CN105634016A - Smooth output method for combined power generation system of wind farm group and thermal power plant - Google Patents

Abstract

The present invention provides a smooth output method for a combined power generation system of a wind farm group and a thermal power plant, comprising the steps of: acquiring a data set consisting of a wind power generation power predicted value of each wind farm in the wind farm group, and adding all the wind power generation power predicted values in the data sets corresponding to the all wind farms to obtain a comprehensive data set consisting of total power generation power of the wind farm group; fitting the comprehensive data set through a polynomial fitting algorithm to obtain a wind power smooth output formula, and calculating a wind power smooth output value; calculating the sum of the wind power smooth output value and a standard output value of the thermal power plant, so as to obtain a total smooth output value; and determining the actual output conditions of the wind farm group and the thermal power plant according to the total smooth output value, the total power generation power of the wind farm group, and the minimum output value, the maximum output value and the standard output value of the thermal power plant. According to the smooth output method of the present invention, the obtained smooth output curve does not delay, and low energy consumption, little pollution, and stable electric energy output can be ensured.

Description

A kind of smooth method of exerting oneself of wind farm group and thermal power plant combined generating system

Technical field

The present invention relates to technical field of electric power, in particular it relates to a kind of smooth method of exerting oneself of wind farm group and thermal power plant combined generating system.

Background technology

Thermal power generation is the generation mode that most important, technology is the most ripe at present, and current thermal power generation still occupies very big ratio in China's power field, but thermal power generation exists the shortcomings such as energy consumption is high, seriously polluted.

In recent years, the renewable and clean energy resources such as wind energy are more and more is applied to power field, wind farm group and thermal power plant combined generating system are a kind of electricity generation systems combining wind-power electricity generation and thermal power generation, this electricity generation system increases the proportion of wind power supply when wind energy resources abundance, give full play to that wind generating technology energy consumption is low, pollute little advantage, when wind energy resources is sufficient not, thermal power generation is utilized to meet the needs of operation of power networks. Fig. 1 is the structural representation of wind farm group and thermal power plant combined generating system, and multiple wind energy turbine set access public electric wire net with a thermal power plant.

Wind energy resources also exists the problem of randomness and undulatory property, causes that the power of wind-power electricity generation has undulatory property, it is provided that just steady not to the electric energy of electrical network, affects the even running of electrical network. In order to reduce this impact, it is necessary to wind-power electricity generation is carried out power and stabilizes, to reduce the power swing impact on electrical network.

Northeast Electric Power University's aerospace, Yan Gangui et al. utilize first-order low-pass ripple algorithm to realize the control strategy that wind power fluctuation is stabilized. The operating high fdrequency component of wind energy turbine set is mainly filtered by this control strategy, reduce the rate of change of wind power, thering is provided relatively stable power output for power system, energy-storage system is then the amplitude being changed output by its discharge and recharge, and the electric energy making injection electrical network is more steady. But practical application finding, this output smoothing curve utilizing first-order low-pass ripple algorithm to obtain exists certain time-lag action, as shown in Figure 2, thinner line is the independent power curve of wind-powered electricity generation, thicker line is the smooth power curve of wind storage utilizing this control strategy to obtain, as ise apparent from FIG. 2, the smooth power curve of wind storage lags behind the independent power curve of wind-powered electricity generation. This is because this, to utilize first-order low-pass ripple algorithm to realize the wind power control strategy stabilized of fluctuation be adopt this sampled value to be weighted obtaining this filtering output value with filtering output value last time, and concrete formula is:

Y (n)=�� X (n)+(1-��) Y (n-1)

In above formula, �� is filter factor; X (n) is this sampled value; Y (n-1) is filtering output value last time; Y (n) is this filtering output value.

Visible, this utilize first-order low-pass ripple algorithm to realize the wind power control strategy stabilized of fluctuation to there is also weak point.

