CN107292427A - The maximum allowable current-carrying capacity probabilistic forecasting method and device of transmission line of electricity - Google Patents

The maximum allowable current-carrying capacity probabilistic forecasting method and device of transmission line of electricity Download PDF

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Publication number
CN107292427A
CN107292427A CN201710422586.4A CN201710422586A CN107292427A CN 107292427 A CN107292427 A CN 107292427A CN 201710422586 A CN201710422586 A CN 201710422586A CN 107292427 A CN107292427 A CN 107292427A
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China
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mrow
msub
forecast
wind speed
transmission line
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Inventor
叶琳
宣东海
朱炳铨
竺佳
竺佳一
孙维真
李云鹏
龚向阳
马琳
王威
占震滨
赵玉芳
王波
李湘林
肖艳炜
张锋
于钦刚
李红云
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State Grid Zhejiang Electric Power Co Ltd
Ningbo Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Beijing Guowang Fuda Technology Development Co Ltd
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State Grid Zhejiang Electric Power Co Ltd
Ningbo Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Beijing Guowang Fuda Technology Development Co Ltd
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Application filed by State Grid Zhejiang Electric Power Co Ltd, Ningbo Power Supply Co of State Grid Zhejiang Electric Power Co Ltd, Beijing Guowang Fuda Technology Development Co Ltd filed Critical State Grid Zhejiang Electric Power Co Ltd
Priority to CN201710422586.4A priority Critical patent/CN107292427A/en
Publication of CN107292427A publication Critical patent/CN107292427A/en
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    • 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
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • 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 a kind of maximum allowable current-carrying capacity probabilistic forecasting method and device of transmission line of electricity, this method includes：Obtain the probability data of forecast wind speed；The probability data of wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting.The present invention can realize the probabilistic forecasting to the maximum allowable current-carrying capacity of transmission line of electricity based on the probability data of forecast wind speed, existing dynamic compatibilization current-carrying capacity Predicting Technique is solved when predicting maximum allowable current-carrying capacity, do not consider the accuracy of weather forecast to cause the problem of confidence level is not high, practicality is not strong that predict the outcome, the credible result degree that the embodiment of the present invention is predicted is high, practical, can be for regulation and control center reference, in order to prearrange power system operating mode.

Description

The maximum allowable current-carrying capacity probabilistic forecasting method and device of transmission line of electricity
Technical field
The present invention relates to technical field of electric power, more particularly to the maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity and Device.
Background technology
With national economy sustained and rapid development, power load constantly rises.Load area of concentration transmission line of electricity is in electricity consumption Peak period is limited by stability limitation, and ability to transmit electricity bottleneck problem is protruded very much.
According to current design criteria, the permission running temperature of steel-reinforced aluminum conductor is defined as 70 DEG C.Transmission line of electricity stability limitation is According to harsh meteorological condition：Environment temperature take 40 DEG C, wind speed take 0.5m/s, intensity of sunshine 1000W/m2Come what is calculated.And Meteorological condition in actual moving process generally to be preferred over rigor condition.According to pertinent literature, 0.5m/s is compared during wind speed 1.0m/s When current-carrying capacity to increase 15%~20%；Intensity of sunshine 100W/m2When compare 1000W/m2When current-carrying capacity to improve 15%~30%； Such as 10 DEG C of environment temperature reduction, current-carrying capacity will increase by 5%~20%.Dynamic compatibilization technology is exactly not break through current art code Provide on the premise of (wire running temperature), by on-Line Monitor Device, to wire running status (conductor temperature, current-carrying capacity etc.) Monitored in real time with meteorological condition (environment temperature, sunshine, wind speed etc.), while according to real-time calculating, fully excavating environment side The potentiality in face, so as to improve the conveying capacity of transmission line of electricity to greatest extent.Using power transmission line dynamic capacity increase technology, technically Can improve transmission line of electricity maximum allowable current-carrying capacity (can Equivalent Conversion be transmission capacity respective value).
