CN119602494B - A method, device, equipment and storage medium for automatic control of high voltage circuit breaker - Google Patents
A method, device, equipment and storage medium for automatic control of high voltage circuit breaker Download PDFInfo
- Publication number
- CN119602494B CN119602494B CN202510145512.5A CN202510145512A CN119602494B CN 119602494 B CN119602494 B CN 119602494B CN 202510145512 A CN202510145512 A CN 202510145512A CN 119602494 B CN119602494 B CN 119602494B
- Authority
- CN
- China
- Prior art keywords
- brightness
- circuit breaker
- voltage circuit
- image
- closing
- 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
Classifications
-
- 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
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01H—ELECTRIC SWITCHES; RELAYS; SELECTORS; EMERGENCY PROTECTIVE DEVICES
- H01H33/00—High-tension or heavy-current switches with arc-extinguishing or arc-preventing means
- H01H33/02—Details
- H01H33/59—Circuit arrangements not adapted to a particular application of the switch and not otherwise provided for, e.g. for ensuring operation of the switch at a predetermined point in the AC cycle
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Power Engineering (AREA)
- Computing Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
- Driving Mechanisms And Operating Circuits Of Arc-Extinguishing High-Tension Switches (AREA)
Abstract
本申请公开了一种高压断路器的自动控制方法、装置、设备及存储介质，涉及控制或调节系统技术领域，方法通过图像亮度直观反映当地的日照强度，并将电网以及高压断路器所在环境的亮度进行区间划分以及分类，通过定义权重值的大小以反映光照强度的强弱，并根据任意日照强度下的权重值来控制触头的接入数量，保证了光伏发电的稳定性同时，避免了人工或者装置对高压断路器的冗余控制或欠缺控制对电网带来的波动或者非必要损耗，最后通过pid算法精确控制触头的开合闸，进一步防止触头控制不到位。
The present application discloses an automatic control method, device, equipment and storage medium for a high-voltage circuit breaker, and relates to the technical field of control or regulation systems. The method intuitively reflects the local sunlight intensity through image brightness, and divides and classifies the brightness of the power grid and the environment where the high-voltage circuit breaker is located into intervals, and defines the size of the weight value to reflect the intensity of the light, and controls the number of contacts connected according to the weight value under any sunlight intensity, thereby ensuring the stability of photovoltaic power generation and avoiding the fluctuation or unnecessary loss of the power grid caused by redundant control or lack of control of the high-voltage circuit breaker by manual or device, and finally accurately controls the opening and closing of the contacts through the PID algorithm to further prevent the contacts from being controlled inadequately.
Description
Technical Field
The present application relates to the field of control or regulation systems, and in particular, to an automatic control method, apparatus, device, and storage medium for a high voltage circuit breaker.
Background
With the increasing safety requirements on electricity consumption in aspects of domestic electricity consumption, industrial electricity consumption, agricultural electricity consumption and the like, the urban and regional overhead power supply network and the remote high-voltage transmission line are required to be comprehensively developed, and higher requirements are put forward on power allocation of the power system line, operation stability of the high-voltage switch, high-efficiency utilization of resources such as safety of a control system, electric energy and communication and deep development of intelligent power grid technology, so that the intelligent level of high-voltage electrical equipment is increasingly focused.
The high-voltage circuit breaker needs to improve stability and operation intelligence level of a high-voltage switch of a power station, and is used as important equipment in a power system of the power station, the high-voltage circuit breaker has an opening and closing function, wherein the control function means that the high-voltage switch of the power station can switch partial load through opening and closing operation, the protection function is used for reducing the influence range of power grid fluctuation, power failure faults and the like of the power station, and the failed part is led to exit the power grid through opening and closing.
The high-voltage circuit breaker of the power station not only can switch on and off load current under the normal working condition of the power station, but also can timely cut off fault lines under the condition that the power system of the power station has faults such as overvoltage, overcurrent and the like, thereby achieving the protection effect on the power system and electrical equipment. The switching-on and switching-off operation of the high-voltage switch is completed by different types of operating mechanisms such as electromagnetism, hydraulic pressure, springs, motors and the like, and the response capability and the control performance of the operating mechanisms influence the switching-on and switching-off capability of the high-voltage switch.
At present, switching on and off of a high-voltage circuit breaker of a power station is mainly manually controlled to be switched on and off at a terminal monitoring base station or is performed through a safety device or a safety system, after the sudden events such as power grid fluctuation, power failure and the like occur, the switching on and off is performed through the safety device or the safety system, the switching on and off is performed after the sudden events are eliminated, no definite switching on and off operation exists for daily operation, the power grid and the high-voltage circuit breaker are always in a continuous working state in daily operation, the continuous working state is obviously redundant for photovoltaic power generation with random power generation characteristics, and not only fatigue and faults are generated on all relevant components in continuous working, but also the service lives of all relevant components are shortened or are directly damaged.
Disclosure of Invention
The application mainly aims to provide an automatic control method, device, equipment and storage medium for a high-voltage circuit breaker, which are used for solving the problems that in the prior art, redundant control of the high-voltage circuit breaker easily causes fatigue and faults of all relevant components which work continuously, and the service lives of all the relevant components are shortened or the relevant components are directly damaged.