Summary of the invention

The main purpose of the embodiment of the present invention is in that to provide a kind of smooth method of exerting oneself of wind farm group and thermal power plant combined generating system, utilizes first-order low-pass ripple algorithm to stabilize wind power to fluctuate the problem that obtained output smoothing curve exists time delay phenomenon solving prior art.

To achieve these goals, the embodiment of the present invention provides a kind of smooth method of exerting oneself of wind farm group and thermal power plant combined generating system, including:

Step A, for each wind energy turbine set in wind farm group, obtain the data acquisition system being made up of the Wind power forecasting value of this wind energy turbine set, the Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set is added, obtains the synthetic data set being made up of the total generated output of wind farm group;

Step B, utilizes fitting of a polynomial algorithm that described synthetic data set is fitted, and obtains the smooth formula of exerting oneself of wind-powered electricity generation, and smooths out force value according to the smooth formula calculating wind-powered electricity generation of exerting oneself of described wind-powered electricity generation;

Step C, calculates described wind-powered electricity generation and smooths out force value and thermal power plant benchmark and go out force value sum, always smoothed out force value;

Step D, according to described always smoothing out force value, the total generated output of described wind farm group and thermal power plant minimum load value, EIAJ value, benchmark go out force value, it is determined that the actual situation of exerting oneself in wind farm group and thermal power plant;

Described step A particularly as follows:

Step A1, for each wind energy turbine set in wind farm group, obtains the data acquisition system P being made up of the Wind power forecasting value of this wind energy turbine set_j:

P_j={ (p_ji,t_i) | j=1,2..., k; I=1,2..., m}

Step A2, is added the Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set, obtains the synthetic data set P being made up of the total generated output of wind farm group:

P={ (p_i,t_i) | i=1,2..., m}

$p_i=\underset{j=1}{\overset{k}{\mathrm{\Σ}}}{p}_{\mathrm{ji}}$

Wherein, k is the wind energy turbine set sum in wind farm group, and j is wind energy turbine set serial number, and m is the number of samples of data acquisition system corresponding to each wind energy turbine set, described synthetic data set, and i is sample sequence number, P_jFor the data acquisition system that jth wind energy turbine set is corresponding, p_jiFor the Wind power forecasting value of jth wind energy turbine set, P is synthetic data set, p_iFor the total generated output of wind farm group, t_iFor p_ji��p_iThe corresponding time;

Described step B specifically includes:

Step B1, according to the total generated output p of wind farm group in described synthetic data set P_iFluctuation tendency, it is determined that described wind-powered electricity generation smooths the exponent number n of formula of exerting oneself, and wherein n is natural number;

Step B2, matching has the multinomial of described exponent number n:

a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀;

Wherein, a₀��a_nFor multinomial coefficient;

Step B3, calculates described multinomial a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀Generated output p total with described wind farm group_iSquared difference and Err:

$\mathrm{Err}=\underset{i=0}{\overset{m}{\mathrm{\Σ}}}{(a_n{t_i}^n+a_{n-1}{t_i}^{n-1}+\·\·\·+a_1{t}_i+a_0-p_i)}^2;$

Step B4, when utilizing method of least square to calculate described squared difference and Err for minima, multinomial coefficient a₀��a_nCorresponding occurrence ��₀����_n;

Step B5, utilizes described occurrence ��₀����_nBuild smooth formula X (t) of exerting oneself of wind-powered electricity generation:

X (t)=��_ntⁿ+��_n-1t^n-1+��+��₁t+��₀;

Wherein, t is the time;

Step B6, calculates and works as t=t_iTime, the value of smooth formula X (t) of exerting oneself of described wind-powered electricity generation:

X(t_i)=��_nt_i ⁿ+��_n-1t_i ^n-1+��+��₁t_i+��₀

Wherein, X (t_i) smooth out force value for wind-powered electricity generation;

Described step C particularly as follows:

Calculate wind-powered electricity generation and smooth out force value X (t_i) go out force value sum with thermal power plant benchmark, always smoothed out force value:

Y(t_i)=X (t_i)+P_default

Wherein, Y (t_i) for always to smooth out force value, P_defaultForce value is gone out for thermal power plant benchmark;

