CN115809761B - Voltage quality analysis method and system based on low-voltage transformer area - Google Patents
Voltage quality analysis method and system based on low-voltage transformer area Download PDFInfo
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Abstract
The invention relates to a voltage quality detection technology, and discloses a voltage quality analysis method based on a low-voltage transformer area, which comprises the following steps: identifying the voltage quality event according to the voltage data of the head end of the platform area to obtain an identified voltage quality event; generating a voltage quality service rule according to the identified voltage quality event, and determining a voltage quality cause according to the voltage quality service rule; acquiring electric power basic data of a target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data, and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes; constructing a voltage quality analysis model according to a platform region voltage quality analysis index system and a voltage quality cause by utilizing a random forest algorithm; and analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain the voltage quality cause of the voltage event to be diagnosed. The invention further provides a voltage quality analysis system based on the low-voltage transformer area. The invention can improve the accuracy of judging the voltage quality event cause.
Description
Technical Field
The invention relates to the technical field of voltage quality detection, in particular to a voltage quality analysis method and system based on a low-voltage transformer area.
Background
With the social development and the improvement of the economic level, users gradually develop from the initial power-on requirement to the power-on requirement, but in order to know the actual power-on condition of the users and improve the life quality of the users, the voltage qualification rate of the power quality of the power supply enterprises needs to be analyzed to determine the cause of the voltage quality event.
The existing voltage quality analysis is to monitor the voltage quality event of the transformer area in real time and analyze the cause of the voltage quality event through experience or simple business rules. In practical application, the situation that the cause of misjudgment and missed judgment is caused by lack of experience may exist, and subsequent correction of the voltage quality problem may be caused, so that the accuracy is lower when the cause of the voltage quality event is judged.
Disclosure of Invention
The invention provides a voltage quality analysis method and a system based on a low-voltage transformer area, and mainly aims to solve the problem of low accuracy in judging voltage quality event causes.
In order to achieve the above object, the present invention provides a voltage quality analysis method based on a low-voltage transformer area, including:
s1, acquiring the first-end voltage data of a target low-voltage station area, and identifying a voltage quality event according to the first-end voltage data of the station area to obtain an identified voltage quality event;
S2, generating a voltage quality service rule according to the identification voltage quality event according to a preset time period, and determining a voltage quality cause of the target low-voltage station area according to the voltage quality service rule;
s3, acquiring electric power basic data of the target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data, and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes;
s4, constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm;
s5, analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain a voltage quality cause of the voltage event to be diagnosed, wherein the step of analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain the voltage quality cause of the voltage event to be diagnosed comprises the following steps:
s51, normalizing the voltage quality data corresponding to the voltage quality event to be diagnosed to obtain normalized voltage quality data, and matching the normalized voltage quality data with the clustering data to obtain a voltage quality data set to be trained;
S52, classifying the voltage quality data set to be trained by using the voltage quality analysis model to obtain a classified data set;
s53, calculating the classification score of the voltage quality event to be diagnosed according to the classification data set by using the following weighted average formula:
wherein ,
for the classification score,/->
For the number of classifications in the classification dataset, +.>
For the number of leaf nodes in the classification dataset, < > for each leaf node in the classification dataset>
For the +.o in the voltage quality analysis model>
Decision tree corresponding +.>
Weights of individual classification features, +.>
Is->
Weights of individual classification features, +.>
Is->
Weights of the decision tree +.>
For decision tree number, ++>
The number of the classified features;
and S54, when the classification score is larger than a preset classification threshold value, determining the voltage quality cause of the voltage event to be diagnosed.
Optionally, the identifying the voltage quality event according to the first-end voltage data of the platform area to obtain an identified voltage quality event includes:
extracting operation voltage data in the transformer area head end voltage data;
comparing the operation voltage data with a preset voltage threshold value to obtain a voltage comparison value;
and identifying the voltage quality event according to the voltage comparison value to obtain an identified voltage quality event.
Optionally, the identifying the voltage quality event according to the voltage comparison value to obtain an identified voltage quality event includes:
acquiring a rated upper limit ratio and a rated lower limit ratio of the voltage over-limit value, and acquiring the voltage duration of the operation voltage data;
when the voltage contrast value is larger than the rated upper limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a high voltage event;
and when the voltage contrast value is smaller than the rated lower limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a low voltage event.
Optionally, the generating the voltage quality service rule according to the identified voltage quality event according to the preset time period includes:
dividing the identified voltage quality event into a low voltage event and a high voltage event according to the same time period;
determining a first busbar rule, a first feeder rule and a first station area self rule corresponding to the low voltage event, and determining a second busbar rule, a second feeder rule and a second station area self rule corresponding to the high voltage event;
Generating a low-voltage service rule according to the first bus bar rule, the first feeder line rule and the first station area self rule, and generating a high-voltage service rule according to the second bus bar rule, the second feeder line rule and the second station area self rule;
and collecting the low-voltage service rule and the high-voltage service rule as voltage quality service rules.
