CN104158175A - Calculation method for real-time electricity classified load of power system distribution transformer terminal - Google Patents
Calculation method for real-time electricity classified load of power system distribution transformer terminal Download PDFInfo
- Publication number
- CN104158175A CN104158175A CN201410175379.XA CN201410175379A CN104158175A CN 104158175 A CN104158175 A CN 104158175A CN 201410175379 A CN201410175379 A CN 201410175379A CN 104158175 A CN104158175 A CN 104158175A
- Authority
- CN
- China
- Prior art keywords
- real
- electricity consumption
- distribution transformer
- electricity
- time
- 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.)
- Granted
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Disclosed is a calculation method for a real-time electricity classified load of a power system distribution transformer terminal. The calculation method comprises an S1 step of collecting real-time telemetry data of all power distribution terminals in an area every 15 minutes; an S2 step of storing the real-time telemetry data into a high-speed timing sequence database; an S3 step of doing statistics of the total electricity sale quantity Wp of a power distribution terminal in the last month, various electricity utilization class information and the power sale quantity of all users in the last month; an S4 step of obtaining the total electricity sale quantity of all electricity utilization classes of the power distribution terminal; an S5 step of obtaining the proportion of electricity sale of an electricity utilization class in the last month; an S6 step of reading out real-time electricity utilization classified loads; and an S7 step of accumulating to obtain the total classified load condition in the area. According to the invention, basic load data can be collected remotely in real time at present, the real-time electricity utilization classified load condition in the area can be calculated by using a specific method, and analysis of the real-time electricity classified load condition is facilitated for a power sector.
Description
Technical field
The present invention relates to a kind of computational methods of electric power system distribution transformer terminals electricity consumption classed load, especially relate to the computational methods of the real-time electricity consumption classed load of a kind of electric power system distribution transformer terminals.
Background technology
The electricity consumption classed load formation of adding up a region or a circuit and even a transformer is one of modal statistical item of power departments at different levels, but the variation of load is fast changing, therefore the statistics of conventional electric power can only be added up by the electric weight (such as monthly electric weight) based in the long period, the real time data with reference significance cannot be provided, cannot calculate real-time electricity consumption classed load.
By traditional way, calculate real-time electricity consumption classed load, must gather all electricity consumption users real-time power load of (comprising high pressure user, low-voltage customer), according to different electricity consumption users, different users' real-time power load is always added up by different electricity consumption classification loads, can calculate.But because the ammeter in current most domestic area does not still possess the ability that gathers real time data, implement and substantially cannot by traditional method.
Summary of the invention
Technical problem to be solved by this invention, just be to provide a kind of real-time, the efficient real-time electricity consumption classed load of electric power system distribution transformer terminals computational methods, can calculate real-time electricity consumption classed load forms, to take advantage of sale of electricity unit price to draw compared with the mode of total electricity price more timely with traditional accumulative total electric weight, be conducive to large-scale purchase sale of electricity enterprise estimate purchase, sale of electricity cost, and improve the assurance ability of power department to real-time electricity consumption classed load situation.
