CN105896538A - Modeling method for auxiliarypower load correction model based on measured data - Google Patents

Abstract

The invention discloses a modeling method of an auxiliary power load correction model based on measured data. The method is characterized by comprising the following steps of 1) determining a main auxiliary power medium-voltage load of a thermal power plant; 2) determining a relation between an important load and a working condition of a unit in a boiler system; 3) determining load characteristics of a medium-voltage auxiliary machine of a steam turbine system under different outputs of the unit; 4) proposing an auxiliary power static correction load model based on the auxiliary power load characteristics and simultaneously considering voltage and frequency static characteristics of an auxiliary power load; and 5) completing unknown parameters in the auxiliary power load correction model by applying a least square method on the basis of actual data of the power plant. The method has the beneficial effects that the relation between the auxiliary power load and the operation condition of the generator unit is researched on the basis of actual operation data of the power plant, the static correction model of the auxiliary power load is built according to the relation, and the deviation between a traditional auxiliary power load model result and actual data can be effectively solved; and the auxiliary power load correction model has certain reasonableness and very high precision and is of great significance to calculation of an actual power grid.

Description

A kind of station service load correction model modeling method based on measured data

Technical field

The invention belongs to load modeling technical field, particularly relate to the modeling of a kind of station service load correction model based on measured data Method.

Background technology

Along with constantly expanding of system scale constantly occurs with Novel electric equipment, the dynamic characteristic of load also becomes to become increasingly complex. Optimistic or conservative load model is used will power grid security or economical operation to be adversely affected.1996 North America blackout are exactly Cause simulation result the most optimistic owing to research worker have employed more conservative load model, cause a field loss load 30GW Serious accident.The levels of precision of load model is to the short circuit current of power system, little interference, transient stability and voltage stabilization etc. Calculate and HVDC dynamic characteristics suffers from material impact.

Traditional load modeling method mainly has two kinds: Component Based and Measurement-based approach.Along with load scale and the expansion of kind Greatly, Component Based efficiency and precision are the highest, the most less employing.Load is considered as an entirety by Measurement-based approach, based on reality Survey data and utilize modern control theory and identification algorithm to determine the known variables in load model.At present in achievement in research, conventional Some load modeling methods the most only consider the pass between the active power of load and reactive power and the voltage of system and frequency System, have ignored the other influences factor of load power.

Summary of the invention

The present invention is directed to the problem that prior art exists, it is provided that a kind of station service load correction model based on measured data is built Mould method, the static modification model set up can effectively solve the deviation of tradition station service load model result and real data, essence Du Genggao, reasonability is higher, and the calculating to actual electric network is significant.

The technical solution adopted in the present invention is, a kind of station service load correction model modeling method based on measured data, including such as Lower step:

Step 1) establish thermal power plant station service in press load composition, including steam generator system load and turbine system load, its Middle steam generator system load includes that the load of blower fan and coal pulverizer, turbine system load include the load of middle pressure subsidiary engine；

Step 2) establish the relation of the load in steam generator system and unit operating mode, i.e. research blower fan and coal pulverizer is gained merit with unit The fluctuation tendency exerted oneself；

Step 3) establish the middle pressure subsidiary engine of the turbine system part throttle characteristics when different unit output；

Step 4) there is proportional relationship according to meritorious the exerting oneself of the station service payload including blower fan, coal pulverizer and unit, And the voltage of station service load and static frequency characteristic, set up the static modification load model of station service；

Step 5) obtain active power unknown in station service static modification load model according to measured data by method of least square Gain merit the relevant parameter exerted oneself with reactive power and unit.

