CN116566050A - Comprehensive power distribution management system based on artificial intelligence - Google Patents
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Abstract
The invention relates to the technical field of power distribution management, in particular to an artificial intelligence-based comprehensive power distribution management system, which comprises a management platform, a supervision analysis unit, an allocation feedback unit, a risk assessment unit, a fault risk unit, an early warning unit and a safety management unit, wherein the supervision analysis unit is used for monitoring the distribution feedback unit; the invention collects the energy consumption data of the power distribution equipment and carries out monitoring, evaluation and analysis, thereby being beneficial to timely early warning, analyzing the power consumption from the angles of the power supply area, the power consumption user value, the average user increase value and the average power demand of the power distribution equipment, effectively guaranteeing the authenticity of the analysis result of the preset power consumption in the power supply area, improving the accuracy of subsequent power allocation, carrying out power distribution feedback evaluation and analysis on the user data from the angles of the power consumption user value and the power consumption value, carrying out reasonable management and power distribution on the power distribution equipment according to the fed-back information, and improving the working efficiency of the power distribution equipment so as to improve the management effect on the power distribution equipment.
Description
Technical Field
The invention relates to the technical field of power distribution management, in particular to an artificial intelligence-based comprehensive power distribution management system.
Background
With the continuous improvement of living standard and economy of people, the living and production of people in areas are increasingly kept away from each other, so that the waste of power in each power grid source is avoided in order to improve the collaborative development of power among the areas, the power in each power grid source needs to be allocated, and as the use of power equipment used by families and workshops is increased, the power load is also increased, and the reasonable allocation of power is particularly necessary;
however, at present, the power distribution in each power grid source is manually distributed mainly through workers, in the current power consumption analysis, the workers do not consider the power supply area and the power consumption user condition of the power distribution equipment, the influence of the power supply area and the power consumption user of the power distribution equipment on the power consumption cannot be reflected, further, the unreasonable distribution condition exists, and when the power distribution is carried out on the power distribution equipment, the situation of delayed distribution exists, further, reasonable optimization management cannot be carried out according to the delayed risk condition, the working efficiency of the power distribution equipment is reduced, and the problem that early warning is not timely exists in the fault risk early warning management cannot be carried out on the power distribution equipment.
Disclosure of Invention
The invention aims to provide an artificial intelligence-based comprehensive power distribution management system for solving the technical defects, which is characterized in that whether power distribution equipment needs to be distributed again is judged by collecting energy consumption data of the power distribution equipment and carrying out monitoring evaluation analysis, so that early warning is facilitated in time, the power consumption is analyzed from the power supply area, the power consumption user value, the average user increment value and the average power demand angle of the power distribution equipment, the comprehensiveness of analysis data and the analysis range are improved, the authenticity of the preset power consumption analysis result in the power supply area is effectively ensured, the accuracy of subsequent power distribution is improved, meanwhile, the power distribution feedback evaluation analysis is carried out on the user data from the two angles of the power consumption user quantity and the power consumption value, so that whether the power distribution of the power distribution equipment is normal or not is judged, the power distribution equipment is reasonably managed and distributed according to the feedback information, the work efficiency of the power distribution equipment is improved, and the management effect of the power distribution equipment is improved.
The aim of the invention can be achieved by the following technical scheme: an artificial intelligence-based comprehensive power distribution management system comprises a management platform, a supervision and analysis unit, an allocation feedback unit, a risk assessment unit, a fault risk unit, an early warning unit and a safety management unit;
when the management platform generates a management instruction, the management instruction is sent to the supervision and analysis unit, the supervision and analysis unit immediately collects energy consumption data of the power distribution equipment after receiving the management instruction, the energy consumption data comprise power supply areas, power utilization user values and power consumption of the power distribution equipment, monitors, evaluates and analyzes the energy consumption data, and sends an obtained distribution signal to the distribution feedback unit, the risk evaluation unit and the fault risk unit;
the distribution feedback unit immediately collects user data of a power supply area after receiving a distribution signal, wherein the user data comprises a power consumption user quantity and a power consumption value, performs distribution feedback evaluation analysis on the user data, sends obtained insufficient signals, proper value signals and excessive signals to the early warning unit through the supervision analysis unit, and immediately makes preset early warning operation corresponding to the insufficient signals, the proper value signals and the excessive signals after receiving the insufficient signals, the proper value signals and the excessive signals;
the fault risk unit immediately collects state data of the power distribution equipment after receiving the distribution signal, wherein the state data comprises the running temperature, the reactive power value and the running decibel value of the power distribution equipment, performs fault risk assessment analysis on the state data, sends an obtained risk signal to the early warning unit, and immediately controls an alarm lamp on the power distribution equipment to be red after receiving the risk signal;
and the risk assessment unit immediately collects operation data of the power distribution equipment after receiving the distribution signal, wherein the operation data comprises reaction time length and electromagnetic value, performs fault delay assessment analysis and formulation processing comparison analysis on the operation data, and sends the obtained primary delay signal, secondary delay signal and tertiary delay signal to the safety management unit.
