CN103093104B - Based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow - Google Patents

Abstract

The present invention relates to electric system Transmission Expansion Planning in Electric field, for the following net capacity nargin of auxiliary Electric Power Network Planning human assessment, the identification of discrimination system weak link and unreasonable grid structure, the reliability balancing power network planning scheme and economy etc., the technical scheme that the present invention takes is, based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow, comprise the steps: step 1): defined declaration is carried out to utilization rate of electric transmission line: step 2): set up following N load probabilistic distribution model and generator stoppage in transit probability model; Step 3): generate random load and the random shut down condition of generator; Step 4): minimum with each genset gross capability cost is economic dispatch objective function, meets constraint condition simultaneously; Step 5): by DC power flow or AC power flow method computational scheme trend value; Step 6): record circuit emulates the Line Flow value obtained at every turn.The present invention is mainly used in electric system Transmission Expansion Planning in Electric.

Description

Based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow

Technical field

The present invention relates to electric system Transmission Expansion Planning in Electric field, specifically, relate to the utilization rate of electric transmission line computing method based on Probabilistic Load Flow.

Background technology

The quality evaluating power network planning scheme mainly depends on the design of assessment indicator system, and evaluation index plays an important role in the process.Transmission Expansion Planning in Electric evaluation index mainly comprises three major types: reliability index, economic index and dirigibility index ^[1-4], but the utilization power of transmission line of electricity is seldom considered in existing research.And utilization rate of electric transmission line can reflect planning circuit load level and spare condition, again can the reliability of assessed form and economy, preferably significant to intensive transformation by extensive style to power network planning scheme, therefore carry out correlative study significant.

At present, started to explore power transmission capacity of pow nargin abroad and carried out indirect analysis circuit and utilize level, main thought portrays by available transfer capability (AvailableTransferCapability, ATC) index and analyze ^[5,6,7].But ATC, also can by the impact of the factors such as electricity transaction in electricity market situation mainly for assessment of transmittability between the stability of transmission system and net ^[8], be difficult to the utilization power of science reflection Electric Power Network Planning circuit.Domestic in power transmission network assessment and the planning field power network line utilization ratio evaluation criterion that nothing is ripe temporarily, usually adopt the indexs such as annual peak load utilization factor, maximum load rate and Rate of average load to weigh circuit capacity nargin and actual motion level ^[9,10].These indexs are added up by electrical network historical data mostly, and future plan electrical network relates to a large amount of uncertain factor, as out of service in the uncertainty of Mid-long term load forecasting, the change of generator output plan, equipment failure etc., and future plan system does not have available statistical data, these indexs are made also to be difficult to be suitable for the analysis and assessment to following Electric Power Network Planning.

Probabilistic Load Flow (ProbabilisticLoadFlow, PLF) now obtains comparatively widespread use in Electric Power Network Planning field, and method mainly contains Monte Carlo simulation approach, convolution method, the Cumulant Method Using etc. in conjunction with Gram-Charlier progression ^[11,12,13].PLF method is that science considers that the various uncertain factor of electric system provides effective means, also for the utilization factor of further analysis circuit provides possibility.

List of references/works:

[1] Jiang Guozhen. the research [D] of Electric Power Network Planning System of Comprehensive Evaluation and method. Hubei: the Central China University of Science and Technology, 2009.

[2] Gao Yan, Kang Chongqing, Zhong Jin, etc. the Economic Value Evaluation of reliability and decision-making [J] in generation transmission expansion. Proceedings of the CSEE, 2007,27 (25): 56-60.

[3] Zhao Junguang, Tang Henghai, Wu Qifu. the research of economy assessment method for electric power gird planning and software simulating [J]. east china electric power, 2009,37 (2): 222-225.

[4] Jinhua is levied, Cheng Haozhong, Yang Xiaomei, etc. based on the Flexible planning method [J] of connection number model. Proceedings of the CSEE, 2006,26 (12): 16-20.