Described step D specifically includes:

Step D1, calculates and described always smooths out force value Y (t_i) and the total generated output p of wind farm group_iDifference DELTA p_i:

��p_i=Y (t_i)-p_i;

Step D2, makes wind farm group according to the total generated output p of described wind farm group_iExert oneself;

Step D3, if described difference DELTA p_iLess than or equal to thermal power plant minimum load value P_minTime, make thermal power plant according to its minimum load value P_minExert oneself; If described difference DELTA p_iMore than or equal to thermal power plant EIAJ value P_maxTime, make thermal power plant according to its EIAJ value P_maxExert oneself; If described difference DELTA p_iMore than thermal power plant minimum load value P_minAnd less than thermal power plant EIAJ value P_maxTime, make thermal power plant according to described difference DELTA p_iExert oneself.

By means of technique scheme, the present invention carries out fitting of a polynomial by the total generated output of wind farm group in interval that whole plan is exerted oneself, the smooth power curve finally given will not delayed time delay, compared to the method utilizing first-order low-pass wave method to stabilize light thermo-power station power swing, the present invention has the smooth effect of exerting oneself more optimized, simultaneously, the present invention is added together as entirety to control the actual situation of exerting oneself of cogeneration using wind farm group carries out the result that power swing stabilizes with exerting oneself of thermal power plant, low to guarantee whole system power consumption, pollute few, and the electric energy that is supplied to electrical network is steady.

Accompanying drawing explanation

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below the accompanying drawing used required during embodiment is described is briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the premise not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.

Fig. 1 is the wind farm group structural representation with thermal power plant combined generating system of background of invention offer;

Fig. 2 be background of invention provide utilize first-order low-pass ripple algorithm carry out wind-powered electricity generation fluctuation stabilize before and after power curve contrast schematic diagram;

Fig. 3 is the smooth method flow schematic diagram of exerting oneself of wind farm group provided by the invention and thermal power plant combined generating system;

Fig. 4 is smooth front and back power curve contrast schematic diagram of exerting oneself provided by the invention.

Detailed description of the invention

Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only a part of embodiment of the present invention, rather than whole embodiments. Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of protection of the invention.

The present invention provides a kind of smooth method of exerting oneself of wind farm group and thermal power plant combined generating system, as it is shown on figure 3, the method includes:

Step S1, for each wind energy turbine set in wind farm group, obtain the data acquisition system being made up of the Wind power forecasting value of this wind energy turbine set, Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set is added, obtains the synthetic data set being made up of the total generated output of wind farm group.

Step S2, utilizes fitting of a polynomial algorithm that synthetic data set is fitted, and obtains the smooth formula of exerting oneself of wind-powered electricity generation, and smooths out force value according to the smooth formula calculating wind-powered electricity generation of exerting oneself of wind-powered electricity generation.

Step S3, calculating wind-powered electricity generation smooths out force value and goes out force value sum with thermal power plant benchmark, is always smoothed out force value.

Step S4, according to always smoothing out force value, the total generated output of wind farm group and thermal power plant minimum load value, EIAJ value, benchmark go out force value, it is determined that the actual situation of exerting oneself in thermal power plant.

With formula form, the detailed process of said method is illustrated below:

Step S1 specifically includes following two steps:

Step S11, for each wind energy turbine set in wind farm group, obtains the data acquisition system P being made up of the Wind power forecasting value of this wind energy turbine set_j:

P_j={ (p_ji,t_i) | j=1,2..., k; I=1,2..., m}

This step can obtain Wind power forecasting value from the power prediction system SCADA of each wind energy turbine set, and namely this wind energy turbine set is being planned the interval performance number predicted of individually exerting oneself of exerting oneself by power prediction system SCADA.