In order to achieve the above object, the present application provides the following technical solutions:
An automatic control method of a high-voltage circuit breaker, the high-voltage circuit breaker is used for controlling opening and closing of a plurality of power grid lines, the automatic control method comprises:
step S1, acquiring a plurality of image data of an outdoor environment where the high-voltage circuit breaker is located based on a natural time period;
step S2, respectively obtaining an image brightness average value of each image data through a visual algorithm;
Step S3, defining at least two continuous brightness intervals in sequence from low to high according to the value of the visible light brightness;
Step S4, defining a weight coefficient based on each brightness interval, wherein the size of all weight coefficients is from low to high along with the values of all visible light brightness, and all weight coefficients are positioned in intervals [0,1 ];
step S5, respectively classifying the brightness average values of all the images into all brightness intervals through a classification algorithm, and obtaining a weight coefficient based on each brightness average value of the images;
Step S6, defining the weight coefficient as a closing proportion, and acquiring the number of contacts of the high-voltage circuit breaker;
Step S7, obtaining the product of the closing proportion and the contact quantity, and defining the product as the actual closing quantity;
Step S8, the actual closing quantity is sent to the high-voltage circuit breaker;
And S9, controlling the contact switching-on corresponding to the actual switching-on number through a self-adaptive control algorithm.
As a further improvement of the present application, step S2 of obtaining an image brightness average value of each image data by a visual algorithm, respectively, includes:
step S21, importing a cv2 software package through an import statement of python;
step S22, each image data is respectively read through a cv2.Imread function of the cv2 software package and stored in an img variable;
Step S23, converting all image data in the img variable into gray images through a cv2.cvtColor function of the cv2 software package and storing the gray images into a gray variable;
Step S24, respectively obtaining the average brightness of each gray image in the gray variable through a cv2.Mean function of the cv2 software package, and storing the average brightness into an average_brightness variable;
Step S25, defining all average brightness in the average_brightness variable as an average value of all image brightness.
As a further improvement of the present application, step S5, classifying, by a classification algorithm, all the image luminance averages into all the luminance intervals, respectively, and obtaining a weight coefficient based on each image luminance average, includes:
step S51, defining a data set to be classified according to the average value of all the image brightness , wherein,For the set of data to be classified,For the first of the data sets to be classifiedThe average value of the brightness of the individual images,The number of the brightness averages of all the images;
step S52, defining a category set according to the number of all brightness intervals , wherein,For the set of categoriesThe first of (3)The number of brightness intervals is one,The number of all brightness intervals;
Step S53, calculating the conditional probability of each image brightness average value in the data set to be classified in each brightness interval according to the formula (1):
(1);
Wherein, Is the firstConditional probability of the data set to be classified within a luminance interval,Is the firstThe edge probabilities of the individual luminance intervals,To at the firstUnder the brightness intervalConditional probability of average of individual image brightness;
step S54, respectively classifying the brightness average value of each image into the brightness interval with the highest conditional probability;
Step S55, the weight coefficient of the current brightness interval is defined as the weight coefficient of the average value of all the image brightness in the current brightness interval.
As a further improvement of the present application, step S9, controlling, by an adaptive control algorithm, contact closing corresponding to the actual closing number, includes:
step S91, obtaining a motion characteristic vector of a contact of the high-voltage circuit breaker;
step S92, constructing a contact motion self-adaptive tracking control model based on a PID algorithm;
step S93, calculating control signals of the contacts corresponding to the actual closing quantity based on the contact motion self-adaptive tracking control model;
And step S94, outputting the control signal to the contacts corresponding to the actual closing quantity so as to perform closing.
As a further improvement of the present application, step S91, obtaining a motion feature vector of a contact of a high voltage circuit breaker, includes:
Step S911, the motion signals of the current contact are segmented, and the energy entropy of all the motion signals of the current contact is calculated according to the formula (2):
(2);
Wherein, The energy entropy of all motion signals for the current contact,Is the first contact of the current contactThe segment motion signal is used to determine the motion of the segment,For the total number of segments of the motion signal of the current contact,Characterizing the motion signal of the current contact;
Step S912, calculating a feature vector of the motion signal of the current contact based on equation (3) according to the energy entropy of the current contact:
(3);
Wherein, As the feature vector of the current contact,Motion time based parameters for current contactIs characterized by a movement path.
As a further improvement of the present application, the contact motion adaptive tracking control model is characterized by the formula (4):
(4);
Wherein, In order to provide for the control signal to be provided,As the difference between the current contact position and the desired closing position,Proportional gain for the adaptive tracking control model for contact motion,For the integration time constant of the contact motion adaptive tracking control model,A differential time constant for the adaptive tracking control model of contact movement,Is the motion time parameter.
