CN104158175B - A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load - Google Patents
A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load Download PDFInfo
- Publication number
- CN104158175B CN104158175B CN201410175379.XA CN201410175379A CN104158175B CN 104158175 B CN104158175 B CN 104158175B CN 201410175379 A CN201410175379 A CN 201410175379A CN 104158175 B CN104158175 B CN 104158175B
- Authority
- CN
- China
- Prior art keywords
- electricity consumption
- distribution transformer
- transformer terminals
- real
- 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.)
- Active
Links
Abstract
The computational methods of a kind of power system distribution transformer terminals real-time electricity consumption classed load: S1 gathers the real-time telemetry data of all distribution transformer terminals in somewhere for every 15 minutes；Real-time telemetry data are stored in high speed time series database by S2；S3 adds up total electricity sales amount Wp of certain distribution transformer terminals last month, each electricity consumption classification information, a upper monthly electricity sales amount of all users；S4 obtains the electricity sales amount summation of the last month of all electricity consumption classifications under certain distribution transformer terminals；S5 obtains the history sale of electricity last month ratio of a certain electricity consumption classification；S6 reads corresponding distribution transformer terminals Real-time Load P in timing sequence libraryrIt is multiplied by the electricity consumption ratio of this distribution transformer terminals all electricity consumptions last month class users, obtains real-time electricity consumption classed load；S7 is cumulative draws the total classed load situation in area.The present invention utilize at present can in real time a distant place gather data basic load data, with ad hoc approach calculate area real-time electricity consumption classed load situation, facilitate power department that real-time electricity consumption classed load situation is analyzed.
Description
Technical field
The present invention relates to the computational methods of a kind of power system distribution transformer terminals electricity consumption classed load, especially relate to a kind of electricity
The computational methods of Force system distribution transformer terminals real-time electricity consumption classed load.
Background technology
The electricity consumption classed load composition adding up a region or a circuit or even a transformator is Electricity Departments at different levels
One of modal statistical item of door, but the change of load is fast changing, therefore the statistics of conventional electric power can only
Add up based on the electricity (the most monthly electricity) in the long period, it is impossible to the real-time number with reference significance is provided
According to, i.e. cannot calculate real-time electricity consumption classed load.
By traditional way, calculate real-time electricity consumption classed load, it is necessary to gather all electricity consumption users (include high voltage customer,
Low-voltage customer) real-time power load, according to different electricity consumption users, by the real-time power load of different users by difference
Electricity consumption classification load always adds up, and can calculate.But owing to the ammeter in current most domestic area does not possesses
Gather the ability of real time data, will implement by traditional method and substantially cannot.
Summary of the invention
The technical problem to be solved, is just to provide a kind of power system distribution transformer terminals real-time, efficient and uses in real time
Electricity classed load computational methods, can calculate real-time electricity consumption classed load and constitute, take advantage of sale of electricity list with traditional accumulative electricity
Valency show that the mode of total electricity price is compared more timely, the most large-scale purchase sale of electricity enterprise estimate purchase, sale of electricity cost, and improve
The power department assurance ability to real-time electricity consumption classed load situation.