[5]AvailableTransferCapabilityDefinitionandDetermination.Availabletransfercapabilitydefinitionanddetermination：areferencedocumentpreparedbyTTCtaskforce[R].NewJersey：NorthAmericanElectricReliabilityCouncil，1996.

[6]HamoudG.Assessmentofavailabletransfercapabilityoftransmissionsystems[J].IEEETransonPowerSystems，2000，15(1)：27-32.

[7]LuoX，PattonAD，SinghC.Realpowertransfercapabilitycalculationsusingmulti-layerfeed-forwardneuralnetworks[J].IEEETransonPowerSystems，2000，15(2)：903-908.

[8] Cui Yali, not towards red, Wang Xifan. the research [J] of transmission system transmission capacity available. Electric Power Automation Equipment, 2003,23 (4): 70-75.

[9] Han Liu, Zhuan Bo, Wang Zhidong, etc. electrical network utilization ratio index study [J]. east china electric power, 2011,39 (6): 850-854.

[10] Peng's winter, Gao Yi, Wang Zhidong, etc. power transmission network utilization ratio evaluation study [J]. electrical applications, 2012,31 (13): 24-27.

[11] fourth is bright, Li Shenghu, Huang Kai. based on the probabilistic load flow [J] of Monte Carlo simulation. and electric power network technique, 2001,25 (11): 10-14.

[12]AllanRN，LeiteDaSilvaAM，BurchettRCEvaluationMethodsandAccuracyinProbabilisticLoadFlowSolutions[J].IEEETransonPowerApparatusandSystems，1981，100(5)：2539-2546.

[13]PeiZhang，LeeST.ProbabilisticloadflowcomputationusingthemethodofcombinedcumulantsandGram-Charlierexpansion[J].IEEETransonPowerSystems，2004，19(1)：676-682.

Summary of the invention

The present invention is intended to overcome the deficiencies in the prior art, take into full account following load probabilistic distribution, genset stoppage in transit probability and economic load dispatching distribute uncertain factors such as exerting oneself, a kind of power transmission line utilization factor computing method are proposed, the method result of calculation can objectively respond following circuit and utilize level, the following net capacity nargin of Electric Power Network Planning human assessment can be assisted, the identification of discrimination system weak link and unreasonable grid structure, the reliability of balance power network planning scheme and economy etc., for achieving the above object, the technical scheme that the present invention takes is, based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow, comprise the steps:

Step 1): defined declaration is carried out to following N utilization rate of electric transmission line:

" following N each hour conveying electricity total value accounts for theoretical limit and carry the ratio of electricity " is selected to reflect the average utilization power of following power network line, namely the probability distribution function of the through-put power of following N circuit is adopted to represent the distribution situation of following line transmission electricity, wherein N represents year planning horizon, and following N utilization rate of electric transmission line computing formula is as follows:

$I=\frac{\∫f\left(S\right)\mathrm{dS}}{C}---\left(1\right)$

In formula, I is following N utilization rate of electric transmission line, S is the applied power that circuit flows through, probable value corresponding when f (S) is for following N circuit occurring applied power S, C is the rated capacity of this circuit, for the circuit that there is two-way charge transport in probation, molecule should be through-put power numerical value sum;

Step 2): set up following N load probabilistic distribution model and generator stoppage in transit probability model;

Step 3): carry out Monte-Carlo step according to load probabilistic distribution and generator stoppage in transit probability distribution, generate random load and the random shut down condition of generator;

Step 4): according to system total load value, system total network loss value and each generator shut down condition, carry out the optimization of genset economic dispatch, minimum with each genset gross capability cost is economic dispatch objective function, meets constraint condition simultaneously;

Step 5): exert oneself according to each load value and each genset, by DC power flow or AC power flow method computational scheme trend value;

Step 6): record circuit emulates the Line Flow value obtained at every turn, obtains the probability distribution function of through-put power, utilizes the nominal transmission capability value computing electric power line utilization factor of formula (1) and circuit.

