CN114994441B - Intelligent electric power efficiency monitoring device - Google Patents
Intelligent electric power efficiency monitoring device Download PDFInfo
- Publication number
- CN114994441B CN114994441B CN202210627777.5A CN202210627777A CN114994441B CN 114994441 B CN114994441 B CN 114994441B CN 202210627777 A CN202210627777 A CN 202210627777A CN 114994441 B CN114994441 B CN 114994441B
- Authority
- CN
- China
- Prior art keywords
- equipment
- energy efficiency
- fault
- loss
- control cabinet
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012806 monitoring device Methods 0.000 title claims abstract description 16
- 238000004458 analytical method Methods 0.000 claims abstract description 67
- 238000013508 migration Methods 0.000 claims abstract description 44
- 230000005012 migration Effects 0.000 claims abstract description 44
- 230000002159 abnormal effect Effects 0.000 claims abstract description 35
- 238000012544 monitoring process Methods 0.000 claims abstract description 27
- 238000012423 maintenance Methods 0.000 claims abstract description 25
- 238000013024 troubleshooting Methods 0.000 claims abstract description 14
- 238000012795 verification Methods 0.000 claims description 23
- 230000003139 buffering effect Effects 0.000 claims description 12
- 230000001360 synchronised effect Effects 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000007781 pre-processing Methods 0.000 claims description 8
- 230000005856 abnormality Effects 0.000 claims description 4
- 238000012546 transfer Methods 0.000 claims description 4
- 230000001419 dependent effect Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 4
- 230000002265 prevention Effects 0.000 abstract description 4
- 238000011161 development Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000010891 electric arc Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000000034 method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R21/00—Arrangements for measuring electric power or power factor
- G01R21/06—Arrangements for measuring electric power or power factor by measuring current and voltage
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
- G01R22/06—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods
- G01R22/061—Details of electronic electricity meters
- G01R22/068—Arrangements for indicating or signaling faults
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Power Engineering (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Entrepreneurship & Innovation (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Testing Electric Properties And Detecting Electric Faults (AREA)
Abstract
The invention discloses an intelligent power efficiency monitoring device, which relates to the technical field of power monitoring and comprises an energy efficiency monitoring module, an overhaul analysis module and an overhaul linkage module; the energy efficiency monitoring module is used for analyzing energy efficiency loss according to the monitored energy efficiency data and judging whether the energy efficiency loss of the electrical control cabinet is abnormal or not according to the change trend of the energy efficiency migration value along with the real-time temperature, so that the quality of electric energy is improved, and the utilization rate of the electric energy is improved; when the electrical control cabinet has a loss abnormal event, the maintenance analysis module is used for analyzing maintenance coefficients of various electrical equipment in the power grid and sequentially troubleshooting the electrical equipment according to the size of the maintenance coefficients, so that the troubleshooting efficiency is improved; when the fault equipment is found, the maintenance linkage module is used for carrying out fault linkage analysis on the fault equipment to obtain corresponding fault linkage equipment; then troubleshooting is carried out on the fault linkage equipment, whether a fault occurs or not is judged, the active prevention effect is achieved, and the fault troubleshooting efficiency is further improved.
Description
Technical Field
The invention relates to the technical field of electric energy monitoring, in particular to an intelligent electric energy efficiency monitoring device.
Background
With the rapid development of global economy and science and technology, environmental and energy problems are paid more and more attention, and in order to prevent the environmental and energy problems from becoming a bottleneck restricting the progress of human society, active research is carried out in the fields of energy exploitation, transformation, consumption and the like in countries around the world. The industrial development must realize sustainability, and the important basis for realizing green industry in all countries is to improve industrial energy efficiency.