But traffic department controls angularly, it is necessary in some months, several all and several day from the method for operation and stability limitation It is preceding with regard to schedule ahead power system operating mode.And the maximum of weather forecast parameter prediction circuit is utilized in current dynamic compatibilization technology Allow in flow, do not consider the accuracy of weather forecast, so that the practicality that causes to predict the outcome is not high, so, prior When arranging power system operating mode, the conveying capacity of circuit still can not be made full use of, causes the effect of dynamic compatibilization can not be abundant Play.
The content of the invention
The embodiment of the present invention provides a kind of maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity, to improve transmission of electricity The confidence level and practicality of the maximum allowable current-carrying capacity look-ahead result of circuit, to prearrange power system operating mode, the party Method includes：
Obtain the probability data of forecast wind speed；
The probability data of wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting.
In one embodiment, the probability data of the forecast wind speed includes：Forecast the accuracy rate of wind speed, partially strong rate and on the weak side Rate.
In one embodiment, the probability-distribution function of the forecast wind speed is as follows：
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind Power graded forecast accuracy rate；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k The corresponding minimum windspeed of level wind-force；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum of k-1 grades of wind-force Wind speed；vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k The corresponding maximum wind velocity of+light breeze power.
In one embodiment, the probability data of the wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity is carried out Probabilistic forecasting, including：
The wind speed of the setting elevation of forecast is scaled the wind speed at transmission line of electricity terrain clearance Z, Z is the liftoff height of wire Degree；
According to the probability data of the wind speed at transmission line of electricity terrain clearance Z, current-carrying capacity maximum allowable to transmission line of electricity is carried out Probabilistic forecasting.
In one embodiment, the probability data of the wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity is carried out Probabilistic forecasting, including：
V ' corresponding with A is determined as follows：
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I is that transmission line of electricity maximum permits Perhaps current-carrying capacity；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed； V is forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value；
According to v ' corresponding with A, I ' is determined.
The embodiment of the present invention also provides a kind of transmission line of electricity maximum allowable current-carrying capacity probabilistic forecasting device, defeated to improve The confidence level and practicality of the maximum allowable current-carrying capacity look-ahead result of electric line, should to prearrange power system operating mode Device includes：
Forecast data obtains module, the probability data for obtaining forecast wind speed；
Current-carrying capacity prediction module, for the probability data of wind speed according to weather report, enters to the maximum allowable current-carrying capacity of transmission line of electricity Row probabilistic forecasting.
In one embodiment, the probability data of the forecast wind speed includes：Forecast the accuracy rate of wind speed, partially strong rate and on the weak side Rate.
In one embodiment, the probability-distribution function of the forecast wind speed is as follows：
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind Power graded forecast accuracy rate；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k The corresponding minimum windspeed of level wind-force；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum of k-1 grades of wind-force Wind speed；vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k The corresponding maximum wind velocity of+light breeze power.
In one embodiment, the current-carrying capacity prediction module is further used for：
The wind speed of the setting elevation of forecast is scaled the wind speed at transmission line of electricity terrain clearance Z, Z is the liftoff height of wire Degree；
According to the probability data of the wind speed at transmission line of electricity terrain clearance Z, current-carrying capacity maximum allowable to transmission line of electricity is carried out Probabilistic forecasting.
In one embodiment, the current-carrying capacity prediction module is further used for：
V ' corresponding with A is determined as follows：
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I is that transmission line of electricity maximum permits Perhaps current-carrying capacity；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed； V is forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value；
According to v ' corresponding with A, I ' is determined.
In the embodiment of the present invention, the probability data of forecast wind speed is obtained；The probability data of wind speed according to weather report, to power transmission line The maximum allowable current-carrying capacity in road carries out probabilistic forecasting；It can be realized based on the probability data of forecast wind speed and transmission line of electricity maximum is permitted Perhaps the probabilistic forecasting of current-carrying capacity, solves existing dynamic compatibilization current-carrying capacity Predicting Technique when predicting maximum allowable current-carrying capacity, no Consider the accuracy of weather forecast to cause predict the outcome the problem of confidence level is not high, practicality is not strong, the embodiment of the present invention The credible result degree predicted is high, practical, can be for regulation and control center reference, in order to prearrange power system operating mode.