In step 2) in,

Set up following N load probabilistic distribution model specifically to comprise the steps:

1), Electric Power Network Planning personnel are predicted by total load, estimate the load peak of annual system loading point in following N: P _peak1, P _peak2..., P _peakN, wherein P _peak1, P _peak2, P _peakNrepresent the load peak of following 1st year, following 2nd year and following this load point of N respectively, subscript peak represents the implication of maximal value;

2), according to this area's history equivalence year based model for load duration curve (LoadDurationCurve, LDC) load peak in curve data and each prediction year, make the LDC curve in each prediction year, obtain the LDC curve of following N according to the time power load distributing in each prediction year;

3), to the LDC curve of following N analyze, get minimum load P in curve _minwith peak load P _max, by interval [P _min, P _max] being divided equally into M sub-range, M represents sub-range sum, and represents by its load in section intermediate value: P _int1, P _int2..., P _intM, wherein P _int1, P _int2, P _intMrepresent the 1st respectively, 2, the load intermediate value in a M sub-range, subscript int represents the implication in interval; The time that load drops on each sub-range is respectively: T _int1, T _int2..., T _intM, wherein T _int1, T _int2, T _intMrepresent respectively load drop on the 1st, 2, time in a M sub-range, then the power load distributing Probability p in a kth sub-range _kcan be expressed as:

$p_k=\frac{T_{\mathrm{intk}}}{8760\×N}$ k＝1，2，3，...，M(2a)

$\underset{k=1}{\overset{M}{\mathrm{\Σ}}}{p}_k=1---\left(2b\right)$

Wherein, k represents that sub-range is numbered, T _intkrepresent that load drops on the time in a kth sub-range.

Set up following N generator outage model:

Suppose that generator exists two states: (1) maintenance or fault cause shut down condition; (2) normal operating condition, its probability distribution function meets Two-point distribution, and the forced outage rate according to unit is sampled to its random state.

In step 4) in,

Economic dispatch objective function:

$\min F=\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}(a_m\×{P_m}^2+b_m\×P_m+c_m)---\left(3\right)$

In formula, F represents generator output total cost, and be the quadratic function of generator active power, m represents that generator is numbered, N _grepresent systems generate electricity unit number, P _mrepresent m platform generator active power of output, a _m, b _m, c _mit is the cost coefficient of m platform generator;

Economic dispatch constraint condition:

1) power-balance constraint condition

$\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}{P}_m=P_{\mathrm{LOAD}}+P_{\mathrm{LOSS}}---\left(4\right)$

In formula, P _lOADthe total load of expression system, subscript LOAD represents the implication of load, P _lOSStotal network loss of expression system, subscript LOSS represents the implication of network loss;

2) generating set power bound condition:

$P_m^{\min }\≤P_m\≤P_m^{\max }---\left(5\right)$

In formula, P _m ^minand P _m ^maxbe respectively m platform generator active power minimum value and maximal value.

In step 4) in, the quadratic function that generator output cost adopts the cubic function of active power or consideration to comprise valve point effect calculates.

In step 4) in, system total network loss value adopts and obtains as the evaluation method of the total network loss value of system by the K% of system total load value, and wherein K% represents estimation coefficient.

Technical characterstic of the present invention and effect:

The utilization rate of electric transmission line index proposed by the present invention, truly can reflect the capacity utilization power of following circuit, and can be used for searching the identification of network system weak link and unreasonable grid structure.Under following power network line meets the condition of reliability in hypothesis, utilize this index also can carry out the economic analysis of following power network planning scheme, for Electric Power Network Planning personnel choose programme, calculate the economic indexs such as investment return period time foundation is provided.The computing method that the present invention proposes adopt Monte-Carlo Simulation algorithm, take into full account the uncertainty of following electrical network, as load forecasting model, genset stoppage in transit probability and economic dispatch are exerted oneself, compare plant factor index traditional at present, more can the following electrical network utilization power of accurate evaluation, especially for the newly-built transmission line of electricity not having historical data in following electrical network, estimate line efficiency index by analogue simulation, for Electric Power Network Planning personnel provide data foundation, there is very strong practical value.