Preferably, the power distribution feedback evaluation analysis process of the supervision and analysis unit is as follows:
s1: acquiring the duration from the starting time of the power distribution equipment to the current time, marking the duration as a time threshold, acquiring the power supply area of the power distribution equipment in the time threshold, simultaneously acquiring the total number of households and the number of non-entered households in the power supply area in the time threshold, marking the difference between the total number of households and the number of non-entered households as power utilization user values, dividing the time threshold into o sub-time periods, wherein o is a positive number greater than zero, acquiring the power utilization user values of the power supply area in each sub-time period, constructing a set A of the power utilization user values, acquiring the difference between two subsets connected in the set A, marking the difference as a user increment value, and acquiring the average user increment value YZ of the power supply area in the time threshold;
s12: acquiring the electricity consumption of each electricity consumption user value in the power supply area in each sub-time period, acquiring the difference value between the electricity consumption of each electricity consumption user value in two connected sub-time periods, marking the difference value as an electricity consumption floating value, acquiring the average electricity consumption floating value of each electricity consumption user value in a time threshold, constructing a set B of the average electricity consumption floating values, removing the largest subset and the smallest subset in the set B, acquiring the average value of the set B, and marking the average value as the average electricity consumption PX;
s13: obtaining a demand evaluation coefficient X according to a formula, and comparing the demand evaluation coefficient X with a preset demand evaluation coefficient threshold value recorded and stored in the demand evaluation coefficient X:
if the demand evaluation coefficient X is smaller than or equal to a preset demand evaluation coefficient threshold value, no signal is generated;
if the demand evaluation coefficient X is greater than the preset demand evaluation coefficient threshold, generating a distribution signal.
Preferably, the monitoring, evaluating and analyzing process of the distribution feedback unit is as follows:
the method comprises the steps of collecting a period of time after distribution of power distribution equipment, marking the period of time as distribution time, obtaining a power consumption user quantity of a power supply area and a power consumption value of a power consumption user in the distribution time, obtaining a user power consumption total value of the power supply area in the distribution time, obtaining a line reactive power loss value in the power supply area in the distribution time, marking the sum of the user power consumption total value and the line reactive power loss value as a distribution power consumption value, and comparing the distribution power consumption value with a preset distribution power consumption value area level recorded and stored in the distribution power consumption value and the distribution power consumption value:
if the allocation power consumption value is larger than the maximum value in the preset allocation power consumption value interval, generating an insufficient signal;
if the allocation power consumption value is within the preset allocation power consumption value interval, generating a proper value signal;
if the allocation power consumption value is smaller than the minimum value in the preset allocation power consumption value interval, generating an excessive signal.
Preferably, the fault risk assessment analysis process of the fault risk unit is as follows:
step one: acquiring the operation temperature of power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking the operation temperature as a Y axis on a time X axis, drawing an operation temperature curve in the rectangular coordinate system in a dot drawing mode, drawing an operation temperature threshold curve in the coordinate system, acquiring the number of points corresponding to the operation temperature curve positioned above the operation temperature threshold curve from the coordinate system, marking the number of points as an abnormal point value, acquiring the area surrounded by the abnormal point value and the operation temperature threshold curve, and marking the area as an over-temperature area GM;
step two: acquiring a line reactive power value of distribution equipment in each sub-time period, analyzing the line reactive power value and a preset line reactive power value threshold, marking the total number of sub-time periods corresponding to the line reactive power value larger than the preset line reactive power value threshold as an abnormal range value, marking the sum of parts of the line reactive power value larger than the preset line reactive power value threshold as a risk power sum, and marking the product of a normal range value and the risk power sum as a power risk coefficient GA;
step three: acquiring operation decibel values of power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking the time X axis and the operation temperature as the Y axis, drawing an operation decibel value bar chart in the rectangular coordinate system in a drawing mode, drawing a preset operation decibel value threshold curve in the coordinate system, acquiring a time length corresponding to the operation decibel value exceeding the preset operation decibel value threshold curve from the coordinate system, and marking the time length as abnormal sound time length YX;
step four: comparing and analyzing the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX with a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value which are recorded and stored in the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX:
if the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are all smaller than or equal to a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value correspondingly, no signal is generated;
and if at least one of the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX is correspondingly larger than a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value, generating a risk signal.
