CN116505663B - Farm power consumption safety state monitoring and early warning system - Google Patents
Farm power consumption safety state monitoring and early warning system Download PDFInfo
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- CN116505663B CN116505663B CN202310775984.XA CN202310775984A CN116505663B CN 116505663 B CN116505663 B CN 116505663B CN 202310775984 A CN202310775984 A CN 202310775984A CN 116505663 B CN116505663 B CN 116505663B
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 37
- 230000005611 electricity Effects 0.000 claims abstract description 85
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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Abstract
The invention relates to the technical field of electricity consumption monitoring, and particularly discloses a farm electricity consumption safety state monitoring and early warning system, which comprises: the power monitoring module is used for monitoring the power parameters of each farm device in the shed; the farm equipment management platform is communicated with the power monitoring module through an NB-loT network and is used for receiving the power parameters acquired by the power monitoring module; the six-element environment data collector is used for collecting environment data in each shed; the agricultural meteorological station is used for monitoring environmental parameters outside the shed; the early warning analysis end is in communication connection with the farm equipment management platform, the six-element environment data collector and the agricultural meteorological station and is used for carrying out simulation analysis on the electric power parameters of each farm equipment according to preset environment data inside and outside the shed, comparing and analyzing the simulation analysis result with the electric power parameters on the farm equipment management platform and carrying out early warning on the farm electricity utilization safety according to the analysis result.
Description
Technical Field
The invention relates to the technical field of electricity consumption monitoring, in particular to a farm electricity consumption safety state monitoring and early warning system.
Background
With the rapid development of intelligent equipment and the Internet of things technology, the traditional planting mode is gradually replaced by the mode of planting crops by an intelligent farm, and various sensing assemblies and automatic control equipment are integrated in the intelligent farm, so that intelligent control can be automatically performed on a planting shed according to a real-time environment state, environmental parameters of crops are adjusted, and the growth of the crops is utilized; and for the automatic control equipment configured in the intelligent farm, because the automatic control equipment runs automatically, the running safety and the electricity safety of the automatic control equipment need to be monitored in real time so as to ensure the safe and normal running of the automatic control equipment.
In the prior art, in the electricity safety monitoring process, a corresponding electric energy parameter acquisition module is arranged on the intelligent equipment, equipment electricity utilization data are acquired in real time and analyzed, and the state of the equipment is evaluated by combining normal electricity utilization historical data of the equipment.
However, in the prior art, although the equipment electricity consumption data can be accurately collected, in the judging process, the collected electricity consumption data can be judged only in a larger range due to the uncertainty of intelligent control, and the sensitivity of an electricity consumption safety monitoring result is lower; meanwhile, single electricity consumption data monitoring cannot completely judge the running state of equipment, so that the intelligent equipment management in the intelligent farm is not facilitated.
Disclosure of Invention
The invention aims to provide a farm electricity safety state monitoring and early warning system, which solves the following technical problems:
how to monitor the farm electricity safety more accurately and to realize the comprehensive management of farm equipment.
The aim of the invention can be achieved by the following technical scheme:
a farm electricity safety status monitoring and early warning system, the system comprising:
the power monitoring module is used for monitoring the power parameters of each farm device in the shed;
the farm equipment management platform is communicated with the power monitoring module through an NB-loT network and is used for receiving the power parameters acquired by the power monitoring module;
the six-element environment data collector is used for collecting environment data in each shed;
the agricultural meteorological station is used for monitoring environmental parameters outside the shed;
the early warning analysis end is in communication connection with the farm equipment management platform, the six-element environment data collector and the agricultural meteorological station and is used for carrying out simulation analysis on the electric power parameters of each farm equipment according to preset environment data inside and outside the shed, comparing and analyzing the simulation analysis result with the electric power parameters on the farm equipment management platform and carrying out early warning on the farm electricity utilization safety according to the analysis result.
In one embodiment, the process of simulating analysis includes:
preset environmental parameters corresponding to the operation type of each farm device;
and acquiring preset environmental data inside and outside the shed in the operation process of each farm device, carrying out predictive analysis on each farm device according to the change condition of the environmental data inside and outside the shed, and taking the predictive result as a simulation analysis result.