Accompanying drawing explanation

Fig. 1 utilization rate of electric transmission line algorithm flow chart

Fig. 2 respectively predicts the LDC curve in year.

The LDC curve of the following N of Fig. 3.

Fig. 4 is NewEngland39 node system, as the example system of research.

Fig. 5 is the coming 10 years load probabilistic distribution based on history equivalence LDC curve of example system 4 node.

Fig. 6 is meritorious the exert oneself situation of example system 31 node generator after economic dispatch.

Fig. 7 is the probability distribution of example system line 02-03 transmission power.

Embodiment

Following transmission line of electricity capacity utilizes level not have suitable index to reflect at present, available transfer capability index is larger by electric power transactions impact, and the indexs such as peak load utilization factor, maximum load rate and Rate of average load are all based on historical data, following circuit utilization power can not be estimated.The present invention proposes utilization rate of electric transmission line index concept, and set up a kind of probability load flow calculation method based on Monte-Carlo Simulation algorithm and calculate this index.The method adopts probabilistic load flow model, take into full account that following load probabilistic distribution, genset stoppage in transit probability and economic load dispatching distribute uncertain factors such as exerting oneself, result of calculation can objectively respond following circuit and utilize level, can assist the following net capacity nargin of Electric Power Network Planning human assessment, the identification of discrimination system weak link and unreasonable grid structure, the reliability balancing power network planning scheme and economy etc.

The present invention proposes utilization rate of electric transmission line index, be used for reflecting the capacity utilization power of following transmission line of electricity, and take into full account the uncertainty of following electrical network, establish a set of probability load flow calculation method based on Monte-Carlo Simulation and calculate this index, Fig. 1 is utilization rate of electric transmission line index calculating method process flow diagram, and concrete steps are as follows:

Step 1: defined declaration is carried out to the utilization rate of electric transmission line of following N.

" following N each hour conveying electricity total value accounts for theoretical limit and carry the ratio of electricity " is selected to reflect the average utilization power of following power network line, due to the transmission electricity of following circuit cannot be measured, the probability distribution function of the through-put power of following N circuit is adopted to represent the distribution situation of following line transmission electricity, wherein N represents year planning horizon, and following N utilization rate of electric transmission line computing formula is as follows:

$I=\frac{\∫f\left(S\right)\mathrm{dS}}{C}---\left(1\right)$

In formula, I is following N utilization rate of electric transmission line, and S is the applied power that circuit flows through, and probable value corresponding when f (S) is for following N circuit occurring applied power S, C is the rated capacity of this circuit.For the circuit that there is two-way charge transport in probation, molecule should be through-put power numerical value sum;

Step 2: set up following N load probabilistic distribution model and generator stoppage in transit probability model.

Following N load probabilistic distribution model is based on year based model for load duration curve (LoadDurationCurve, LDC), and computation model is as follows:

Electric Power Network Planning personnel predicted by total load, estimates the load peak of annual system loading point in following N: P _peak1, P _peak2..., P _peakN.Wherein P _peak1, P _peak2, P _peakNrepresent the load peak of this load point of the 1st year future, following 2nd year and following N respectively, subscript peak represents the implication of maximal value.

According to this area's history equivalence LDC curve data and the load peak in each prediction year, make the LDC curve in each prediction year, obtain the time power load distributing of prediction year (8760 hours), as shown in Figure 2, represent the LDC curve in following each prediction year.