The power system has a large amount of nonlinear, impact and fluctuating loads, such as high-power frequency conversion equipment and dragging devices, electrified railways, rectifying equipment in the electrochemical industry, induction heating furnaces, electric arc furnaces and the like, and the loads cause waveform distortion (harmonic waves), voltage fluctuation, flicker, three-phase imbalance and asymmetry of a power grid, so that the power quality of the power grid is seriously reduced. The method comprises the following steps of firstly, accurately detecting and analyzing the power quality, measuring the power quality level of a power grid, analyzing and judging reasons causing various power quality problems, and providing a basis for improving the power quality; based on the defects, the invention provides an intelligent power efficiency monitoring device.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an intelligent power energy efficiency monitoring device.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides an intelligent power energy efficiency monitoring apparatus, which includes an energy efficiency monitoring module, an FPGA controller, an overhaul analysis module, an information sorting module, and an overhaul linkage module;
the energy efficiency monitoring module is used for monitoring energy efficiency data of the electrical control cabinet in real time, carrying out energy efficiency loss analysis according to the monitored energy efficiency data and calculating to obtain an energy efficiency migration value EQ;
then establishing a first analysis array according to the energy efficiency transfer value EQ and the real-time temperature DT1 of the electrical control cabinet acquired at the same time; judging whether the energy efficiency loss of the electrical control cabinet is abnormal or not according to the variation trend of the energy efficiency migration value EQ in the first analysis array along with the real-time temperature DT1;
when the electrical control cabinet has a loss abnormal event, the overhaul analysis module is used for carrying out overhaul coefficient JX analysis on various electrical equipment in the power grid and sequentially carrying out troubleshooting on the electrical equipment according to the JX size;
when the fault equipment is found, the maintenance linkage module is used for carrying out fault linkage analysis on the fault equipment and calculating to obtain a fault linkage value GL of the corresponding verification equipment; if GL is larger than the linkage threshold value, the corresponding verification equipment is marked as fault linkage equipment of the reference equipment; and then troubleshooting the fault linkage equipment and judging whether a fault problem occurs.
Further, the specific analysis steps of the energy efficiency monitoring module are as follows:
firstly, preprocessing monitored energy efficiency data, wherein the preprocessing is to remove obviously wrong or useless data; calculating the difference between the input power CWt and the output power JWt to obtain the loss power SHt; marking the real-time temperature of the electrical control cabinet as DT1;
the power losses at two different points in time are obtained and marked as first power loss WS1 and second power loss WSAnd (3) loss power WS2, calculating by using an energy efficiency migration calculation formula to obtain an energy efficiency migration value EQ, wherein the specific calculation formula is as follows:
wherein eta is a compensation factor, WS0 is represented as a preset energy efficiency migration threshold, and T0 is represented as a time difference of two different time points.
Further, the energy efficiency monitoring module further includes:
establishing an energy efficiency migration curve of the electrical control cabinet by taking the energy efficiency migration value EQ as an independent variable and taking the real-time temperature DT1 as a dependent variable; deriving an energy efficiency migration curve to obtain a migration derivative curve;
marking a point in the migration derivative curve where the derivative is 0 as a stagnation point; calculating the time difference of the acquisition moments of the energy efficiency migration values corresponding to the two adjacent stagnation points to obtain a migration duration ZT; if ZT is more than or equal to the time length threshold value, and the real-time temperature DT1 at the moment meets the condition that (RT-mu) is more than or equal to DT1 and less than or equal to (RT + mu), judging that the energy efficiency loss of the electrical control cabinet is normal at the moment; wherein RT is a temperature threshold corresponding to the electrical control cabinet; mu is a compensation factor;
otherwise, judging that the energy efficiency loss of the electrical control cabinet is abnormal, and generating a loss abnormal signal.
Furthermore, the energy efficiency monitoring module is used for transmitting the loss abnormal signal to the FPGA controller, and the FPGA controller drives the control alarm module to give an alarm after receiving the loss abnormal signal and controls the electrical control cabinet to enter a standby mode.
Furthermore, the information sorting module is used for recording loss abnormal events of the electrical control cabinet, analyzing the loss abnormal events from the loss abnormal time, duration, influence range and fault equipment in combination with the medium-voltage power grid topology to obtain a loss analysis result; time stamping the loss analysis result and storing the loss analysis result into a database; wherein there are multiple malfunctioning devices in one loss anomaly event; the influence range is expressed as an area of a power failure region caused by a loss abnormality.