Further, described step 4) in set up the static modification load model of station service specific as follows:

Commonly using electric load model based on tradition, to set up station service load correction model as follows:

$\left\{\begin{array}{c}P=P_N{P_G}^{\mathrm{\α}}{U}^{0.08}(1+2.9\mathrm{\Δ}f)\\ Q=Q_N{P_G}^{\mathrm{\β}}{U}^{1.6}(1+1.8\mathrm{\Δ}f)\end{array}\right.---\left(2\right)$

Wherein, P and Q is respectively active power and the reactive power of station service load, P_NAnd Q_NIt is respectively the volume of station service load Determine active power and reactive power, P_G ^αAnd P_G ^βRepresent that the active power of station service load and reactive power gain merit with unit respectively The correlation coefficient of power, the active power of α and β respectively station service load and reactive power and unit are gained merit the index of correlation exerted oneself, U is the voltage perunit value of station service bus, and Δ f is the perunit value of frequency departure.

Further, described step 5) obtain station service static modification load model according to measured data by method of least square The active power of middle the unknown and reactive power and unit gain merit the relevant parameter exerted oneself particularly as follows:

Formula (2) correction model is converted and can obtain:

$\left\{\begin{array}{c}\ln P={\mathrm{lnP}}_N+{\mathrm{\αlnP}}_G+0.08\ln U+\ln \left(1+2.9\mathrm{\Δ}f\right)\\ \ln Q={\mathrm{lnQ}}_N+{\mathrm{\βlnP}}_G+1.6\ln U+\ln \left(1+1.8\mathrm{\Δ}f\right)\end{array}\right.---\left(3\right)$

Order

y₁=lnP, a₀=lnP_N,x₁=lnP_G,x₂=lnU, x₃=ln (1+2.9 Δ f), y₂=lnQ, b₀=lnQ_N,

x₄=ln (1+1.8 Δ f), then (3) formula can transform to:

$\left\{\begin{array}{c}{y}_1=a_0+{\mathrm{\αx}}_1+0.08x_2+x_3\\ y_2=b_0+{\mathrm{\βx}}_1+1.6x_2+x_4\end{array}\right.---\left(4\right)$

Recycling method of least square carries out parameter estimation and can be described as:

$\left\{\begin{array}{c}\underset{a_0,\mathrm{\α}}{{\mathrm{minJ}}_1}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_1-a_0-{\mathrm{\αx}}_1-0.08x_2-x_3\right)}^2\\ \underset{b_0,\mathrm{\β}}{{\mathrm{minJ}}_2}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_2-b_0-{\mathrm{\βx}}_1-1.6x_2-x_4\right)}^2\end{array}\right.---\left(5\right)$

Utilize extremum conditions:

$\frac{\∂J_1}{\∂a_0}=\frac{\∂J_1}{\∂\mathrm{\α}}=\frac{\∂J_2}{\∂b_0}=\frac{\∂J_2}{\∂\mathrm{\β}}=0---\left(6\right)$

Parameter a is tried to achieve by formula (5)₀,α,b₀, the value of β, α and β is respectively the active power of station service load and idle merit Rate and unit are gained merit the index of correlation exerted oneself, a₀And b₀It is respectively the most right of the specified active power of station service load and reactive power Number.

The invention has the beneficial effects as follows: the static modification model set up by the present invention can effectively solve tradition station service load mould Type result and the deviation of real data, precision is higher, and reasonability is higher, and the calculating to actual electric network is significant.

Accompanying drawing explanation

The flow chart of Fig. 1 present invention；

The part throttle characteristics figure of Fig. 2 primary air fan and pressure fan；

Fig. 3 coal pulverizer part throttle characteristics figure；

Fig. 4 is water circulating pump part throttle characteristics figure；

Fig. 5 is station service burden with power and unit is gained merit the graph of a relation exerted oneself；

Fig. 6 is station service load or burden without work and unit is gained merit the graph of a relation exerted oneself.

Detailed description of the invention

Now technical scheme is described in further detail.

