, sending the marked abnormal analysis result to the cloud to obtain feedback data, and performing data optimization on the energy distribution scheme according to the feedback data.
2. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 1, wherein: the data collection unit (10) comprises an energy consumption collection module (11) and an energy source introduction module (12);
the energy consumption acquisition module (11) is used for monitoring the running state of the engine base in real time and judging and collecting the energy consumption data of the engine base according to the running state of the engine base;
the energy source introducing module (12) is used for judging and collecting green energy sources according to the unit environment and conveying the collected green energy sources to the machine base for energy supply.
3. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 2, wherein: the data analysis unit (20) comprises an interference analysis module (21) and a data comparison module (22);
the interference analysis module (21) is used for collecting data of the installation environment of the unit and evaluating the interference degree of the energy consumption data collected by the energy consumption collection module (11);
the data comparison module (22) is used for comparing different positions of the energy consumption data collected by the energy consumption collection module (11), and judging the comprehensive value of the collected energy consumption data according to the comparison result.
4. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 3, wherein: the interference analysis module (21) evaluates the interference degree of the energy consumption data collected by the energy consumption acquisition module (11) as follows:
environmental interference assessment: the method comprises the steps of carrying out numerical value acquisition on environmental factors such as environmental noise, air temperature change and humidity change, and judging the accuracy and stability of data acquisition equipment according to the numerical value;
electromagnetic interference assessment: the method comprises the steps of carrying out numerical value acquisition on electromagnetic signal interference from other equipment in a unit installation area, and judging that the transmitted data are abnormal or distorted according to the numerical value;
signal transmission interference assessment: and carrying out numerical value acquisition on interference from the cable line signal transmission line, and judging the influence on the signal quality of the data acquisition equipment according to the numerical value.
5. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 3, wherein: the data comparison module (22) judges the expression of the comprehensive value of the collected energy consumption data according to the comparison result as follows:
；
wherein the energy consumption data received by the energy consumption acquisition module (11) is that，/>Representing the energy consumption data acquired at the ith position of the machine base, < >>Similarly, for two positions +.> and />The energy consumption difference can be defined as: i.e. position->And position->The energy consumption difference between the two is absolute value, which represents the energy consumption distribution difference degree of different positions, and the energy consumption difference expression is as follows:
；
wherein ,the data collection unit represents the position with the largest energy consumption difference in the whole machine base and the difference value is the data collection unit +.>Then the position number corresponding to this position is represented, < +.> and />The value expression defining a location is as follows:
；
wherein ,indicating the number of positions of the stand> and />Respectively express and position->The corresponding difference value maximum position pair and one position in the difference value minimum position pair.
6. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 3, wherein: the energy consumption analysis unit (30) comprises a prediction analysis module (31) and a scheme making module (32);
the prediction analysis module (31) is used for predicting the energy consumption data acquired by the energy consumption acquisition module (11) subsequently according to the evaluation result of the interference analysis module (21) and the mechanical aging of the unit;
the scheme making module (32) is used for analyzing the energy demand of the prediction result of the prediction analysis module (31) so as to make an energy distribution scheme according to the analysis result.
7. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 6, wherein: the implementation control unit (40) comprises an implementation scheme module (41) and a state reminding module (42);
the scheme implementation module (41) is used for uploading the energy distribution scheme manufactured by the scheme manufacturing module (32) to the cloud and controlling the unit;
the state reminding module (42) is used for monitoring the running state of the engine base in real time, analyzing and labeling the abnormal running state and uploading the abnormal running state to the cloud.
8. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 7, wherein: the scheme implementation module (41) controls the unit as follows:
the power consumption of the alcohol refining unit is controlled by sending an instruction for adjusting the power supply voltage to the unit;
the fuel consumption of the alcohol refining unit is regulated by sending an instruction for controlling the opening and closing of a valve to the unit;
the water resource utilization condition of the alcohol refining unit is optimized by sending a flow adjusting instruction to the unit.