Step S12, is added the Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set, obtains the synthetic data set P being made up of the total generated output of wind farm group:

P={ (p_i,t_i) | i=1,2..., m}

$p_i=\underset{j=1}{\overset{k}{\mathrm{\Σ}}}{p}_{\mathrm{ji}}$

Wherein, k is the wind energy turbine set sum in wind farm group, and j is wind energy turbine set serial number, and m is the number of samples of data acquisition system corresponding to each wind energy turbine set, synthetic data set, and i is sample sequence number, P_jFor the data acquisition system that jth wind energy turbine set is corresponding, p_jiFor the Wind power forecasting value of jth wind energy turbine set, P is synthetic data set, p_iFor the total generated output of wind farm group, t_iFor p_ji��p_iThe corresponding time.

Wherein, the total generated output p of wind farm group_iFor t_iThe Wind power forecasting value p of each wind energy turbine set in moment wind farm group_jiSum, synthetic data set P contain whole plan exert oneself interval the total generated output p of wind farm group_i��

It is rapid that step S2 specifically includes following steps:

Step S21, according to the total generated output p of wind farm group in synthetic data set P_iFluctuation tendency, it is determined that wind-powered electricity generation smooths the exponent number n of formula of exerting oneself, and wherein n is natural number.

It is also preferred that the left this step performs according to following concrete steps:

Step S211, according to the total generated output p of wind farm group in synthetic data set P_iFluctuation tendency, it is determined that smooth power curve waveform;

Step S212, according to smooth power curve waveform, it is determined that wind-powered electricity generation smooths the exponent number n of formula of exerting oneself.

Such as, when smooth power curve waveform is straight line, it is determined that wind-powered electricity generation smooths the exponent number n=1 of formula of exerting oneself; When smooth power curve waveform is parabola, it is determined that wind-powered electricity generation smooths the exponent number n=2 of formula of exerting oneself.

Step S22, matching has the multinomial of exponent number n:

a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀;

Wherein, a₀��a_nFor multinomial coefficient.

Step S23, evaluator a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀Generated output p total with wind farm group_iSquared difference and Err:

$\mathrm{Err}=\underset{i=0}{\overset{m}{\mathrm{\Σ}}}{(a_n{t_i}^n+a_{n-1}{t_i}^{n-1}+\·\·\·+a_1{t}_i+a_0-p_i)}^2.$

Step S24, when utilizing method of least square to calculate squared difference and Err for minima, multinomial coefficient a₀��a_nCorresponding occurrence ��₀����_n��

It is also preferred that the left this step is according to calculating in the following way:

Respectively to multinomial coefficient a₀��a_nSeek partial derivative, obtain equation below group:

$\left\{\begin{array}{c}m{a}_0+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t}_i\right)a_1+\·\·\·+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^n\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{p}_i\\ \left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t}_i\right)a_0+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^2\right)a_1+\·\·\·+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^{n+1}\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t}_i{p}_i\\ \·\·\·\\ \·\·\·\\ \·\·\·\\ \left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^n\right)a_0+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^{n+1}\right)a_1+\·\·\·+\left(\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^{2n}\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{t_i}^n{p}_i\end{array}\right.$

Solve above equation group, obtain multinomial coefficient a₀��a_nCorresponding occurrence ��₀����_n��

Step S25, utilizes occurrence ��₀����_nBuild smooth formula X (t) of exerting oneself of wind-powered electricity generation:

X (t)=��_ntⁿ+��_n-1t^n-1+��+��₁t+��₀;

Wherein, t is the time;

Step S26, calculates and works as t=t_iTime, the value of smooth formula X (t) of exerting oneself of wind-powered electricity generation:

X(t_i)=��_nt_i ⁿ+��_n-1t_i ^n-1+��+��₁t_i+��₀

Wherein, X (t_i) smooth out force value for wind-powered electricity generation.

Concrete, this step utilize fitting of a polynomial algorithm whole plan is exerted oneself interval the total generated output data of wind farm group be fitted, obtain smooth go out force value be the result after the power swing to wind farm group is stabilized, due to be not as existing utilize first-order low-pass ripple algorithm adopt adjacent filtering output value to calculate current filtering output value, therefore the present invention obtains smooth power curve (curve that smooth formula of exerting oneself is corresponding) will not delayed time delay, smooth effect optimizes more.

