CN106532686A - Area power distribution network load prediction method based on electric automobile charging apparatus - Google Patents

Area power distribution network load prediction method based on electric automobile charging apparatus Download PDF

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Publication number
CN106532686A
CN106532686A CN201610986582.4A CN201610986582A CN106532686A CN 106532686 A CN106532686 A CN 106532686A CN 201610986582 A CN201610986582 A CN 201610986582A CN 106532686 A CN106532686 A CN 106532686A
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China
Prior art keywords
load
section
charging
plot
ratio
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CN201610986582.4A
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Inventor
王晓洁
王博
张猛
王延安
徐彬
肖萌
赵旭东
宋向前
李静
王俊霞
张干珍
戎晓雪
杨涛
王志磊
徐大伟
王子翔
杨正东
张倩
潘韦如
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State Grid Corp of China SGCC
Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
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State Grid Corp of China SGCC
Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
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Priority to CN201610986582.4A priority Critical patent/CN106532686A/en
Publication of CN106532686A publication Critical patent/CN106532686A/en
Pending legal-status Critical Current

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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses an area power distribution network load prediction method based on an electric automobile charging apparatus. The method is characterized by comprising the following steps: 1, according to an area municipal regulatory detailed plan, controlling such basic content as the land use property, land area, floor area ratio and the like of an area, and obtaining area load prediction; 2, according to the quantity and the charging demand of various electric automobiles, obtaining area electric automobile load prediction; and 3, erecting an area power distribution network planning load prediction model comprising an electric automobile charging load, and bringing forward a load balancing guiding mode of electric automobile charging management weight cost and multistep electricity price. According to the invention, based on analysis of charging behavior of the electric automobiles, a charging management mode taking such constraint conditions of the electric automobiles as charging power, charging time, charging modes, transformer available capacity and the like into consideration is brought forward.

Description

Based on the section distribution network load Forecasting Methodology that charging electric vehicle is configured
Technical field
The present invention relates to section distribution network planning field, specifically a kind of section configured based on charging electric vehicle Distribution network load Forecasting Methodology.
Background technology
Electric automobile is that a kind of development prospect occurred under the background for being devoted to solving environmental pollution and energy crisis is wide Wealthy green traffic instrument, electric automobile combustion of fossil fuels unlike traditional automobile, but be with electric power Power is originated, and greatly reduces the discharge of pollutant, is the important means for solving the energy and environmental problem.Our countries are to electronic vapour The development of car and its electrically-charging equipment proposes many incentive policies, encourages the use of electric automobile and the construction of electrically-charging equipment.Work Letter portion《Development of Electric Vehicles strategic research is reported》Prediction, the year two thousand thirty whole nation electric automobile recoverable amount are up to 60,000,000.With The popularization and application of electric automobile, charging electric vehicle facility is needed badly perfect.Thus consider to fill in the distribution network planning of section Electric load is necessary.
The section distribution network planning carried out now is generally basede on section municipal administration regulatory plan (abbreviation regulatory control), regulatory control The substances such as land use property, land area, plot ratio to section are controlled.Load prediction is then wrapped according in regulatory control The plot property for containing is calculated, and generally comprises cultural facility, urban operating mechanism, office, business and residential electric power.Obviously bear in planning The prediction of lotus does not consider charging electric vehicle load.With the popularization and application of electric automobile, charging load will be to electrical network Produce material impact.How charging electric vehicle load to be considered into wherein urgently to be resolved hurrily in the distribution network planning of section.And how It is that we need the problem of discussion by accessing in power distribution network for electric automobile load rational and orderly.At present, Chinese scholars are in electricity A series of researchs have been done on the orderly charging problems of electrical automobile, but which has not been associated with section distribution network planning, and do not had The access of charging load is considered jointly from Demand-side and supply side.
The content of the invention
In order to solve the above problems, the invention provides the section distribution network load prediction configured based on charging electric vehicle Method, on the basis of analysis charging electric vehicle behavior, proposes to consider the charge power of electric automobile, charging interval, charging The Charge Management pattern of the constraints such as mode and transformator active volume.