Solve the problems of the technologies described above, the technical solution used in the present invention is:
Computational methods for the real-time electricity consumption classed load of electric power system distribution transformer terminals, is characterized in that comprising the following steps:
S1 obtains all distribution transformer terminals information in somewhere in marketing system, as somewhere has 1 ... R ... S distribution transformer terminals;
S2 metering main website is at interval of the real-time telemetry data that gather all distribution transformer terminals in somewhere for 15 minutes by wireless GPRS: comprise meritorious, idle, voltage, electric current and power factor;
S3 is by all 1 ... R ... Real-time Load (the P of S distribution transformer terminals
1p
rp
s) telemetry deposits high speed time series database in;
S4 reads all electricity consumption classification information in marketing system, as somewhere has 1 ... k ... l electricity consumption classification;
S5 reads all user profile under certain distribution transformer terminals in marketing system, as certain distribution transformer terminals has 1 ... m ... n electricity consumption user;
S6 obtains, adds up distribution transformer terminals R total electricity sales amount of last month, each electricity consumption user's power consumption by marketing system; The sale of electricity total amount of supposing this distribution transformer terminals last month is W
p, the upper monthly electricity sales amount that belongs to all users of this distribution transformer terminals is respectively: W
p1, W
p2..., W
pm..., W
pn, W
p=∑ (W
p1+ W
p2+ ...+W
pm+ ...+W
pn); " the classification electricity sales amount " that belong to the different electricity consumption classification users of this distribution transformer terminals is respectively W
f1, W
f2... W
fk..., W
fl, W
p=∑ (W
f1+ W
f2+ ...+W
fk+ ...+W
fl);
S7 is by under this distribution transforming 1 ... m ... n user is according to 1 ... k ... l class electricity consumption classification, is added upper monthly power demand respectively, and " the classification electricity sales amount " that draws user last month of all electricity consumption classifications under this distribution transformer terminals is W
f1, W
f2..., W
fk..., W
fl; The wherein electricity sales amount W of k class electricity consumption classification last month
fk=W
p1+ ...+W
pm, so analogize, by " classification electricity sales amount " (the W last month of different classes of user under same distribution transformer terminals
f1, W
f2..., W
fk..., W
fl) calculate;
The electricity sales amount that S8 calculates each each electricity consumption classification of this distribution transforming accounts for the proportionality coefficient of total electricity sales amount, as K class user's electricity consumption proportionality coefficient k=W
fk/ W
p;
S9 reads the Real-time Load P of corresponding distribution transformer terminals R in timing sequence library
rbe multiplied by this distribution transformer terminals all electricity consumption classifications last month user's electricity consumption ratio, obtain the real-time electricity consumption classed load P of all electricity consumption classifications of all distribution transformer terminals
rk=kP
r; The like, calculate respectively;
S10 calculates all electricity consumption classed loads of all distribution transformings in somewhere by S5~S9;
S11, by the different electricity consumption classification user classed loads of cumulative all distribution transformer terminals, draws the total classed load situation P in area
k=P
1k+ P
2k+ ...+P
rk+ ...+P
sk, by continuous calculating, real-time analysis goes out the in real time total power load P of user of all electricity consumption classifications
1, P
2..., P
k, P
l.
The present invention utilizes at present in real time on the basis of distant place image data, calculates the real-time electricity consumption classed load situation in area with ad hoc approach, facilitates power department to analyze real-time electricity consumption classed load situation.
Beneficial effect: several respects data aggregate such as the historical electricity sales amount of corresponding relation, electricity consumption classification information on load, distribution transformer terminals, distribution transformer terminals low-voltage customer electricity sales amount and the real-time electricity consumption classed load of distribution transformer terminals situation that the present invention is based on distribution transformer terminals and electricity consumption user is analyzed, and finally obtains the real-time electricity consumption classed load situation in area.
The computational methods of electric power system of the present invention based on the real-time electricity consumption classed load of distribution transformer terminals, can consider from the angle that facilitates power department to grasp real-time electricity consumption formation, form statistical method as basis taking the existing electricity consumption of distribution transformer terminals, the sale of electricity composition historical data of using distribution transformer terminals, has realized the calculating of the real-time electricity consumption classed load of distribution transformer terminals quickly.Both the electricity consumption that had made power department can hold in real time each electricity consumption classification load under different Statistical Criterias forms, and increases work efficiency, and realizes again without the hardware of the algorithm with complicated and high configuration.
Brief description of the drawings
Fig. 1 is flow chart of the present invention;
Fig. 2 is the Foshan day electricity consumption classed load analysis chart of specific embodiment.