In order to achieve the above purpose, the present application further provides the following technical solutions:
An automatic control device of a high voltage circuit breaker, the automatic control device being applied to the automatic control method of a high voltage circuit breaker as described above, the automatic control device comprising:
The image data acquisition module is used for acquiring a plurality of image data of the outdoor environment where the high-voltage circuit breaker is located based on a natural time period;
the image brightness average value acquisition module is used for respectively acquiring the image brightness average value of each image data through a visual algorithm;
the brightness interval definition module is used for sequentially defining at least two continuous brightness intervals according to the value of the visible brightness from low to high;
The weight coefficient definition module is used for defining a weight coefficient based on each brightness interval, the size of all the weight coefficients is from low to high along with the value of all the visible light brightness, and all the weight coefficients are positioned in intervals [0,1 ];
The image brightness average value classification module is used for classifying all the image brightness average values to all brightness intervals through a classification algorithm respectively, and obtaining a weight coefficient based on each image brightness average value;
the contact closing proportion definition module is used for defining the weight coefficient as a closing proportion and acquiring the number of contacts of the high-voltage circuit breaker;
The actual closing quantity definition module is used for obtaining the product of the closing proportion and the contact quantity and defining the product as the actual closing quantity;
The actual closing quantity sending module is used for sending the actual closing quantity to the high-voltage circuit breaker;
and the high-voltage circuit breaker control module is used for controlling the contact switching-on corresponding to the actual switching-on number through a self-adaptive control algorithm.
In order to achieve the above purpose, the present application further provides the following technical solutions:
an electronic device comprises a processor and a memory coupled with the processor, wherein the memory stores program instructions executable by the processor, and the automatic control method of the high-voltage circuit breaker is realized when the processor executes the program instructions stored by the memory.
In order to achieve the above purpose, the present application further provides the following technical solutions:
A storage medium having stored therein program instructions which, when executed by a processor, enable the automatic control method of a high voltage circuit breaker as described above.
The method comprises the steps of obtaining a plurality of image data of an outdoor environment where a high-voltage circuit breaker is located based on a natural time period, respectively obtaining an image brightness average value of each image data through a visual algorithm, sequentially defining at least two continuous brightness intervals according to the value of visible brightness from low to high, defining a weight coefficient based on each brightness interval, enabling the value of all the weight coefficients to be small to large along with the value of all the visible brightness from low to high, enabling all the weight coefficients to be located in intervals [0,1], respectively classifying all the image brightness average values to all the brightness intervals through a classification algorithm, obtaining a weight coefficient based on each image brightness average value, defining the weight coefficient as a closing proportion, obtaining the number of contacts of the high-voltage circuit breaker, obtaining the product of the closing proportion and the number of the contacts, defining the product as the actual closing number, sending the actual closing number to the high-voltage circuit breaker, and controlling the closing of the contacts corresponding to the actual closing number through a self-adaptive control algorithm. According to the application, the local sunlight intensity is visually reflected through the image brightness, the brightness of the environment where the power grid and the high-voltage circuit breaker are located is divided and classified, the intensity of the illumination intensity is reflected by defining the weight value, the access quantity of the contacts is controlled according to the weight value under any sunlight intensity, the stability of photovoltaic power generation is ensured, meanwhile, the fluctuation or unnecessary loss of the power grid caused by the redundant control or the lack control of the high-voltage circuit breaker by manpower or the device is avoided, and finally, the opening and closing of the contacts are accurately controlled through a pid algorithm, so that the contact control is further prevented from being in place.
Drawings
Fig. 1 is a schematic flow chart of steps of an embodiment of an automatic control method of a high voltage circuit breaker according to the present application;
Fig. 2 is a schematic diagram of functional modules of an embodiment of an automatic control device of a high voltage circuit breaker according to the present application;
FIG. 3 is a schematic diagram of an embodiment of an electronic device of the present application;
FIG. 4 is a schematic diagram illustrating the structure of an embodiment of a storage medium according to the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terms "first," "second," "third," and the like in this disclosure are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "first," "second," and "third" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise. All directional indications (such as up, down, left, right, front, rear) in embodiments of the present application are merely used to explain the relative positional relationship, movement, etc. between the components in a particular pose (as shown in the drawings), and if the particular pose changes, the directional indication changes accordingly. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
As shown in fig. 1, the present embodiment provides an embodiment of an automatic control method of a high-voltage circuit breaker, where the high-voltage circuit breaker is used to control opening and closing of a plurality of power grid lines.
In particular, the high voltage circuit breaker of the present embodiment may be provided as an Integrated Gate Commutated Thyristor (IGCT), INTEGRATED GATE-Commutated Thyristor), or as GCT (Gate-Commutated Thyristor), i.e. a Gate commutated thyristor. IGCTs combine the characteristics of GTO (gate turn-off) thyristors and MOSFETs (metal oxide semiconductor field effect transistors). Is a novel power electronic device which appears in the later 90 s of the 20 th century. IGCT functions like a turn-off thyristor (GTO) as a fully controllable power switch, with both on and off being controlled by a control signal (gate). Due to the combination of MOSFET characteristics, its performance is much superior compared to conventional GTOs. The capacity is equivalent to that of the GTO, but the switching speed is 10 times faster than that of the GTO, and a buffer circuit which is large and complex in the application of the GTO can be omitted.
Specifically, IGCT has the following characteristics:
① The switching loss is low, and the switching frequency can be arbitrarily selected to meet the requirement of the final application. The power equipment can only work within 250Hz under rated current, and the working frequency of IGCT can reach 4 times of the speed. For example, in a motor drive system, if a faster switching speed is chosen, the efficiency of the system will be improved. On the other hand, if a lower switching speed is chosen for the IGCT, the efficiency of the inverter system will be improved with lower losses.
② The ancillary circuits are simplified-the IGCT is unique in that it can operate without a snubber circuit, which is very advantageous for design. The inverter without the buffer circuit has low loss, compact structure, fewer used elements and better reliability. The integration of the freewheeling diode in the IGCT structure allows for a simplification of IGCT-based equipment.