The present invention is employed the following technical solutions：Based on the section distribution network load Forecasting Methodology that charging electric vehicle is configured, Characterized in that, described method is comprised the following steps：
Step 1：According to section municipal administration regulatory plan, land use property, land area to section, plot ratio It is controlled Deng substance, obtains section load prediction；
Step 2：According to quantity and the charge requirement of all kinds of electric automobiles, section electric automobile load prediction is obtained；
Step 3：The section distribution network planning load forecasting model comprising charging electric vehicle load is built, electronic vapour is proposed Car Charge Management weights the load balancing bootmode of expense and step price.
Further, the specific implementation of step 1 is：
Obtain section Construction intensity figure；
Identification section regulatory control relevant parameter, carries out load prediction,
Further, the detailed process of load prediction is：
1) utilize formula Wz=A × R × m0×Kj×Kr×Ky... calculate the load in sub- plot, wherein, WzFor sub- plot Load (W), A are sub- plot land area (m2), and R is plot ratio, m0For unit load density (W/m2), KjFor building up rate (%), KrFor occupancy rate (%), KyFor the electricity consumption simultaneity factor (%) of user in sub- plot；
2) utilize formula Wf=(∑ Wz)×Kz... calculate the load in point plot, wherein, WfFor a point plot load (W), Kz For sub- plot load simultaneity factor (%)；
3) utilize formula Wp=(∑ Wf)×Kf/106... calculate section load, wherein, WpFor section load (MW), KfFor The electricity consumption simultaneity factor (%) in each point of plot；
4) utilize formula Sp=Wp×Rs... calculate power transformation capacity needed for section, wherein, SpThe power transformation capacity for needed for section (MVA), RsFor capacity-load ratio (MVA/MW).
Further, the process that implements of step 2 is：
1) calculate public charging aggregate demand W of section electric automobileG=GC × KGC+SC×KSC+JC×KJC+LC×KLC+CC× KCC；
2) calculate section electric automobile individual's charging aggregate demand
3) calculate section electric automobile total load WC=WG+WS；
Wherein, WcFor section electric automobile total load (MW)；WGFor the public charging aggregate demand of section electric automobile；WSFor piece Area's electric automobile individual's charging aggregate demand；GC is officer's car aggregate demand (MW)；KGCFor officer's car public demands ratio (%)；SC is Private car aggregate demand (MW)；KSCFor private car public demands ratio (%)；JC is buses aggregate demand (MW)；KJCFor buses Public demands ratio (%), general value are 1；LC is logistic car aggregate demand (MW)；KLCFor logistic car public demands ratio (%)； CC is taxi aggregate demand (MW)；KCCFor taxi public demands ratio (%)；KGCsFor officer's car private demand ratio (%)；For private car private demand ratio (%)；KJCsFor buses private demand ratio (%), general value is 0；For thing Stream car private demand ratio (%)；For taxi private demand ratio (%).
Further, the detailed process of step 3 is：
1) calculate point plot total load in moment t
2) calculate section prediction load WP=Wp+WG×a1×β1+WS×a2×β2；
Wherein, WF(t, j) is point plot total load, W in moment tf(t, j) is point plot conventional load in moment t, WPLoad is predicted for section, the saturation loading value after the development stability of section, GC is typically takeni(t,j)、SCi(t,j)、JCi(t,j)、 LCi(t,j)、CCi(t, j) is respectively load of all kinds of electric automobiles in moment t.
The invention has the beneficial effects as follows：On the basis of analysis charging electric vehicle behavior, propose to consider electric automobile The Charge Management pattern of the constraintss such as charge power, charging interval, charging modes and transformator active volume.In the pattern Under, charging electric vehicle desirable load to be predicted and is combined with conventional load prediction, and be applied in distribution network planning, formation is examined Consider the section distribution network planning load prediction results of electromobile charging management pattern, obtain good result.The pattern is not only fitted For the section distribution network planning load prediction comprising charging electric vehicle load, and to comprising other polynary loads or distribution The section distribution network planning load prediction of formula new forms of energy has reference.