Preferably, the fault delay evaluation analysis process of the risk evaluation unit is as follows:
acquiring the time length from the moment when the distribution feedback unit receives the distribution signal to the moment when the distribution equipment completes electrical distribution, marking the time length as a reaction time length, comparing the reaction time length with a preset reaction time length threshold value, analyzing, and if the reaction time length is longer than the preset reaction time length threshold value, acquiring the part of the reaction time length exceeding the preset reaction time length threshold value, and marking the part as a delay time length YC;
and acquiring electromagnetic values of power distribution equipment in each sub-time period, so as to acquire a difference value between two connected electromagnetic values, marking the difference value as an electromagnetic floating value, further acquiring an electromagnetic fluctuation value in unit time, acquiring a maximum value and a minimum value of the electromagnetic fluctuation value in unit time, and marking an excess value between the maximum value and the minimum value of the electromagnetic fluctuation value in unit time as an electromagnetic span interference value DK.
Preferably, the formulation process of the risk assessment unit is compared with the analysis process as follows:
the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are called from the fault risk unit, and a fault evaluation risk coefficient G is obtained according to a formula;
according to the formulaObtaining a delay risk assessment coefficient, wherein alpha, beta and epsilon are respectively preset compensation factors of delay time length, electromagnetic span interference value and fault assessment risk coefficient, alpha, beta and epsilon are positive numbers larger than zero, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W is compared with a preset delay risk assessment coefficient interval recorded and stored in the delay risk assessment coefficient W:
if the delay risk assessment coefficient W is larger than the maximum value in the preset delay risk assessment coefficient interval, generating a first-stage delay signal; if the delay risk assessment coefficient W is located in a preset delay risk assessment coefficient interval, generating a secondary delay signal; and if the delay risk assessment coefficient W is smaller than the minimum value in the preset delay risk assessment coefficient interval, generating a three-level delay signal.
The beneficial effects of the invention are as follows:
(1) The invention collects the energy consumption data of the power distribution equipment and carries out monitoring, evaluation and analysis to judge whether the power distribution equipment needs to distribute power again, thereby being beneficial to timely early warning, analyzing the power consumption from the power supply area, the power consumption user value, the average user increase value and the average power demand angle of the power distribution equipment, being beneficial to improving the comprehensiveness of analysis data and expanding the analysis range, effectively guaranteeing the authenticity of the analysis result of the preset power consumption in the power supply area, improving the accuracy of subsequent power allocation, carrying out power distribution feedback evaluation and analysis on the user data from the two angles of the power consumption user value and the power consumption value to judge whether the power distribution of the power distribution equipment is normal, carrying out reasonable management and power distribution on the power distribution equipment according to the feedback information, and improving the working efficiency of the power distribution equipment so as to improve the management effect on the power distribution equipment;
(2) According to the invention, in the running process of the power distribution equipment and in the distribution process, the state data of the power distribution equipment is collected, the fault risk assessment analysis is carried out, and comprehensive analysis is carried out in a deep, formulated and feedback mode, so that the fault risk condition of the power distribution equipment is judged, early warning maintenance is carried out timely, the running safety and the working efficiency of the power distribution equipment are improved, the data support is improved in the distribution process of the power distribution equipment, the accuracy of an analysis result is improved, the assessment analysis is carried out on the distribution fault delay risk of the power distribution equipment in a progressive and data feedback mode, the running allocation delay grade of the power distribution equipment is judged, the maintenance is carried out timely, the delay risk of power distribution of the power distribution equipment is reduced, and the running safety of the power distribution equipment is improved.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a flow chart of the system of the present invention;
FIG. 2 is an analytical chart of example 2 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.