As shown in figs 1 to 6, a kind of station service load correction model modeling method based on measured data of the present invention, step 1) Establish and the main station service of thermal power plant is pressed load: more than the 70% of the power consumption Zhan Quan factory of steam generator system and steamer system, wherein Peak load in steam generator system is blower fan and coal pulverizer, and the main loads in steamer system is middle pressure subsidiary engine, in middle pressure subsidiary engine relatively Big load is water circulating pump, solidifying pump and closed cold pump；

Step 2) establish the relation of the important load in steam generator system and unit operating mode.Load maximum in steam generator system is blower fan, Blower fan includes primary air fan, pressure fan and air-introduced machine.Needed for the payload of primary air fan, pressure fan and air-introduced machine and unit Air required for coal dust amount, burning, the exhaust gas volumn of generation have directly association.As a example by certain million unit, different units When exerting oneself, the part throttle characteristics of primary air fan and pressure fan is as shown in Figure 2.Primary air fan and pressure fan load and unit are gained merit and are exerted oneself Fluctuation tendency is consistent.But unit is gained merit, the fluctuation exerted oneself lags behind the fluctuation of primary air fan and pressure fan, i.e. receives dispatch command After, primary air fan and pressure fan can first adjust, and unit output just can meet dispatch command after needing a period of time.

Except blower fan, coal pulverizer is also the important load in steam generator system, and its size depends on the quantity of coal dust needed for boiler, with The operating condition of unit is directly related.As a example by million units, during different unit output, coal pulverizer part throttle characteristics is as shown in Figure 3. Similar to blower fan, coal pulverizer load is completely the same with the fluctuation tendency of unit output, and the fluctuation of unit output lags behind coal pulverizer The fluctuation of load.

Step 3) establish the middle pressure subsidiary engine of the steam turbine system part throttle characteristics when different unit output.Mainly bearing in steam turbine system Lotus is middle pressure subsidiary engine, and middle pressure subsidiary engine is mainly water circulating pump, solidifying pump and closed cold pump, and its payload is the most unrelated with unit operating mode, Fluctuate the least.As a example by million units, during different unit output, water circulating pump part throttle characteristics is as shown in Figure 4.Water circulating pump load Fluctuation range is the least, and it doesn't matter for the size exerted oneself of gaining merit with unit, it is believed that is constant load.

Step 4) set up the static modification load model of station service.

Tradition station service Static Load model is as follows:

$\left\{\begin{array}{c}P=P_N{U}^{0.08}(1+2.9\mathrm{\Δ}f)\\ Q=P_{N}tan\left(\arccos 0.8\right)U^{1.6}(1+1.8\mathrm{\Δ}f)\end{array}\right.---\left(1\right)$

In formula: P and Q is respectively active power and the reactive power of station service load, P_NAnd Q_NIt is respectively the volume of station service load Determining active power and reactive power, U is the voltage perunit value of station service bus, and Δ f is the perunit value of frequency departure.

From step 2) and step 3), the size of the station service loads such as primary air fan, pressure fan, air-introduced machine and coal pulverizer with The steam turbine system loadings such as meritorious the exerting oneself of unit exists directly proportional relation, water circulating pump are constant loads.Therefore, station service load Can represent by power function with the relation of unit output, simultaneously take account of voltage and the static frequency characteristic of station service load, base In formula (1), station service load correction model is proposed as follows:

$\left\{\begin{array}{c}P=P_N{P_G}^{\mathrm{\α}}{U}^{0.08}(1+2.9\mathrm{\Δ}f)\\ Q=Q_N{P_G}^{\mathrm{\β}}{U}^{1.6}(1+1.8\mathrm{\Δ}f)\end{array}\right.---\left(2\right)$

In above formula, P_G ^αAnd P_G ^βRepresent that the active power of station service load and reactive power and unit are gained merit the phase relation exerted oneself respectively Number, wherein, P_GFor the perunit value of unit output, for measured data, α and β is respectively active power and the nothing of station service load Merit power and unit are gained merit the index of correlation exerted oneself.

Step 5) improve the unknown parameter in station service load correction model.

In formula (14), the active power of α and β respectively station service load and reactive power are gained merit to unit the relevant finger exerted oneself Number, needs to utilize measured data identification to obtain.Additionally, due to Service Power in Thermal Power Plant load is in large scale, it is impossible to count station-service The specified active-power P of electric load_NWith rated reactive power Q_N.Therefore, the specified active-power P of station service load_NWith specified nothing Merit power Q_NIt is also required to utilize measured data identification to obtain.