Embodiment
Below, the invention will be further described by reference to the accompanying drawings:
The computational methods preferred embodiment of the real-time electricity consumption classed load of electric power system distribution transformer terminals of the present invention, comprises the following steps:
S1 obtains all distribution transformer terminals information in somewhere in marketing system, as somewhere has 4 distribution transformer terminals A, B, C, D;
S2 metering main website is at interval of the real-time telemetry data that gather all distribution transformer terminals in somewhere for 15 minutes by wireless GPRS: comprise meritorious, idle, voltage, electric current and power factor;
S3 is by the Real-time Load (P of all 4 distribution transformings
a, P
b, P
c, P
d) telemetry deposits high speed time series database in;
S4 reads all electricity consumption classification information in marketing system, E as total in somewhere, two electricity consumption classifications of F;
S5 reads all user profile under A distribution transformer terminals in marketing system, as total in certain distribution transformer terminals H, I, J, tetra-electricity consumption users of K; (H, I, J user belong to the electricity consumption of E class, and K user belongs to the electricity consumption of F class)
S6 obtains, adds up distribution transformer terminals A total electricity sales amount of last month, each electricity consumption user's power consumption by marketing system; The sale of electricity total amount of supposing this distribution transformer terminals last month is W
a, the upper monthly electricity sales amount that belongs to all users of this distribution transformer terminals is respectively: W
ah, W
ai, W
aj, W
ak, W
a=∑ (W
ah+ W
ai+ W
aj+ W
ak); " the classification electricity sales amount " that belong to the different electricity consumption classification users of this distribution transformer terminals is respectively W
fe, W
ff,, W
p=∑ (W
fe+ W
ff);
S7 according to E, F class electricity consumption classification, is added H, I, J, K user under this distribution transforming respectively by upper monthly power demand, and " the classification electricity sales amount " that draws user last month of all electricity consumption classifications under this distribution transformer terminals is W
fe, W
ff; The wherein electricity sales amount W of E class electricity consumption classification last month
fe=W
ah+ W
ai+ W
aj, W
ff=W
ak, different classes of user's last month under distribution transformer terminals A " classification electricity sales amount " (W
fe, W
ff) calculate;
The electricity sales amount that S8 calculates each each electricity consumption classification of this distribution transforming accounts for the proportionality coefficient of total electricity sales amount, as E class user's electricity consumption proportionality coefficient e=W
fe/ W
a, f=W
ff/ W
a
S9 reads the Real-time Load P of corresponding distribution transformer terminals A in timing sequence library
abe multiplied by this distribution transformer terminals all electricity consumption classifications last month user's electricity consumption ratio, obtain the real-time electricity consumption classed load P of all electricity consumption classifications of all distribution transformer terminals E
ea=eP
a; The like, calculate P
fa=fP
a
S10 calculates all electricity consumption classed load P of all distribution transformings in somewhere by S5~S9
eb, P
fb, P
ec, P
fc, P
ed, P
fd;
S11, by the different electricity consumption classification user classed loads of cumulative all distribution transformer terminals, draws the total classed load situation P in area
e=P
ea+ P
eb+ P
ec+ P
ed, P
f=P
fa+ P
fb+ P
fc+ P
fd, the in real time total power load of user that can real-time analysis goes out all electricity consumption classifications is respectively P
e, P
f.