By institute in following N sometimes load value (8760 × N hour) carry out statistical study, draw out the LDC curve of following N, as Fig. 3 shows, load is at interval [P _c1, P _c2] between hourage be (T _c2-T _c1).Wherein, P _c1, P _c2represent two load values on LDC curve, subscript C represents the implication of curve, T _c1represent that on LDC curve, load is P _c1time corresponding accumulation hourage, T _c2represent that on LDC curve, load is P _c2time corresponding accumulation hourage.

The LDC curve of following N is analyzed, gets minimum load P in curve _minwith peak load P _max, by interval [P _min, P _max] be divided equally into M sub-range (M represents sub-range sum), and represent by its load in section intermediate value: P _int1, P _int2..., P _intM, wherein P _int1, P _int2, P _intMrepresent the 1st respectively, 2, the load intermediate value in a M sub-range, subscript int represents the implication in interval.The time that load drops on each sub-range is respectively: Tint1, T _int2..., T _intM, wherein T _int1, T _int2, T _intMrepresent respectively load drop on the 1st, 2, time in a M sub-range, then the power load distributing Probability p in a kth sub-range _kcan be expressed as:

$p_k=\frac{T_{\mathrm{intk}}}{8760\×N}$ k＝1，2，3，...，M(2a)

$\underset{k=1}{\overset{M}{\mathrm{\Σ}}}{p}_k=1---\left(2b\right)$

Wherein, k represents that sub-range is numbered, T _intkrepresent that load drops on the time in a kth sub-range, subscript int represents interval implication, p _krepresent the power load distributing probability in a kth sub-range.

Generator outage model:

Suppose that generator exists two states: (1) maintenance or fault cause shut down condition; (2) normal operating condition.Its probability distribution function meets Two-point distribution, and the forced outage rate according to unit is sampled to its random state.

Step 3: carry out Monte-Carlo step according to load probabilistic distribution and generator stoppage in transit probability distribution, generates random load and the random shut down condition of generator.

Step 4: according to system total load value, system total network loss value and each generator shut down condition, carry out the optimization of genset economic dispatch, minimum for objective function with each genset gross capability cost, meet constraint condition simultaneously.And adopt the K% pressing total load value as the evaluation method of the total network loss value of system, wherein K% is estimation coefficient, can obtain from actual motion department of Utilities Electric Co..Generator output cost can be thought of as the quadratic function of active power, cubic function or comprise the quadratic function of valve point effect.

Step 5: exert oneself according to each load value and each genset, by DC power flow or AC power flow method computational scheme trend value.

Step 6: record circuit emulates the Line Flow value obtained at every turn, obtains the probability distribution function of through-put power, utilizes the nominal transmission capability value computing electric power line utilization factor of formula (1) and circuit.

The present invention is further illustrated below in conjunction with the drawings and specific embodiments.

A preferred forms of the present invention is provided for NewEngland39 node system (Fig. 4).Suppose that year load growth rate is 5%, the computing method of the utilization factor of power transmission line coming 10 years be described in detail as follows:

Step 1: establish N=10, using formula (1) as example system power line road utilization factor computing formula.

Step 2: the year load peak obtaining coming 10 years according to example system standard year load peak and year load growth rate, according to history equivalence year based model for load duration curve (LoadDurationCurve, LDC), coming 10 years load probabilistic distribution model is set up.Fig. 5 is the coming 10 years load probabilistic distribution based on history equivalence LDC curve of example system 4 node.Generator stoppage in transit probability distribution obeys Two-point distribution, and the forced outage rate according to unit is sampled to its random state.

Step 3: carry out Monte-Carlo step according to load probabilistic distribution and generator stoppage in transit probability distribution, generates random load and the random shut down condition of generator.

Step 4: use for reference certain grid company domestic announce network loss situation, in calculating network loss estimation COEFFICIENT K % be taken as 2.0%, the economic dispatch objective function of genset and constraint condition as follows, in this example, generator output cost is the quadratic function of active power.If make numerical results more accurate, generator output cost also can be thought of as the quadratic function that the cubic function of active power or consideration comprise valve point effect.