Optionally, the determining the voltage quality cause of the target low-voltage station area according to the voltage quality service rule includes:
acquiring target voltage quality data of the target low-voltage transformer area;
comparing the target voltage quality data with the service rule data in the voltage quality service rule to obtain a rule comparison value;
and determining the voltage quality cause of the target low-voltage station according to the rule contrast value.
Optionally, the extracting the voltage quality index in the power basic data includes:
determining a platform head end voltage curve, a platform head end current curve and a platform head end voltage event synchronous rate of the target low-voltage platform according to the electric power basic data;
generating a low-voltage quality event index according to the platform area head end voltage curve, the platform area head end current curve and the platform area head end voltage event synchronous rate;
Determining a standing account class index according to the standing account data in the electric power basic data, and determining a topological net rack class index according to the topological data in the electric power basic data;
determining an operation type index according to operation data in the electric power basic data, the transformer area head end voltage curve and the transformer area head end current curve;
and collecting the low-voltage quality event index, the standing account type index, the topology net rack type index and the operation type index as the voltage quality index.
Optionally, the constructing a platform area voltage quality analysis index system by using the voltage quality index includes:
determining a first-level index of the voltage quality indexes according to a preset index dimension;
determining a second level index of the voltage quality indexes according to the first level index;
and constructing the transformer area voltage quality analysis index system according to the primary index and the secondary index by using a preset hierarchical structure.
Optionally, before the constructing a voltage quality analysis model according to the platform area voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm, the method further includes:
acquiring data to be trained, and clustering the original data by using a preset fuzzy clustering algorithm to obtain clustered data;
Sampling the cluster data by using a preset resampling algorithm to obtain sampled cluster data;
splitting the sampled cluster data into decision trees by using a preset splitting algorithm, wherein the splitting algorithm is as follows:
wherein ,
for minimum mean square error>
As a function of the minimum value +.>
For the +.>
Split node->
For a first subset of partitions in said sampled clustered data,/a subset of partitions>
Dividing a subset for a second division in said sampled clustered data,>
for a first number of categories of said first subset of divisions,/a first number of categories of->
A second number of partitions for the second partitioned subset;
and generating the random forest algorithm according to the decision tree.
Optionally, the constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm includes:
generating voltage quality original data by using the platform region voltage quality analysis index system and the voltage quality cause;
performing data classification training on the voltage quality original data by utilizing the random forest algorithm to obtain a voltage quality classification data set;
calculating a loss value of the random forest algorithm according to the voltage quality classification data set and a preset loss function;
And when the loss value is smaller than a preset loss threshold value, taking a random forest model corresponding to the random forest algorithm as the voltage quality analysis model.
In order to solve the above problems, the present invention also provides a voltage quality analysis system based on a low voltage transformer area, the system comprising:
the voltage quality event identification module is used for acquiring the first-end voltage data of the target low-voltage transformer area, and identifying the voltage quality event according to the first-end voltage data of the transformer area to obtain an identified voltage quality event;
the voltage quality cause determining module is used for generating a voltage quality service rule according to the identification voltage quality event according to a preset time period and determining the voltage quality cause of the target low-voltage station area according to the voltage quality service rule;
the system comprises a voltage quality analysis index system construction module, a power quality analysis index system and a power quality analysis index system, wherein the voltage quality analysis index system construction module is used for acquiring electric power basic data of the target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes;
the voltage quality analysis model construction module is used for constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by utilizing a preset random forest algorithm;
And the voltage quality cause analysis module is used for analyzing the voltage quality event to be diagnosed by utilizing the voltage quality analysis model to obtain the voltage quality cause of the voltage event to be diagnosed.
According to the embodiment of the invention, the voltage quality event is identified through the voltage data of the head end of the platform area, and the voltage quality business rule is generated according to the identified voltage quality event, so that the voltage quality cause is determined; according to the low-voltage transformer area ledger, operation, topology, superior feeder lines, buses, voltage quality events and other information in a plurality of power application systems, a voltage quality analysis index system is extracted, a voltage quality analysis model is built, intelligent analysis of transformer area voltage quality event causes is achieved, the voltage quality event causes are automatically given out, business responsibility complexity is reduced, manual analysis workload is reduced, misjudgment omission rate is reduced, improvement of voltage quality problems is guided, and therefore transformer area voltage qualification rate and residential user electricity consumption quality are improved. Therefore, the voltage quality analysis method and system based on the low-voltage transformer area can solve the problem of low accuracy in judging the cause of the voltage quality event.