9. The energy consumption monitoring and remote control system of an alcohol refining unit according to claim 1, wherein: the data optimization unit (50) comprises an evaluation feedback module (51) and a scheme update module (52);
the evaluation feedback module (51) is used for collecting feedback information of the energy allocation scheme modified by the user after the state reminding module (42) is uploaded to the cloud;
the scheme updating module (52) is used for updating the energy distribution scheme according to the feedback information acquired by the evaluation feedback module (51), predicting the updated scheme and judging the implementation of the scheme according to the prediction result.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116937818A (en) * | 2023-09-19 | 2023-10-24 | 北京松岛菱电设备有限公司 | High-voltage direct-current power distribution cabinet monitoring system for monitoring inside in real time |
| CN116937819A (en) * | 2023-09-19 | 2023-10-24 | 北京松岛菱电设备有限公司 | Remote power distribution cabinet monitoring system with learning function |
| CN117455080A (en) * | 2023-12-25 | 2024-01-26 | 深圳市宏大联合实业有限公司 | Production workshop environment optimization method and system based on Internet of things |
| CN117452900A (en) * | 2023-12-22 | 2024-01-26 | 广东正德工业科技股份有限公司 | Industrial production energy consumption monitoring system and method based on artificial intelligence |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2138914A2 (en) * | 2008-06-27 | 2009-12-30 | Robert Bosch GmbH | Method and device for optimising, monitoring or analysing a process |
| CN102063078A (en) * | 2009-11-13 | 2011-05-18 | 深圳达实智能股份有限公司 | System for remotely monitoring energy consumption of central air-conditioning |
| US20170108885A1 (en) * | 2015-10-14 | 2017-04-20 | Honeywell International Inc. | System for dynamic control with interactive visualization to optimize energy consumption |
| CN109283898A (en) * | 2018-09-03 | 2019-01-29 | 安徽伟迈信息技术有限公司 | A kind of plant area's energy consumption monitoring management system |
| CN109426205A (en) * | 2017-09-05 | 2019-03-05 | 万洲电气股份有限公司 | A kind of industrial intelligent Optimization of Energy Saving system |
| CN113848843A (en) * | 2021-10-21 | 2021-12-28 | 万洲电气股份有限公司 | Self-diagnosis analysis system based on intelligent optimization energy-saving system |
| CN116600446A (en) * | 2023-07-17 | 2023-08-15 | 智隆(广州)网络科技有限公司 | Intelligent street lamp system based on Internet of things technology |
-
2023
- 2023-08-21 CN CN202311047760.3A patent/CN116755377A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2138914A2 (en) * | 2008-06-27 | 2009-12-30 | Robert Bosch GmbH | Method and device for optimising, monitoring or analysing a process |
| CN102063078A (en) * | 2009-11-13 | 2011-05-18 | 深圳达实智能股份有限公司 | System for remotely monitoring energy consumption of central air-conditioning |
| US20170108885A1 (en) * | 2015-10-14 | 2017-04-20 | Honeywell International Inc. | System for dynamic control with interactive visualization to optimize energy consumption |
| CN109426205A (en) * | 2017-09-05 | 2019-03-05 | 万洲电气股份有限公司 | A kind of industrial intelligent Optimization of Energy Saving system |
| CN109283898A (en) * | 2018-09-03 | 2019-01-29 | 安徽伟迈信息技术有限公司 | A kind of plant area's energy consumption monitoring management system |
| CN113848843A (en) * | 2021-10-21 | 2021-12-28 | 万洲电气股份有限公司 | Self-diagnosis analysis system based on intelligent optimization energy-saving system |
| CN116600446A (en) * | 2023-07-17 | 2023-08-15 | 智隆(广州)网络科技有限公司 | Intelligent street lamp system based on Internet of things technology |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116937818A (en) * | 2023-09-19 | 2023-10-24 | 北京松岛菱电设备有限公司 | High-voltage direct-current power distribution cabinet monitoring system for monitoring inside in real time |
| CN116937819A (en) * | 2023-09-19 | 2023-10-24 | 北京松岛菱电设备有限公司 | Remote power distribution cabinet monitoring system with learning function |
| CN116937818B (en) * | 2023-09-19 | 2023-12-08 | 北京松岛菱电设备有限公司 | High-voltage direct-current power distribution cabinet monitoring system for monitoring inside in real time |
| CN116937819B (en) * | 2023-09-19 | 2023-12-08 | 北京松岛菱电设备有限公司 | Remote power distribution cabinet monitoring system with learning function |
| CN117452900A (en) * | 2023-12-22 | 2024-01-26 | 广东正德工业科技股份有限公司 | Industrial production energy consumption monitoring system and method based on artificial intelligence |
| CN117452900B (en) * | 2023-12-22 | 2024-05-03 | 广东正德智能设备有限公司 | Industrial production energy consumption monitoring system and method based on artificial intelligence |
| CN117455080A (en) * | 2023-12-25 | 2024-01-26 | 深圳市宏大联合实业有限公司 | Production workshop environment optimization method and system based on Internet of things |
| CN117455080B (en) * | 2023-12-25 | 2024-04-05 | 深圳市宏大联合实业有限公司 | Production workshop environment optimization method and system based on Internet of things |
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