③ The gate drive power is low, the GTO adopts a traditional anode short circuit structure to realize on-state voltage drop and low turn-off loss, and the gate trigger current is increased. The transparent anode emission technology adopted by the IGCT leads the trigger current and the trailing edge current to be very small, the total on-state gate current is only 1/10 of GTO, and the gate trigger probability is reduced.
④ The integrated of the high-reliability IGCT device and the large-scale anti-parallel diode can reduce the storage time, greatly reduce the absolute value and the discreteness of the turn-off time and ensure that the IGCT can be safely applied to medium-high voltage series connection. If overcurrent failure occurs, the device burns out to turn off the device, and the risk to adjacent elements is avoided like an IGBT, so that the safety of the whole circuit is enhanced.
Specifically, the automatic control method comprises the following steps:
step S1, acquiring a plurality of image data of an outdoor environment where the high-voltage circuit breaker is located based on a natural time period.
Preferably, the image data of the outdoor environment where the high-voltage circuit breaker is located can be directly shot and obtained through an external camera end, the acquisition difficulty is avoided, and the same shooting angle is adopted as much as possible so as to ensure the accuracy of subsequent brightness detection.
And S2, respectively acquiring an image brightness average value of each image data through a visual algorithm.
Step S3, defining at least two continuous brightness intervals in sequence according to the magnitude of the visible light brightness from low to high.
For example, six brightness intervals can be defined sequentially, specifically、、、、、The critical value of each section can be adjusted according to actual needs.
Step S4, defining a weight coefficient based on each brightness interval, wherein the size of all weight coefficients is from low to high along with the value of all visible light brightness, and all weight coefficients are positioned in the interval [0,1 ].
Preferably, the weight coefficients are 0, 0.2, 0.4, 0.6, 0.8, 1.0 in order according to the above six luminance interval definitions.
And S5, respectively classifying the brightness average values of all the images into all brightness intervals by a classification algorithm, and obtaining a weight coefficient based on each brightness average value of the images.
And S6, defining a weight coefficient as a closing proportion, and acquiring the number of contacts of the high-voltage circuit breaker.
And S7, obtaining the product of the closing proportion and the number of contacts, and defining the product as the actual closing number.
And S8, transmitting the actual closing quantity to the high-voltage circuit breaker.
And S9, controlling the contact switching-on of the corresponding actual switching-on quantity through a self-adaptive control algorithm.
Further, step S2, respectively obtaining an average value of the image brightness of each image data through a visual algorithm, includes:
Step S21, importing the cv2 software package through the import statement of python.
In step S22, each image data is read by the cv2.Imread function of the cv2 software package and stored in the img variable.
In step S23, all image data in the img variable is converted into a grayscale image by the cv2.cvttcolor function of the cv2 software package and stored in the gray variable.
And step S24, respectively obtaining the average brightness of each gray image in the gray variable through a cv2.Mean function of the cv2 software package, and storing the average brightness in the average_brightness variable.
In step S25, all average luminance in the average_brightness variable is defined as all image luminance average.
Preferably, the main implementation codes of steps S21 to S26 are as follows:
import cv2
import matplotlib.pyplot as plt
def is_dark(image_path, threshold=100):
img = cv2.imread(image_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
average_brightness = cv2.mean(gray)[0]
if average_brightness<threshold:
return True
else:
return False
Further, step S5, classifying, by a classification algorithm, the luminance average values of all the images into all the luminance intervals, and obtaining a weight coefficient based on each luminance average value of the images, includes:
step S51, defining a data set to be classified according to the average value of all the image brightness , wherein,For a data set to be classified,To the first of the data sets to be classifiedThe average value of the brightness of the individual images,The number of brightness averages of all images.
Step S52, defining a category set according to the number of all brightness intervals, wherein,For a collection of categoriesThe first of (3)The number of brightness intervals is one,The number of all brightness intervals.
Step S53, calculating the conditional probability of each image brightness average value in the data set to be classified in each brightness interval according to the formula (1):
(1)。
Wherein, Is the firstConditional probability of the data set to be classified in each luminance interval,Is the firstThe edge probabilities of the individual luminance intervals,To at the firstUnder the brightness intervalConditional probability of average luminance of individual images.
Step S54, each image brightness average value is classified into the brightness section with the highest conditional probability.
Step S55, the weight coefficient of the current brightness interval is defined as the weight coefficient of the average value of all the image brightness in the current brightness interval.
Preferably, the classification algorithm of the present embodiment prefers a naive bayes classification, which assumes that the presence of a particular feature in a class is independent of the presence of any other feature, i.e. each feature is independent of the others. Therefore, the actual situation is constrained, if the attributes are associated, the classification accuracy is reduced, but the classification effect of naive Bayes is more accurate in the actual application process. Naive bayes recognize which category the term to be classified belongs to by solving, for a given term to be classified, which is the largest of the probabilities of the occurrence of the respective categories under the condition that the term occurs.
Specifically, naive bayes are defined as follows:
① Let x= { a1, a2, a 3., a, an is an item to be classified and, and each a is a feature of x.
② There is a category set c= { y1, y2, y3, &...
③ Calculate P (y1|x), P (y2|x), and..the term P (ym|x).
④ If P (yk|x) =max { P (y1|x), P (y2|x),. The.i., P (ym|x) }, then x e yk.