Further, the specific analysis steps of the overhaul analysis module are as follows:
acquiring all loss analysis results of the electrical control cabinet within a preset time;
counting the failure frequency of a corresponding electrical device as C1 for a certain electrical device; marking the duration of each fault as CT1 and the influence range as CM1; calculating to obtain a fault influence value CG by using a formula CG = CT1 × a1+ CM1 × a2, wherein a1 and a2 are coefficient factors;
comparing the fault impact value CG with a fault threshold value; counting the number of times that the CG is larger than or equal to the fault threshold value to be C2, and when the CG is larger than or equal to the fault threshold value, obtaining the difference value between the CG and the fault threshold value and summing the difference value to obtain a total value PZ of the super influence; calculating a fault deviation value PW by using PW = C2 × a3+ PZ × a4, wherein a3 and a4 are coefficient factors;
using a formula
And calculating to obtain a maintenance coefficient JX of the corresponding electrical equipment, wherein g1 and g2 are coefficient factors.
Further, the concrete analysis steps of the maintenance linkage module are as follows:
calling a loss analysis result of the electrical control cabinet in ninety days before the current time of the system from the database;
counting the number of synchronous faults of the verification equipment and the reference equipment as synchronous fault frequency W1 aiming at the same verification equipment; intercepting a time period between adjacent synchronous faults as an equipment buffering time period, and setting the fault frequency of the reference equipment in each equipment buffering time period as an equipment buffering frequency Hi;
comparing the buffering frequency Hi of the equipment with a frequency threshold, and counting the frequency W2 of the frequency threshold which is less than or equal to Hi; when Hi is less than or equal to the frequency threshold, obtaining the difference between Hi and the frequency threshold, and summing to obtain a difference CH; calculating a difference coefficient CX by using a formula CX = W2 × g3+ CH × g4, wherein g3 and g4 are coefficient factors;
the fault linkage value GL of the corresponding verification device is calculated by using the formula GL = W1 × g5+ CX × g6, wherein g5 and g6 are coefficient factors.
Further, the maintenance linkage module further comprises: marking the currently found fault equipment as reference equipment; and collecting fault equipment in all loss analysis results, if a certain fault equipment and reference equipment appear in the same loss analysis result, considering that the fault equipment and the reference equipment synchronously fail, and marking the corresponding fault equipment as verification equipment.
Compared with the prior art, the invention has the beneficial effects that:
1. the energy efficiency monitoring module is used for monitoring energy efficiency data of the electrical control cabinet in real time, carrying out energy efficiency loss analysis according to the monitored energy efficiency data, preprocessing the monitored energy efficiency data, and calculating to obtain loss power SHt; acquiring loss powers WS1 and WS2 of two different time points, and calculating by using an energy efficiency migration calculation formula to obtain an energy efficiency migration value EQ; then establishing a first analysis array according to the energy efficiency transfer value EQ and the real-time temperature DT1 of the electrical control cabinet acquired at the same time; judging whether the energy efficiency loss of the electrical control cabinet is abnormal or not according to the variation trend of the energy efficiency migration value EQ in the first analysis array along with the real-time temperature DT1; the system can remind an administrator to overhaul and maintain various electrical equipment in the power grid, find out the cause of abnormal loss, further improve the quality of electric energy and improve the utilization rate of the electric energy;
2. when the electrical control cabinet has a loss abnormal event, the maintenance analysis module is used for analyzing maintenance coefficients of various electrical equipment in the power grid and acquiring all loss analysis results of the electrical control cabinet within preset time; counting the failure times of corresponding electrical equipment aiming at certain electrical equipment, and calculating to obtain a failure influence value CG when the electrical equipment fails each time; comparing the fault influence value CG with a fault threshold value, and calculating to obtain a fault deviation value PW; using a formula
Calculating to obtain a maintenance coefficient JX of the corresponding electrical equipment; then, the electrical equipment is sequentially checked according to the magnitude of the overhaul coefficient JX so as to find out the fault equipment as soon as possible and improve the overhaul efficiency;