Solving above-mentioned technical problem, the technical solution used in the present invention is:
The computational methods of a kind of power system distribution transformer terminals real-time electricity consumption classed load, 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 transforming
Terminal；
S2 is measured main website and was gathered the real-time telemetry number of all distribution transformer terminals in somewhere at interval of 15 minutes by wireless GPRS
According to: include gaining merit, idle, voltage, electric current and power factor；
S3 is by all 1 ... R ... the Real-time Load (P of S distribution transformer terminals1…Pr…Ps) telemetry is when being stored in high speed
Sequence data base；
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
Individual electricity consumption user；
S6 is obtained by marketing system, total electricity sales amount of statistics distribution transformer terminals R last month, the power consumption of each electricity consumption user；
The sale of electricity total amount assuming this distribution transformer terminals last month is Wp, belong to upper monthly the selling of all users of this distribution transformer terminals
Electricity is respectively as follows: Wp1、Wp2、...、Wpm、...、Wpn, Wp=∑ (Wp1+Wp2+...+Wpm+...+Wpn)；Belong to this
" the classification electricity sales amount " of the different electricity consumption class users of distribution transformer terminals is respectively Wf1、Wf2、...Wfk、...、Wfl, Wp
=∑ (Wf1+Wf2+...+Wfk+...+Wfl)；
S7 is by under this distribution transforming 1 ... m ... n user is according to 1 ... k ... l class electricity consumption classification, by upper monthly power demand phase respectively
Add, show that " the classification electricity sales amount " of user last month of all electricity consumption classifications under this distribution transformer terminals is Wf1、Wf2、...、
Wfk、...、Wfl；The wherein electricity sales amount W of k class electricity consumption classification last monthfk=Wp1+...+Wpm, and so on, join same
Last month " classification the electricity sales amount " (W of different classes of user under transformer terminalsf1、Wf2、...、Wfk、...、Wfl) calculate；
S8 calculates this distribution transforming electricity sales amount that respectively each electricity consumption is classified and accounts for the proportionality coefficient of total electricity sales amount, such as K class user
Electricity consumption proportionality coefficient k=Wfk/Wp；
S9 reads the Real-time Load P of corresponding distribution transformer terminals R in timing sequence libraryrIt is multiplied by this distribution transformer terminals all electricity consumptions last month class
The electricity consumption ratio of other user, obtains the real-time electricity consumption classed load P of all distribution transformer terminals all electricity consumptions classificationrk=k Pr；
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 class users classed loads of cumulative all distribution transformer terminals, draws the total classed load in area
Situation Pk=P1k+P2k+...+Prk+...+Psk, by constantly calculating, the user analyzing all electricity consumption classifications in real time is real-time
Total power load P1、P2、…、Pk…、Pl。
The present invention utilizes and can gather on the basis of data in a distant place in real time at present, calculates the real-time electricity consumption in area with ad hoc approach
Classed load situation, facilitates power department to be analyzed real-time electricity consumption classed load situation.
Beneficial effect: the present invention is based on distribution transformer terminals and the corresponding relation of electricity consumption user, electricity consumption classification information on load, distribution transforming
Several sides such as terminal history electricity sales amount, distribution transformer terminals low-voltage customer electricity sales amount and distribution transformer terminals real-time electricity consumption classed load situation
Face data aggregate is analyzed, and finally gives the real-time electricity consumption classed load situation in area.
The power system of present invention computational methods based on distribution transformer terminals real-time electricity consumption classed load, it is possible to from facilitating electric power
Department grasps the angle of real-time electricity consumption composition and considers, and based on the existing electricity consumption of distribution transformer terminals is constituted statistical method, uses
The sale of electricity composition historical data of distribution transformer terminals, achieves the calculating of distribution transformer terminals real-time electricity consumption classed load quickly.Both made
Power department can be held the electricity consumption of each electricity consumption classification load under different Statistical Criteria in real time and constitute, and improves work efficiency, again without
Need to realize with the hardware of complicated algorithm and high configuration.
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention；
Fig. 2 is the Foshan day electricity consumption classed load analysis chart of specific embodiment.