Example 1:
referring to fig. 1-2, the invention discloses an artificial intelligence based comprehensive power distribution management system, which comprises a management platform, a supervision and analysis unit, an allocation feedback unit, a risk assessment unit, a fault risk unit, an early warning unit and a safety management unit, wherein the management platform is in one-way communication connection with the supervision and analysis unit, the supervision and analysis unit is in two-way communication connection with the allocation feedback unit, the supervision and analysis unit is in one-way communication connection with the risk assessment unit, the fault risk unit and the early warning unit, the fault risk unit is in one-way communication connection with the risk assessment unit and the early warning unit, and the risk assessment unit is in one-way communication connection with the safety management unit;
when the management platform generates a management instruction, the management instruction is sent to the supervision and analysis unit, the supervision and analysis unit immediately collects energy consumption data of the power distribution equipment after receiving the management instruction, the energy consumption data comprise power supply areas, power consumption user values and power consumption of the power distribution equipment, the energy consumption data are monitored, evaluated and analyzed, whether the power distribution equipment needs to distribute power again or not is judged, early warning is facilitated, and the specific monitoring, evaluation and analysis process is as follows:
acquiring the duration from the starting time of the power distribution equipment to the current time, marking the duration as a time threshold, acquiring the power supply area of the power distribution equipment in the time threshold, simultaneously acquiring the total number of households and the number of non-entered households in the power supply area in the time threshold, marking the difference between the total number of households and the number of non-entered households as power utilization user values, dividing the time threshold into o sub-time periods, wherein o is a positive number greater than zero, acquiring the power utilization user values of the power supply area in each sub-time period, constructing a set A of the power utilization user values, acquiring the difference between two subsets connected in the set A, marking the difference as a user increment value, acquiring the average user increment value of the power supply area in the time threshold, marking the average user increment value as YZ, and indicating that the power supply amount required by the power distribution equipment in the power supply area is greater as the value of the average user increment value YZ is greater;
acquiring the electricity consumption of each electricity consumption user value in a power supply area in each sub-time period, acquiring the difference value between the electricity consumption of each electricity consumption user value in two connected sub-time periods, marking the difference value as an electricity consumption floating value, acquiring the average electricity consumption floating value of each electricity consumption user value in a time threshold, constructing a set B of the average electricity consumption floating value, removing the largest subset and the smallest subset in the set B, acquiring the average value of the set B, and marking the average value as an average required electricity quantity PX, wherein the average required electricity quantity PX is an influence parameter reflecting the power supply distribution of power distribution equipment in the power supply area, and the larger the value of the average required electricity quantity PX is, the larger the required power supply quantity of the power distribution equipment in the power supply area is;
according to the formulaObtaining a demand evaluation coefficient, wherein a1 and a2 are preset scale factor coefficients of an average increment value and an average electric quantity required by a user respectively, the scale factor coefficients are used for correcting deviation of various parameters in a formula calculation process, so that calculation is more accurate and parameter data, a3 is a preset correction coefficient, a1 and a2 are positive numbers larger than zero, X is a demand evaluation coefficient, and the demand evaluation coefficient X is compared with a preset demand evaluation coefficient threshold value recorded and stored in the demand evaluation coefficient X:
if the demand evaluation coefficient X is smaller than or equal to a preset demand evaluation coefficient threshold value, no signal is generated;
if the demand evaluation coefficient X is larger than a preset demand evaluation coefficient threshold value, generating an allocation signal, and sending the allocation signal to an allocation feedback unit, a risk evaluation unit and a fault risk unit;
the distribution feedback unit immediately collects user data of a power supply area after receiving a distribution signal, wherein the user data comprises a power consumption user quantity and a power consumption value, and performs distribution feedback evaluation analysis on the user data to judge whether the distribution of the power of the distribution equipment is normal or not so as to improve the management effect on the distribution equipment, and the specific distribution feedback evaluation analysis process is as follows:
the method comprises the steps of collecting a period of time after distribution of power distribution equipment, marking the period of time as distribution time, obtaining a power consumption user quantity of a power supply area and a power consumption value of a power consumption user in the distribution time, obtaining a user power consumption total value of the power supply area in the distribution time, obtaining a line reactive power loss value in the power supply area in the distribution time, marking the sum of the user power consumption total value and the line reactive power loss value as a distribution power consumption value, and comparing the distribution power consumption value with a preset distribution power consumption value area level recorded and stored in the distribution power consumption value and the distribution power consumption value:
if the allocation power consumption value is larger than the maximum value in the preset allocation power consumption value interval, the power distribution is abnormal, and an insufficient signal is generated;
if the allocation power consumption value is within the preset allocation power consumption value interval, generating a proper value signal;
if the power allocation value is smaller than the minimum value in the preset power allocation value interval, the power allocation is abnormal, an excessive signal is generated, the insufficient signal, the proper value signal and the excessive signal are sent to the early warning unit through the supervision and analysis unit, the early warning unit immediately makes preset early warning operation corresponding to the insufficient signal, the proper value signal and the excessive signal after receiving the insufficient signal, the proper value signal and the excessive signal, and further the power distribution equipment is managed and distributed reasonably according to the feedback information, so that the working efficiency of the power distribution equipment is improved.