Economic dispatch objective function:

$\min F=\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}(a_m\×{P_m}^2+b_m\×P_m+c_m)---\left(3\right)$

In formula, F represents generator output total cost, and be the quadratic function of generator active power, m represents that generator is numbered, N _grepresent systems generate electricity unit sum, subscript G represents the implication of generator, P _mrepresent m platform generator active power of output, a _m, b _m, c _mit is the cost coefficient of m platform generator;

Economic dispatch constraint condition:

1) power-balance constraint condition:

$\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}{P}_m=P_{\mathrm{LOAD}}+P_{\mathrm{LOSS}}---\left(4\right)$

In formula, P _lOADthe total load of expression system, subscript LOAD represents the implication of load, P _lOSStotal network loss of expression system, subscript LOSS represents the implication of network loss;

2) generating set power bound condition:

$P_m^{\min }\≤P_m\≤P_m^{\max }---\left(5\right)$

In formula, P _m ^minand P _m ^maxbe respectively m platform generator active power minimum value and maximal value.

Fig. 6 is meritorious the exert oneself situation of example system 31 node generator after economic dispatch.

Step 5: this example system adopts the AC power flow based on Newton-Laphson algorithm to carry out Load flow calculation, and Fig. 7 is the probability distribution situation of example system line 02-03 through-put power.

Step 6: record circuit emulates the Line Flow value obtained at every turn, obtain the probability distribution function of through-put power, utilize the nominal transmission capability value computing electric power line utilization factor of formula (1) and circuit, result of calculation is as shown in table 1.

The each bar line efficiency of table 1 coming 10 years system

Tab.1Iofeachlineduring10forecastingyears

As can be seen from result of calculation, the computing method that the present invention proposes can the utilization factor index of effective computing system circuit, and utilization factor index can reflect weak link and the irrational mix layout of system:

Weak link: the utilization factor of circuit 02-03 is 77.84%, the probability that there is overload is higher, especially, when the All other routes of connected node 2 or node 3 break down, any power flow transfer all may cause circuit 02-03 to transship, and needs to pay close attention in later stage planning construction.

Unreasonable rack: the utilization factor of circuit 11-12 is 6.83%, the utilization factor of circuit 12-13 is 7.54%, equal to 10%.Observing system connection layout can be found out, two circuits are node 12 place load and power, but the utilization factor of two passages is all lower, and the grid structure of illustrative system may design unreasonable.Therefore, if scheme is not yet finally determined, can by being improved the waste avoiding construction fund to programme.

In addition, under the following power network line of hypothesis meets the condition of reliability, utilize this index also can assist Electric Power Network Planning personnel decision rule scheme economy, calculate economic indexs such as investing return period.

Claims (4)

1., based on utilization rate of electric transmission line computing method for Probabilistic Load Flow, it is characterized in that, comprise the steps:

Step 1): defined declaration is carried out to following N utilization rate of electric transmission line:

" following N each hour conveying electricity total value accounts for theoretical limit and carry the ratio of electricity " is selected to reflect the average utilization power of following power network line, namely the probability distribution function of the through-put power of following N circuit is adopted to represent the distribution situation of following line transmission electricity, wherein N represents year planning horizon, and following N utilization rate of electric transmission line computing formula is as follows:

$I=\frac{\∫f\left(S\right)ds}{C}---\left(1\right)$

In formula, I is following N utilization rate of electric transmission line, S is the applied power that circuit flows through, probable value corresponding when f (S) is for following N circuit occurring applied power S, C is the rated capacity of this circuit, for the circuit that there is two-way charge transport in probation, molecule should be through-put power numerical value sum;

Step 2): set up following N load probabilistic distribution model and generator stoppage in transit probability model;

Step 3): carry out Monte-Carlo step according to load probabilistic distribution and generator stoppage in transit probability distribution, generate random load and the random shut down condition of generator;