Description of the drawings
Fig. 1 is the inventive method flow chart；
Fig. 2 is section Construction intensity figure；
Fig. 3 is the charging flow figure after this method is arranged.
Specific embodiment
As shown in figure 1, the section distribution network load Forecasting Methodology configured based on charging electric vehicle is comprised the following steps：
Step 1：According to section municipal administration regulatory plan, land use property, land area to section, plot ratio It is controlled Deng substance, obtains section load prediction；
Step 2：According to quantity and the charge requirement of all kinds of electric automobiles, section electric automobile load prediction is obtained；
Step 3：The section distribution network planning load forecasting model comprising charging electric vehicle load is built, electronic vapour is proposed Car Charge Management weights the load balancing bootmode of expense and step price.
First, section distribution network planning load prediction：
Section distribution network planning is generally basede on section municipal administration regulatory plan [5] (abbreviation regulatory control), and regulatory control is to section Land use property, land area, the substance such as plot ratio be controlled.Fig. 2 show section Construction intensity figure.Identification Section regulatory control relevant parameter, carries out load prediction, such as shown in formula (1) (2) (3) (4).
The carry calculation in sub- plot is shown in formula (1), Wz=A × R × m0×Kj×Kr×Ky……(1)。
Wherein, WzFor sub- plot load (W), A is sub- plot land area (m2), and R is plot ratio, m0It is close for unit load Degree (W/m2), KjFor building up rate (%), KrFor occupancy rate (%), KyFor the electricity consumption simultaneity factor (%) of user in sub- plot.
The carry calculation in point plot is shown in formula (2).Wf=(∑ Wz)×Kz……(2)。
Wherein, WfFor a point plot load (W), KzFor sub- plot load simultaneity factor (%).
Wp=(∑ Wf)×Kf/106... (3), wherein, WpFor section load (MW), KfElectricity consumption for each point of plot is same When rate (%).
Known section load WpPower transformation capacity needed for section [6] S can be obtainedpShown in formula (4).Sp=Wp×Rs... (4), its In, SpPower transformation capacity (MVA), R for needed for sectionsFor capacity-load ratio (MVA/MW).
2nd, electric automobile load prediction
Regional electric automobile charging pile infrastructure load prediction equation below (5) (6) (7).
WG=GC × KGC+SC×KSC+JC×KJC+LC×KLC+CC×KCC……(5)
WC=WG+WS……(7)
Wherein, WcFor section electric automobile total load (MW)；WGFor the public charging aggregate demand of section electric automobile；WSFor piece Area's electric automobile individual's charging aggregate demand；GC is officer's car aggregate demand (MW)；KGCFor officer's car public demands ratio (%)；SC is Private car aggregate demand (MW)；KSCFor private car public demands ratio (%)；JC is buses aggregate demand (MW)；KJCFor buses Public demands ratio (%), general value are 1；LC is logistic car aggregate demand (MW)；KLCFor logistic car public demands ratio (%)； CC is taxi aggregate demand (MW)；KCCFor taxi public demands ratio (%)；KGCsFor officer's car private demand ratio (%)；For private car private demand ratio (%)；KJCsFor buses private demand ratio (%), general value is 0；For thing Stream car private demand ratio (%)；For taxi private demand ratio (%).
3rd, consider the load prediction of electromobile charging management pattern
Consider the load condition of point each charging pile of plot, the total load in this point of plot is calculated as shown in formula (8).Section Total load is calculated sees formula (9).