Claims (1)
1. computational methods for the real-time electricity consumption classed load of electric power system distribution transformer terminals, is characterized in that comprising the following steps:
S1 obtains all distribution transformer terminals information in somewhere in marketing system;
S2 metering main website is at interval of the real-time telemetry data that gather all distribution transformer terminals in somewhere for 15 minutes by wireless GPRS: comprise meritorious, idle, voltage, electric current and power factor;
S3 deposits the Real-time Load telemetry of all distribution transformer terminals in high speed time series database;
S4 reads all electricity consumption classification information in marketing system;
S5 reads all user profile under certain distribution transformer terminals in marketing system;
S6 obtains, adds up distribution transformer terminals R total electricity sales amount of last month, each electricity consumption user's power consumption by marketing system;
S7 is by under this distribution transforming 1 ... m ... n user is according to 1 ... k ... l class electricity consumption classification, is added upper monthly power demand respectively, and " the classification electricity sales amount " that draws user last month of all electricity consumption classifications under this distribution transformer terminals is W
f1, W
f2..., W
fk..., W
fl; The wherein electricity sales amount W of k class electricity consumption classification last month
fk=W
p1+ ...+W
pm; So analogize, by " classification electricity sales amount " (the W last month of different classes of user under same distribution transformer terminals
f1, W
f2..., W
fk..., W
fl) calculate;
The electricity sales amount that S8 calculates each each electricity consumption classification of this distribution transforming accounts for the proportionality coefficient of total electricity sales amount;
S9 reads the Real-time Load P of corresponding distribution transformer terminals R in timing sequence library
rbe multiplied by this distribution transformer terminals all electricity consumption classifications last month user's electricity consumption ratio, obtain the real-time electricity consumption classed load P of all electricity consumption classifications of all distribution transformer terminals
rk=kP
r; The like calculate respectively;
S10 calculates all electricity consumption classed loads of all distribution transformings in somewhere by S5~S9;
S11, by the different electricity consumption classification user classed loads of cumulative all distribution transformer terminals, draws the total classed load situation P in area
k=P
1k+ P
2k+ ...+P
rk+ ...+P
sk, by continuous calculating, real-time analysis goes out the in real time total power load P of user of all electricity consumption classifications
1, P
2..., P
k, P
l.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410175379.XA CN104158175B (en) | 2014-04-28 | 2014-04-28 | A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410175379.XA CN104158175B (en) | 2014-04-28 | 2014-04-28 | A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104158175A true CN104158175A (en) | 2014-11-19 |
CN104158175B CN104158175B (en) | 2016-08-24 |
Family
ID=51883618
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410175379.XA Active CN104158175B (en) | 2014-04-28 | 2014-04-28 | A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104158175B (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105260944A (en) * | 2015-10-10 | 2016-01-20 | 燕山大学 | Method for calculating statistical line loss based on LSSVM (Least Square Support Vector Machine) algorithm and association rule mining |
CN110417058A (en) * | 2019-08-06 | 2019-11-05 | 杭州继保南瑞电子科技有限公司 | The grid-connected interface monitor system of distributed power generation access utility network |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109783528B (en) * | 2018-11-23 | 2019-09-10 | 国网江苏省电力有限公司电力科学研究院 | A kind of electricity consumption schema extraction method and system |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006174564A (en) * | 2004-12-14 | 2006-06-29 | Tokyo Electric Power Co Inc:The | Optimum tidal current calculation method and optimum tidal current calculation device |
CN102999791A (en) * | 2012-11-23 | 2013-03-27 | 广东电网公司电力科学研究院 | Power load forecasting method based on customer segmentation in power industry |
CN103413254A (en) * | 2013-09-04 | 2013-11-27 | 国家电网公司 | Medium-and-long-term load prediction research and management integration application system |
CN103489045A (en) * | 2013-09-26 | 2014-01-01 | 国家电网公司 | Demand response load optimization potential evaluation method based on multi-scene design |
CN103544652A (en) * | 2013-09-26 | 2014-01-29 | 广东电网公司中山供电局 | Power grid industry classification load automatic statistical method and system |
CN103618383A (en) * | 2013-11-28 | 2014-03-05 | 国家电网公司 | Power distribution network monitoring and management system |