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Fig. 1 is a flow chart of a voltage quality analysis method based on a low-voltage transformer area according to an embodiment of the invention;
FIG. 2 is a flow chart illustrating a voltage quality event recognition process according to an embodiment of the present invention;
FIG. 3 is a flow chart of determining voltage quality cause according to an embodiment of the present invention;
fig. 4 is a functional block diagram of a low voltage transformer area-based voltage quality analysis system according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a voltage quality analysis method based on a low-voltage transformer area. The execution subject of the low-voltage-zone-based voltage quality analysis method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the low voltage zone-based voltage quality analysis method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a voltage quality analysis method based on a low-voltage transformer area according to an embodiment of the invention is shown. In this embodiment, the voltage quality analysis method based on the low-voltage transformer area includes:
s1, acquiring the first-end voltage data of a target low-voltage station area, and identifying a voltage quality event according to the first-end voltage data of the station area to obtain an identified voltage quality event;
in one practical application scene, the low-voltage transformer area is the end of power supply for residential users by a power supply enterprise, the voltage quality of the transformer area directly influences the actual power utilization condition and life quality of residents, and meanwhile, the voltage qualification rate is one of important indexes for measuring the power quality of the power supply enterprise.
In the embodiment of the invention, the first-end voltage data of the transformer area refer to first-end operation voltage data, voltage threshold and duration time of the transformer area, wherein the first-end voltage data of the transformer area of the target low-voltage transformer area can be acquired through an electricity consumption information acquisition system.
In the embodiment of the invention, the voltage quality event comprises a low voltage event and a high voltage event, for example, the low voltage event comprises a low bus voltage, a long power supply radius, a small wire diameter, line load transfer, insufficient reactive compensation or equipment fault and the like; the high voltage event includes a bus voltage being high, reactive excess, etc.
In the embodiment of the present invention, referring to fig. 2, the step of identifying a voltage quality event according to the voltage data of the head end of the platform area to obtain an identified voltage quality event includes:
s21, extracting operation voltage data in the voltage data of the head end of the platform area;
s22, comparing the operation voltage data with a preset voltage threshold value to obtain a voltage comparison value;
s23, identifying the voltage quality event according to the voltage comparison value to obtain an identified voltage quality event.
In detail, the operation voltage data refers to effective voltage data of the head end of the current transformer area, and the operation voltage data, the voltage threshold value and the voltage duration can be collected through the electricity consumption information collection system. And comparing the preset voltage threshold value of the operation voltage data, namely calculating the difference value between the operation voltage data and the voltage threshold value, taking the voltage difference value as a voltage comparison value, and identifying the voltage quality event according to the voltage comparison value to identify the low voltage event and the high voltage event.
Specifically, the identifying the voltage quality event according to the voltage comparison value to obtain an identified voltage quality event includes:
acquiring a rated upper limit ratio and a rated lower limit ratio of the voltage over-limit value, and acquiring the voltage duration of the operation voltage data;
When the voltage contrast value is larger than the rated upper limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a high voltage event;
and when the voltage contrast value is smaller than the rated lower limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a low voltage event.
In detail, the rated upper limit ratio means 10% exceeding the voltage threshold, the rated lower limit ratio means 10% less than the voltage threshold, and the voltage duration threshold is 1 minute. When the voltage contrast value exceeds 10% of the voltage threshold value and the voltage duration is longer than 1 minute, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a high voltage event; and when the voltage contrast value is smaller than 10% of the voltage threshold value and the voltage duration is longer than 1 minute, identifying the voltage quality event corresponding to the voltage data of the head end of the platform area as a low voltage event.
Specifically, the low voltage time and high voltage event of the head end of the transformer area need to be subjected to the cause of the occurrence of the voltage quality event, so that the analysis of the business rule of the voltage quality is needed.
S2, generating a voltage quality service rule according to the identification voltage quality event according to a preset time period, and determining a voltage quality cause of the target low-voltage station area according to the voltage quality service rule;
in the embodiment of the invention, for voltage quality events of a plurality of transformer areas on the same feeder line in the same time period, simple business rules for voltage quality analysis need to be formulated, and the cause judgment of the superior feeder line or bus of the transformer areas is attributed through the business rules. The voltage quality service rules comprise feeder line service rules, bus service rules and service rules of the transformer area.
In the embodiment of the present invention, the generating the voltage quality service rule according to the identified voltage quality event according to the preset time period includes:
dividing the identified voltage quality event into a low voltage event and a high voltage event according to the same time period;
determining a first busbar rule, a first feeder rule and a first station area self rule corresponding to the low voltage event, and determining a second busbar rule, a second feeder rule and a second station area self rule corresponding to the high voltage event;
generating a low-voltage service rule according to the first bus bar rule, the first feeder line rule and the first station area self rule, and generating a high-voltage service rule according to the second bus bar rule, the second feeder line rule and the second station area self rule;
And collecting the low-voltage service rule and the high-voltage service rule as voltage quality service rules.
In detail, voltage quality events can occur in the same time period in a plurality of areas on the same feeder line, namely, the voltage quality events occurring in the same time period are divided into high voltage events and low voltage events, and bus bar rules, feeder line rules and area self rules of the low voltage events and the high voltage events are respectively determined, so that voltage quality business rules are generated according to the bus bar rules, the feeder line rules and the area self rules.