WP=Wp+WG×a1×β1+WS×a2×β2……(9)
Wherein, WF(t, j) is point plot total load, W in moment tf(t, j) is point plot conventional load in moment t, WPLoad is predicted for section, the saturation loading value after the development stability of section, GC is typically takeni(t,j)、SCi(t,j)、JCi(t,j)、 LCi(t,j)、CCi(t, j) is respectively load of all kinds of electric automobiles in moment t.According to practical situation, during charging electric vehicle Sequence only need to consider load variations, j=from point plot level granularity<1 2 ... NF>Represent ground block number, NF-GCFor public affair Car charging pile is numbered, NF-SCNumber for private car charging pile, NF-JCNumber for buses charging pile, NF-LCFor logistic car charging pile Numbering, NF-GCNumber for taxi charging pile.a1, a2It is for simultaneity factor, relevant with charging priority (administrative weight charge).β1、 β2The peak load coefficient that disappears (different charge periods take different numerical value) is named as, it is relevant with step price.To ensure in charging process Transformer station's nonoverload (i.e. whole section nonoverload) involved by the section, i.e.,：
Simultaneously should meet distribution transforming it is not heavily loaded (load factor be 80% and above and continue 2 hours), the not heavily loaded (load factor of circuit For 70% and above and continue 1 hour) and condition needed for meeting N-1.And quarter monitoring charging pile, line is taken in charging process Whether the facilities such as road, distribution transforming, ring main unit, transformer station transship, and set off-limit alarm function.
Charging electric vehicle price is made up of administrative weight expense and step price two parts, with the charging priority of vehicle It is constraints with charge period, charging price can be calculated.By taking private car as an example, computing formula such as formula (11).
Wherein, PSCFor charging price, l1、l2、l3For charging priority, a1, a2There is fuzzy mathematics pass with equation group (11) System.
As can be seen here, charge in low-valley interval and priority is again low, then charge low, otherwise fill in peak period high priority Electricity, then collect the charges higher.In the same manner, other vehicles also can calculate the charging fees thus collected by this equation.
4th, effect analyses
As shown in figure 3, by taking the private car in a point of plot as an example, when user is connected to charging pile, charging electric vehicle System can obtain the battery information for accessing vehicle automatically, and at this moment, user can set charge period and charging according to the situation of oneself Priority.System rank will be ranked according to selected by user, and the user of the first priority charges in advance, and second, third is preferential Level user sequentially queues up charging.The load factor situation of monitoring device at any time in charging process, once it is out-of-limit, phase will be interrupted immediately Charging to low priority vehicle, waits load level to be further continued for charging after lowering.Charging expense is by charge period and preferentially Level is together decided on.
The present invention proposes a kind of electromobile charging management pattern by analyzing charging electric vehicle behavior.Considering electronic Under automobile Charge Management pattern, comprehensive section static state saturation loading demand and dynamic load variation characteristic have been built comprising electronic The section distribution network planning load forecasting model of automobile charging load.Meanwhile, electromobile charging management is proposed for the pattern The load balancing bootmode of weighting expense and step price.Power grid construction investment will effectively be reduced and Electric Load Forecasting will be lifted Survey, the goodness of fit between power grid construction sequential and need for electricity.
It should be pointed out that the above specific embodiment can make those skilled in the art that the present invention is more fully understood Concrete structure, but limit the invention never in any form.Therefore, although description and drawings and Examples are to the present invention Creation has been carried out detailed description, it will be understood by those skilled in the art, however, that still can repair to the invention Change or equivalent；And all are without departing from technical scheme and its improvement of the spirit and scope of the invention, which is covered In the middle of the protection domain of the invention patent.

Claims (5)

1. the section distribution network load Forecasting Methodology for being configured based on charging electric vehicle, it is characterised in that described method includes Following steps：
Step 1：According to bases such as section municipal administration regulatory plan, land use properties, land area, plot ratio to section This content is controlled, and obtains section load prediction；
Step 2：According to quantity and the charge requirement of all kinds of electric automobiles, section electric automobile load prediction is obtained；
Step 3：The section distribution network planning load forecasting model comprising charging electric vehicle load is built, proposes that electric automobile fills The load balancing bootmode of electric administrative weight expense and step price.
2. it is according to claim 1 based on charging electric vehicle configure section distribution network load Forecasting Methodology, its feature It is that the specific implementation of step 1 is：
Obtain section Construction intensity figure；
Identification section regulatory control relevant parameter, carries out load prediction.