Brief description of the drawings
Technical scheme in order to illustrate the embodiments of the present invention more clearly, makes required in being described below to embodiment Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for For those of ordinary skill in the art, on the premise of not paying creative work, other can also be obtained according to these accompanying drawings Accompanying drawing.In the accompanying drawings：
Fig. 1 is the schematic diagram of the maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity in the embodiment of the present invention；
Fig. 2 is forecast wind velocity distributing paremeter schematic diagram in the embodiment of the present invention；
Fig. 3 saves the maximum allowable current-carrying capacity curve map under each probable value of 500kV transmission lines of electricity for certain in the embodiment of the present invention；
Fig. 4 is the schematic diagram of the maximum allowable current-carrying capacity probabilistic forecasting device of transmission line of electricity in the embodiment of the present invention.
Embodiment
For the purpose, technical scheme and advantage of the embodiment of the present invention are more clearly understood, below in conjunction with the accompanying drawings to this hair Bright embodiment is described in further details.Here, the schematic description and description of the present invention is used to explain the present invention, but simultaneously It is not as a limitation of the invention.
In order to improve the confidence level and practicality of the maximum allowable current-carrying capacity look-ahead result of transmission line of electricity, to pacify in advance Power system operating mode is arranged, the embodiment of the present invention provides a kind of maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity, such as Fig. 1 Shown, this method includes：
Step 101, the probability data for obtaining forecast wind speed；
The probability data of step 102, according to weather report wind speed, current-carrying capacity maximum allowable to transmission line of electricity carries out probability pre- Survey.
Flow is it is known that the maximum allowable current-carrying capacity probabilistic forecasting of the transmission line of electricity of the embodiment of the present invention as shown in Figure 1 Method has merged probability weather forecast data and power transmission line dynamic capacity increase technology, according to probabilistic weather forecast data pair The maximum allowable current-carrying capacity of transmission line of electricity carries out probabilistic forecasting, can improve the practicality and confidence level predicted the outcome, and electric power is adjusted Degree department, which refers to predict the outcome, comes prior reasonable arrangement power system operating mode and scheduling controlling, makes full use of transmission line of electricity to convey Ability.
When it is implemented, first obtaining the probability data of forecast wind speed.In one embodiment, the probability data of wind speed is forecast It can include：Forecast accuracy rate, partially strong rate and the rate on the weak side of wind speed.Forecast wind speed is a kind of probability forecast, can long-time statistical Obtain forecasting accuracy rate, partially strong rate and the rate on the weak side of wind speed.For forecast wind speed, inventor considers：Wind scale refers to basis The grade that wind is made to ground object contributions degree, for representing the size of wind speed.Conventional Beaufort scale from zero to 12 have divided ten Three Estates, chinese national standard altogether《GB/T 28591-2012 wind scales》Defined wind scale by Zero to ten seven have divided 18 grades altogether.The wind scale span of forecast is not more than 2 grades.Weather monitoring station layout compared with For intensive urban area, on the basis of wind scale forecast, the wind speed forecasting by 3h in following 24h is also directly given, with The air speed value of determination is represented.Due under strong wind weather, wind scale forecast accuracy about 40%~60%, and forecast rate on the weak side More than partially strong rate is forecast, therefore：
Assuming that in the case of wind scale k forecast accurately, wind speed is uniformly distributed in the corresponding wind speed interval of k grades of wind-force, Its probability density is p (v)=fkc/(vk_max-vk_min),v∈[vk_min,vk_max], as shown in Fig. 2 being designated as p in Fig. 2c；Work as wind-force When graded forecast is partially strong, wind speed is uniformly distributed in the corresponding wind speed interval of low one-level (k-1 grades) wind-force, and its probability density is p (v)=fks/(vk-1_max-vk-1_min),v∈[vk-1_min,vk-1_max], p is designated as in Fig. 2s；When wind scale forecast is on the weak side, wind Speed is uniformly distributed in the corresponding wind speed interval of high one-level (k+1 grades) wind-force, its probability density p (v)=fkw/(vk+1_max- vk+1_min),v∈[vk+1_min,vk+1_max], p is designated as in Fig. 2w；
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind Power graded forecast accuracy rate；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k The corresponding minimum windspeed of level wind-force；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum of k-1 grades of wind-force Wind speed；vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k The corresponding maximum wind velocity of+light breeze power.