In one embodiment, the predictive process for each farm device includes:
by the formula Obtaining real-time predicted power of kth farm equipment +.>；
wherein ,i=1, 2, …, < >>；/>A measuring function for the kth farm equipment; />Is the starting point in time of the kth farm equipment; />Presetting an environmental parameter change function for the ith shed; />Is an external environment influence coefficient; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment in the ith shed; />Is the efficiency coefficient of the kth farm equipment.
In one embodiment, the external environmental impact coefficientThe acquisition process of (1) comprises:
by the formulaCalculating to obtain external environment influence coefficient->；
wherein ,the number of environmental parameters is preset outside the shed for the kth farm equipment, j=1, 2, …, < >>；/>Presetting an environmental parameter change function outside a jth shed; />Presetting an environment parameter standard value outside a j-th shed; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment for the jth shed outside; />Is the external environment shadow of the kth farm equipmentAnd (5) sounding the threshold.
In one embodiment, the farm equipment includes an automatic irrigation sprinkler and an automatic ventilation device;
when the farm equipment is an automatic irrigation spraying machine, the corresponding preset environmental parameters comprise soil humidity, environmental humidity and environmental temperature;
when the farm equipment is an automatic ventilation device, the corresponding preset environmental parameters include carbon dioxide concentration, environmental temperature and environmental humidity.
In one embodiment, the process of pre-warning the farm electrical safety according to the analysis result comprises the following steps:
fitting the real-time power P (t) of the kth farm equipment according to the electric power parameters on the farm equipment management platform;
by the formulaCalculating to obtain real-time error coefficient->；
And when the error coefficient reaches or exceeds a preset threshold value, early warning is carried out.
In one embodiment, the system further comprises an electricity usage anomaly big data analysis model;
the electricity consumption abnormal big data analysis model is used for predicting daily electricity consumption according to input environmental parameters;
the early warning analysis end is also used for judging and analyzing according to the predicted daily electricity consumption and the actual daily electricity consumption, and early warning is carried out according to a judgment and analysis result.
In one embodiment, the process of acquiring the electricity consumption abnormal big data analysis model comprises the following steps:
taking environmental data and corresponding electricity utilization data in the electricity utilization safety state of the farm as a group of samples, and acquiring a plurality of groups of samples according to the historical environmental data and the corresponding electricity utilization data of the farm;
and based on the time sequence analysis model, performing machine learning training through a plurality of groups of samples to obtain the power consumption abnormal big data analysis model.
In one embodiment, the early warning analysis end performs early warning according to the judgment analysis result, and the early warning process includes:
by the formulaCalculating to obtain electricity consumption difference +.>；
Wherein Q is the actual daily electricity quantity;predicting electricity consumption for a day;
when the electricity consumption difference reaches or exceeds a difference threshold, early warning is carried out;
otherwise, throughCalculating to obtain a risk value G;
when the risk value reaches or exceeds the risk threshold value, early warning is carried out;
wherein ,is the maximum value of the daily real-time error coefficient, < >>Is a correction coefficient.
The invention has the beneficial effects that:
(1) According to the invention, on one hand, the operation effect of the equipment can be accurately judged, on the other hand, the prediction result can be used as a reference basis for accurate electricity consumption parameters, so that the operation safety of the electric power parameters can be accurately judged, the electric leakage and equipment power failure problems in the operation process of the equipment can be technically judged in time, and the stable safety of farm operation and maintenance is ensured.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a logic block diagram of the farm electrical safety status monitoring and early warning system of the present invention.
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.
Referring to fig. 1, in one embodiment, a farm power consumption safety state monitoring and early warning system is provided, the system includes a power monitoring module, a farm equipment management platform, a six-element environmental data collector, an agricultural weather station and an early warning analysis end, the power monitoring module is arranged on each farm equipment, and can acquire real-time data of common power parameters, such as current, power consumption and the like, and the farm equipment includes intelligent equipment commonly used in intelligent farms, such as an automatic irrigation spray machine, an automatic ventilation device and the like; uploading the acquired power parameters to a farm equipment management platform through an NB-loT network, so that the power parameters of a plurality of equipment can be acquired; the six-element environmental data collector can collect environmental data in each shed, such as illumination data, gas data, temperature data, soil data and the like in the shed, the agricultural weather station is arranged outside the shed, and can collect environmental parameters outside the shed, and the main collected environmental parameters comprise the illumination data, the gas data, the temperature data and the like; through the early warning analysis end, the electric power parameters of each farm device can be simulated and analyzed according to preset environmental data inside and outside the shed, the simulation analysis result is compared with the electric power parameters on the farm device management platform, and early warning is carried out on the farm electricity safety according to the analysis result.