And then calculating each conditional probability in the ③ th step through the following steps:
a set of items to be classified of known classification is found, this set being called a training sample set.
And (5) counting to obtain the conditional probability estimation of each characteristic attribute under each category. Namely:
P(a1|y1),P(a2|y1),......,P(an|y1)。
P(a1|y2),P(a2|y2),......,P(an|y2)。
......
P(a1|ym),P(a2|ym),......,P(an|ym)。
Assuming that the various feature attributes are conditional independent, there are, according to the bayesian principle:
P(yi|x)=P(x|yi)P(yi)/P(x)。
Since the denominator is constant for all categories, it is only necessary to maximize the numerator. And because each characteristic attribute is independent of the condition, then:
P(x|yi)P(yi)=P(a1|yi)P(a2|yi)......P(an|yi)P(yi)。
The above preferred matters are also schematic illustrations, and the symbol meanings of the preferred matters are not mutually identical with those of other formulas in the embodiment.
Further, step S9, controlling, by an adaptive control algorithm, contact switching on corresponding to the actual switching on number, includes:
And S91, acquiring a motion characteristic vector of the contact of the high-voltage circuit breaker.
And step S92, constructing a contact motion self-adaptive tracking control model based on a PID algorithm.
And step S93, calculating control signals of the contacts corresponding to the actual closing quantity based on the contact motion self-adaptive tracking control model.
And step S94, outputting a control signal to the contacts corresponding to the actual closing quantity to perform closing.
Preferably, prior to extracting the motion feature vector of the current stylus, analysis of the PID tracking control architecture of the stylus motion is required.
This example illustrates the test performed on a ZN63 high voltage circuit breaker. In the testing process, a striking auxiliary marker is stuck to the contact position of the high-voltage circuit breaker, ink points on the marker are used as contact movement markers, and the influence of the similar markers on the control accuracy is reduced. In the embodiment, the movement condition of the contact is analyzed under the switching-on and switching-off states of the circuit breaker.
The initial coordinates of the contact dot mark are defined as (0, 0), and after the contact movement, the coordinates of the dot mark become (25.71, -8.13), and the coordinates of the last contact movement are (5.73, -11.13). And in the movement process of the contact, a PID controller is adopted for tracking control.
In the high-voltage circuit breaker obtained by the method, after the tracking time reaches 22ms in a closing state, the contact movement speed starts to drop, and before 22ms, the contact movement speed is in a continuously increased state. In the process, 22ms is an adaptive node for tracking control, and 0-22 ms is a PID adaptive process. In the open state, the contact movement speed starts to decrease after the tracking time reaches 15ms, and the contact movement speed is in a continuously increasing state before 15 ms. In the process, 15ms is an adaptive node of tracking control, and 0-15 ms is a PID adaptive process.
Further, step S91, obtaining a motion feature vector of the high voltage circuit breaker contact, includes:
Step S911, the motion signals of the current contact are segmented, and the energy entropy of all the motion signals of the current contact is calculated according to the formula (2):
(2)。
Wherein, The energy entropy of all motion signals for the current contact,Is the first contact of the current contactThe segment motion signal is used to determine the motion of the segment,For the total number of segments of the motion signal of the current contact,Characterizing the motion signal of the current contact.
Step S912, calculating a feature vector of the motion signal of the current contact based on equation (3) according to the energy entropy of the current contact:
(3)。
Wherein, As the feature vector of the current contact,Motion time based parameters for current contactIs characterized by a movement path.
Further, the stylus motion adaptive tracking control model is characterized by equation (4):
(4)。
Wherein, In order to control the signal of the power supply,As the difference between the current contact position and the desired closing position,Proportional gain for the adaptive tracking control model for contact motion,For the integration time constant of the contact motion adaptive tracking control model,A differential time constant for the adaptive tracking control model of contact motion,Is a motion time parameter.
The embodiment is based on a natural time period, a plurality of image data of an outdoor environment where a high-voltage circuit breaker is located are obtained, an image brightness average value of each image data is obtained through a visual algorithm, at least two continuous brightness intervals are defined in sequence according to the value of visible brightness from low to high, a weight coefficient is defined based on each brightness interval, the value of all the weight coefficients is small to large along with the value of all the visible brightness from low to high, all the weight coefficients are located in intervals [0,1], all the image brightness average values are respectively classified into all the brightness intervals through a classification algorithm, a weight coefficient is obtained based on each image brightness average value, the weight coefficient is defined as a closing proportion, the contact number of the high-voltage circuit breaker is obtained, the product of the closing proportion and the contact number is obtained, the product is defined as an actual closing number, the actual closing number is sent to the high-voltage circuit breaker, and the contact closing corresponding to the actual closing number is controlled through an adaptive control algorithm. According to the embodiment, the local sunlight intensity is visually reflected through the image brightness, the brightness of the environment where the power grid and the high-voltage circuit breaker are located is divided and classified, the intensity of the illumination intensity is reflected through the definition of the weight value, the access quantity of the contacts is controlled according to the weight value under any sunlight intensity, the stability of photovoltaic power generation is ensured, meanwhile, fluctuation or unnecessary loss of the power grid caused by redundant control or lack control of the high-voltage circuit breaker by manpower or devices is avoided, and finally the contacts are accurately controlled to be opened or closed through a pid algorithm, so that the contact control is further prevented from being in place.
