CN102075014A - Large grid real-time scheduling method for accepting access of wind power - Google Patents

Abstract

The invention relates to a large grid real-time scheduling method for accepting access of wind power, which belongs to the technical field of power system operation and control. The method comprises: according to the characteristics of wind power and load fluctuation and the control characteristics of generator sets, classifying the generator sets in the whole grid; acquiring the current plan, real-time output, connecting line plan, numerical weather prediction and other related information of each generator set; performing ultrashort period load prediction and wind power output prediction to work out the output regulation amount at next moment of real-time scheduling generator sets and construct an active real-time scheduling model with the smallest wind loss; working out the output regulation amount of the real-time scheduling generator sets including the wind power generator sets by using a simplex method; and transmitting the next output regulation amount of thermal power generator sets directly, and giving the output maximum value at next moment of the wind power generator sets. In the invention, the combined optimized scheduling of the wind power generator sets and traditional generator sets is performed to eliminate wind power generation prediction deviation and load prediction deviation in advance, so the wind power accepting capability of a power grid is improved to the maximum extent while the operation economy of the power grid is guaranteed.

Description

The big real-time power network dispatching method that the wind-powered electricity generation of dissolving inserts

Technical field

The invention belongs to power system operation and control technology field, the big real-time power network dispatching method that particularly a kind of wind-powered electricity generation of dissolving inserts,

Background technology

The influence of factors such as the environmental pollution that causes of tradition fired power generating unit, global warming makes with the wind-powered electricity generation to be that the regenerative resource of representative has obtained large development in recent years.Along with the continuous growth of wind-powered electricity generation proportion, its influence that normal management and running cause to electrical network also becomes more and more important.To comprise that all units of fired power generating unit, Hydropower Unit and wind-powered electricity generation unit claim the whole network unit in the electric power system at present.

Generally comprise several wind energy turbine set in the electrical network at present, many typhoons group of motors is formed a wind energy turbine set.Because inherent characteristics such as randomness that wind-powered electricity generation exists and fluctuation, traditional scheduling mode can't adapt to the dispatching of power netwoks control after large-scale wind power inserts.Traditional scheduler side mainly adopts plan a few days ago to add the pattern of real-time automatic generation control (AGC), mainly there is following problem in this scheduling method: (1) is because wind-powered electricity generation predicts the outcome and often there is very large deviation in actual exerting oneself a few days ago, make plan a few days ago in commission and have very large deviation between the actual conditions, make that the output of wind electric field plan have is too small and cause the bigger windage loss of abandoning to lose, and the excessive generation load deviation of system that causes of the output of wind electric field plan that has widens, and has increased the weight of the burden of AGC unit.(2) because the control ability of AGC unit is limited, and for the guaranteed output balance, the dispatcher has to adjust scheduling strategy according to the amount of unbalance of power, and workload is very big temporarily, and this kind scheduling method makes the fail safe of system and the quality of power supply be difficult to guarantee.(3) owing to the anti-peak regulation characteristic of wind-powered electricity generation, further increased the burden of AGC unit, the problem that AGC regulates the nargin deficiency can often appear, influenced the fail safe and the quality of power supply of system.

Adopt the load prediction system a few days ago that forms by various prediction algorithms that second day system loading is predicted in the current power system.Adopt data acquisition and supervisor control (SCADA) to read value of exerting oneself in real time of all generators of the whole network in real time, control centre in the grid company is responsible for arranging the department of unit output plan, all generating sets all will be exerted oneself it in real time and are reported to the control centre, and generate electricity according to the instruction that the control centre provides.

Summary of the invention

The objective of the invention is for solving the meritorious scheduling controlling difficult problem after access is concentrated in the large-scale wind power field, the big real-time power network dispatching method that a kind of wind-powered electricity generation of dissolving inserts is proposed, it is meritorious in advance control of cycle that this method is introduced with 15 minutes based on prediction, can reduce the operation of power networks risk, improve the dissolve ability of electrical network to greatest extent, improve performance driving economy wind-powered electricity generation.