To sum up, the probability density distribution of forecast wind speed is corresponding using the partially strong rate of forecast, forecast accuracy, forecast rate on the weak side Three-level is uniformly distributed expression, as shown in Figure 2.
So, under the k level wind-force of forecast, the probability-distribution function of forecast wind speed is：
And：fks+fkc+fkw=1； (2)
Certainly, above-mentioned formula (1) is an instantiation of the probability-distribution function of forecast wind speed, the probability point of forecast wind speed Cloth function can be with the function formula of other changes, and the present invention is not limited this, and related change case all should fall into the present invention Protection domain.
As described above, in embodiment, proposing to consider the maximum allowable current-carrying capacity of transmission line of electricity of weather forecast probability data Probabilistic forecasting method, based on the prior distribution for the probability data that wind speed is forecast in weather forecast data, respectively using corresponding Probabilistic model come describe forecast wind scale, in this, as the number of the maximum allowable current-carrying capacity probabilistic forecasting of computing electric power line According to basis, can the further maximum allowable current-carrying capacity of look-ahead transmission line of electricity exactly, improve the practicality predicted the outcome, in advance Survey result and be available for center reference, prearrange the method for operation of power network.
In one embodiment, inventor by surface roughness and near-earth SEQUENCING VERTICAL it is considered that in surface layer, stablized The influence of degree, wind speed with altitude significant changes form a vertical wind profile.Therefore, the probability data of wind speed according to weather report, right The maximum allowable current-carrying capacity of transmission line of electricity carries out probabilistic forecasting, can include：The wind speed of the setting elevation of forecast is scaled defeated Wind speed at electric line terrain clearance Z, Z is wire terrain clearance；According to the probability number of the wind speed at transmission line of electricity terrain clearance Z According to current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting, so can further improve transmission line of electricity maximum allowable The precision of prediction of current-carrying capacity.In one embodiment, the wind speed of the setting elevation of forecast, for example, can be the 10m elevations of forecast Wind speed.The wind speed of the 10m elevations of forecast is wherein scaled the wind speed at transmission line of electricity terrain clearance Z, can be used a variety of Mode, for example, can use power exponent Wind outline method, and this method adaptability is more excellent, and conversion formula is as follows：
Wherein, vZFor the wind speed at the obtained transmission line of electricity terrain clearance Z that converts；The calibrated altitude that v provides for weather bureau For the forecast wind speed (m/s) at 10m；Z is wire terrain clearance；z0For wind shear exponent, value is shown in Table 1.
Wind shear exponent value under the different terrain of table 1
In one embodiment, inventor is also contemplated that for the forecast intensity of sunshine in weather forecast data and forecast Environment temperature, wherein, the forecast of temperature is a bound scope in addition to lattice point forecast data, and general forecast all can not The situation of light radiation intensity forecast is provided, determines that following too conservative processing can be taken to arrange during the maximum allowable current-carrying capacity of transmission line of electricity Apply：
Forecasting the environment temperature can use lattice point forecasting the environment temperature data；If without lattice point forecast data, using website The higher limit of forecasting the environment temperature data；
Forecast intensity of sunshine can be determined as follows：
Wherein, QsFor forecast intensity of sunshine；A~G is constant, and its value is as shown in table 2：
The parameter of intensity of sunshine empirical equation under the different air conditionses of table 2
Parameter value Clean air Pollute air
A -42.2391 53.1821
B 63.8044 14.2110
C -1.9220 6.6138×10-1
D 3.46921×10-2 -3.1658×10-2
E -3.61118×10-4 5.4654×10-4
F 1.94318×10-6 -4.3446×10-6
G -4.07608×10-9 1.3236×10-8
HcFor sun altitude；
Hc=arcsin (cos Lat cosδcosω+sin Latsinδ)； (5)
Wherein, LatFor the latitude of transmission line of electricity site；δ is the angle change as caused by seasonal variations；
N is the number of days undergone since the beginning of the year；
ω is the angle of different hours, and 12 points of high noon is 0 °, per hour 15 °.