The present invention uses the unknown parameter in least squares identification station service load correction model, and concrete grammar is as follows:

Correction model is converted and can obtain:

$\left\{\begin{array}{c}\ln P={\mathrm{lnP}}_N+{\mathrm{\αlnP}}_G+0.08\ln U+\ln \left(1+2.9\mathrm{\Δ}f\right)\\ \ln Q={\mathrm{lnQ}}_N+{\mathrm{\βlnP}}_G+1.6\ln U+\ln \left(1+1.8\mathrm{\Δ}f\right)\end{array}\right.---\left(3\right)$

Order

y₁=lnP, a₀=lnP_N,x₁=lnP_G,x₂=lnU, x₃=ln (1+2.9 Δ f), y₂=lnQ, b₀=lnQ_N,x₄=ln (1+1.8 Δ f), then (3) formula can transform to:

$\left\{\begin{array}{c}{y}_1=a_0+{\mathrm{\αx}}_1+0.08x_2+x_3\\ y_2=b_0+{\mathrm{\βx}}_1+1.6x_2+x_4\end{array}\right.---\left(4\right)$

Utilize linear least square to carry out parameter estimation can be described as:

$\left\{\begin{array}{c}\underset{a_0,\mathrm{\α}}{{\mathrm{minJ}}_1}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_1-a_0-{\mathrm{\αx}}_1-0.08x_2-x_3\right)}^2\\ \underset{b_0,\mathrm{\β}}{{\mathrm{minJ}}_2}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_2-b_0-{\mathrm{\βx}}_1-1.6x_2-x_4\right)}^2\end{array}\right.---\left(5\right)$

Utilize extremum conditions:

$\frac{\∂J_1}{\∂a_0}=\frac{\∂J_1}{\∂\mathrm{\α}}=\frac{\∂J_2}{\∂b_0}=\frac{\∂J_2}{\∂\mathrm{\β}}=0---\left(6\right)$

Utilize equation group can try to achieve parameter a₀,α,b₀, the value of β.Wherein, α and β is respectively the active power of station service load Gain merit the index of correlation exerted oneself with reactive power and unit, a₀And b₀It is respectively the specified active power of station service load and reactive power Natural logrithm, J₁、J₂By the model set up and the deviation of real data.

Extract 100 groups of data from the measured data in certain power plant in June, 2015, utilize method of least square to join according to formula (2) It is as follows that number identification can get station service load model:

$\left\{\begin{array}{c}P=30840{P_G}^{0.51}{U}^{0.08}(1+2.9\mathrm{\Δ}f)\\ Q=24740{P_G}^{0.37}{U}^{1.6}(1+1.8\mathrm{\Δ}f)\end{array}\right.---\left(7\right)$

Fig. 5 and Fig. 6 is respectively the contrast of formula (7) and measured data, by Fig. 5 and Fig. 6 experimental result it can be seen that this The bright load model result global error related to is less, and mean error is all less than 3%.

The result obtained, as the training set of neutral net, is repaiied by the 100 groups of data used by method of least square with station service load Positive model contrasts, and result is as shown in table 1:

1 two kinds of model error contrasts of table

As known from Table 1, correction model and the neural network model result of station service load are closer to, with real data deviation relatively Little, mean error is respectively 2.17% and 1.70%.The above results shows, the station service that station service load correction model is assumed is born Lotus and generating set meritorious has certain reasonability in power function relationship between exerting oneself.

With the above-mentioned desirable embodiment according to the present invention for enlightenment, by above-mentioned description, relevant staff is the most permissible In the range of without departing from this invention technological thought, carry out various change and amendment.The technical scope of this invention is also The content being not limited in description, it is necessary to determine its technical scope according to right.