3. the maintenance linkage module is used for carrying out fault linkage analysis on fault equipment; marking the fault equipment found currently as reference equipment, and marking the fault equipment which is in the same loss analysis result with the reference equipment as verification equipment; calculating to obtain a fault linkage value GL of corresponding verification equipment; if GL is larger than the linkage threshold value, the corresponding verification equipment is marked as fault linkage equipment of the reference equipment; then troubleshooting is carried out on the fault linkage equipment, whether a fault problem occurs or not is judged, the active prevention effect is achieved, and the fault troubleshooting efficiency is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a system block diagram of an intelligent power efficiency monitoring device according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an intelligent power energy efficiency monitoring device comprises an energy efficiency monitoring module, an FPGA controller, an alarm module, a maintenance analysis module, an information arrangement module, a database and a maintenance linkage module;
in the embodiment, the energy efficiency monitoring module is suitable for energy efficiency monitoring in an embedded installation environment of a power grid power station, and the power quality can be monitored online only by arranging a mounting hole at a corresponding position of an electrical control cabinet for fixing and then connecting the mounting hole;
the energy efficiency monitoring module is used for monitoring the energy efficiency data of the electrical control cabinet in real time and analyzing energy efficiency loss according to the monitored energy efficiency data, and the specific analysis steps are as follows:
firstly, preprocessing monitored energy efficiency data, wherein the preprocessing shows that obvious errors or useless data are removed; the energy efficiency data comprises input current, input voltage, output current, output voltage and real-time temperature of the electrical control cabinet;
calculating the product of the input current and the input voltage to obtain the input power CWt of the electric control cabinet; calculating the product of the output current and the output voltage to obtain the output power JWt of the electric control cabinet;
calculating the difference between the input power CWt and the output power JWt to obtain the loss power SHt; marking the real-time temperature of the electrical control cabinet as DT1;
acquiring loss powers of two different time points (namely adjacent moments), marking the loss powers as a first loss power WS1 and a second loss power WS2, and calculating by using an energy efficiency migration calculation formula to obtain an energy efficiency migration value EQ, wherein the specific calculation formula is as follows:
wherein eta is a compensation factor, WS0 is represented as a preset energy efficiency migration threshold, and T0 is represented as a time difference of two different time points;
establishing a first analysis array, wherein the first analysis array comprises an energy efficiency transfer value EQ and a real-time temperature DT1 of the electrical control cabinet acquired at the same time; the energy efficiency migration value EQ corresponds to the real-time temperature DT1 one by one;
establishing an energy efficiency migration curve of the electrical control cabinet by taking the energy efficiency migration value EQ as an independent variable and taking the real-time temperature DT1 as a dependent variable; deriving an energy efficiency migration curve to obtain a migration derivative curve;
marking a point in the migration derivative curve where the derivative is 0 as a stagnation point; calculating the time difference of the acquisition time of the energy efficiency migration values corresponding to two adjacent stagnation points to obtain a migration and stagnation duration ZT;
comparing the migration duration ZT with a duration threshold; if ZT is more than or equal to the time length threshold value, and the real-time temperature DT1 at the moment meets the condition that (RT-mu) is more than or equal to DT1 and less than or equal to (RT + mu), judging that the energy efficiency loss of the electrical control cabinet is normal at the moment; wherein RT is a temperature threshold corresponding to the electric control cabinet; mu is a compensation factor;
otherwise, judging that the energy efficiency loss of the electrical control cabinet is abnormal, and generating a loss abnormal signal;
the energy efficiency monitoring module is used for transmitting the loss abnormal signal to the FPGA controller, the FPGA controller drives the control alarm module to give an alarm after receiving the loss abnormal signal, and controls the electrical control cabinet to enter a standby mode, so that a manager can overhaul and maintain various electrical equipment in the power grid, find out the cause of loss abnormality, further improve the power quality and improve the power utilization rate;
the information sorting module is used for recording loss abnormal events of the electrical control cabinet, analyzing the loss abnormal events from the loss abnormal time, duration, influence range, fault equipment and other dimensions by combining medium-voltage power grid topology to obtain loss analysis results, and stamping the loss analysis results to store the loss analysis results into a database; there may be multiple faulty devices in one of the loss anomaly events; the influence range is expressed as the area of a power failure region caused by loss abnormality;