Example 2:
the fault risk unit immediately collects state data of the power distribution equipment after receiving the distribution signal, wherein the state data comprises running temperature, line reactive power value and running decibel value of the power distribution equipment, and performs fault risk assessment analysis on the state data to judge fault risk conditions of the power distribution equipment so as to timely perform early warning maintenance, improve running safety and working efficiency of the power distribution equipment, and the specific fault risk assessment analysis process is as follows:
acquiring the operation temperature of the power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking the operation temperature as a Y axis and drawing an operation temperature curve in the rectangular coordinate system in a dot drawing mode, drawing an operation temperature threshold curve in the rectangular coordinate system, acquiring the number of points corresponding to the position of the operation temperature curve above the operation temperature threshold curve from the coordinate system, marking the number of points as abnormal point values, acquiring the area surrounded by the abnormal point values and the operation temperature threshold curve, and marking the area as an over-temperature area GM, wherein the larger the number of the over-temperature area GM is, the larger the fault risk of the power distribution equipment is;
acquiring line reactive power values of power distribution equipment in each sub-time period, analyzing the line reactive power values and a preset line reactive power value threshold, marking the total number of sub-time periods corresponding to the line reactive power values larger than the preset line reactive power value threshold as an abnormal range value, marking the sum of parts of the line reactive power values larger than the preset line reactive power value threshold as a risk power sum, and marking the product of a normal range value and the risk power sum as a power risk coefficient GA, wherein the larger the value of the power risk coefficient GA is, the smaller the working efficiency of the power distribution equipment is;
acquiring operation decibel values of power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking a time X axis and an operation temperature as a Y axis, drawing an operation decibel value bar chart in the rectangular coordinate system in a drawing mode, drawing a preset operation decibel value threshold curve in the coordinate system, acquiring a time length corresponding to the operation decibel value exceeding the preset operation decibel value threshold curve from the coordinate system, and marking the time length as abnormal sound time length YX, wherein the abnormal sound time length YX is an influence parameter reflecting the operation fault risk of the power distribution equipment;
and comparing and analyzing the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX with a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value which are recorded and stored in the battery:
if the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are all smaller than or equal to a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value correspondingly, no signal is generated;
if at least one of the excess temperature area GM, the power risk coefficient GA and the abnormal sound duration YX is correspondingly larger than a preset excess temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value, a risk signal is generated and sent to an early warning unit, and the early warning unit immediately controls an alarm lamp on the power distribution equipment to be red after receiving the risk signal, so that the running condition of the power distribution equipment is intuitively known, maintenance and overhaul treatment can be timely carried out, and the work efficiency of the power distribution equipment is improved;
the risk assessment unit immediately collects operation data of the power distribution equipment after receiving the distribution signal, wherein the operation data comprises reaction time length and electromagnetic values, and performs fault delay assessment analysis on the operation data to judge the operation allocation delay level of the power distribution equipment so as to timely maintain, improve the operation safety of the power distribution equipment, and the specific fault delay assessment analysis process is as follows:
acquiring the time length from the moment when the distribution feedback unit receives the distribution signal to the moment when the distribution equipment completes electrical distribution, marking the time length as a reaction time length, comparing the reaction time length with a preset reaction time length threshold value, and analyzing the reaction time length, if the reaction time length is larger than the preset reaction time length threshold value, acquiring the part of the reaction time length exceeding the preset reaction time length threshold value, marking the part of the reaction time length as a delay time length YC, wherein the larger the value of the delay time length YC is, the lower the working efficiency of the distribution equipment is, and the higher the fault risk is;
acquiring electromagnetic values of power distribution equipment in each sub-time period, acquiring a difference value between two connected electromagnetic values, marking the difference value as an electromagnetic floating value, further acquiring an electromagnetic fluctuation value in unit time, acquiring a maximum value and a minimum value of the electromagnetic fluctuation value in unit time, marking an excessive value between the maximum value and the minimum value of the electromagnetic fluctuation value in unit time as an electromagnetic span interference value, and marking as DK;