3. it is according to claim 2 based on charging electric vehicle configure section distribution network load Forecasting Methodology, its feature It is that the detailed process of load prediction is：
1) utilize formula Wz=A × R × m0×Kj×Kr×Ky... calculate the load in sub- plot, wherein, WzFor sub- plot load (W), A is sub- plot land area (m2), and R is plot ratio, m0For unit load density (W/m2), KjFor building up rate (%), KrFor Occupancy rate (%), KyFor the electricity consumption simultaneity factor (%) of user in sub- plot；
2) utilize formula Wf=(∑ Wz)×Kz... calculate the load in point plot, wherein, WfFor a point plot load (W), KzFor son Plot load simultaneity factor (%)；
3) utilize formula Wp=(∑ Wf)×Kf/106... calculate section load, wherein, WpFor section load (MW), KfFor each Divide the electricity consumption simultaneity factor (%) in plot；
4) utilize formula Sp=Wp×Rs... calculate power transformation capacity needed for section, wherein, SpThe power transformation capacity for needed for section (MVA), RsFor capacity-load ratio (MVA/MW).
4. it is according to claim 1 based on charging electric vehicle configure section distribution network load Forecasting Methodology, its feature It is that the process that implements of step 2 is：
1) calculate public charging aggregate demand W of section electric automobileG=GC × KGC+SC×KSC+JC×KJC+LC×KLC+CC×KCC；
2) calculate section electric automobile individual's charging aggregate demand
3) calculate section electric automobile total load WC=WG+WS；
Wherein, WcFor section electric automobile total load (MW)；WGFor the public charging aggregate demand of section electric automobile；WSFor section electricity Electrical automobile individual's charging aggregate demand；GC is officer's car aggregate demand (MW)；KGCFor officer's car public demands ratio (%)；SC is private savings Car aggregate demand (MW)；KSCFor private car public demands ratio (%)；JC is buses aggregate demand (MW)；KJCIt is public for buses Demand percentage (%), general value are 1；LC is logistic car aggregate demand (MW)；KLCFor logistic car public demands ratio (%)；CC is Taxi aggregate demand (MW)；KCCFor taxi public demands ratio (%)；KGCsFor officer's car private demand ratio (%)； For private car private demand ratio (%)；KJCsFor buses private demand ratio (%), general value is 0；For logistic car Private demand ratio (%)；For taxi private demand ratio (%).
5. it is according to claim 1 based on charging electric vehicle configure section distribution network load Forecasting Methodology, its feature It is that the detailed process of step 3 is：
1) calculate point plot total load in moment t
2) calculate section prediction load WP=Wp+WG×a1×β1+WS×a2×β2；
Wherein, WF(t, j) is point plot total load, W in moment tf(t, j) is point plot conventional load, W in moment tPFor Load is predicted in section, typically takes the saturation loading value after the development stability of section, GCi(t,j)、SCi(t,j)、JCi(t,j)、LCi (t,j)、CCi(t, j) is respectively load of all kinds of electric automobiles in moment t.
CN201610986582.4A 2016-11-09 2016-11-09 Area power distribution network load prediction method based on electric automobile charging apparatus Pending CN106532686A (en)

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CN107122856A (en) * 2017-04-26 2017-09-01 天津天大求实电力新技术股份有限公司 Space saturation load forecasting method under new situation
CN109118104A (en) * 2018-08-27 2019-01-01 天津津电供电设计所有限公司 Distribution network planning method and device
CN109978241A (en) * 2019-03-11 2019-07-05 清华四川能源互联网研究院 A kind of determination method and device of electric car charging load
CN109978241B (en) * 2019-03-11 2022-01-11 清华四川能源互联网研究院 Method and device for determining charging load of electric automobile
WO2021098352A1 (en) * 2019-11-22 2021-05-27 国网福建省电力有限公司 Active power distribution network planning model establishment method taking into consideration site selection and capacity determination of electric vehicle charging stations
US11878602B2 (en) 2019-11-22 2024-01-23 State Grid Fujian Electric Power Co., Ltd. Method for establishing active distribution network planning model considering location and capacity determination of electric vehicle charging station
CN113435663A (en) * 2021-07-15 2021-09-24 国网冀北电力有限公司唐山供电公司 CNN-LSTM combined load prediction method considering electric vehicle charging load influence
CN113978303A (en) * 2021-11-16 2022-01-28 国网天津市电力公司 Charging method and system for electric automobile
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