In one embodiment, if transmission line of electricity each point forecasting the environment temperature or forecast intensity of sunshine are different, take therein Maximum, the parameter in being calculated as the maximum allowable current-carrying capacity prediction of transmission line of electricity.
In one embodiment, transmission line of electricity carrying current calculation is derived by the thermal balance of conductor overheating and radiating, heat Equilibrium equation is：
Wj+Ws=WR+WF； (7)
Wherein, WjThe heating power produced for unit length conductor resistance；WsFor unit length wire sunshine absorbed power； WRFor the heat loss through radiation power of unit length wire；WFFor the heat loss through convection power of unit length wire.
The Morgan equation for calculating current-carrying capacity can be derived according to equation of heat balance, inventor is it is considered that Morgan is public Formula calculating process is complex, is simplified under certain condition, can shorten calculating process, and such as simplified Morgan equation is fitted For when Reynolds number be 100~3000 when, i.e., environment temperature be 40 DEG C, wind speed 0.5m/s, conductor temperature be no more than 120 DEG C When, the carrying current calculation available for diameter 4.2mm~100mm wires.In one embodiment, determined according to weather forecast data Transmission line of electricity current-carrying capacity, can include determining transmission line of electricity current-carrying capacity as follows：
Wherein, I is the maximum allowable current-carrying capacity of transmission line of electricity；θ is the current-carrying temperature rise of wire；V is forecast wind speed；D is wire External diameter；ε is the radiation coefficient of conductive line surfaces；S is Stefan-Bao Erci coefficients；TcFor conductor temperature；T0For forecasting the environment temperature； asFor wire heat absorption coefficient；QsFor forecast intensity of sunshine；ζ, τ are constant；RdFor the D.C. resistance of wire.In embodiment, ζ and τ can To choose different constants according to different wires.
After wire it can be seen from formula (8) is determined, the maximum allowable current-carrying capacity of transmission line of electricity and forecast wind speed, forecasting the environment Temperature, forecast intensity of sunshine are relevant.It is also known that, the maximum allowable current-carrying capacity of transmission line of electricity is most sensitive to wind speed, so The accuracy of measuring wind speed has considerable influence to the maximum allowable carrying current calculation of transmission line of electricity.Therefore as it was previously stated, in embodiment In can introduce wind speed forecasting probability data prior distribution, described using probabilistic model forecast wind speed.
In one embodiment, too conservative treatment measures, forecast day can be taken during the maximum allowable current-carrying capacity of transmission line of electricity Clean air parameter is chosen according to parameter during Strength co-mputation to be calculated, i.e. A=-42.2391；B=63.8044；C=- 1.9220；D=3.46921 × 10-2；E=-3.61118 × 10-4；F=1.94318 × 10-6；G=-4.07608 × 10-9.When After transmission line wire, each shaft tower position are determined, bringing formula (3) into formula (8) can be reduced to：
I=(Av0.485+B)C (9)
Wherein：
When a certain period wind direction forecast wind direction numbering is that f, Wind Speed Forecast grade are k grades, then transmission line of electricity is maximum allowable Current-carrying capacity I is a function on forecasting wind speed v：
I=f (v) v ∈ (vk-1_min,vk+1_max) (10)
By formula (10), the maximum allowable current-carrying capacity of transmission line of electricity is with forecast wind speed monotonic increase, and forecast wind speed v is one Stochastic variable, then the maximum allowable current-carrying capacity I of the period transmission line of electricity be considered as a probability-distribution function.