when the electrical control cabinet has a loss abnormal event, the maintenance analysis module is used for analyzing maintenance coefficients of various electrical equipment in the power grid, and the electrical equipment is sequentially checked according to the size of the maintenance coefficient JX to find out faulty equipment, so that the maintenance efficiency is improved; the specific analysis steps are as follows:
acquiring all loss analysis results of the electrical control cabinet within a preset time;
counting the failure times of corresponding electrical equipment as C1 aiming at certain electrical equipment; marking the duration of each fault as CT1 and the influence range as CM1; calculating to obtain a fault influence value CG by using a formula CG = CT1 × a1+ CM1 × a2, wherein a1 and a2 are coefficient factors;
comparing the fault impact value CG with a fault threshold value; counting the number of times that the CG is larger than or equal to the fault threshold value to be C2, and when the CG is larger than or equal to the fault threshold value, obtaining the difference value between the CG and the fault threshold value and summing the difference value to obtain a total value PZ of the super influence; calculating a fault deviation value PW by using PW = C2 × a3+ PZ × a4, wherein a3 and a4 are coefficient factors;
normalizing the failure times and the failure deviation value, taking the numerical value, and utilizing a formula
Calculating to obtain a maintenance coefficient JX of the corresponding electrical equipment, wherein g1 and g2 are coefficient factors;
the electrical equipment is sequentially checked according to the magnitude of the overhaul coefficient JX so as to find out the fault equipment as soon as possible, and the checking efficiency is improved;
in this embodiment, after the faulty equipment is found, the overhaul linkage module is used for performing fault linkage analysis on the faulty equipment to obtain corresponding faulty linkage equipment, and then troubleshooting is performed on the faulty linkage equipment to judge whether a fault problem occurs, so that an active prevention effect is achieved, and the fault troubleshooting efficiency is further improved; the specific analysis steps are as follows:
calling a loss analysis result of the electrical control cabinet in ninety days before the current time of the system from the database;
marking the currently found fault equipment as reference equipment; acquiring fault equipment in all loss analysis results, and if certain fault equipment and reference equipment appear in the same loss analysis result, considering that the fault equipment and the reference equipment synchronously fail; marking the corresponding fault equipment as verification equipment;
counting the number of synchronous faults of the verification equipment and the reference equipment as synchronous fault frequency W1 aiming at the same verification equipment; intercepting a time period between adjacent synchronous faults as an equipment buffering time period, and setting the fault frequency of the reference equipment in each equipment buffering time period as an equipment buffering frequency Hi;
comparing the buffering frequency Hi of the equipment with a frequency threshold, and counting the frequency W2 of the frequency threshold which is less than or equal to Hi; when Hi is less than or equal to the frequency threshold, obtaining the difference value between Hi and the frequency threshold, and summing to obtain a difference value CH; calculating to obtain a difference coefficient CX by using a formula CX = W2 Xg 3+ CH Xg 4, wherein g3 and g4 are coefficient factors;
calculating a fault linkage value GL of the corresponding verification device by using a formula GL = W1 × g5+ CX × g6, wherein g5 and g6 are coefficient factors;
comparing the fault linkage value GL with a linkage threshold value; and if the GL is larger than the linkage threshold value, marking the corresponding verification equipment as the fault linkage equipment of the reference equipment.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
when the intelligent power energy efficiency monitoring device works, an energy efficiency monitoring module is used for monitoring energy efficiency data of an electrical control cabinet in real time, carrying out energy efficiency loss analysis according to the monitored energy efficiency data, preprocessing the monitored energy efficiency data, and calculating to obtain loss power SHt; acquiring loss powers WS1 and WS2 of two different time points, and calculating by using an energy efficiency migration calculation formula to obtain an energy efficiency migration value EQ; establishing a first analysis array, wherein the first analysis array comprises an energy efficiency migration value EQ and a real-time temperature DT1 of the electric control cabinet, which are acquired at the same time, and analyzing to obtain a migration and stagnation time length ZT; if ZT is not less than the time length threshold value, and the real-time temperature DT1 at the moment meets the condition that (RT-mu) is not less than DT1 and not more than (RT + mu), judging that the energy efficiency loss of the electrical control cabinet at the moment is normal; otherwise, judging that the energy efficiency loss of the electrical control cabinet is abnormal, and generating a loss abnormal signal; the system can remind an administrator to overhaul and maintain various electrical equipment in the power grid, find out the cause of abnormal loss, further improve the quality of electric energy and improve the utilization rate of the electric energy;