in addition, the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are called from the fault risk unit;
according to the formulaObtaining a fault evaluation risk coefficient, wherein b1, b2 and b3 are respectively preset weight coefficients of an over-temperature area, a power risk coefficient and abnormal sound duration, b4 is a preset influence factor, b1, b2, b3 and b4 are positive numbers larger than zero, G is the fault evaluation risk coefficient, the coefficient is a specific numerical value obtained by quantizing each parameter, the subsequent comparison is convenient, and the corresponding operation coefficient is preliminarily set according to the quantity of sample data and each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affectedCan be used;
according to the formulaObtaining a delay risk assessment coefficient, wherein alpha, beta and epsilon are respectively preset compensation factors of delay time length, electromagnetic span interference value and fault assessment risk coefficient, alpha, beta and epsilon are positive numbers larger than zero, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W is compared with a preset delay risk assessment coefficient interval recorded and stored in the delay risk assessment coefficient W:
if the delay risk assessment coefficient W is larger than the maximum value in the preset delay risk assessment coefficient interval, generating a first-stage delay signal;
if the delay risk assessment coefficient W is located in a preset delay risk assessment coefficient interval, generating a secondary delay signal;
if the delay risk assessment coefficient W is smaller than the minimum value in the preset delay risk assessment coefficient interval, generating a three-level delay signal, wherein delay risk degrees corresponding to the first-level delay signal, the second-level delay signal and the three-level delay signal are sequentially increased, the first-level delay signal, the second-level delay signal and the three-level delay signal are sent to a safety management unit, and the safety management unit immediately makes a preset management optimization scheme corresponding to the first-level delay signal, the second-level delay signal and the three-level delay signal after receiving the first-level delay signal, the second-level delay signal and the three-level delay signal so as to reduce delay risk of power distribution equipment and facilitate improving working efficiency of the power distribution equipment;
in summary, the invention collects the energy consumption data of the power distribution equipment and carries out monitoring, evaluation and analysis to judge whether the power distribution equipment needs to distribute power again, thereby being beneficial to timely early warning, analyzing the power consumption from the angles of the power supply area, the power consumption user value, the average user increment value and the average power demand of the power distribution equipment, being beneficial to improving the comprehensiveness of analysis data and expanding the analysis range, effectively guaranteeing the authenticity of the analysis result of the preset power consumption in the power supply area, improving the accuracy of subsequent power allocation, carrying out power distribution feedback evaluation analysis on the user data from the angles of the power consumption user value and the power consumption value so as to judge whether the power distribution of the power distribution equipment is normal, carrying out reasonable management and power distribution on the power distribution equipment according to the feedback information, and improving the working efficiency of the power distribution equipment so as to improve the management effect on the power distribution equipment;
in addition, in the running process of the power distribution equipment and in the distribution process, state data of the power distribution equipment are collected, fault risk assessment analysis is carried out, comprehensive analysis is carried out through deep, formula and feedback modes, so that fault risk conditions of the power distribution equipment are judged, early warning maintenance is carried out timely, running safety and working efficiency of the power distribution equipment are improved, data support is improved in the distribution process of the power distribution equipment, accuracy of analysis results is improved, assessment analysis is carried out on distribution fault delay risks of the power distribution equipment in a progressive mode and a data feedback mode, running allocation delay grades of the power distribution equipment are judged, maintenance is carried out timely, delay risks of power distribution of the power distribution equipment are reduced, and running safety of the power distribution equipment is improved.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected; the above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (6)
1. The comprehensive power distribution management system based on the artificial intelligence is characterized by comprising a management platform, a supervision and analysis unit, an allocation feedback unit, a risk assessment unit, a fault risk unit, an early warning unit and a safety management unit;
when the management platform generates a management instruction, the management instruction is sent to the supervision and analysis unit, the supervision and analysis unit immediately collects energy consumption data of the power distribution equipment after receiving the management instruction, the energy consumption data comprise power supply areas, power utilization user values and power consumption of the power distribution equipment, monitors, evaluates and analyzes the energy consumption data, and sends an obtained distribution signal to the distribution feedback unit, the risk evaluation unit and the fault risk unit;