As shown in fig. 2, this embodiment provides an embodiment of an automatic control device for a high-voltage circuit breaker, in this embodiment, the automatic control device is applied to the automatic control method in the above embodiment, and the automatic control device includes an image data acquisition module 1, an image brightness average value acquisition module 2, a brightness interval definition module 3, a weight coefficient definition module 4, an image brightness average value classification module 5, a contact closing proportion definition module 6, an actual closing number definition module 7, an actual closing number transmission module 8, and a high-voltage circuit breaker control module 9 that are electrically connected in sequence.
The system comprises an image data acquisition module 1, an image brightness average value acquisition module 2, a contact closing proportion definition module 6, an actual closing quantity definition module 7, a closing quantity transmission module 8 and a self-adaptive control closing quantity control module, wherein the image data acquisition module 1 is used for acquiring a plurality of image data of an outdoor environment where a high-voltage circuit breaker is located based on a natural time period, the image brightness average value acquisition module 2 is used for respectively acquiring an image brightness average value of each image data through a visual algorithm, the brightness interval definition module 3 is used for sequentially defining at least two continuous brightness intervals from low to high according to the value of the visible brightness, the weight coefficient definition module 4 is used for defining a weight coefficient based on each brightness interval, the value of all weight coefficients is from low to high, the weight coefficient is from small to large according to the value of all the visible brightness, the weight coefficient is located in an interval [0,1], the image brightness average value classification module 5 is used for respectively classifying all image brightness average values into all brightness intervals through a classification algorithm, the weight coefficient is obtained based on each image brightness average value, the contact closing proportion definition module 6 is used for defining the weight coefficient as a closing proportion, the contact quantity of the high-voltage circuit breaker is obtained, the product of the actual closing quantity definition module 7 is used for obtaining the product of the closing proportion and is used for the actual closing quantity, and is defined as the actual closing quantity, and the actual closing quantity is used for controlling the closing quantity through the self-adaptive control closing quantity control of the high-voltage circuit breaker through the high-voltage circuit breaker.
Further, the image brightness average value obtaining module 2 specifically includes a first image brightness average value obtaining sub-module, a second image brightness average value obtaining sub-module, a third image brightness average value obtaining sub-module, a fourth image brightness average value obtaining sub-module, and a fifth image brightness average value obtaining sub-module which are electrically connected in sequence, where the first image brightness average value obtaining sub-module is electrically connected with the image data obtaining module, and the fifth image brightness average value obtaining sub-module is electrically connected with the brightness interval defining module.
The image brightness average value obtaining system comprises a first image brightness average value obtaining sub-module, a second image brightness average value obtaining sub-module, a third image brightness average value obtaining sub-module and a fourth image brightness average value obtaining sub-module, wherein the first image brightness average value obtaining sub-module is used for importing a cv2 software package through an import statement of python, the second image brightness average value obtaining sub-module is used for respectively reading each image data through a cv2.Imread function of the cv2 software package and storing the image data into an img variable, the third image brightness average value obtaining sub-module is used for converting all image data in the img variable into gray images through a cv2. Cvcolor function of the cv2 software package and storing the gray images into a gray variable, the fourth image brightness average value obtaining sub-module is used for respectively obtaining average brightness of each gray image in the gray variable through a cv2.Mean function of the cv2 software package and storing the average brightness of each gray image into an average value of the average brightness of the images, and the fifth image brightness average value obtaining sub-module is used for defining all average brightness of the average brightness of all the images in the brightness.
Further, the image brightness average value classification module 5 specifically includes a first image brightness average value classification sub-module, a second image brightness average value classification sub-module, a third image brightness average value classification sub-module, a fourth image brightness average value classification sub-module, and a fifth image brightness average value classification sub-module which are electrically connected in sequence, where the first image brightness average value classification sub-module is electrically connected with the weight coefficient definition module, and the fifth image brightness average value classification sub-module is electrically connected with the contact closing proportion definition module.
The first image brightness average value classification sub-module is used for defining a data set to be classified according to the average value of all the image brightness, wherein,For a data set to be classified,To the first of the data sets to be classifiedThe average value of the brightness of the individual images,The number of brightness averages of all images.
The second image brightness average value classification submodule is used for defining a class set according to the number of all brightness intervals, wherein,For a collection of categoriesThe first of (3)The number of brightness intervals is one,The number of all brightness intervals.
The third image brightness average value classification submodule is used for calculating the conditional probability of each image brightness average value in the data set to be classified in each brightness interval according to the formula (1):
(1)。
Wherein, Is the firstConditional probability of the data set to be classified in each luminance interval,Is the firstThe edge probabilities of the individual luminance intervals,To at the firstUnder the brightness intervalConditional probability of average luminance of individual images.
The fourth image brightness average value classifying sub-module is used for respectively classifying each image brightness average value into a brightness interval with the highest conditional probability.
The fifth image brightness average value classification sub-module is used for defining the weight coefficient of the current brightness interval as the weight coefficient of the brightness average value of all the images in the current brightness interval.