when the electrical control cabinet has a loss abnormal event, the maintenance analysis module is used for analyzing maintenance coefficients of various electrical equipment in the power grid and acquiring all loss analysis results of the electrical control cabinet within a preset time; counting the failure times of corresponding electrical equipment aiming at certain electrical equipment, and calculating to obtain a failure influence value CG when the electrical equipment fails each time; comparing the fault influence value CG with a fault threshold value, and calculating to obtain a fault deviation value PW; using formulas
ComputingObtaining a maintenance coefficient JX of the corresponding electrical equipment; then, electrical equipment is checked in sequence according to the size of the overhaul coefficient JX, so that faulty equipment can be found as soon as possible, and the overhaul efficiency is improved;
when the fault equipment is found, the maintenance linkage module is used for carrying out fault linkage analysis on the fault equipment; marking the currently found fault equipment as reference equipment; collecting fault equipment in all loss analysis results, and if a certain fault equipment and a reference equipment appear in the same loss analysis result, considering that the fault equipment and the reference equipment synchronously fail; calculating to obtain a fault linkage value GL of the corresponding verification equipment, and if the GL is greater than a linkage threshold value, marking the corresponding verification equipment as fault linkage equipment of the reference equipment; then troubleshooting is carried out on the fault linkage equipment, whether a fault problem occurs or not is judged, the active prevention effect is achieved, and the fault troubleshooting efficiency is further improved.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (7)
1. An intelligent power energy efficiency monitoring device is characterized by comprising an energy efficiency monitoring module, an FPGA controller, an overhaul analysis module, an information arrangement module and an overhaul linkage module;
the energy efficiency monitoring module is used for monitoring energy efficiency data of the electrical control cabinet in real time, analyzing energy efficiency loss according to the monitored energy efficiency data and calculating to obtain an energy efficiency migration value EQ;
then establishing a first analysis array according to the energy efficiency transfer value EQ and the real-time temperature DT1 of the electrical control cabinet acquired at the same time; judging whether the energy efficiency loss of the electrical control cabinet is abnormal or not according to the variation trend of the energy efficiency migration value EQ in the first analysis array along with the real-time temperature DT1;
when the electrical control cabinet has a loss abnormal event, the overhaul analysis module is used for carrying out overhaul coefficient JX analysis on various electrical equipment in the power grid and sequentially carrying out troubleshooting on the electrical equipment according to the JX size;
when the fault equipment is found, the maintenance linkage module is used for carrying out fault linkage analysis on the fault equipment and calculating to obtain a fault linkage value GL of the corresponding verification equipment; if GL is larger than the linkage threshold value, the corresponding verification equipment is marked as fault linkage equipment of the reference equipment; then, troubleshooting is carried out on the fault linkage equipment, and whether a fault problem occurs is judged;
the specific judgment steps corresponding to the verification equipment are as follows:
marking the currently found fault equipment as reference equipment;
and collecting fault equipment in all loss analysis results, if a certain fault equipment and reference equipment appear in the same loss analysis result, considering that the fault equipment and the reference equipment synchronously fail, and marking the corresponding fault equipment as verification equipment.
2. The intelligent power energy efficiency monitoring device according to claim 1, wherein the energy efficiency monitoring module specifically analyzes the following steps:
firstly, preprocessing monitored energy efficiency data, wherein the preprocessing is to remove obviously wrong or useless data; calculating the difference between the input power CWt and the output power JWt to obtain the loss power SHt; marking the real-time temperature of the electrical control cabinet as DT1;
acquiring loss powers of two different time points, marking the loss powers as a first loss power WS1 and a second loss power WS2, and calculating by using an energy efficiency migration calculation formula to obtain an energy efficiency migration value EQ, wherein the specific calculation formula is as follows:
where η is a compensation factor, WS0 is represented as a preset energy efficiency migration threshold, and T0 is represented as a time difference between two different time points.