In Fig. 4 dotted line show certain wind farm group whole plan exert oneself interval the total generated output p of wind farm group_iThe curve of composition, utilizes method provided by the invention to obtain smooth power curve shown in solid in Fig. 4 after carrying out smooth exerting oneself, by contrasting it can be seen that smooth exert oneself after the smooth power curve that obtains reduce power swing, and be absent from time delay phenomenon.

Due to present invention research is the combined generating system collectively constituted by wind farm group and thermal power plant, this system should reduce thermal power generation as far as possible and use wind-power electricity generation, to ensure that power consumption is low, it is few to pollute, but the minimum load in thermal power plant can not reduce to zero again, this is accomplished by being added together, with exerting oneself of thermal power plant, the actual situation of exerting oneself controlling cogeneration as entirety using wind farm group carries out the result (smoothing force value) that power swing stabilizes, to guarantee that whole system power consumption is low, it is few to pollute, and the electric energy being supplied to electrical network is steady.

Step S3 particularly as follows:

Calculate wind-powered electricity generation and smooth out force value X (t_i) go out force value sum with thermal power plant benchmark, always smoothed out force value:

Y(t_i)=X (t_i)+P_default

Wherein, Y (t_i) for always to smooth out force value, P_defaultGoing out force value for thermal power plant benchmark, be go out force value under the default situations of thermal power plant, this benchmark goes out force value and can set according to the concrete condition (needing to consider the machine unit characteristic in thermal power plant) in thermal power plant.

Step S4 specifically includes following steps:

Step S41, calculates and always smooths out force value Y (t_i) and the total generated output p of wind farm group_iDifference DELTA p_i:

��p_i=Y (t_i)-p_i;

Step S42, makes wind farm group according to the total generated output p of wind farm group_iExert oneself;

Step S43, if difference DELTA p_iLess than or equal to thermal power plant minimum load value P_minTime, make thermal power plant according to its minimum load value P_minExert oneself;

If difference DELTA p_iMore than or equal to thermal power plant EIAJ value P_maxTime, make thermal power plant according to its EIAJ value P_maxExert oneself;

If difference DELTA p_iMore than thermal power plant minimum load value P_minAnd less than thermal power plant EIAJ value P_maxTime, make thermal power plant according to difference DELTA p_iExert oneself.

In above step, thermal power plant EIAJ value P_maxWith minimum load value P_minIt is the peak power that can export of thermal power plant and minimum power respectively, can set according to the concrete condition (needing to consider the machine unit characteristic in thermal power plant) in thermal power plant. Generally, P_min< P_default< P_max��

It is also preferred that the left thermal power plant minimum load value P_min, EIAJ value P_max, benchmark go out force value P_defaultThere is following relation:

$P_{\mathrm{default}}=\frac{P_{\max }+P_{\min }}{2}.$

Such as, as thermal power plant minimum load value P_min=500MW, EIAJ value P_max=1000MW, benchmark goes out force value P_default=750MW.

By step 4, whole wind farm group and thermal power plant combined generating system will be exerted oneself according to following strategy:

Force value Y (t is smoothed out when always_i) and the total generated output p of wind farm group_iDifference DELTA p_iLess than or equal to thermal power plant minimum load value P_minTime, as long as illustrating that thermal power plant exports electric energy according to its minimum power, add and the electric energy sum of wind farm group output, it is possible to meet and always smooth out force value;

Force value Y (t is smoothed out when always_i) and the total generated output p of wind farm group_iDifference DELTA p_iMore than or equal to thermal power plant EIAJ value P_maxTime, illustrate that thermal power plant needs, according to its maximum power output electric energy, to add and the electric energy sum of wind farm group output, just can substantially meet and always smooth out force value;

Force value Y (t is smoothed out when always_i) and the total generated output p of wind farm group_iDifference DELTA p_iMore than thermal power plant minimum load value P_minAnd less than thermal power plant EIAJ value P_maxTime, illustrate suitably to exert oneself (difference DELTA p in thermal power plant_i), add and the electric energy sum of wind farm group output, can meet and always smooth out force value;