Detailed description of the invention
Below, in conjunction with accompanying drawing, the invention will be further described:
The computational methods preferred embodiment of the power system distribution transformer terminals real-time electricity consumption classed load of the present invention, including following
Step:
S1 obtains all distribution transformer terminals information in somewhere in marketing system, as somewhere have 4 distribution transformer terminals A,
B、C、D；
S2 is measured main website and was gathered the real-time telemetry number of all distribution transformer terminals in somewhere at interval of 15 minutes by wireless GPRS
According to: include gaining merit, idle, voltage, electric current and power factor；
S3 is by the Real-time Load (P of all 4 distribution transformingsa、Pb、Pc、Pd) telemetry is stored in high speed time series database；
S4 reads all electricity consumption classification information in marketing system, as somewhere has two electricity consumption classifications of E, F；
S5 reads all user profile under A distribution transformer terminals in marketing system, as certain distribution transformer terminals have H, I, J,
Tetra-electricity consumption users of K；(H, I, J user is belonging to E class electricity consumption, and K user belongs to F class electricity consumption)
S6 is obtained by marketing system, total electricity sales amount of statistics distribution transformer terminals A last month, the power consumption of each electricity consumption user；
The sale of electricity total amount assuming this distribution transformer terminals last month is Wa, belong to upper monthly the selling of all users of this distribution transformer terminals
Electricity is respectively as follows: Wah、Wai、Waj、Wak, Wa=∑ (Wah+Wai+Waj+Wak)；Belong to the different electricity consumptions of this distribution transformer terminals
" the classification electricity sales amount " of class users is respectively Wfe、Wff, Wp=∑ (Wfe+Wff)；
Upper monthly power demand according to E, F class electricity consumption classification, is separately summed by S7 by H, I, J, K user under this distribution transforming,
" the classification electricity sales amount " that draw user last month of all electricity consumption classifications under this distribution transformer terminals is Wfe、Wff；Wherein E class
The electricity sales amount W of electricity consumption classification last monthfe=Wah+Wai+Waj, Wff=Wak, under distribution transformer terminals A, the last month of different classes of user " divides
Class electricity sales amount " (Wfe、Wff) calculate；
S8 calculates this distribution transforming electricity sales amount that respectively each electricity consumption is classified and accounts for the proportionality coefficient of total electricity sales amount, such as E class user
Electricity consumption proportionality coefficient e=Wfe/Wa, f=Wff/Wa
S9 reads the Real-time Load P of corresponding distribution transformer terminals A in timing sequence libraryaIt is multiplied by this distribution transformer terminals all electricity consumptions last month class
The electricity consumption ratio of other user, obtains the real-time electricity consumption classed load P of all distribution transformer terminals all electricity consumptions classification Eea=e Pa；
The like, calculate Pfa=f Pa
S10 calculates all electricity consumption classed load P of all distribution transformings in somewhere by S5～S9eb、Pfb, Pec、Pfc, Ped、
Pfd；
S11, by the different electricity consumption class users classed loads of cumulative all distribution transformer terminals, draws the total classed load in area
Situation Pe=Pea+Peb+Pec+Ped,Pf=Pfa+Pfb+Pfc+Pfd, the user that can analyze all electricity consumption classifications in real time the most always uses
Electric load is respectively Pe、Pf。
Claims (1)
1. computational methods for power system distribution transformer terminals real-time electricity consumption classed load, is characterized in that comprising the following steps:
S1 obtains all distribution transformer terminals information in somewhere in marketing system；
S2 metering main website gathered the real-time telemetry data of somewhere all distribution transformer terminals at interval of 15 minutes by wireless GPRS: include gaining merit, idle, voltage, electric current and power factor；
The Real-time Load telemetry of all distribution transformer terminals is stored in high speed time series database by S3；
S4 reads all electricity consumption classification information in marketing system；
S5 reads all user profile under certain distribution transformer terminals in marketing system；
Total electricity sales amount that S6 is obtained by marketing system, adds up this distribution transformer terminals last month, the power consumption of each electricity consumption user；
S7 is by under this distribution transformer terminals 1 ... m ... n user 1 ... K ... L class electricity consumption category classification, is separately summed by monthly power demand in each electricity consumption classification, show that " the classification electricity sales amount " of user last month of all electricity consumption classifications under this distribution transformer terminals is Wf1、Wf2、...、WfK、...、WfL；The wherein electricity sales amount W of K class electricity consumption classification last monthfKAll user's power consumption last month sums belonging to K classification equal under this distribution transformer terminals；