the distribution feedback unit immediately collects user data of a power supply area after receiving a distribution signal, wherein the user data comprises a power consumption user quantity and a power consumption value, performs distribution feedback evaluation analysis on the user data, sends obtained insufficient signals, proper value signals and excessive signals to the early warning unit through the supervision analysis unit, and immediately makes preset early warning operation corresponding to the insufficient signals, the proper value signals and the excessive signals after receiving the insufficient signals, the proper value signals and the excessive signals;
the fault risk unit immediately collects state data of the power distribution equipment after receiving the distribution signal, wherein the state data comprises the running temperature, the reactive power value and the running decibel value of the power distribution equipment, performs fault risk assessment analysis on the state data, sends an obtained risk signal to the early warning unit, and immediately controls an alarm lamp on the power distribution equipment to be red after receiving the risk signal;
and the risk assessment unit immediately collects operation data of the power distribution equipment after receiving the distribution signal, wherein the operation data comprises reaction time length and electromagnetic value, performs fault delay assessment analysis and formulation processing comparison analysis on the operation data, and sends the obtained primary delay signal, secondary delay signal and tertiary delay signal to the safety management unit.
2. The artificial intelligence based integrated power distribution management system of claim 1, wherein the power distribution feedback evaluation analysis process of the supervision analysis unit is as follows:
s1: acquiring the duration from the starting time of the power distribution equipment to the current time, marking the duration as a time threshold, acquiring the power supply area of the power distribution equipment in the time threshold, simultaneously acquiring the total number of households and the number of non-entered households in the power supply area in the time threshold, marking the difference between the total number of households and the number of non-entered households as power utilization user values, dividing the time threshold into o sub-time periods, wherein o is a positive number greater than zero, acquiring the power utilization user values of the power supply area in each sub-time period, constructing a set A of the power utilization user values, acquiring the difference between two subsets connected in the set A, marking the difference as a user increment value, and acquiring the average user increment value YZ of the power supply area in the time threshold;
s12: acquiring the electricity consumption of each electricity consumption user value in the power supply area in each sub-time period, acquiring the difference value between the electricity consumption of each electricity consumption user value in two connected sub-time periods, marking the difference value as an electricity consumption floating value, acquiring the average electricity consumption floating value of each electricity consumption user value in a time threshold, constructing a set B of the average electricity consumption floating values, removing the largest subset and the smallest subset in the set B, acquiring the average value of the set B, and marking the average value as the average electricity consumption PX;
s13: obtaining a demand evaluation coefficient X according to a formula, and comparing the demand evaluation coefficient X with a preset demand evaluation coefficient threshold value recorded and stored in the demand evaluation coefficient X:
if the demand evaluation coefficient X is smaller than or equal to a preset demand evaluation coefficient threshold value, no signal is generated;
if the demand evaluation coefficient X is greater than the preset demand evaluation coefficient threshold, generating a distribution signal.
3. The artificial intelligence based integrated power distribution management system of claim 1, wherein the process of monitoring, evaluating and analyzing the distribution feedback unit is as follows:
the method comprises the steps of collecting a period of time after distribution of power distribution equipment, marking the period of time as distribution time, obtaining a power consumption user quantity of a power supply area and a power consumption value of a power consumption user in the distribution time, obtaining a user power consumption total value of the power supply area in the distribution time, obtaining a line reactive power loss value in the power supply area in the distribution time, marking the sum of the user power consumption total value and the line reactive power loss value as a distribution power consumption value, and comparing the distribution power consumption value with a preset distribution power consumption value area level recorded and stored in the distribution power consumption value and the distribution power consumption value:
if the allocation power consumption value is larger than the maximum value in the preset allocation power consumption value interval, generating an insufficient signal;
if the allocation power consumption value is within the preset allocation power consumption value interval, generating a proper value signal;
if the allocation power consumption value is smaller than the minimum value in the preset allocation power consumption value interval, generating an excessive signal.