In any of the above situation, wind farm group is all according to the total generated output p of wind farm group_iExerting oneself, namely exert oneself according to its actual peak power that can export, its main cause is: wind-powered electricity generation smooths out force value X (t_i) it is to the total generated output p of wind farm group_iCarrying out fluctuates stabilize after result, X (t_i) and p_iDifference is also little, and always smooths out force value Y (t_i)=X (t_i)+P_default, thermal power plant benchmark goes out force value P_default> 0, therefore, always smooths out force value Y (t_i) always more than the total generated output p of wind farm group_i, in this case, individually can not meet by wind farm group output electric energy (even if exerting oneself according to its actual peak power that can export) and always smooth out force value Y (t_i) requirement, in addition it is also necessary to thermal power plant output electric energy supplements, low based on power consumption, pollute few principle, reduces the ratio of thermal power generation, it is necessary to wind farm group is exerted oneself according to its actual peak power that can export, namely according to the total generated output p of wind farm group as far as possible_iExert oneself.

Particular embodiments described above; the purpose of the present invention, technical scheme and beneficial effect have been further described; it is it should be understood that; the foregoing is only specific embodiments of the invention; the protection domain being not intended to limit the present invention; all within the spirit and principles in the present invention, any amendment of making, equivalent replacement, improvement etc., should be included within protection scope of the present invention.

Claims (6)

1. the smooth method of exerting oneself of a wind farm group and thermal power plant combined generating system, it is characterised in that including:

Step A, for each wind energy turbine set in wind farm group, obtain the data acquisition system being made up of the Wind power forecasting value of this wind energy turbine set, the Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set is added, obtains the synthetic data set being made up of the total generated output of wind farm group;

Step B, utilizes fitting of a polynomial algorithm that described synthetic data set is fitted, and obtains the smooth formula of exerting oneself of wind-powered electricity generation, and smooths out force value according to the smooth formula calculating wind-powered electricity generation of exerting oneself of described wind-powered electricity generation;

Step C, calculates described wind-powered electricity generation and smooths out force value and thermal power plant benchmark and go out force value sum, always smoothed out force value;

Step D, according to described always smoothing out force value, the total generated output of described wind farm group and thermal power plant minimum load value, EIAJ value, benchmark go out force value, it is determined that the actual situation of exerting oneself in wind farm group and thermal power plant;

Described step A particularly as follows:

Step A1, for each wind energy turbine set in wind farm group, obtains the data acquisition system P being made up of the Wind power forecasting value of this wind energy turbine set_j:

P_j={ (p_ji,t_i) | j=1,2..., k; I=1,2..., m}

Step A2, is added the Wind power forecasting value in data acquisition system corresponding for all wind energy turbine set, obtains the synthetic data set P being made up of the total generated output of wind farm group:

P={ (p_i,t_i) | i=1,2..., m}

$p_i=\underset{j=1}{\overset{k}{\mathrm{\&Sigma;}}}{p}_{\mathrm{ji}}$

Wherein, k is the wind energy turbine set sum in wind farm group, and j is wind energy turbine set serial number, and m is the number of samples of data acquisition system corresponding to each wind energy turbine set, described synthetic data set, and i is sample sequence number, P_jFor the data acquisition system that jth wind energy turbine set is corresponding, p_jiFor the Wind power forecasting value of jth wind energy turbine set, P is synthetic data set, p_iFor the total generated output of wind farm group, t_iFor p_ji��p_iThe corresponding time;

Described step B specifically includes:

Step B1, according to the total generated output p of wind farm group in described synthetic data set P_iFluctuation tendency, it is determined that described wind-powered electricity generation smooths the exponent number n of formula of exerting oneself, and wherein n is natural number;

Step B2, matching has the multinomial of described exponent number n:

a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀;

Wherein, a₀��a_nFor multinomial coefficient;