S8 calculates the electricity sales amount of each electricity consumption of this distribution transformer terminals classification and accounts for the proportionality coefficient of total electricity sales amount；
S9 reads the Real-time Load P of corresponding distribution transformer terminals in timing sequence libraryrIt is multiplied by the electricity consumption ratio of this distribution transformer terminals each electricity consumption last month class users, obtains the real-time electricity consumption classed load P of this distribution transformer terminals each electricity consumption classificationrK=k Pr；
S10 is calculated the real-time electricity consumption classed load of each electricity consumption classification of all distribution transformer terminals in somewhere by S5～S9；
S11, by the active user classed load of the different electricity consumption classifications of cumulative all distribution transformer terminals, draws area electricity consumption classed load situation P in real timeK=P1K+P2K+...+PrK+...+PsK, and so on, analyze the user real-time electricity consumption classed load P of each electricity consumption classification in real time1、P2、…、PK…、PL。
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 CN104158175A (en) | 2014-11-19 |
| CN104158175B true 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 (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109783528A (en) * | 2018-11-23 | 2019-05-21 | 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 |
Families Citing this family (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 |
| CN110417058B (en) * | 2019-08-06 | 2020-10-30 | 杭州继保南瑞电子科技有限公司 | Grid-connected interface monitoring system for distributed power generation access to public power grid |
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 |
|---|
| 地区供电公司电力营销负荷管理系统的研究与实现;费新生;《中国优秀博硕士学位论文全文数据库 (硕士) 信息科技辑》;20060815;第I138-357页 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109783528A (en) * | 2018-11-23 | 2019-05-21 | 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 |
| 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 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104158175A (en) | 2014-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Baiyegunhi et al. | Rural household fuel energy transition: evidence from Giwa LGA Kaduna State, Nigeria | |
| Asadinejad et al. | Evaluation of residential customer elasticity for incentive based demand response programs | |
| Blodgett et al. | Accuracy of energy-use surveys in predicting rural mini-grid user consumption | |
| Campillo et al. | Is real-time electricity pricing suitable for residential users without demand-side management? | |
| Young et al. | Potential impacts of residential PV and battery storage on Australia's electricity networks under different tariffs | |
| Hong et al. | Long term probabilistic load forecasting and normalization with hourly information | |
| Darghouth et al. | Customer-economics of residential photovoltaic systems (Part 1): The impact of high renewable energy penetrations on electricity bill savings with net metering | |
| Stephen et al. | Domestic load characterization through smart meter advance stratification | |
| He et al. | Residential demand response behavior analysis based on Monte Carlo simulation: The case of Yinchuan in China | |
| Al-Shaalan | Reliability evaluation in generation expansion planning based on the expected energy not served | |
| Ida et al. | A stated preference analysis of smart meters, photovoltaic generation, and electric vehicles in Japan: Implications for penetration and GHG reduction | |
| Hartvigsson et al. | Linking household and productive use of electricity with mini-grid dimensioning and operation | |
| Gerbec et al. | An approach to customers daily load profile determination | |
| Zhao et al. | Modeling demand response under time-of-use pricing | |
| CN104158175B (en) | A kind of computational methods of power system distribution transformer terminals real-time electricity consumption classed load | |
| Dent et al. | The application of a data mining framework to energy usage profiling in domestic residences using UK data | |
| Sanchez-Lopez et al. | The diverse impacts of COVID-19 on electricity demand: the case of Chile | |
| Nataf et al. | An economic comparison of battery energy storage to conventional energy efficiency technologies in Colorado manufacturing facilities | |
| Rahman et al. | Electricity tariffs evaluation using smart load monitoring devices for residential consumer | |
| Behera et al. | A hybrid short term load forecasting model of an Indian grid | |
| Kowalska-Pyzalska | An analysis of factors enhancing adoption of smart metering platforms: An agent-based modeling approach | |
| Toma et al. | Electric energy consumption behavior of university students | |
| Muangjai et al. | An apply IoT for collection and analysis of specific energy consumption in production line of ready-to-drink juice at the second royal factory Mae Chan | |
| Woo et al. | Residential demand response evaluation: a scoping study | |
| vom Scheidt et al. | A data-driven Recommendation Tool for Sustainable Utility Service Bundles |
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 |