Taking an automatic irrigation spraying machine as an example, in an intelligent farm, the automatic irrigation spraying machine can perform corresponding spraying irrigation operation according to the humidity data of soil, and meanwhile, the operation parameters of the automatic irrigation spraying machine are adjusted according to other environmental factors; in the monitoring process of the automatic irrigation spraying machine, the early warning analysis end correspondingly sets preset environmental parameters including soil humidity, environmental humidity and environmental temperature according to the operation type of the automatic irrigation spraying machine, acquires preset environmental data inside and outside a shed in the operation process of each farm device, carries out predictive analysis on the automatic irrigation spraying machine through the change conditions of the soil humidity, the environmental humidity and the environmental temperature inside and outside the shed, further can carry out reverse pushing on the working operation state of the automatic irrigation spraying machine based on the actual working effect of the automatic irrigation spraying machine, further carries out comparative analysis on the predicted electricity utilization data and the actual data, on one hand, can accurately judge the operation effect of the device, on the other hand, can be used as a reference basis for accurate electricity utilization parameters, further can accurately judge the operation safety of the electric power parameters, timely carries out technical judgment on the problems of electric leakage and equipment power failure existing in the operation process of the device, and ensures the stable safety of farm operation and maintenance.
As an embodiment of the present invention, there is provided a prediction process for each farm device, specifically, first performing data fitting according to empirical data corresponding to the farm device and corresponding preset environmental parameters, to obtain an objective function of each farm deviceAnd the influence coefficient of the preset environmental parameter variation function on farm equipment +.>Then by the formula Obtaining real-time predicted power of kth farm equipment +.>； wherein ,/>I=1, 2, …, < >>；/>A measuring function for the kth farm equipment; />Is the starting point in time of the kth farm equipment; />Presetting an environmental parameter change function for the ith shed; />Is an external environment influence coefficient; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment in the ith shed; />Efficiency coefficient for the kth farm equipment;
coefficient of external environmental influenceThe acquisition process of (1) comprises:
by the formulaCalculating to obtain external environment influence coefficient；
wherein ,the number of environmental parameters is preset outside the shed for the kth farm equipment, j=1, 2, …, < >>；/>Presetting an environmental parameter change function outside a jth shed; />Presetting an environment parameter standard value outside a j-th shed; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment for the jth shed outside; />Is the threshold value of the external environment influence of the kth farm equipment.
By the technical scheme, the method is based on the environmental data before the farm equipment worksAnd state data of change of environmental data during its operation +.>Substituting the power into the measuring and calculating function of the equipment to further realize the prediction process of the standard power, wherein the efficiency coefficient of farm equipment is +.>According to the conversion rate data calculated by the corresponding equipment, further obtaining the real-time predicted power +.>The method comprises the steps of carrying out a first treatment on the surface of the It should be noted that +.>Is the influence of the external environment influence coefficient on the prediction process, wherein the external environment influence coefficient is +.>According to the deviation condition of the related farm equipment out-of-shed preset environmental parameter relative to the corresponding standard value, the predicted power is obtained based on the out-of-shed preset environmental parameter in the standard value state, so that the power is obtained by the formula/>Calculating to obtain external environment influence coefficient->Further, a correction process of the prediction result is realized; wherein the farm equipment external environment influence threshold and influence coefficient +.>According to the fitting of the experience data, the environment data and the corresponding standard value are obtained, and therefore the external environment influence coefficient is obtained.
As one embodiment of the invention, the process of early warning the farm electricity safety according to the analysis result comprises the following steps: fitting the real-time power P (t) of the kth farm equipment according to the electric power parameters on the farm equipment management platform; by the formula Calculating to obtain real-time error coefficient->；
And when the error coefficient reaches or exceeds a preset threshold value, early warning is carried out.