Further, the high-voltage circuit breaker control module 9 specifically includes a first high-voltage circuit breaker control sub-module, a second high-voltage circuit breaker control sub-module, a third high-voltage circuit breaker control sub-module and a fourth high-voltage circuit breaker control sub-module which are electrically connected in sequence, wherein the first high-voltage circuit breaker control sub-module is electrically connected with the actual closing quantity sending module, and the fourth high-voltage circuit breaker control sub-module is electrically connected with the sunrise and sunset time acquisition module.
The high-voltage circuit breaker control system comprises a first high-voltage circuit breaker control submodule, a second high-voltage circuit breaker control submodule, a third high-voltage circuit breaker control submodule and a fourth high-voltage circuit breaker control submodule, wherein the first high-voltage circuit breaker control submodule is used for acquiring a contact movement characteristic vector of a high-voltage circuit breaker, the second high-voltage circuit breaker control submodule is used for constructing a contact movement self-adaptive tracking control model based on a PID algorithm, the third high-voltage circuit breaker control submodule is used for respectively calculating control signals of contacts corresponding to the actual closing quantity based on the contact movement self-adaptive tracking control model, and the fourth high-voltage circuit breaker control submodule is used for outputting the control signals to the contacts corresponding to the actual closing quantity to conduct closing.
The first high-voltage circuit breaker control submodule specifically comprises a first high-voltage circuit breaker control unit and a second high-voltage circuit breaker control unit which are electrically connected in sequence, wherein the first high-voltage circuit breaker control unit is electrically connected with the actual closing quantity sending module, and the second high-voltage circuit breaker control unit is electrically connected with the second high-voltage circuit breaker control submodule.
The first high-voltage circuit breaker control unit is used for carrying out segmentation processing on the motion signals of the current contact, and calculating the energy entropy of all the motion signals of the current contact according to the formula (2):
(2)。
Wherein, The energy entropy of all motion signals for the current contact,Is the first contact of the current contactThe segment motion signal is used to determine the motion of the segment,For the total number of segments of the motion signal of the current contact,Characterizing the motion signal of the current contact.
The second high-voltage circuit breaker control unit is used for calculating the eigenvector of the motion signal of the current contact based on the formula (3) according to the energy entropy of the current contact:
(3)。
Wherein, As the feature vector of the current contact,Motion time based parameters for current contactIs characterized by a movement path.
Further, the second high voltage circuit breaker control submodule is equipped with a contact motion adaptive tracking control model characterized by the formula (4):
(4)。
Wherein, In order to control the signal of the power supply,As the difference between the current contact position and the desired closing position,Proportional gain for the adaptive tracking control model for contact motion,For the integration time constant of the contact motion adaptive tracking control model,A differential time constant for the adaptive tracking control model of contact motion,Is a motion time parameter.
It should be noted that, the present embodiment is a functional module embodiment based on the foregoing method embodiment, and the preferred, expanded, limited, and exemplified portions of the present embodiment may be referred to the foregoing embodiments, which is not repeated herein.
The embodiment is based on a natural time period, a plurality of image data of an outdoor environment where a high-voltage circuit breaker is located are obtained, an image brightness average value of each image data is obtained through a visual algorithm, at least two continuous brightness intervals are defined in sequence according to the value of visible brightness from low to high, a weight coefficient is defined based on each brightness interval, the value of all the weight coefficients is small to large along with the value of all the visible brightness from low to high, all the weight coefficients are located in intervals [0,1], all the image brightness average values are respectively classified into all the brightness intervals through a classification algorithm, a weight coefficient is obtained based on each image brightness average value, the weight coefficient is defined as a closing proportion, the contact number of the high-voltage circuit breaker is obtained, the product of the closing proportion and the contact number is obtained, the product is defined as an actual closing number, the actual closing number is sent to the high-voltage circuit breaker, and the contact closing corresponding to the actual closing number is controlled through an adaptive control algorithm. According to the embodiment, the local sunlight intensity is visually reflected through the image brightness, the brightness of the environment where the power grid and the high-voltage circuit breaker are located is divided and classified, the intensity of the illumination intensity is reflected through the definition of the weight value, the access quantity of the contacts is controlled according to the weight value under any sunlight intensity, the stability of photovoltaic power generation is ensured, meanwhile, fluctuation or unnecessary loss of the power grid caused by redundant control or lack control of the high-voltage circuit breaker by manpower or devices is avoided, and finally the contacts are accurately controlled to be opened or closed through a pid algorithm, so that the contact control is further prevented from being in place.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 3, the electronic device 10 includes a processor 101 and a memory 102 coupled to the processor 101.
The memory 102 stores program instructions for implementing the automatic control method of the high voltage circuit breaker of any of the embodiments described above.
The processor 101 is configured to execute program instructions stored in the memory 102 for automatic control of the high voltage circuit breaker.
The processor 101 may also be referred to as a CPU (Central Processing Unit ). The processor 101 may be an integrated circuit chip with signal processing capabilities. Processor 101 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Further, fig. 4 is a schematic structural diagram of a storage medium according to an embodiment of the present application, referring to fig. 4, where the storage medium 11 according to an embodiment of the present application stores a program instruction 111 capable of implementing all the methods described above, where the program instruction 111 may be stored in the storage medium in the form of a software product, and includes several instructions for making a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) execute all or part of the steps of the methods described in the embodiments of the present application. The storage medium includes a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random-access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes, or a terminal device such as a computer, a server, a mobile phone, a tablet, etc.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other forms.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units. The foregoing is only the embodiments of the present application, and the patent scope of the application is not limited thereto, but is also covered by the patent protection scope of the application, as long as the equivalent structure or equivalent flow changes made by the description and the drawings of the application or the direct or indirect application in other related technical fields are adopted.