Step 4): according to system total load value, system total network loss value and each generator shut down condition, carry out the optimization of genset economic dispatch, minimum with each genset gross capability cost is economic dispatch objective function, meets constraint condition simultaneously;

Step 5): exert oneself according to each load value and each genset, by DC power flow or AC power flow method computational scheme trend value;

Step 6): record circuit emulates the Line Flow value obtained at every turn, obtains the probability distribution function of through-put power, utilizes the nominal transmission capability value computing electric power line utilization factor of formula (1) and circuit;

In step 2) in, set up following N load probabilistic distribution model and specifically comprise the steps:

1), Electric Power Network Planning personnel are predicted by total load, estimate the load peak of annual system loading point in following N: P _peak1, P _peak2..., P _peakN, wherein P _peak1, P _peak2, P _peakNrepresent the load peak of following 1st year, following 2nd year and following this load point of N respectively, subscript peak represents the implication of maximal value;

2), according to this electrical network covering area history equivalence year based model for load duration curve (LoadDurationCurve, LDC) load peak in curve data and each prediction year, make the LDC curve in each prediction year, obtain the LDC curve of following N according to the time power load distributing in each prediction year;

3), to the LDC curve of following N analyze, get minimum load P in curve _minwith peak load P _max, by interval [P _min, P _max] being divided equally into M sub-range, M represents sub-range sum, and represents by its load in section intermediate value: P _int1, P _int2..., P _intM, wherein P _int1, P _int2, P _intMrepresent the 1st respectively, 2, the load intermediate value in a M sub-range, subscript int represents the implication in interval; The time that load drops on each sub-range is respectively: T _int1, T _int2..., T _intM, wherein T _int1, T _int2, T _intMrepresent respectively load drop on the 1st, 2, time in a M sub-range, then the power load distributing Probability p in a kth sub-range _kcan be expressed as:

$p_k=\frac{T_{\mathrm{int}k}}{8760\×N},k=1,2,3,...,M---\left(2a\right)$

$\underset{k=1}{\overset{M}{\Σ}}{p}_k=1---\left(2b\right)$

Wherein, k represents that sub-range is numbered, T _intkrepresent that load drops on the time in a kth sub-range;

Set up following N generator outage model:

Suppose that generator exists two states: (1) maintenance or fault cause shut down condition; (2) normal operating condition, its probability distribution function meets Two-point distribution, and the forced outage rate according to unit is sampled to its random state.

2., as claimed in claim 1 based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow, it is characterized in that: in step 4) in,

Economic dispatch objective function:

$\min F=\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}(a_m\×{P_m}^2+b_m\×P_m+c_m)---\left(3\right)$

In formula, F represents generator output total cost, and be the quadratic function of generator active power, m represents that generator is numbered, N _grepresent systems generate electricity unit number, P _mrepresent m platform generator active power of output, a _m, b _m, c _mit is the cost coefficient of m platform generator;

Economic dispatch constraint condition:

1) power-balance constraint condition

$\underset{m=1}{\overset{N_G}{\mathrm{\Σ}}}{P}_m=P_{LOAD}+P_{LOSS}---\left(4\right)$

In formula, P _lOADthe total load of expression system, subscript LOAD represents the implication of load, P _lOSStotal network loss of expression system, subscript LOSS represents the implication of network loss;

2) generating set power bound condition:

$P_m^{min}\≤P_m\≤P_m^{max}---\left(5\right)$

In formula, P _m ^minand P _m ^maxbe respectively m platform generator active power minimum value and maximal value.

3., as claimed in claim 1 based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow, it is characterized in that: in step 4) in, the quadratic function that generator output cost adopts the cubic function of active power or consideration to comprise valve point effect calculates.

4. as claimed in claim 1 based on the utilization rate of electric transmission line computing method of Probabilistic Load Flow, it is characterized in that: in step 4) in, system total network loss value adopts and obtains as the evaluation method of the total network loss value of system by the K% of system total load value, and wherein K% represents estimation coefficient.