Through the technical scheme, the embodiment provides a specific process of early warning the farm electricity safety according to the analysis result, and the embodiment aims at each farm device through the formulaCalculating to obtain real-time error coefficient->Analyzing and judging by acquiring the deviation condition of the whole period from the starting time point to the current time point of the equipment, so that the real-time error coefficient +.>And an early warning process is realized.
It should be noted that, the preset threshold is set according to the empirical data fitting of the corresponding farm equipment, which will not be described in detail herein.
As an embodiment of the invention, the farm equipment can also be an automatic ventilation device; when the farm equipment is an automatic ventilation device, the corresponding preset environmental parameters comprise carbon dioxide concentration, environmental temperature and environmental humidity; the specific prediction process is the same as that of the automatic irrigation sprayer, and will not be described in detail herein.
As one embodiment of the present invention, the system further includes an electricity consumption abnormality big data analysis model;
the electricity consumption abnormal big data analysis model is used for predicting daily electricity consumption according to input environmental parameters;
the early warning analysis end is also used for judging and analyzing according to the predicted daily electricity consumption and the actual daily electricity consumption, and early warning is carried out according to a judgment and analysis result.
The process for acquiring the power consumption abnormal big data analysis model comprises the following steps:
taking environmental data and corresponding electricity utilization data in the electricity utilization safety state of the farm as a group of samples, and acquiring a plurality of groups of samples according to the historical environmental data and the corresponding electricity utilization data of the farm;
and based on the time sequence analysis model, performing machine learning training through a plurality of groups of samples to obtain the power consumption abnormal big data analysis model.
Through the technical scheme, the system in the embodiment further comprises an electricity consumption abnormal big data analysis model, wherein the electricity consumption abnormal big data analysis model is used as a group of samples according to the environmental data and the corresponding electricity consumption data in the electricity consumption safety state of the farm, and a plurality of groups of samples are obtained according to the historical environmental data and the corresponding electricity consumption data of the farm; based on the time sequence analysis model, performing machine learning training through a plurality of groups of samples to obtain an electricity consumption abnormal big data analysis model, so that the daily electricity consumption can be predicted according to the input environmental parameters through the electricity consumption abnormal big data analysis model; the early warning analysis end judges and analyzes according to the predicted daily electricity consumption and the actual daily electricity consumption, and early warning is carried out according to the judgment and analysis result; in the process, the comparison of the predicted daily electricity consumption and the actual electricity consumption can accurately judge the operation effect, the starting sensitivity and the abnormal electricity consumption condition of the farm equipment when the farm equipment is operated, so that the electricity consumption safety of the farm is ensured.
It should be noted that the process of performing machine training based on the time series analysis model is implemented based on the prior art, and will not be further described herein.
As one implementation mode of the invention, the early warning analysis end carries out early warning according to the judgment analysis result, and the early warning process comprises the following steps:
by the formulaCalculating to obtain electricity consumption difference +.>；
Wherein Q is the actual daily electricity quantity;predicting electricity consumption for a day;
when the electricity consumption difference reaches or exceeds a difference threshold, early warning is carried out;
otherwise, throughCalculating to obtain a risk value G;
when the risk value reaches or exceeds the risk threshold value, early warning is carried out;
wherein ,is the maximum value of the daily real-time error coefficient, < >>Is a correction coefficient.