In one embodiment, if giving the setting value I ' of a maximum allowable current-carrying capacity of transmission line of electricity so that power transmission line The maximum allowable current-carrying capacity I >=I ' in road probability is A, because I is with v monotonic increases, then the probability-distribution function of wind speed according to weather report, Current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting, can include：
V ' corresponding with A is determined as follows：
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I is that transmission line of electricity maximum permits Perhaps current-carrying capacity；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed； V is forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value.
After the A of a given determination, corresponding v ' can be tried to achieve, according to v ', the maximum allowable current-carrying of transmission line of electricity is determined The setting value I ' of amount, i.e., be transmission line of electricity using v ' as the I brought into formula (8), the formula tried to achieve (8) of the v in formula (8) The setting value I ' of maximum allowable current-carrying capacity.
The method of operation and emergency preplan are arranged for convenience of traffic department, in one embodiment, is provided respectively according to weather report It is respectively 98%, 90% that the probability data of wind speed, which calculates probable value, and the 50% maximum allowable current-carrying capacity of transmission line of electricity is scheduled for Departments' reference.Fig. 3 is the probability data according to forecast wind speed, one day certain province 500kV calculated according to present invention method The maximum allowable current-carrying capacity of transmission line of electricity under each probable value of transmission line of electricity.
Based on same inventive concept, a kind of maximum allowable current-carrying capacity probability of transmission line of electricity is additionally provided in the embodiment of the present invention Property prediction meanss, as described in the following examples.Because the device solves the principle and the maximum allowable current-carrying of transmission line of electricity of problem Measure probabilistic forecasting method similar, therefore the implementation of the device may refer to the maximum allowable current-carrying capacity probabilistic forecasting of transmission line of electricity The implementation of method, repeats part and repeats no more.
Fig. 4 is the schematic diagram of the maximum allowable current-carrying capacity probabilistic forecasting device of transmission line of electricity in the embodiment of the present invention, such as Fig. 4 Shown, the device can include：
Forecast data obtains module 401, the probability data for obtaining forecast wind speed；
Current-carrying capacity prediction module 402, for the probability data of wind speed according to weather report, to the maximum allowable current-carrying capacity of transmission line of electricity Carry out probabilistic forecasting.
In one embodiment, the probability data of the forecast wind speed includes：Forecast the accuracy rate of wind speed, partially strong rate and partially Weak rate.
In one embodiment, the probability-distribution function of forecast wind speed is：
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind Power graded forecast accuracy rate；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k The corresponding minimum windspeed of level wind-force；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum of k-1 grades of wind-force Wind speed；vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k The corresponding maximum wind velocity of+light breeze power.
In one embodiment, current-carrying capacity prediction module 402 can be further used for：
The wind speed of the setting elevation of forecast is scaled the wind speed at transmission line of electricity terrain clearance Z, Z is the liftoff height of wire Degree；
According to the probability data of the wind speed at transmission line of electricity terrain clearance Z, current-carrying capacity maximum allowable to transmission line of electricity is carried out Probabilistic forecasting.
In one embodiment, current-carrying capacity prediction module 402 can be further used for：
V ' corresponding with A is determined as follows：
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I is that transmission line of electricity maximum permits Perhaps current-carrying capacity；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed； V is forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value；
According to v ' corresponding with A, I ' is determined.
The embodiment of the present invention also provides a kind of computer equipment, and the maximum allowable current-carrying capacity of transmission line of electricity is carried to realize Prior probability is predicted, to prearrange power system operating mode, and the computer equipment includes memory, processor and be stored in deposit Realized on reservoir and the computer program that can run on a processor, described in the computing device during computer program above-mentioned The maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity.