Specifically, for a low voltage event, the first busbar rule is to determine a busbar voltage threshold, the first feeder rule includes determining a power supply radius, a line diameter, line load transfer/load set power consumption, reactive compensation deficiency, medium voltage line or equipment fault, and the first station self rule includes determining a distribution transformer rational gear, meter fault, distribution transformer pile head contact, distribution transformer internal resistance, three-phase imbalance, load fluctuation, transient fault/transient phenomenon, power failure due to construction or long-term fault, and distribution transformer overload. For a high-voltage event, the second busbar rule is to determine the busbar voltage threshold value, the second feeder rule comprises determining reactive power surplus, feeder no-load or light-load and line load transfer, and the second station area rule comprises determining distribution transformer reasonable gear, reactive power reverse, meter fault, three-phase unbalance, load fluctuation, distribution transformer light-load and transient fault/transient phenomenon.
Further, according to the formulated voltage quality service rule, the causes of the voltage quality events of a plurality of areas on the same feeder line in the same time period are analyzed based on the voltage quality service rule, so that the causes of the voltage quality events are determined.
In the embodiment of the present invention, referring to fig. 3, the determining, according to the voltage quality service rule, a voltage quality cause of the target low-voltage area includes:
s31, acquiring target voltage quality data of the target low-voltage transformer area;
s32, comparing the target voltage quality data with the service rule data in the voltage quality service rule to obtain a rule comparison value;
s33, determining the voltage quality cause of the target low-voltage station according to the rule contrast value.
In detail, the target voltage quality data comprises bus voltage, feeder power supply radius, line diameter, line load transfer and load set power consumption of a target low-voltage station area, distribution shift position, distribution pile head, distribution internal resistance, load fluctuation, distribution load capacity and the like of the station area, wherein the target voltage quality data of the target low-voltage station area can be obtained through a marketing service application system and a power consumption information acquisition system.
Specifically, the target voltage quality data is subjected to data rule comparison with busbar service rules, feeder line service rules and platform region own rules in a preset voltage quality service to obtain rule comparison values. If the bus voltage of the target low-voltage transformer area is higher than the bus voltage in the business rule data, the voltage quality factor is that the bus voltage is higher, and if the feeder radius of the target low-voltage transformer area is longer than the feeder radius in the business rule data, the voltage quality factor is that the feeder radius is longer.
Further, for low voltage events, the upper bus causes are low bus voltage, feeder level causes comprise long power supply radius, small wire diameter, line load transfer/load concentrated power consumption, insufficient reactive compensation, medium voltage line or equipment faults, and the transformer area causes comprise unreasonable gear setting, meter faults, poor pile head contact of the transformer, overlarge internal resistance of the transformer, three-phase imbalance, load fluctuation, transient faults/transient phenomena, power failure caused by construction or long-term faults, and transformer overload. For high voltage events, the upper bus causes are higher bus voltage, feeder level causes comprise reactive power surplus, feeder no-load or light-load, line load transfer, and the district causes comprise unreasonable gear setting, reactive power reverse transfer, meter fault, three-phase imbalance, load fluctuation, light-load distribution and transient fault/transient phenomenon.
Furthermore, based on the voltage quality factor of the target low-voltage station, a station area quality analysis index system can be established, and factor influencing the voltage quality can be determined, so that the subsequent processing of the voltage quality can be improved, and the efficiency of the voltage quality processing can be improved.
S3, acquiring electric power basic data of the target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data, and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes;
in the embodiment of the invention, the electric power basic data comprises the standing book data, the operation data, the topology data, the upper feeder line data and the bus operation data of the target low-voltage transformer area, wherein the standing book data comprises buses, feeder lines, medium-voltage wires, medium-voltage cables, distribution transformers and the transformer area; the operation data comprises a bus, a feeder line and a station area; the topology data comprises distribution transformer, line segments, switch connection relations and the like of the feeder line.
In detail, the electric power basic data of the target low-voltage area can be acquired from multiple channels through a dispatching automation system, a power grid PMS system, a marketing business application system and an electric power consumption information acquisition system.
In the embodiment of the invention, the voltage quality index comprises a low voltage quality index and a high voltage quality index, and comprises a standing account type index, a voltage event type index, an operation type index, a topological net rack type index and the like.
In the embodiment of the present invention, the extracting the voltage quality index in the electric power basic data includes:
determining a platform head end voltage curve, a platform head end current curve and a platform head end voltage event synchronous rate of the target low-voltage platform according to the electric power basic data;
generating a low-voltage quality event index according to the platform area head end voltage curve, the platform area head end current curve and the platform area head end voltage event synchronous rate;
determining a standing account class index according to the standing account data in the electric power basic data, and determining a topological net rack class index according to the topological data in the electric power basic data;
determining an operation type index according to operation data in the electric power basic data, the transformer area head end voltage curve and the transformer area head end current curve;
and collecting the low-voltage quality event index, the standing account type index, the topology net rack type index and the operation type index as the voltage quality index.