The big real-time power network dispatching method that the wind-powered electricity generation of dissolving that the present invention proposes inserts is characterized in that this method was a scheduling slot with 15 minutes, and whole day is divided into 96 scheduling slots, may further comprise the steps:

(1) according to the characteristics of wind-powered electricity generation and load fluctuation and the control characteristic of unit, the whole network unit is divided into a plurality of plan units, a plurality of Real-Time Scheduling unit and a plurality of automatic-generation-control unit three parts, all wind-powered electricity generation units all divide the Real-Time Scheduling unit into; The plan unit is followed the tracks of operation plan a few days ago, and the Real-Time Scheduling unit is followed the tracks of the Real-Time Scheduling plan, and automatic-generation-control unit is responsible for the generation load amount of unbalance in the real-time balance electrical network;

(2) plan a few days ago, the interconnection plan of reading generating set from prognoses system a few days ago, and read values of exerting oneself in real time of all generators of the whole network in real time from data acquisition and supervisor control;

(3) from the historical load database of electric power system, read the information of historical load, adopt diurnal periodicity multiple spot extrapolation to predict the load value of next scheduling slot

And increment

(4) at the initial time of each scheduling slot, each wind energy turbine set is gathered the data (wind speed, atmospheric density, wind direction, temperature etc.) and the reporting scheduling center of numerical weather forecast, the control centre is according to the information that receives, employing is based on the model of artificial neural net, obtain the non-linear relation of the output and the input of wind energy turbine set by training, and dope j output of wind electric field value of next scheduling slot historical data

J is a positive integer;

(5) total regulated quantity Δ P of the Real-Time Scheduling unit output of next scheduling slot initial time:

$\mathrm{\ΔP}={\mathrm{\ΔP}}_D^n-{\mathrm{\ΔP}}_T^n-{\mathrm{\ΔP}}_{\mathrm{sche}}^n-{\mathrm{\ΔP}}_{\mathrm{AGC}}^n$

Wherein,

Be the ultra-short term value increment,

Be the interconnection plan next constantly increment,

Be plan a few days ago unit output next constantly increment,

Be next adjustment amount of exerting oneself constantly of AGC unit, next AGC unit output plan is constantly pressed Get, wherein P _MazBe the given upper limit of exerting oneself of unit, P _MinBe the given lower limit of exerting oneself of unit;

(6) each Real-Time Scheduling unit output plan of the next scheduling slot initial time of calculating:

After calculating total regulated quantity Δ P according to previous step, according to the upper and lower adjustment capacity of Real-Time Scheduling unit, each unit of total score dispensings such as cost of electricity-generating coefficient is adjusted, and sets up the meritorious Real-Time Scheduling model of abandoning the wind minimum of formula (a)-(d):

$\left\{\begin{array}{ccc}\min & \underset{i}{\mathrm{\Σ}}{r}_i\left|{\mathrm{\ΔP}}_i\right|\underset{j}{\mathrm{\Σ}}{w}_j{\mathrm{\ΔP}}_j^w,i\∈{N_G}^{\mathrm{rt}}& \left(a\right)\\ s.t.& \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{\mathrm{\ΔP}}_i+\underset{j\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}(P_j^{\mathrm{For}}-P_j^0-{\mathrm{\ΔP}}_j^w)=\mathrm{\ΔP}& \left(b\right)\\ & \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{ij}}{\mathrm{\ΔP}}_i+\underset{k\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{kj}}{\mathrm{\ΔP}}_k^w\≤\stackrel{\‾}{T_j}-T_j,j\∈M_{\mathrm{tie}}& \left(c\right)\\ & \mathrm{\Δ}{\underset{\‾}{P}}_i\≤{\mathrm{\ΔP}}_i\≤\mathrm{\Δ}{\stackrel{\‾}{P}}_i,i\∈N_G^{\mathrm{rt}}& \left(d\right)\\ & {\mathrm{\ΔP}}_j^w\≥0& \end{array}\right.$

Wherein, r _iBe that the current generating unit of conventional electric generators i adjusts cost; w _jBe that wind energy turbine set j abandons wind power cost, abandon wind, general w in order to reduce _j〉=100r _i

Δ P is next adjusting total amount of exerting oneself constantly of Real-Time Scheduling unit;

Δ P _iBe the adjustment amount of next period Real-Time Scheduling unit i,

Number for the Real-Time Scheduling unit of the whole network except that the wind-powered electricity generation unit;