3. The intelligent power energy efficiency monitoring device according to claim 2, wherein the energy efficiency monitoring module further comprises:
establishing an energy efficiency migration curve of the electrical control cabinet by taking the energy efficiency migration value EQ as an independent variable and taking the real-time temperature DT1 as a dependent variable; deriving an energy efficiency migration curve to obtain a migration derivative curve;
marking a point in the migration derivative curve where the derivative is 0 as a stagnation point; calculating the time difference of the acquisition time of the energy efficiency migration values corresponding to two adjacent stagnation points to obtain a migration and stagnation duration ZT; if ZT is not less than the time length threshold value, and the real-time temperature DT1 at the moment meets the condition that (RT-mu) is not less than DT1 and not more than (RT + mu), judging that the energy efficiency loss of the electrical control cabinet at the moment is normal; wherein RT is a temperature threshold corresponding to the electrical control cabinet; mu is a compensation factor;
otherwise, judging that the energy efficiency loss of the electrical control cabinet is abnormal, and generating a loss abnormal signal.
4. The intelligent power energy efficiency monitoring device according to claim 3, wherein the energy efficiency monitoring module is configured to transmit an abnormal loss signal to the FPGA controller, and the FPGA controller drives the control alarm module to give an alarm after receiving the abnormal loss signal and controls the electrical control cabinet to enter a standby mode.
5. The intelligent power energy efficiency monitoring device according to claim 1, wherein the information arrangement module is used for recording loss abnormal events of the electrical control cabinet, and analyzing the loss abnormal events from dimensions of loss abnormal time, duration, influence range and fault equipment by combining with a medium-voltage power grid topology to obtain a loss analysis result; time stamping the loss analysis result and storing the loss analysis result into a database; wherein there are multiple faulty devices in one loss anomaly event; the influence range is expressed as an area of a power failure region caused by a loss abnormality.
6. The intelligent power energy efficiency monitoring device according to claim 5, wherein the specific analysis steps of the overhaul analysis module are as follows:
acquiring all loss analysis results of the electrical control cabinet within a preset time;
counting the failure frequency of a corresponding electrical device as C1 for a certain electrical device; marking the duration of each fault as CT1 and the influence range as CM1; calculating to obtain a fault influence value CG by using a formula CG = CT1 × a1+ CM1 × a2, wherein a1 and a2 are coefficient factors;
comparing the fault impact value CG with a fault threshold value; counting the number of times that the CG is larger than or equal to the fault threshold value to be C2, and when the CG is larger than or equal to the fault threshold value, obtaining the difference value between the CG and the fault threshold value and summing the difference value to obtain a total value PZ of the super influence; calculating a fault deviation value PW by using PW = C2 × a3+ PZ × a4, wherein a3 and a4 are coefficient factors;
using formulas
And calculating to obtain a maintenance coefficient JX of the corresponding electrical equipment, wherein g1 and g2 are coefficient factors.
7. The intelligent power energy efficiency monitoring device according to claim 5, wherein the concrete analysis steps of the overhaul linkage module are as follows:
calling a loss analysis result of the electrical control cabinet in ninety days before the current time of the system from the database;
counting the number of synchronous faults of the verification equipment and the reference equipment as synchronous fault frequency W1 aiming at the same verification equipment; intercepting a time period between adjacent synchronous faults as an equipment buffering time period, and setting the fault frequency of the reference equipment in each equipment buffering time period as an equipment buffering frequency Hi;
comparing the buffering frequency Hi of the equipment with a frequency threshold, and counting the frequency W2 of the frequency threshold which is less than or equal to Hi; when Hi is less than or equal to the frequency threshold, obtaining the difference value between Hi and the frequency threshold, and summing to obtain a difference value CH; calculating a difference coefficient CX by using a formula CX = W2 × g3+ CH × g4, wherein g3 and g4 are coefficient factors;
the fault linkage value GL of the corresponding verification device is calculated by using the formula GL = W1 × g5+ CX × g6, wherein g5 and g6 are coefficient factors.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210627777.5A CN114994441B (en) | 2022-06-06 | 2022-06-06 | Intelligent electric power efficiency monitoring device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210627777.5A CN114994441B (en) | 2022-06-06 | 2022-06-06 | Intelligent electric power efficiency monitoring device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114994441A CN114994441A (en) | 2022-09-02 |