In detail, determining the low voltage event synchronous rate of the low voltage quality event index according to the obtained voltage curve, current curve and voltage event synchronous rate of the target low voltage platform region in the electric power basic data, namely, determining whether the public variable number of the low voltage event occurs in the same time period under the same feeder line, whether the voltage is lower than the lower limit, the duration that the voltage is lower than the lower limit, namely, determining the duration that any phase voltage in three phases of the head end of the platform region is lower than the lower limit, the total duration that the voltage is out of limit and the number of low voltage coverage phases.
Specifically, determining a ledger class index according to ledger data in the electric power basic data, wherein the ledger class index comprises a design sequence and an operation period; determining topological net rack type indexes including feeder line power supply radius, main line minimum radius and load distribution coefficient according to the topological data in the electric power basic data; and determining operation indexes according to operation data in the electric power basic data, the platform region head end voltage curve and the platform region head end current curve, wherein the operation indexes comprise a bus voltage minimum value during out-of-limit, a feeder load rate maximum value during out-of-limit, a voltage average value during out-of-limit, a phase-out-of-limit and phase-out-of-limit long-term voltage difference minimum value, a phase-out-of-limit and phase-out-of-limit long-term voltage difference maximum value, three-phase unbalance, a three-phase unbalance and a phase-out-of-limit voltage difference and the like.
Further, the low-voltage quality event index, the ledger class index, the topology grid frame class index and the operation class index are collected to be the voltage quality index, so that a voltage quality analysis index system is built according to indexes corresponding to a plurality of class indexes, and a voltage quality analysis model is built according to the voltage quality analysis index system, and diagnosis of the voltage quality events of different low-voltage areas is achieved.
In the embodiment of the present invention, the constructing a system of a transformer area voltage quality analysis index by using the voltage quality index includes:
determining a first-level index of the voltage quality indexes according to a preset index dimension;
determining a second level index of the voltage quality indexes according to the first level index;
and constructing the transformer area voltage quality analysis index system according to the primary index and the secondary index by using a preset hierarchical structure.
In detail, the standing account type index, the voltage event type index, the operation type index and the topology net rack type index in the voltage quality index are used as primary indexes according to the index dimension, and corresponding secondary indexes are determined according to the index dimension corresponding to the primary indexes. If the ledger class index is used as a first-level index, the design sequence and the operation age corresponding to the ledger class are used as a second-level index. And layering the index data in the voltage quality index according to the hierarchical structure, namely according to the sequence of the first-level index and the second-level index, so as to generate a platform region voltage quality analysis index system.
Specifically, in order to accurately analyze the voltage quality, a voltage quality analysis model is constructed according to a platform region voltage quality analysis index system so as to accurately judge the voltage quality event cause subsequently.
S4, constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm;
in the embodiment of the invention, the random forest algorithm is an algorithm which combines a plurality of decision trees, wherein each data set is randomly selected with a return, and meanwhile, part of characteristics are randomly selected as input, and the random forest algorithm is an algorithm which takes the decision tree as an estimator.
In the embodiment of the present invention, before the constructing a voltage quality analysis model according to the platform area voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm, the method further includes:
acquiring data to be trained, and clustering the original data by using a preset fuzzy clustering algorithm to obtain clustered data;
sampling the cluster data by using a preset resampling algorithm to obtain sampled cluster data;
splitting the sampled cluster data into decision trees by using a preset splitting algorithm, wherein the splitting algorithm is as follows:
wherein ,
for minimum mean square error>
As a function of the minimum value +.>
For the +.>
Split node->
For a first subset of partitions in said sampled clustered data,/a subset of partitions >
Dividing a subset for a second division in said sampled clustered data,>
for a first number of categories of said first subset of divisions,/a first number of categories of->
A second number of partitions for the second partitioned subset;
and generating the random forest algorithm according to the decision tree.
In detail, the fuzzy clustering algorithm first determines the range of the number of classifications, typically sets the number of classifications
Is in the range of +.>
，/>
Representing the number of all data samples to be trained; for each +.>
The values are clustered once, and then the data obtained by each clustering are analyzed according to the result judgment indexes, and the relation among the data is obtained by searching inflection points and differential minimum points in the judgment indexes, so that the optimal clustering number is determined.
Specifically, a resampling algorithm (bootstrap) is utilized to extract a training set with a sample capacity of N, and the training set is repeated for K times, so that K training sets can be obtained, and each training set can generate a decision tree corresponding to the training set. In the process of generating the decision tree, for each split node, calculating the minimum mean square value of each split node by utilizing a split algorithm, obtaining an optimal segmentation criterion of the decision tree according to the minimum mean square value, training each decision tree according to the segmentation criterion until reaching a termination condition, obtaining each trained decision tree, and aggregating a plurality of decision trees into a random forest model, namely generating a random forest algorithm.
Further, analyzing the voltage quality event cause sample according to a random forest algorithm, and constructing a voltage quality analysis model by combining a voltage quality analysis index system for subsequent judgment of the voltage quality event cause, and meanwhile, after the voltage quality event after cause diagnosis is verified manually or on site, adding the voltage quality event into an existing training sample to be used as a sample for next model training.