-
2014
- 2014-04-28 CN CN201410175379.XA patent/CN104158175B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006174564A (en) * | 2004-12-14 | 2006-06-29 | Tokyo Electric Power Co Inc:The | Optimum tidal current calculation method and optimum tidal current calculation device |
JP5077316B2 (en) * | 2004-12-14 | 2012-11-21 | 東京電力株式会社 | Optimal tidal current calculation method and optimal tidal current calculator |
CN102999791A (en) * | 2012-11-23 | 2013-03-27 | 广东电网公司电力科学研究院 | Power load forecasting method based on customer segmentation in power industry |
CN103413254A (en) * | 2013-09-04 | 2013-11-27 | 国家电网公司 | Medium-and-long-term load prediction research and management integration application system |
CN103489045A (en) * | 2013-09-26 | 2014-01-01 | 国家电网公司 | Demand response load optimization potential evaluation method based on multi-scene design |
CN103544652A (en) * | 2013-09-26 | 2014-01-29 | 广东电网公司中山供电局 | Power grid industry classification load automatic statistical method and system |
CN103618383A (en) * | 2013-11-28 | 2014-03-05 | 国家电网公司 | Power distribution network monitoring and management system |
Non-Patent Citations (1)
Title |
---|
费新生: "地区供电公司电力营销负荷管理***的研究与实现", 《中国优秀博硕士学位论文全文数据库 (硕士) 信息科技辑》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105260944A (en) * | 2015-10-10 | 2016-01-20 | 燕山大学 | Method for calculating statistical line loss based on LSSVM (Least Square Support Vector Machine) algorithm and association rule mining |
CN110417058A (en) * | 2019-08-06 | 2019-11-05 | 杭州继保南瑞电子科技有限公司 | The grid-connected interface monitor system of distributed power generation access utility network |
Also Published As
Publication number | Publication date |
---|---|
CN104158175B (en) | 2016-08-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Stephen et al. | Domestic load characterization through smart meter advance stratification | |
Campillo et al. | Is real-time electricity pricing suitable for residential users without demand-side management? | |
Lee et al. | Assessment of demand response and advanced metering | |
CN103489045B (en) | Demand response load optimization potential evaluation method based on multi-scene design | |
CN103413253B (en) | A kind of classification of the annual peak load based on economy, meteorologic factor Forecasting Methodology | |
CN102982489A (en) | Power customer online grouping method based on mass measurement data | |
CN102999791A (en) | Power load forecasting method based on customer segmentation in power industry | |
Hartvigsson et al. | Linking household and productive use of electricity with mini-grid dimensioning and operation | |
CN105069527A (en) | Zone area reasonable line loss prediction method based on data mining technology | |
CN204288281U (en) | Industrial enterprise's electric energy management system | |
CN107292513A (en) | A kind of method that power customer management is realized based on svm classifier algorithm | |
CN109634940A (en) | A kind of typical low pressure platform area's electricity consumption model building method based on magnanimity low-voltage platform area electricity consumption data | |
CN110109971A (en) | A kind of low-voltage platform area user power utilization Load Characteristic Analysis method | |
Zhao et al. | Modeling demand response under time-of-use pricing | |
CN104376502A (en) | Electric power customer credit comprehensive evaluation method based on grey relational degree | |
CN105046360A (en) | Power load weight management system based on peak-valley time period and peak-valley time period management method | |
CN202907195U (en) | Communication base station energy consumption management system | |
CN105320999A (en) | Combination method for demand response based time-of-use power price strategy suitable for smart grid development | |
CN103401239A (en) | Power demand side assisting in distribution line overload remission method | |
CN104158175A (en) | Calculation method for real-time electricity classified load of power system distribution transformer terminal | |
CN104517232A (en) | Taxpayer group association method for digging up taxable amount jump reason | |
Xu et al. | Spatial-temporal load forecasting using AMI data | |
Thanos et al. | Evaluating demand response programs by means of key performance indicators | |
CN105741049A (en) | Space-time whole process oriented line loss change analysis method | |
CN104467193A (en) | Four-division line loss quasi real-time on-line monitoring scheme based on daily frequentness monitoring |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
CP03 | Change of name, title or address | ||
CP03 | Change of name, title or address |
Address after: 528011 No. 1 South Fenjiang Road, Chancheng District, Guangdong, Foshan Patentee after: FOSHAN POWER SUPPLY BUREAU OF GUANGDONG POWER GRID CORPORATION Address before: 528000 Fenjiang South Road, Chancheng District, Guangdong, No. 1, No. Patentee before: Foshan Power Supply Bureau, Guangdong Power Grid Corporation |