Claims (7)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510145512.5A CN119602494B (en) | 2025-02-10 | 2025-02-10 | A method, device, equipment and storage medium for automatic control of high voltage circuit breaker |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202510145512.5A CN119602494B (en) | 2025-02-10 | 2025-02-10 | A method, device, equipment and storage medium for automatic control of high voltage circuit breaker |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119602494A CN119602494A (en) | 2025-03-11 |
| CN119602494B true CN119602494B (en) | 2025-06-03 |
Family
ID=94841226
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202510145512.5A Active CN119602494B (en) | 2025-02-10 | 2025-02-10 | A method, device, equipment and storage medium for automatic control of high voltage circuit breaker |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119602494B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115809407A (en) * | 2022-11-14 | 2023-03-17 | 广西电网有限责任公司电力科学研究院 | A circuit breaker fault diagnosis method and system based on vibration characteristic analysis |
| CN118131029A (en) * | 2023-12-29 | 2024-06-04 | 广东电网有限责任公司江门供电局 | High-voltage circuit breaker fault diagnosis system |
| CN119255442A (en) * | 2024-07-30 | 2025-01-03 | 云南华尔贝光电技术有限公司 | A method, device, equipment and storage medium for automatic control of lighting fixtures |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9860965B2 (en) * | 2006-03-28 | 2018-01-02 | Wireless Environment, Llc | Cloud connected lighting system |
| CN106526467B (en) * | 2016-10-14 | 2019-07-19 | 西安交通大学 | A method for measuring the opening and closing speed characteristics of high-voltage circuit breakers based on machine vision |
| CN110752669A (en) * | 2019-10-29 | 2020-02-04 | 国网湖南省电力有限公司 | A system for evaluating the abnormal state of the energy storage spring of a circuit breaker |
| CN110889383A (en) * | 2019-11-29 | 2020-03-17 | 南京航硕电气有限公司 | On-line monitoring system for state of isolating switch based on AI technology |
| CN114696718B (en) * | 2022-03-03 | 2024-09-13 | 平顶山学院 | Direct motor driving device and method for high-voltage circuit breaker and state sensing system |
-
2025
- 2025-02-10 CN CN202510145512.5A patent/CN119602494B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115809407A (en) * | 2022-11-14 | 2023-03-17 | 广西电网有限责任公司电力科学研究院 | A circuit breaker fault diagnosis method and system based on vibration characteristic analysis |
| CN118131029A (en) * | 2023-12-29 | 2024-06-04 | 广东电网有限责任公司江门供电局 | High-voltage circuit breaker fault diagnosis system |
| CN119255442A (en) * | 2024-07-30 | 2025-01-03 | 云南华尔贝光电技术有限公司 | A method, device, equipment and storage medium for automatic control of lighting fixtures |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119602494A (en) | 2025-03-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20240088785A1 (en) | Resonant switched capacitor converter and control method thereof | |
| US20220263321A1 (en) | Photovoltaic control apparatus and method, and system | |
| CN119602494B (en) | A method, device, equipment and storage medium for automatic control of high voltage circuit breaker | |
| WO2022000466A1 (en) | Electric energy backward-flow control method, converter, and photovoltaic power generation system | |
| CN113507097A (en) | Solid state circuit breaker with power quality monitoring | |
| CN119255442B (en) | Automatic control method, device, equipment and storage medium for lighting fixtures | |
| WO2025044898A1 (en) | Transient voltage control apparatus and method for inverter | |
| CN109510243B (en) | Global MPPT control method and system for photovoltaic system of micro inverter | |
| CN118868338A (en) | A parallel battery management system for power distribution cabinets | |
| CN118889515A (en) | A multi-scenario switching method and system for a grid-connected converter | |
| Paul et al. | LArcNet: Lightweight Neural Network for Real-Time Series AC Arc Fault Detection | |
| CN110445155A (en) | A kind of intelligence phase-change switch, system, method and electronic equipment | |
| CN107968432B (en) | A control method for improving the output utilization rate of photovoltaic panels | |
| CN101404842B (en) | Three-wire system high-power LED driver | |
| CN212183102U (en) | Low-voltage circuit breaker for lane controller | |
| CN115331928A (en) | 10kV on-load voltage regulation intelligent transformer | |
| CN115693963A (en) | Intelligent assembly | |
| CN210310015U (en) | Power distribution system of direct current charging pile | |
| CN215420087U (en) | Zero-crossing trigger circuit and zero-crossing trigger device | |
| Wang et al. | Non-intrusive load monitoring algorithm for coarse-grained electricity consumption data based on YOLO deep neural networks | |
| CN217636244U (en) | Solar energy and commercial power dual-power supply direct current refrigeration control system | |
| CN119199398B (en) | Unified threshold fault detection method for DC microgrid based on multiple mean square error features | |
| Ding et al. | Multi-Feature Non-Intrusive Load Monitoring Method Based on Conditional Batch Normalization Combined with ResNet-KAN | |
| CN221597700U (en) | Control circuit for reducing temperature of frequency converter | |
| CN115549439B (en) | MMC switching loss optimization method and device under low power operation |
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 |