In the embodiment of the present invention, the constructing a voltage quality analysis model according to the platform area voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm includes:
generating voltage quality original data by using the platform region voltage quality analysis index system and the voltage quality cause;
performing data classification training on the voltage quality original data by utilizing the random forest algorithm to obtain a voltage quality classification data set;
calculating a loss value of the random forest algorithm according to the voltage quality classification data set and a preset loss function;
and when the loss value is smaller than a preset loss threshold value, taking a random forest model corresponding to the random forest algorithm as the voltage quality analysis model.
In detail, the voltage quality analysis model is used for diagnosing the subsequent voltage quality event cause, training the random forest model by taking a pre-acquired platform region voltage quality analysis index system and the voltage quality cause as training data, continuously optimizing the random forest model according to a loss value obtained by loss function calculation until the loss value is smaller than a preset loss threshold value, and outputting the current random forest model as the voltage quality analysis model.
Specifically, after diagnosing the voltage quality event cause by using the voltage quality analysis model, the voltage quality event cause is verified manually or on site and then added into the existing sample to be used as a sample for the next model training. In addition, new training samples are required to be added periodically, and the voltage quality analysis model is continuously trained and updated, so that the accuracy of model training is further improved.
S5, analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain the voltage quality cause of the voltage event to be diagnosed.
In the embodiment of the invention, the voltage quality causes for the voltage event to be diagnosed comprise an upper bus cause, a feeder line cause and a platform area self cause. The voltage quality event cause of the voltage event to be diagnosed can be diagnosed by utilizing the voltage quality analysis model, and the voltage quality event cause is automatically given, so that the complexity of service rules is reduced, the workload of manual analysis is reduced, the misjudgment and omission rate is reduced, and the improvement of the voltage quality problem is guided, thereby improving the qualification rate of the radio stations in the station area and the electricity quality of resident users.
In the embodiment of the present invention, the analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain the voltage quality cause of the voltage event to be diagnosed includes:
Normalizing the voltage quality data corresponding to the voltage quality event to be diagnosed to obtain normalized voltage quality data, and matching the normalized voltage quality data with the clustering data to obtain a voltage quality data set to be trained;
classifying the voltage quality data set to be trained by using the voltage quality analysis model to obtain a classified data set;
calculating a classification score of the voltage quality event to be diagnosed according to the classification data set by using a weighted average formula as follows:
wherein ,
for the classification score,/->
For the number of classifications in the classification dataset, +.>
For the number of leaf nodes in the classification dataset, < > for each leaf node in the classification dataset>
For the +.o in the voltage quality analysis model>
Decision tree corresponding +.>
Weights of individual classification features, +.>
Is->
Weights of individual classification features, +.>
Is->
Weights of the decision tree +.>
For decision tree number, ++>
The number of the classified features;
and when the classification score is larger than a preset classification threshold value, determining the voltage quality cause of the voltage event to be diagnosed.
In detail, the voltage quality data corresponding to the voltage quality event to be diagnosed is normalized and matched with the clustering data, the voltage quality analysis model formed by the clustering value corresponding to the voltage quality data is substituted, the voltage quality data set to be trained is classified by utilizing the voltage quality analysis model, the classification score of each classification result is calculated by a weighted calculation average formula, and then the voltage quality cause of the voltage event to be diagnosed is analyzed by the classification score.
Specifically, the classification score is compared with a preset classification threshold, and when the classification score is greater than the preset classification threshold, the voltage quality cause of the voltage event to be diagnosed can be determined. If a weight is set for the voltage quality cause in the upper bus feature, when the calculated weight is greater than the preset weight, the weight of the voltage quality cause in the upper bus feature is 0.6 and the calculated weight is 0.7, it can be determined that the voltage quality cause of the voltage event to be diagnosed is the lower bus voltage.
According to the embodiment of the invention, the voltage quality event is identified through the voltage data of the head end of the platform area, and the voltage quality business rule is generated according to the identified voltage quality event, so that the voltage quality cause is determined; according to the low-voltage transformer area ledger, operation, topology, superior feeder lines, buses, voltage quality events and other information in a plurality of power application systems, a voltage quality analysis index system is extracted, a voltage quality analysis model is built, intelligent analysis of transformer area voltage quality event causes is achieved, the voltage quality event causes are automatically given out, business responsibility complexity is reduced, manual analysis workload is reduced, misjudgment omission rate is reduced, improvement of voltage quality problems is guided, and therefore transformer area voltage qualification rate and residential user electricity consumption quality are improved. Therefore, the voltage quality analysis method and system based on the low-voltage transformer area can solve the problem of low accuracy in judging the cause of the voltage quality event.
Fig. 4 is a functional block diagram of a low voltage transformer area-based voltage quality analysis system according to an embodiment of the present invention.
The low voltage bay-based voltage quality analysis system 100 of the present invention may be installed in an electronic device. Depending on the functions implemented, the low-voltage transformer area-based voltage quality analysis system 100 may include a voltage quality event identification module 101, a voltage quality cause determination module 102, a voltage quality analysis index system construction module 103, a voltage quality analysis model construction module 104, and a voltage quality cause analysis module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the voltage quality event identification module 101 is configured to obtain first-end voltage data of a target low-voltage transformer area, identify a voltage quality event according to the first-end voltage data of the transformer area, and obtain an identified voltage quality event;
the voltage quality cause determining module 102 is configured to generate a voltage quality service rule according to the identified voltage quality event according to a preset time period, and determine a voltage quality cause of the target low-voltage area according to the voltage quality service rule;
The voltage quality analysis index system construction module 103 is configured to obtain electric power basic data of the target low-voltage transformer area, extract a voltage quality index in the electric power basic data, and construct a transformer area voltage quality analysis index system by using the voltage quality index;
the voltage quality analysis model construction module 104 is configured to construct a voltage quality analysis model according to the platform area voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm;
the voltage quality cause analysis module 105 is configured to analyze a voltage quality event to be diagnosed by using the voltage quality analysis model, so as to obtain a voltage quality cause of the voltage event to be diagnosed.
In detail, each module in the low-voltage-zone-based voltage quality analysis system 100 in the embodiment of the present invention adopts the same technical means as the low-voltage-zone-based voltage quality analysis method described in fig. 1 to 3, and can produce the same technical effects, which are not repeated here.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention 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 can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Multiple units or systems as set forth in the system claims may also be implemented by means of one unit or system in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. A method for voltage quality analysis based on a low voltage region, the method comprising:
S1, acquiring the first-end voltage data of a target low-voltage station area, and identifying a voltage quality event according to the first-end voltage data of the station area to obtain an identified voltage quality event;
s2, generating a voltage quality service rule according to the identification voltage quality event according to a preset time period, and determining a voltage quality cause of the target low-voltage station area according to the voltage quality service rule;
the generating a voltage quality service rule according to the identified voltage quality event according to a preset time period includes:
dividing the identified voltage quality event into a low voltage event and a high voltage event according to the same time period;
determining a first busbar rule, a first feeder rule and a first station area self rule corresponding to the low voltage event, and determining a second busbar rule, a second feeder rule and a second station area self rule corresponding to the high voltage event;
generating a low-voltage service rule according to the first bus bar rule, the first feeder line rule and the first station area self rule, and generating a high-voltage service rule according to the second bus bar rule, the second feeder line rule and the second station area self rule;
Collecting the low-voltage service rule and the high-voltage service rule as voltage quality service rules;
the determining the voltage quality cause of the target low-voltage area according to the voltage quality service rule comprises the following steps:
acquiring target voltage quality data of the target low-voltage transformer area;
comparing the target voltage quality data with the service rule data in the voltage quality service rule to obtain a rule comparison value;
determining a voltage quality cause of the target low-voltage station according to the rule contrast value;
s3, acquiring electric power basic data of the target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data, and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes;
s4, constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm;
s5, analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain a voltage quality cause of the voltage quality event to be diagnosed, wherein the analyzing the voltage quality event to be diagnosed by using the voltage quality analysis model to obtain the voltage quality cause of the voltage quality event to be diagnosed comprises the following steps:
S51, normalizing the voltage quality data corresponding to the voltage quality event to be diagnosed to obtain normalized voltage quality data, and matching the normalized voltage quality data with cluster data to obtain a voltage quality data set to be trained;
s52, classifying the voltage quality data set to be trained by using the voltage quality analysis model to obtain a classified data set;
s53, calculating the classification score of the voltage quality event to be diagnosed according to the classification data set by using the following weighted average formula:
wherein ,
for the classification score,/->
For the number of classifications in the classification dataset, +.>
For the number of leaf nodes in the classification dataset, < > for each leaf node in the classification dataset>
For the +.o in the voltage quality analysis model>
Decision tree corresponding +.>
The weights of the individual classification characteristics are chosen,
is->
Weights of individual classification features, +.>
Is->
Weights of the decision tree +.>
For decision tree number, ++>
The number of the classified features; />
And S54, when the classification score is larger than a preset classification threshold value, determining the voltage quality cause of the voltage quality event to be diagnosed.
2. The method for analyzing voltage quality based on low-voltage transformer area according to claim 1, wherein said identifying voltage quality event according to said transformer area head end voltage data, comprises:
Extracting operation voltage data in the transformer area head end voltage data;
comparing the operation voltage data with a preset voltage threshold value to obtain a voltage comparison value;
and identifying the voltage quality event according to the voltage comparison value to obtain an identified voltage quality event.
3. The method for analyzing voltage quality based on low voltage transformer area according to claim 2, wherein the identifying the voltage quality event according to the voltage comparison value, comprises:
acquiring a rated upper limit ratio and a rated lower limit ratio of the voltage over-limit value, and acquiring the voltage duration of the operation voltage data;
when the voltage contrast value is larger than the rated upper limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a high voltage event;
and when the voltage contrast value is smaller than the rated lower limit value and the voltage duration time is larger than a preset voltage duration threshold value, identifying a voltage quality event corresponding to the voltage data of the head end of the platform area as a low voltage event.
4. A low voltage transformer area based voltage quality analysis method according to any one of claims 1 to 3, wherein said extracting a voltage quality index in said power base data comprises:
Determining a platform head end voltage curve, a platform head end current curve and a platform head end voltage event synchronous rate of the target low-voltage platform according to the electric power basic data;
generating a low-voltage quality event index according to the platform area head end voltage curve, the platform area head end current curve and the platform area head end voltage event synchronous rate;
determining a standing account class index according to the standing account data in the electric power basic data, and determining a topological net rack class index according to the topological data in the electric power basic data;
determining an operation type index according to operation data in the electric power basic data, the transformer area head end voltage curve and the transformer area head end current curve;
and collecting the low-voltage quality event index, the standing account type index, the topology net rack type index and the operation type index as the voltage quality index.
5. The low voltage zone-based voltage quality analysis method of claim 1, wherein constructing a zone voltage quality analysis index system using the voltage quality index comprises:
determining a first-level index of the voltage quality indexes according to a preset index dimension;
determining a second level index of the voltage quality indexes according to the first level index;
And constructing the transformer area voltage quality analysis index system according to the primary index and the secondary index by using a preset hierarchical structure.
6. The low-voltage transformer area-based voltage quality analysis method according to claim 1, further comprising, before said constructing a voltage quality analysis model from said transformer area voltage quality analysis index system and said voltage quality cause using a preset random forest algorithm:
acquiring data to be trained, and clustering the original data by using a preset fuzzy clustering algorithm to obtain clustered data;
sampling the cluster data by using a preset resampling algorithm to obtain sampled cluster data;
splitting the sampled cluster data into decision trees by using a preset splitting algorithm, wherein the splitting algorithm is as follows:
wherein ,
for minimum mean square error>
As a function of the minimum value +.>
For the +.>
The number of split nodes is chosen to be the same,
for a first subset of partitions in said sampled clustered data,/a subset of partitions>
Dividing a subset for a second division in said sampled clustered data,>
for a first number of categories of said first subset of divisions,/a first number of categories of->
A second number of partitions for the second partitioned subset;
and generating the random forest algorithm according to the decision tree.
7. The method for analyzing voltage quality based on low-voltage transformer areas according to claim 1, wherein the constructing a voltage quality analysis model according to the transformer area voltage quality analysis index system and the voltage quality cause by using a preset random forest algorithm comprises:
generating voltage quality original data by using the platform region voltage quality analysis index system and the voltage quality cause;
performing data classification training on the voltage quality original data by utilizing the random forest algorithm to obtain a voltage quality classification data set;
calculating a loss value of the random forest algorithm according to the voltage quality classification data set and a preset loss function;
and when the loss value is smaller than a preset loss threshold value, taking a random forest model corresponding to the random forest algorithm as the voltage quality analysis model.
8. A low voltage bay-based voltage quality analysis system, the system comprising:
the voltage quality event identification module is used for acquiring the first-end voltage data of the target low-voltage transformer area, and identifying the voltage quality event according to the first-end voltage data of the transformer area to obtain an identified voltage quality event;
The voltage quality cause determining module is used for generating a voltage quality service rule according to the identification voltage quality event according to a preset time period and determining the voltage quality cause of the target low-voltage station area according to the voltage quality service rule;
the generating a voltage quality service rule according to the identified voltage quality event according to a preset time period includes:
dividing the identified voltage quality event into a low voltage event and a high voltage event according to the same time period;
determining a first busbar rule, a first feeder rule and a first station area self rule corresponding to the low voltage event, and determining a second busbar rule, a second feeder rule and a second station area self rule corresponding to the high voltage event;
generating a low-voltage service rule according to the first bus bar rule, the first feeder line rule and the first station area self rule, and generating a high-voltage service rule according to the second bus bar rule, the second feeder line rule and the second station area self rule;
collecting the low-voltage service rule and the high-voltage service rule as voltage quality service rules;
the determining the voltage quality cause of the target low-voltage area according to the voltage quality service rule comprises the following steps:
Acquiring target voltage quality data of the target low-voltage transformer area;
comparing the target voltage quality data with the service rule data in the voltage quality service rule to obtain a rule comparison value;
determining a voltage quality cause of the target low-voltage station according to the rule contrast value;
the system comprises a voltage quality analysis index system construction module, a power quality analysis index system and a power quality analysis index system, wherein the voltage quality analysis index system construction module is used for acquiring electric power basic data of the target low-voltage transformer area, extracting voltage quality indexes in the electric power basic data and constructing a transformer area voltage quality analysis index system by utilizing the voltage quality indexes;
the voltage quality analysis model construction module is used for constructing a voltage quality analysis model according to the platform region voltage quality analysis index system and the voltage quality cause by utilizing a preset random forest algorithm;
the voltage quality cause analysis module is used for analyzing the voltage quality event to be diagnosed by utilizing the voltage quality analysis model to obtain the voltage quality cause of the voltage quality event to be diagnosed.
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