The embodiment of the present invention also provides a kind of computer-readable recording medium, to realize carry maximum allowable to transmission line of electricity The probabilistic forecasting in advance of flow, to prearrange power system operating mode, the computer-readable recording medium storage has execution The computer program of the maximum allowable current-carrying capacity probabilistic forecasting method of above-mentioned transmission line of electricity.
In summary, in the embodiment of the present invention, the probability data of forecast wind speed is obtained；The probability number of wind speed according to weather report According to current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting；It can be realized based on the probability data of forecast wind speed to defeated The probabilistic forecasting of the maximum allowable current-carrying capacity of electric line, solves existing dynamic compatibilization current-carrying capacity Predicting Technique maximum allowable in prediction During current-carrying capacity, the accuracy of weather forecast is not considered to cause the problem of confidence level is not high, practicality is not strong that predict the outcome, this The credible result degree that inventive embodiments are predicted is high, practical, can be for regulation and control center reference, in order to prearrange power network The method of operation.
It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program Product.Therefore, the present invention can be using the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware Apply the form of example.Moreover, the present invention can be used in one or more computers for wherein including computer usable program code The computer program production that usable storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.) The form of product.
The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product Figure and/or block diagram are described.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided The processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which is produced, to be included referring to Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that in meter Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one The step of function of being specified in individual square frame or multiple square frames.
Particular embodiments described above, has been carried out further in detail to the purpose of the present invention, technical scheme and beneficial effect Describe in detail it is bright, should be understood that the foregoing is only the present invention specific embodiment, the guarantor being not intended to limit the present invention Scope is protected, within the spirit and principles of the invention, any modification, equivalent substitution and improvements done etc. should be included in this Within the protection domain of invention.

Claims (10)

1. a kind of maximum allowable current-carrying capacity probabilistic forecasting method of transmission line of electricity, it is characterised in that including：
Obtain the probability data of forecast wind speed；
The probability data of wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity carries out probabilistic forecasting.
2. the method as described in claim 1, it is characterised in that the probability data of the forecast wind speed includes：Forecast wind speed Accuracy rate, partially strong rate and rate on the weak side.
3. method as claimed in claim 2, it is characterised in that the probability-distribution function of the forecast wind speed is as follows：
<mrow> <mi>p</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>s</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>c</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>w</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>;</mo> </mrow>
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind-force etc. Level forecast accuracy；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k grades of wind The corresponding minimum windspeed of power；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum windspeed of k-1 grades of wind-force； vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k+1 grades The corresponding maximum wind velocity of wind-force.
4. the method as described in claim 1, it is characterised in that the probability data of the wind speed according to weather report, to transmission line of electricity Maximum allowable current-carrying capacity carries out probabilistic forecasting, including：
The wind speed of the setting elevation of forecast is scaled the wind speed at transmission line of electricity terrain clearance Z, Z is wire terrain clearance；
According to the probability data of the wind speed at transmission line of electricity terrain clearance Z, current-carrying capacity maximum allowable to transmission line of electricity carries out probability Property prediction.
5. the method as described in any one of Claims 1-4, it is characterised in that the probability data of the wind speed according to weather report, right The maximum allowable current-carrying capacity of transmission line of electricity carries out probabilistic forecasting, including：
V ' corresponding with A is determined as follows：
<mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>I</mi> <mo>&amp;GreaterEqual;</mo> <msup> <mi>I</mi> <mo>&amp;prime;</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <mi>P</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>&amp;GreaterEqual;</mo> <msup> <mi>v</mi> <mo>&amp;prime;</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <msubsup> <mo>&amp;Integral;</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> </mrow> </msub> <msup> <mi>v</mi> <mo>&amp;prime;</mo> </msup> </msubsup> <mi>p</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mi>d</mi> <mi>v</mi> <mo>=</mo> <mi>A</mi> <mo>;</mo> </mrow>
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I, which is that transmission line of electricity is maximum allowable, to be carried Flow；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed；V is Forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value；
According to v ' corresponding with A, I ' is determined.