Be the wind-powered electricity generation power of abandoning of wind energy turbine set j, the wind-powered electricity generation that it equals next prediction period predicted value of exerting oneself

With next period Real-Time Scheduling planned value Difference;

Current value of exerting oneself for wind energy turbine set j;

S _IjGenerated output is to the sensitivity of section;

(c) M in _TieThe set of expression power grid security power delivery section,

Be the power delivery upper limit of section, this value reads T from described historical load database _jBe the current through-put power of section, this inequality constraints guarantees transmission section nonoverload;

Adopt simplex method to find the solution the Real-Time Scheduling model, draw the adjustment amount Δ P of Real-Time Scheduling unit i _iThe wind-powered electricity generation power of abandoning with next scheduling slot initial time wind energy turbine set j

(7) will plan in real time to issue, the fired power generating unit in the Real-Time Scheduling unit be provided the adjustment amount Δ P of next scheduling slot initial time _i, wind energy turbine set j is provided maximum planned value of exerting oneself of next scheduling slot initial time

After wind energy turbine set receives the maximum planned value of exerting oneself, formulate the generation schedule in this wind energy turbine set; Simultaneously, wind energy turbine set is sent to the control centre in real time with the electric parameters in this wind field field, fan operation state etc.

Characteristics of the present invention and beneficial effect

The present invention is directed to because the randomness of wind-powered electricity generation and prediction difficulty, proposition increases Real-Time Scheduling control (was the cycle with 15 minutes) between the plan a few days ago of wind-powered electricity generation and AGC control, to abandon windage loss mistake minimum is optimization aim, on ultra-short term and next moment wind-powered electricity generation fundamentals of forecasting, set up meritorious Real-Time Scheduling model, wind-powered electricity generation and conventional rack are implemented the combined optimization scheduling, eliminate wind power generation prediction deviation and load prediction deviation in advance.Can reduce the operation of power networks risk, improve the dissolve ability of electrical network to greatest extent, improve performance driving economy wind-powered electricity generation.

Description of drawings

Fig. 1 is the FB(flow block) of the inventive method.

Embodiment

The big real-time power network dispatching method that the wind-powered electricity generation of dissolving that the present invention proposes inserts, its FB(flow block) as shown in Figure 1, it is characterized in that, this method was a scheduling slot with 15 minutes, whole day is divided into 96 scheduling slots, and (experiment shows, 15 minutes forecasting wind speed result can realistic preferably wind speed, will become big greater than 15 minutes errors), may further comprise the steps:

(1) the unit role divides: according to the characteristics of wind-powered electricity generation and load fluctuation and the control characteristic of unit, the whole network unit is divided into a plurality of plan units, a plurality of Real-Time Scheduling unit and a plurality of automatic generation control (AGC) unit three parts, and all wind-powered electricity generation units all divide the Real-Time Scheduling unit into; The plan unit is followed the tracks of operation plan a few days ago, and the Real-Time Scheduling unit is followed the tracks of the Real-Time Scheduling plan, and the AGC unit is responsible for the generation load amount of unbalance in the real-time balance electrical network;

(2) obtaining of related data: plan a few days ago, the interconnection plan of reading generating set from prognoses system a few days ago, and read value of exerting oneself in real time of all generators of the whole network in real time with monitoring control (SCADA) system from data acquisition;

(3) ultra-short term: from the historical load database of electric power system, read the information of historical load, adopt known multiple spot extrapolation diurnal periodicity to predict the load value of next scheduling slot initial time

And increment

(4) the wind-powered electricity generation prediction of exerting oneself: at the initial time of each scheduling slot, each wind energy turbine set is gathered the data (wind speed, atmospheric density, wind direction, temperature etc.) and the reporting scheduling center of numerical weather forecast, the control centre is according to the information that receives, employing is based on the model of known artificial neural net, obtain the non-linear relation of the output and the input of wind energy turbine set by the training that existing wind energy turbine set history is gone out force data, and dope j output of wind electric field value of next scheduling slot initial time

When numerical weather forecast information can not correctly be obtained for some reason, start j the output of wind electric field value that traditional Forecasting Methodology based on mathematical statistics dopes next scheduling slot initial time

J is positive integer (when numerical weather forecast information can not correctly be obtained for some reason, starting traditional Forecasting Methodology based on mathematical statistics);