Step B3, calculates described multinomial a_nt_i ⁿ+a_n-1t_i ^n-1+��+a₁t_i+a₀Generated output p total with described wind farm group_iSquared difference and Err:

$\mathrm{Err}=\underset{i=0}{\overset{m}{\mathrm{\&Sigma;}}}{(a_n{t_i}^n+a_{n-1}{t_i}^{n-1}+...+a_1{t}_i+a_0-p_i)}^2;$

Step B4, when utilizing method of least square to calculate described squared difference and Err for minima, multinomial coefficient a₀��a_nCorresponding occurrence ��₀����_n;

Step B5, utilizes described occurrence ��₀����_nBuild smooth formula X (t) of exerting oneself of wind-powered electricity generation:

X (t)=��_ntⁿ+��_n-1t^n-1+��+��₁t+��₀;

Wherein, t is the time;

Step B6, calculates and works as t=t_iTime, the value of smooth formula X (t) of exerting oneself of described wind-powered electricity generation:

X(t_i)=��_nt_i ⁿ+��_n-1t_i ^n-1+��+��₁t_i+��₀

Wherein, X (t_i) smooth out force value for wind-powered electricity generation;

Described step C particularly as follows:

Calculate wind-powered electricity generation and smooth out force value X (t_i) go out force value sum with thermal power plant benchmark, always smoothed out force value:

Y(t_i)=X (t_i)+P_default

Wherein, Y (t_i) for always to smooth out force value, P_defaultForce value is gone out for thermal power plant benchmark;

Described step D specifically includes:

Step D1, calculates and described always smooths out force value Y (t_i) and the total generated output p of wind farm group_iDifference DELTA p_i:

��p_i=Y (t_i)-p_i;

Step D2, makes wind farm group according to the total generated output p of described wind farm group_iExert oneself;

Step D3, if described difference DELTA p_iLess than or equal to thermal power plant minimum load value P_minTime, make thermal power plant according to its minimum load value P_minExert oneself; If described difference DELTA p_iMore than or equal to thermal power plant EIAJ value P_maxTime, make thermal power plant according to its EIAJ value P_maxExert oneself; If described difference DELTA p_iMore than thermal power plant minimum load value P_minAnd less than thermal power plant EIAJ value P_maxTime, make thermal power plant according to described difference DELTA p_iExert oneself.

2. method according to claim 1, it is characterised in that described step B1 specifically includes:

According to the total generated output p of wind farm group in synthetic data set P_iFluctuation tendency, it is determined that smooth power curve waveform;

According to described smooth power curve waveform, it is determined that described wind-powered electricity generation smooths the exponent number n of formula of exerting oneself.

3. method according to claim 2, it is characterised in that when described smooth power curve waveform is straight line, it is determined that described wind-powered electricity generation smooths the exponent number n=1 of formula of exerting oneself.

4. method according to claim 2, it is characterised in that when described smooth power curve waveform is parabola, it is determined that described wind-powered electricity generation smooths the exponent number n=2 of formula of exerting oneself.

5. method according to claim 1, it is characterised in that described step B4 specifically includes:

Respectively to multinomial coefficient a₀��a_nSeek partial derivative, obtain equation below group:

$\left\{\begin{array}{c}{\mathrm{ma}}_0+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t}_i\right)a_1+...+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^n\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{p}_i\\ \left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t}_i\right)a_0+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^2\right)a_1+...+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^{n+1}\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t}_i{p}_i\\ ...\\ ...\\ ...\\ \left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^n\right)a_0+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^{n+1}\right)a_1+...+\left(\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^{2n}\right)a_n=\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{t_i}^n{p}_i\end{array}\right.$

Solve above equation group, obtain multinomial coefficient a₀��a_nCorresponding occurrence ��₀����_n��

6. method according to claim 1, it is characterised in that described thermal power plant minimum load value P_min, EIAJ value P_max, benchmark go out force value P_defaultThere is following relation:

$P_{\mathrm{default}}=\frac{P_{\max }+P_{\min }}{2}.$