6. a kind of maximum allowable current-carrying capacity probabilistic forecasting device of transmission line of electricity, it is characterised in that including：
Forecast data obtains module, the probability data for obtaining forecast wind speed；
Current-carrying capacity prediction module, for the probability data of wind speed according to weather report, current-carrying capacity maximum allowable to transmission line of electricity carries out general Forthright prediction.
7. device as claimed in claim 6, it is characterised in that the probability data of the forecast wind speed includes：Forecast wind speed Accuracy rate, partially strong rate and rate on the weak side.
8. device as claimed in claim 7, it is characterised in that the probability-distribution function of the forecast wind speed is as follows：
<mrow> <mi>p</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>s</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>c</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mfrac> <msub> <mi>f</mi> <mrow> <mi>k</mi> <mi>w</mi> </mrow> </msub> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> </mrow> </msub> </mrow> </mfrac> </mtd> <mtd> <mrow> <mi>v</mi> <mo>&amp;Element;</mo> <mrow> <mo>&amp;lsqb;</mo> <mrow> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>min</mi> <mo>,</mo> </mrow> </msub> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>+</mo> <mn>1</mn> <mo>_</mo> <mi>max</mi> </mrow> </msub> </mrow> <mo>&amp;rsqb;</mo> </mrow> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>;</mo> </mrow>
Wherein, p (v) is the probability-distribution function of forecast wind speed；V is forecast wind speed；fks+fkc+fkw=1；fksFor k grades of wind-force etc. Level forecast accuracy；fkcPartially strong rate is forecast for k grades of wind scales；fkwRate on the weak side is forecast for k grades of wind scales；vk_minFor k grades of wind The corresponding minimum windspeed of power；vk_maxFor the corresponding maximum wind velocity of k grades of wind-force；vk-1_minFor the corresponding minimum windspeed of k-1 grades of wind-force； vk-1_maxFor the corresponding maximum wind velocity of k-1 grades of wind-force；vk+1_minFor the corresponding minimum windspeed of k+1 grades of wind-force；vk+1_maxFor k+1 grades The corresponding maximum wind velocity of wind-force.
9. device as claimed in claim 6, it is characterised in that the current-carrying capacity prediction module is further used for：
The wind speed of the setting elevation of forecast is scaled the wind speed at transmission line of electricity terrain clearance Z, Z is wire terrain clearance；
According to the probability data of the wind speed at transmission line of electricity terrain clearance Z, current-carrying capacity maximum allowable to transmission line of electricity carries out probability Property prediction.
10. the device as described in any one of claim 6 to 9, it is characterised in that the current-carrying capacity prediction module is further used In：
V ' corresponding with A is determined as follows：
<mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>I</mi> <mo>&amp;GreaterEqual;</mo> <msup> <mi>I</mi> <mo>&amp;prime;</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <mi>P</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>&amp;GreaterEqual;</mo> <msup> <mi>v</mi> <mo>&amp;prime;</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>-</mo> <msubsup> <mo>&amp;Integral;</mo> <msub> <mi>v</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>_</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> <msup> <mi>v</mi> <mo>&amp;prime;</mo> </msup> </msubsup> <mi>p</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mi>d</mi> <mi>v</mi> <mo>=</mo> <mi>A</mi> <mo>;</mo> </mrow>
Wherein, P (I ＞ I ') is the probability that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I '；I, which is that transmission line of electricity is maximum allowable, to be carried Flow；I ' is the setting value of the maximum allowable current-carrying capacity of transmission line of electricity；P (v ＞ v ') is not less than v ' probability for forecast wind speed；V is Forecast wind speed；V ' is so that the maximum allowable current-carrying capacity of transmission line of electricity is not less than I ' minimum windspeed；A is probable value；
According to v ' corresponding with A, I ' is determined.
CN201710422586.4A 2017-06-07 2017-06-07 The maximum allowable current-carrying capacity probabilistic forecasting method and device of transmission line of electricity Pending CN107292427A (en)

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Application publication date: 20171024