Claims (3)

1. a station service load correction model modeling method based on measured data, it is characterised in that comprise the following steps:

Step 1) establish thermal power plant station service in press load composition, including steam generator system load and turbine system load, its Middle steam generator system load includes that the load of blower fan and coal pulverizer, turbine system load include the load of middle pressure subsidiary engine；

Step 2) establish the relation of the load in steam generator system and unit operating mode, i.e. research blower fan and coal pulverizer is gained merit with unit The fluctuation tendency exerted oneself；

Step 3) establish the middle pressure subsidiary engine of the turbine system part throttle characteristics when different unit output；

Step 4) there is proportional relationship according to meritorious the exerting oneself of the station service payload including blower fan, coal pulverizer and unit, And the voltage of station service load and static frequency characteristic, set up the static modification load model of station service；

Step 5) obtain active power unknown in station service static modification load model according to measured data by method of least square Gain merit the relevant parameter exerted oneself with reactive power and unit.

A kind of station service load correction model modeling method based on measured data the most according to claim 1, its feature exists In, described step 4) in set up the static modification load model of station service specific as follows:

Commonly using electric load model based on tradition, to set up station service load correction model as follows:

$\left\{\begin{array}{c}P=P_N{P_G}^{\mathrm{\α}}{U}^{0.08}(1+2.9\mathrm{\Δ}f)\\ Q=Q_N{P_G}^{\mathrm{\β}}{U}^{1.6}(1+1.8\mathrm{\Δ}f)\end{array}\right.---\left(2\right)$

Wherein, P and Q is respectively active power and the reactive power of station service load, P_NAnd Q_NIt is respectively the volume of station service load Determine active power and reactive power, P_G ^αAnd P_G ^βRepresent that the active power of station service load and reactive power gain merit with unit respectively The correlation coefficient of power, the active power of α and β respectively station service load and reactive power and unit are gained merit the index of correlation exerted oneself, U is the voltage perunit value of station service bus, and Δ f is the perunit value of frequency departure.

A kind of station service load correction model modeling method based on measured data the most according to claim 2, its feature exists In, described step 5) obtain unknown gaining merit in station service static modification load model according to measured data by method of least square Power and reactive power and unit gain merit the relevant parameter exerted oneself particularly as follows:

Formula (2) correction model is converted and can obtain:

$\left\{\begin{array}{c}\ln P={\mathrm{lnP}}_N+{\mathrm{\αlnP}}_G+0.08\ln U+\ln \left(1+2.9\mathrm{\Δ}f\right)\\ \ln Q={\mathrm{lnQ}}_N+{\mathrm{\βlnP}}_G+1.6\ln U+\ln \left(1+1.8\mathrm{\Δ}f\right)\end{array}\right.---\left(3\right)$

Order

y₁=lnP, a₀=lnP_N,x₁=lnP_G,x₂=lnU, x₃=ln (1+2.9 Δ f), y₂=lnQ, b₀=lnQ_N,

x₄=ln (1+1.8 Δ f), then (3) formula can transform to:

$\left\{\begin{array}{c}{y}_1=a_0+{\mathrm{\αx}}_1+0.08x_2+x_3\\ y_2=b_0+{\mathrm{\βx}}_1+1.6x_2+x_4\end{array}\right.---\left(4\right)$

Recycling method of least square carries out parameter estimation and can be described as:

$\left\{\begin{array}{c}\underset{a_0,\mathrm{\α}}{{\mathrm{minJ}}_1}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_1-a_0-{\mathrm{\αx}}_1-0.08x_2-x_3\right)}^2\\ \underset{b_0,\mathrm{\β}}{{\mathrm{minJ}}_2}=\underset{i=1}{\overset{l}{\mathrm{\Σ}}}{\left(y_2-b_0-{\mathrm{\βx}}_1-1.6x_2-x_4\right)}^2\end{array}\right.---\left(5\right)$

Utilize extremum conditions:

$\frac{\∂J_1}{\∂a_0}=\frac{\∂J_1}{\∂\mathrm{\α}}=\frac{\∂J_2}{\∂b_0}=\frac{\∂J_2}{\∂\mathrm{\β}}=0---\left(6\right)$

Parameter a is tried to achieve by formula (5)₀,α,b₀, the value of β；

Wherein, the active power of α and β respectively station service load and reactive power and unit are gained merit the index of correlation exerted oneself, a₀And b₀It is respectively the specified active power of station service load and the natural logrithm of reactive power.