Through the above technical solution, this embodiment provides a process that the early warning analysis end performs early warning according to the judgment analysis result, firstly, according to the difference value and the predicted daily electricity consumption of the actual daily electricity consumptionComparing the difference threshold values, when the difference value of the electricity consumption is larger, indicating that the farm equipment has safety risk, and when the difference value of the electricity consumption does not exceed the difference threshold value, passingCalculating to obtain a risk value G, comprehensively judging and obtaining the risk value G according to the power consumption difference value and the real-time error coefficient condition, and correcting the coefficient +.>And carrying out fitting determination according to empirical data, and further realizing a secondary early warning process of risks, wherein a difference value threshold and a risk threshold are obtained after data fitting according to specific equipment conditions of the farm, so that early warning is carried out when the risk value reaches or exceeds the risk threshold, and the electricity safety of the farm is ensured.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (6)
1. A farm electricity safety status monitoring and early warning system, the system comprising:
the power monitoring module is used for monitoring the power parameters of each farm device in the shed;
the farm equipment management platform is communicated with the power monitoring module through an NB-loT network and is used for receiving the power parameters acquired by the power monitoring module;
the six-element environment data collector is used for collecting environment data in each shed;
the agricultural meteorological station is used for monitoring environmental parameters outside the shed;
the early warning analysis end is in communication connection with the farm equipment management platform, the six-element environment data collector and the agricultural meteorological station and is used for carrying out simulation analysis on the electric power parameters of each farm equipment according to preset environment data inside and outside the shed, comparing and analyzing the simulation analysis result with the electric power parameters on the farm equipment management platform and carrying out early warning on the farm electricity utilization safety according to the analysis result;
the process of the simulation analysis comprises the following steps:
preset environmental parameters corresponding to the operation type of each farm device;
acquiring preset environmental data inside and outside a shed in the operation process of each farm device, carrying out predictive analysis on each farm device according to the change condition of the environmental data inside and outside the shed, and taking a predictive result as a simulation analysis result;
the predictive process for each farm device includes:
by the formula Obtaining real-time predicted power of kth farm equipment +.>；
wherein ,i=1, 2, …, < >>；/>A measuring function for the kth farm equipment; />Is the starting point in time of the kth farm equipment; />Presetting an environmental parameter change function for the ith shed;is an external environment influence coefficient; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment in the ith shed; />Efficiency coefficient for the kth farm equipment;
the external environment influence coefficientThe acquisition process of (1) comprises:
by the formulaCalculating to obtain external environment influence coefficient->；
wherein ,the number of environmental parameters is preset outside the shed for the kth farm equipment, j=1, 2, …, < >>；/>Presetting an environmental parameter change function outside a jth shed; />Presetting an environment parameter standard value outside a j-th shed; />Presetting an influence coefficient of an environmental parameter change function on kth farm equipment for the jth shed outside; />Is the threshold value of the external environment influence of the kth farm equipment.
2. The farm electrical safety status monitoring and warning system of claim 1, wherein the farm equipment comprises an automatic irrigation sprinkler and an automatic ventilation device;
when the farm equipment is an automatic irrigation spraying machine, the corresponding preset environmental parameters comprise soil humidity, environmental humidity and environmental temperature;
when the farm equipment is an automatic ventilation device, the corresponding preset environmental parameters include carbon dioxide concentration, environmental temperature and environmental humidity.
3. The farm electrical safety status monitoring and early warning system according to claim 1, wherein the process of early warning the farm electrical safety according to the analysis result comprises:
fitting the real-time power P (t) of the kth farm equipment according to the electric power parameters on the farm equipment management platform;
by the formulaCalculating to obtain real-time error coefficient->；
And when the error coefficient reaches or exceeds a preset threshold value, early warning is carried out.
4. The farm electricity safety status monitoring and early warning system according to claim 3, wherein the system further comprises an electricity consumption abnormality big data analysis model;
the electricity consumption abnormal big data analysis model is used for predicting daily electricity consumption according to input environmental parameters;
the early warning analysis end is also used for judging and analyzing according to the predicted daily electricity consumption and the actual daily electricity consumption, and early warning is carried out according to a judgment and analysis result.
5. The farm electricity safety state monitoring and early warning system according to claim 4, wherein the process of acquiring the electricity consumption abnormality big data analysis model comprises the following steps:
taking environmental data and corresponding electricity utilization data in the electricity utilization safety state of the farm as a group of samples, and acquiring a plurality of groups of samples according to the historical environmental data and the corresponding electricity utilization data of the farm;
and based on the time sequence analysis model, performing machine learning training through a plurality of groups of samples to obtain the power consumption abnormal big data analysis model.
6. The farm electricity safety state monitoring and early warning system according to claim 4, wherein the early warning analysis end performs early warning according to the judgment analysis result, and the early warning process comprises:
by the formulaCalculating to obtain electricity consumption difference +.>；
Wherein Q is the actual daily electricity quantity;predicting electricity consumption for a day;
when the electricity consumption difference reaches or exceeds a difference threshold, early warning is carried out;
otherwise, throughCalculating to obtain a risk value G;
when the risk value reaches or exceeds the risk threshold value, early warning is carried out;
wherein ,is the maximum value of the daily real-time error coefficient, < >>Is a correction coefficient.
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