| CN114994441B true CN114994441B (en) | 2023-04-07 |
Family
ID=83030876
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210627777.5A Active CN114994441B (en) | 2022-06-06 | 2022-06-06 | Intelligent electric power efficiency monitoring device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114994441B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116307875B (en) * | 2023-03-08 | 2023-08-15 | 重庆伏特猫科技有限公司 | Big data-based power order management system |
| CN116381302B (en) * | 2023-04-14 | 2023-11-07 | 杭州中凯通信设备有限公司 | Embedded waterproof electric energy metering box |
| CN116523509B (en) * | 2023-07-04 | 2023-09-19 | 中能聚创(杭州)能源科技有限公司 | Power monitoring analysis method and monitoring analysis system |
| CN116823226A (en) * | 2023-07-06 | 2023-09-29 | 湖南鑫能实业有限公司 | Electric power district fault monitoring system based on big data |
| CN117131110B (en) * | 2023-10-27 | 2024-01-23 | 南京中鑫智电科技有限公司 | Method and system for monitoring dielectric loss of capacitive equipment based on correlation analysis |
| CN117556222B (en) * | 2024-01-10 | 2024-07-16 | 吉林省东启铭网络科技有限公司 | Big data-based power station equipment real-time state evaluation and fault early warning method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6731627B1 (en) * | 1998-11-17 | 2004-05-04 | Cisco Technology, Inc. | Virtual loop carrier system |
| EP2863526A1 (en) * | 2013-10-21 | 2015-04-22 | ST-Ericsson SA | Switched mode power supply peak-efficiency detection |
| CN107885655A (en) * | 2017-08-10 | 2018-04-06 | 清远博云软件有限公司 | A kind of running software effectiveness synthesis analyzing detecting method |
| CN114297908A (en) * | 2021-11-19 | 2022-04-08 | 中国华能集团清洁能源技术研究院有限公司 | Wind turbine generator set energy efficiency state abnormity detection method and system |
-
2022
- 2022-06-06 CN CN202210627777.5A patent/CN114994441B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN114994441A (en) | 2022-09-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114994441B (en) | Intelligent electric power efficiency monitoring device | |
| CN106655159B (en) | New energy power station primary frequency modulation capability test system and test method thereof | |
| AU2020103179A4 (en) | A Fault Locating Method of Power Grid Based on Network Theory | |
| CN103293415B (en) | Mini-inverter fault detecting method based on neural network expert system | |
| CN106100579B (en) | A kind of photovoltaic plant method for diagnosing faults based on data analysis | |
| CN104796082A (en) | System and method for diagnosing faults of photovoltaic power generation systems in online manner | |
| CN102289731A (en) | Method for maintaining state of power transmission equipment based on system risk | |
| CN115037054A (en) | Commutation switch intelligent terminal based on three-phase self-balancing and low-voltage fault location isolation | |
| CN111007419A (en) | Transformer substation direct current system running state on-line monitoring system | |
| CN108459269A (en) | A kind of 10kV pvs (pole-mounted vacuum switch)s state on-line evaluation method and apparatus | |
| CN103310389B (en) | Overhead transmission line fault maintenance method based on fault mode and fault tree establishment | |
| CN111257820A (en) | Three-phase intelligent electric meter wiring remote detection method | |
| CN113708500A (en) | Low-voltage electricity utilization abnormity monitoring system and method | |
| CN106443253A (en) | Power transmission line parameter identification method based on PMU (phasor measurement unit) data | |
| CN118071327B (en) | Intelligent electric operation and maintenance system for photovoltaic power station confluence monitoring | |
| CN114814402A (en) | Abnormal electricity utilization analysis method based on integrated electricity quantity and line loss system big data | |
| CN105515531B (en) | A kind of photovoltaic module decay abnormality diagnostic method based on monitoring system | |
| CN114675212B (en) | Method for studying and judging abnormal connection of neutral point of distribution transformer | |
| CN110635767A (en) | Photovoltaic system and method for inhibiting potential attenuation and monitoring insulation | |
| CN114156865B (en) | Low-voltage distribution network topology generation and fault prediction method considering state perception | |
| CN103487702B (en) | Small-power movable micro-grid connection detecting system | |
| Liu et al. | A resilience enhancement scheme of cyber-physical power system for extreme natural disasters | |
| CN115047371A (en) | Partial discharge-free variable frequency power supply operation detection system based on transformer detection | |
| CN114462692A (en) | Power grid old and old equipment technical improvement strategy optimization and adjustment method | |
| CN113902219A (en) | Analysis method of main transformer load influence factor analysis model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |