CN107506922A - Tea area temporary transformers switching load switching model based on local tea variety - Google Patents
Tea area temporary transformers switching load switching model based on local tea variety Download PDFInfo
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Abstract
The present invention discloses a kind of tea area temporary transformers switching load switching model based on local tea variety, including, tea area power load thermodynamic chart structure module：Nearly Cha areas in 1, three on March to May 31 of tea area are chosen per daily peak load data, analyze the load of tea area's distribution transforming different time, in distribution GIS geography information map, form tea area different periods load thermodynamic chart；Tea planting scope and plucking time structure module, correlation analysis is done with thermodynamic chart and each kind tea picking time, and the substantially plucking time of different cultivars tealeaves is judged according to the change of thermodynamic chart and the change of time；Temporary transformers switching load switching module：According to the difference of local tea variety, in plucking time region earlier, the preferential load using temporary transformers shunting heavy duty distribution transforming, treat that region harvesting peak is gone over, after power load declines, the temporary transformers are moved to the region in other local tea variety regions harvesting evening.The present invention solves the problems, such as tea area shortage of electric power, also improves distribution transforming utilization rate.
Description
Technical field
The present invention relates to electric power analysis technical field, and in particular to tea area electrical energy consumption analysis technology.
Background technology
Xinchang is located in a day grand-mother mountain area, is national well-known " township of well-known tea ", the mu of whole county Tea planting area more than 120,000, and
Form the scale tea making industry for brand with " giant Buddha Dragon Well tea ".With the all-round popularization of electronic tea machine, Xinchang tea frying
Fried from original hand and be changed into present electricity cooker.Plus popularizing for high power three-phase tea machine, tea area load occurs quick-fried in short-term
The situation that hairdo increases, it is more acute that electric power netting safe running situation compares former years.The special mountain area geography and climate in Xinchang, plus each
Local tea varieties distribution in Chan Cha areas is different, and tealeaves sprouts, time for pluck is also not quite identical, busy tea picking on tea grower's daytime, night
The characteristics of late busy tea frying, during spring tea, the tea machine almost all of night tea grower is in starting state, evening tea making load pole
Greatly, the period feature of tea making electricity consumption is fairly obvious.Tea making electricity rates are relatively low, and tea machine is purchased in uncontrollable state.
It is a people's livelihood engineering that spring tea, which protects power supply, and nervous spring tea supply of electric power year by year exists necessarily with ever-increasing tea machine quantity
Contradiction.It is badly in need of us and excavates tea area electrical feature, optimization taiwan area operation, instructs tea grower to produce, lift tea area's electricity consumption good service.
The content of the invention
The technical problem to be solved by the invention is to provide a kind of tea area temporary transformers switching based on local tea variety is negative
Lotus switching model, reasonable arrangement tea area temporary transformers switching load.
In order to solve the above technical problems, the present invention adopts the following technical scheme that：The interim transformation in tea area based on local tea variety
Device switching load switching model, including,
Tea area power load thermodynamic chart structure module：Choose the nearly daily highest in Cha areas in 1, three on March to May 31 in tea area
Load data, the load of tea area's distribution transforming different time is analyzed, in distribution GIS geography information map, form tea area different periods and bear
Lotus thermodynamic chart；
Tea planting scope and plucking time structure module, correlation is done with thermodynamic chart and each kind tea picking time
Analysis, the substantially plucking time of different cultivars tealeaves is judged according to the change of thermodynamic chart and the change of time；
Temporary transformers switching load switching module：It is excellent in plucking time region earlier according to the difference of local tea variety
First using the load of temporary transformers shunting heavy duty distribution transforming, treat that region harvesting peak is gone over, after power load declines, by this
Temporary transformers move to the region in other local tea variety regions harvesting evening.
Preferably, the applicable tea area scope of the model is counties and districts' one-level.
Preferably, load when load factor being more than into 25% is considered as effective tea making load.
Preferably, local tea variety is three black ox morning, big white tea, Dragon Well tea No. 43 kinds, using K-means Algorithm Analysis platforms
Area's tea making load and the relation of time, tea taiwan area on area's March 1 to May 31 are obtained per daily peak load data, analysis is daily most
The time-varying relationship of heavy load rate, by being more than 25% cluster analysis for forming the time to maximum load rate, when obtaining three classes
Between feature taiwan area cluster.
Preferably, it is copolymerized and takes second place for three classes, the morning of the load peak appearance of the first kind, the second class, the load of the 3rd class
Peak occurs the latest.
The present invention uses above-mentioned technical proposal, and the power load during spring tea is analyzed, with 3 days for a cycle, shape
Into thermodynamic chart, the substantially plucking time of different cultivars tealeaves is judged according to the change of thermodynamic chart and the change of time, is rationally pacified
Temporary transformers switching load is arranged, according to the difference of local tea variety, in plucking time region earlier, preferentially using interim transformation
Device shunts the load of heavy duty distribution transforming, treats that region harvesting peak is gone over, after power load declines, the interim change is moved into other
The region in local tea variety region harvesting evening, the problem of so not only solving tea area shortage of electric power, also improves distribution transforming utilization rate.Together
When can also be instructed tea grower on duty with repairing work etc. during purchasing tea machine and carrying out spring tea according to spring tea plucking time.
Embodiment
Seasonal obvious in view of tea area power load, the present invention is analyzed by annual March-May.The geography of the present invention
Position be choose it is corresponding it is at county level be object, therefore, the level of analysis should be at county level.
The present invention is made below in conjunction with specific embodiment and being illustrated.
By choosing seeds for many years, breeding, tealeaves current principal item in Xinchang is 3 black ox early, big white tea, Dragon Well tea No. 43 product
Kind, because the plucking time of every kind of tealeaves is different, the load peak formation time in the kind Tea planting region also has successively.
Load of the invention by analyzing tea area distribution transforming different time, tea area's different periods load " thermodynamic chart " is formed, and
Correlation analysis is done with each kind tea picking time, so as to judge the planting area of different cultivars tealeaves, and then instructs power supply
Attendant carries out specific aim electric service according to time feature to different local tea variety planting areas.
Tea area temporary transformers switching load switching model based on local tea variety, including,
Tea area power load thermodynamic chart structure module：Choose the nearly daily highest in Cha areas in 1, three on March to May 31 in tea area
Load data, the load of tea area's distribution transforming different time is analyzed, in distribution GIS geography information map, form tea area different periods and bear
Lotus thermodynamic chart；
Tea planting scope and plucking time structure module, correlation is done with thermodynamic chart and each kind tea picking time
Analysis, the substantially plucking time of different cultivars tealeaves is judged according to the change of thermodynamic chart and the change of time；
Temporary transformers switching load switching module：It is excellent in plucking time region earlier according to the difference of local tea variety
First using the load of temporary transformers shunting heavy duty distribution transforming, treat that region harvesting peak is gone over, after power load declines, by this
Temporary transformers move to the region in other local tea variety regions harvesting evening.
Wherein, the specific construction method of power load thermodynamic chart structure module is：
Cha Jicha areas power load highest is big more than 10 times than usual, the tea frying busy season general big 5- of electricity consumption maximum load than usual
6 times, load when load factor is more than 25% by the present invention is considered as effective tea making load, by carrying out statistical analysis to load factor,
Tea area load thermodynamic chart is formed, while maximum load rate is gathered more than 25% formation time, maximum load rate formation time
Class, the relation of local tea variety and power load is analyzed according to cluster result.
(1) rule one：Data time is chosen for March 1 to May 31, and every 3 days statistics are once.
【Rule description】According to Xinchang tea picking experience, spring tea plucking time is to the first tenday period of a month in May at the beginning of 3 months.
【Calculation formula】Data source is the public change monitoring system of intelligence.
【Regular foundation】Spring tea planting area and plucking time are relatively concentrated.
(2) rule two：Load statistics is formed into thermodynamic chart, reflection is picked tea-leaves and load variations situation
【Rule description】Assuming that taiwan area maximum load rate is X%, X is carried out with different colours it is corresponding, so as to form heating power
Figure.
【Calculation formula】Multiplying power is X, as follows with the corresponding relation of color：
| X | Color |
| 25≤X ﹤ 35 | Green |
| 35≤X ﹤ 50 | Yellow |
| 50≤X ﹤ 70 | It is orange |
| X≥7 | It is red |
【Regular foundation】Data visualization, reflect the size of data in different colors.
(3) rule three：It is considered as effective tea making load during load factor ＞ 25%
【Rule description】Through statistics, tea area distribution transforming maximum load rate is all less than 25% during non-tea season, therefore chooses load
It is tea making load critical value during rate=25%
【Calculation formula】Load factor=load/capacity * 100%
【Regular foundation】Tea area distribution transforming load factor data are obtained from the public change monitoring system of intelligence, through during counting non-tea season,
Distribution transforming load factor in tea area is all below 25%.
Data cleansing and pretreatment, extraction data are tea area distribution transformer load data, according to following data cleansing rule, to not
Extraction data in monitoring range are cleaned：
Cleaning rule one：X ﹤ 25 data are removed, because its contingency is higher, it is impossible to reflect tea making rule.
Cleaning rule two：Thermodynamic chart without significant change is washed, selects and concentrates the thermodynamic chart of feature to enter with the time
Row comparative analysis.
K-means algorithms are the very typical clustering algorithms based on distance, using evaluation index of the distance as similitude,
Think that the distance of two objects is nearer, its similarity is bigger.The algorithm thinks cluster by forming apart from close object,
Therefore using obtaining compact and independent cluster as final goal.
The selection of k initial classes cluster centre point has large effect to cluster result, because in the algorithm first step
In be center of the random any k object of selection as initial clustering, initially represent a cluster.The algorithm is in each iteration
In remaining each object is concentrated to data, each object is assigned to again according to its distance with each cluster center nearest
Cluster.After all data objects have been investigated, an iteration computing is completed, and new cluster centre is computed.If once
Before and after iteration, J value does not change, and illustrates that algorithm has been restrained.
Formula：
Algorithmic procedure is as follows：
1) K document is randomly selected as barycenter from N number of document.
2) it is measured to remaining each document and arrives the distance of each barycenter, and it is grouped into the class of nearest barycenter.
3) barycenter of obtained each class is recalculated.
4) step of iteration 2~3 is up to new barycenter is equal with the protoplasm heart or terminates less than specified threshold, algorithm.
By the peak load divided by capacity of each taiwan area daily (the 3-5 months), the daily maximum load rate of each taiwan area is obtained.
In whole sequential, date and load factor of each taiwan area load factor for the first time more than 25% are won than the maximum date, and will
Date is converted to corresponding numeral and clustered.Finally find to gather for the more significant classification of three class effects, the load of the first kind
The morning that peak occurs, the second class are taken second place, and the load peak of the 3rd class occurs the latest.
Reflect the situation of change of different cultivars tea picking and tea making load according to above-mentioned analysis, so as to substantially depict
Different cultivars Tea planting scope and plucking time.
| Kind | Pluck the time started | Priority |
| Black ox is early | 2 months 26-March 12 | A |
| Dragon Well tea 43 | 20-April 10 March | B |
| Big white tea | 16-May 5 April | C |
Priority carries out the spring in advance successively to arrange track remodelling and the order A ﹥ B ﹥ C of distribution transforming increase-volume according to priority
Tea harvesting correlation electric service early stage work.
In addition, the relation by analyzing tea area load and local tea variety, so as to tentatively judge the product of each taiwan area Tea planting
Kind, so as to the plucking time sequencing in the coming year according to different cultivars tealeaves, pointedly carry out electric service work, such as root
Instruct tea grower to purchase tea machine, reasonable arrangement distribution transforming increase-volume order, timely switching load according to spring tea plucking time and carry out spring tea
Period is on duty with rushing to repair work etc..
Claims (5)
1. the tea area temporary transformers switching load switching model based on local tea variety, it is characterised in that including,
Tea area power load thermodynamic chart structure module：Nearly Cha areas in 1, three on March to May 31 of tea area are chosen per daily peak load
Data, the load of tea area's distribution transforming different time is analyzed, in distribution GIS geography information map, form tea area different periods load heat
Try hard to；
Tea planting scope and plucking time structure module, correlation point is done with thermodynamic chart and each kind tea picking time
Analysis, the substantially plucking time of different cultivars tealeaves is judged according to the change of thermodynamic chart and the change of time；
Temporary transformers switching load switching module：According to the difference of local tea variety, in plucking time region earlier, preferentially make
With the load of temporary transformers shunting heavy duty distribution transforming, treat that region harvesting peak is gone over, it is after power load declines, this is interim
Transformer moves to the region in other local tea variety regions harvesting evening.
2. the tea area temporary transformers switching load switching model according to claim 1 based on local tea variety, its feature
It is, the applicable tea area scope of the model is counties and districts' one-level.
3. the tea area temporary transformers switching load switching model according to claim 1 based on local tea variety, its feature
It is, load when load factor is more than into 25% is considered as effective tea making load.
4. the tea area temporary transformers switching load switching model according to claim 3 based on local tea variety, its feature
It is, local tea variety is three black ox morning, big white tea, Dragon Well tea No. 43 kinds, using K-means Algorithm Analysis taiwan area tea making loads
With the relation of time, tea taiwan area on area's March 1 to May 31 is obtained per daily peak load data, analyzes daily maximum load rate
Time-varying relationship, by being more than 25% cluster analysis for forming the time to maximum load rate, obtain three class temporal characteristics taiwan areas
Cluster.
5. the tea area temporary transformers switching load switching model according to claim 4 based on local tea variety, its feature
It is, is copolymerized and takes second place for three classes, the morning of the load peak appearance of the first kind, the second class, the load peak appearance of the 3rd class
The latest.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116166940A (en) * | 2023-04-24 | 2023-05-26 | 施维智能计量系统服务(长沙)有限公司 | User power load time characteristic classification and identification method based on thermodynamic diagram |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106649050A (en) * | 2016-09-09 | 2017-05-10 | 西安交通大学 | Multi-parameter running situation graphic representation method for time sequential system |
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| CN106649050A (en) * | 2016-09-09 | 2017-05-10 | 西安交通大学 | Multi-parameter running situation graphic representation method for time sequential system |
Non-Patent Citations (3)
| Title |
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| 林飞武 等: "《移动式储能装置在季节性负荷侧的应用研究》", 《电力与电工》 * |
| 范慧娟: "《茶区供电能力不足的原因及解决措施》", 《电力科技》 * |
| 黄磊 等: "《基于K-means聚类和BP神经网络组合模型的用电负荷预测》", 《电力与能源》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116166940A (en) * | 2023-04-24 | 2023-05-26 | 施维智能计量系统服务(长沙)有限公司 | User power load time characteristic classification and identification method based on thermodynamic diagram |
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