(5) regulated quantity of exerting oneself of computer set: the total regulated quantity Δ P that calculates the Real-Time Scheduling unit output of next scheduling slot initial time:

$\mathrm{\ΔP}={\mathrm{\ΔP}}_D^n-{\mathrm{\ΔP}}_T^n-{\mathrm{\ΔP}}_{\mathrm{sche}}^n-{\mathrm{\ΔP}}_{\mathrm{AGC}}^n$

Wherein,

Be the ultra-short term value increment,

Be the interconnection plan next constantly increment,

Be plan a few days ago the next scheduling slot initial time of unit output increment,

Be the adjustment amount of exerting oneself of the next scheduling slot initial time of AGC unit, in order to guarantee AGC unit spinning reserve capacity, the AGC unit output plan of general next scheduling slot initial time is pressed

Get, wherein P _MazBe the given upper limit of exerting oneself of unit, P _MinBe the given lower limit of exerting oneself of unit;

(6) each Real-Time Scheduling unit output plan of the next scheduling slot initial time of calculating:

After calculating total regulated quantity Δ P according to previous step, (upper limit of exerting oneself that the rise capacity equals unit deducts exerting oneself of current time according to the upper and lower adjustment capacity of Real-Time Scheduling unit, current the exerting oneself that the downward modulation capacity equals unit deducts the unit output lower limit), each unit of cost of electricity-generating coefficient total score dispensing is adjusted, and sets up and abandons the meritorious Real-Time Scheduling model (formula (a)-(d)) of wind minimum:

$\left\{\begin{array}{ccc}\min & \underset{i}{\mathrm{\Σ}}{r}_i\left|{\mathrm{\ΔP}}_i\right|\underset{j}{\mathrm{\Σ}}{w}_j{\mathrm{\ΔP}}_j^w,i\∈{N_G}^{\mathrm{rt}}& \left(a\right)\\ s.t.& \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{\mathrm{\ΔP}}_i+\underset{j\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}(P_j^{\mathrm{For}}-P_j^0-{\mathrm{\ΔP}}_j^w)=\mathrm{\ΔP}& \left(b\right)\\ & \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{ij}}{\mathrm{\ΔP}}_i+\underset{k\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{kj}}{\mathrm{\ΔP}}_k^w\≤\stackrel{\‾}{T_j}-T_j,j\∈M_{\mathrm{tie}}& \left(c\right)\\ & \mathrm{\Δ}{\underset{\‾}{P}}_i\≤{\mathrm{\ΔP}}_i\≤\mathrm{\Δ}{\stackrel{\‾}{P}}_i,i\∈N_G^{\mathrm{rt}}& \left(d\right)\\ & {\mathrm{\ΔP}}_j^w\≥0& \end{array}\right.$

Wherein, r _iBe that the current generating unit of conventional electric generators i adjusts cost; w _jBe that wind energy turbine set j abandons wind power cost, abandon wind, general w in order to reduce _j〉=100r _i

Δ P is the adjusting total amount of exerting oneself of the next scheduling slot initial time of Real-Time Scheduling unit;

Δ P _iThe adjustment amount of the next scheduling slot initial time Real-Time Scheduling unit i that obtains for Model Calculation,

Number for the whole network Real-Time Scheduling unit (except that the wind-powered electricity generation unit);

Be the wind-powered electricity generation power of abandoning of wind energy turbine set j, the wind-powered electricity generation that it equals the prediction of the next scheduling slot initial time predicted value of exerting oneself With next scheduling slot initial time Real-Time Scheduling planned value

Difference;

Current value of exerting oneself for wind energy turbine set j;

S _IjGenerated output is to the sensitivity of section;

(c) M in the formula _TieThe set of expression power grid security power delivery section,

Be the power delivery upper limit of section, this value reads from the historical load database, T _jBe the current through-put power of section, this inequality constraints guarantees transmission section nonoverload;

Adopt known simplex method to find the solution meritorious Real-Time Scheduling model (formula (a)-(d)), draw the adjustment amount Δ P of Real-Time Scheduling unit i _iThe wind-powered electricity generation power of abandoning with next scheduling slot initial time wind energy turbine set j