4. The artificial intelligence based integrated power distribution management system of claim 1, wherein the fault risk assessment analysis process of the fault risk unit is as follows:
step one: acquiring the operation temperature of power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking the operation temperature as a Y axis on a time X axis, drawing an operation temperature curve in the rectangular coordinate system in a dot drawing mode, drawing an operation temperature threshold curve in the coordinate system, acquiring the number of points corresponding to the operation temperature curve positioned above the operation temperature threshold curve from the coordinate system, marking the number of points as an abnormal point value, acquiring the area surrounded by the abnormal point value and the operation temperature threshold curve, and marking the area as an over-temperature area GM;
step two: acquiring a line reactive power value of distribution equipment in each sub-time period, analyzing the line reactive power value and a preset line reactive power value threshold, marking the total number of sub-time periods corresponding to the line reactive power value larger than the preset line reactive power value threshold as an abnormal range value, marking the sum of parts of the line reactive power value larger than the preset line reactive power value threshold as a risk power sum, and marking the product of a normal range value and the risk power sum as a power risk coefficient GA;
step three: acquiring operation decibel values of power distribution equipment in each sub-time period, establishing a rectangular coordinate system by taking the time X axis and the operation temperature as the Y axis, drawing an operation decibel value bar chart in the rectangular coordinate system in a drawing mode, drawing a preset operation decibel value threshold curve in the coordinate system, acquiring a time length corresponding to the operation decibel value exceeding the preset operation decibel value threshold curve from the coordinate system, and marking the time length as abnormal sound time length YX;
step four: comparing and analyzing the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX with a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value which are recorded and stored in the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX:
if the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are all smaller than or equal to a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value correspondingly, no signal is generated;
and if at least one of the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX is correspondingly larger than a preset over-temperature area threshold value, a preset power risk coefficient threshold value and a preset abnormal sound duration threshold value, generating a risk signal.
5. The artificial intelligence based integrated power distribution management system of claim 1, wherein the risk assessment unit fault delay assessment analysis process is as follows:
acquiring the time length from the moment when the distribution feedback unit receives the distribution signal to the moment when the distribution equipment completes electrical distribution, marking the time length as a reaction time length, comparing the reaction time length with a preset reaction time length threshold value, analyzing, and if the reaction time length is longer than the preset reaction time length threshold value, acquiring the part of the reaction time length exceeding the preset reaction time length threshold value, and marking the part as a delay time length YC;
and acquiring electromagnetic values of power distribution equipment in each sub-time period, so as to acquire a difference value between two connected electromagnetic values, marking the difference value as an electromagnetic floating value, further acquiring an electromagnetic fluctuation value in unit time, acquiring a maximum value and a minimum value of the electromagnetic fluctuation value in unit time, and marking an excess value between the maximum value and the minimum value of the electromagnetic fluctuation value in unit time as an electromagnetic span interference value DK.
6. The artificial intelligence based integrated power distribution management system of claim 1, wherein the formulation process of the risk assessment unit compares the analysis process as follows:
the over-temperature area GM, the power risk coefficient GA and the abnormal sound duration YX are called from the fault risk unit, and a fault evaluation risk coefficient G is obtained according to a formula;
according to the formulaObtaining a delay risk assessment coefficient, wherein alpha, beta and epsilon are respectively preset compensation factors of delay time length, electromagnetic span interference value and fault assessment risk coefficient, alpha, beta and epsilon are positive numbers larger than zero, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W is compared with a preset delay risk assessment coefficient interval recorded and stored in the delay risk assessment coefficient W:
if the delay risk assessment coefficient W is larger than the maximum value in the preset delay risk assessment coefficient interval, generating a first-stage delay signal; if the delay risk assessment coefficient W is located in a preset delay risk assessment coefficient interval, generating a secondary delay signal; and if the delay risk assessment coefficient W is smaller than the minimum value in the preset delay risk assessment coefficient interval, generating a three-level delay signal.
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