(7) the issuing and follow the tracks of of plan: the wind-powered electricity generation power of abandoning of the exert oneself regulated quantity and the wind energy turbine set of the next scheduling slot initial time of the Real-Time Scheduling unit that step (6) is obtained is handed down to each power plant, the fired power generating unit in the Real-Time Scheduling unit is provided the adjustment amount Δ P of next scheduling slot initial time _i, wind energy turbine set j is provided next maximum planned value of exerting oneself constantly

After wind energy turbine set j receives the maximum planned value of exerting oneself, formulate the generation schedule (can be by changing the measure of propeller pitch angle or start and stop blower fan, the control of gaining merit is immediately following the operation of the maximum planned value of exerting oneself) in this wind energy turbine set; Simultaneously, wind energy turbine set is sent to the control centre in real time with the electric parameters in this wind field field, fan operation state.

Claims (1)

1. the big real-time power network dispatching method that the wind-powered electricity generation of dissolving inserts is characterized in that this method was a scheduling slot with 15 minutes, and whole day is divided into 96 scheduling slots, may further comprise the steps:

(1) according to the characteristics of wind-powered electricity generation and load fluctuation and the control characteristic of unit, the whole network unit is divided into a plurality of plan units, a plurality of Real-Time Scheduling unit and a plurality of automatic-generation-control unit three parts, all wind-powered electricity generation units all divide the Real-Time Scheduling unit into; The plan unit is followed the tracks of operation plan a few days ago, and the Real-Time Scheduling unit is followed the tracks of the Real-Time Scheduling plan, and automatic-generation-control unit is responsible for the generation load amount of unbalance in the real-time balance electrical network;

(2) plan a few days ago, the interconnection plan of reading generating set from prognoses system a few days ago, and read values of exerting oneself in real time of all generators of the whole network in real time from data acquisition and supervisor control;

(3) from the historical load database of electric power system, read the information of historical load, adopt diurnal periodicity multiple spot extrapolation to predict the load value of next scheduling slot

And increment

(4) at the initial time of each scheduling slot, each wind energy turbine set is gathered the data (wind speed, atmospheric density, wind direction, temperature etc.) and the reporting scheduling center of numerical weather forecast, the control centre is according to the information that receives, employing is based on the model of artificial neural net, obtain the non-linear relation of the output and the input of wind energy turbine set by training, and dope j output of wind electric field value of next scheduling slot historical data

J is a positive integer;

(5) total regulated quantity Δ P of the Real-Time Scheduling unit output of next scheduling slot initial time:

$\mathrm{\ΔP}={\mathrm{\ΔP}}_D^n-{\mathrm{\ΔP}}_T^n-{\mathrm{\ΔP}}_{\mathrm{sche}}^n-{\mathrm{\ΔP}}_{\mathrm{AGC}}^n$

Wherein,

Be the ultra-short term value increment,

Be the interconnection plan next constantly increment,

Be plan a few days ago unit output next constantly increment,

Be next adjustment amount of exerting oneself constantly of AGC unit, next AGC unit output plan is constantly pressed

Get, wherein P _MazBe the given upper limit of exerting oneself of unit, P _MinBe the given lower limit of exerting oneself of unit;

(6) each Real-Time Scheduling unit output plan of the next scheduling slot initial time of calculating:

After calculating total regulated quantity Δ P according to previous step, according to the upper and lower adjustment capacity of Real-Time Scheduling unit, each unit of total score dispensings such as cost of electricity-generating coefficient is adjusted, and sets up the meritorious Real-Time Scheduling model of abandoning the wind minimum of formula (a)-(d):

$\left\{\begin{array}{ccc}\min & \underset{i}{\mathrm{\Σ}}{r}_i\left|{\mathrm{\ΔP}}_i\right|\underset{j}{\mathrm{\Σ}}{w}_j{\mathrm{\ΔP}}_j^w,i\∈{N_G}^{\mathrm{rt}}& \left(a\right)\\ s.t.& \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{\mathrm{\ΔP}}_i+\underset{j\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}(P_j^{\mathrm{For}}-P_j^0-{\mathrm{\ΔP}}_j^w)=\mathrm{\ΔP}& \left(b\right)\\ & \underset{i\∉N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{ij}}{\mathrm{\ΔP}}_i+\underset{k\∈N_G^{\mathrm{wind}}}{\mathrm{\Σ}}{S}_{\mathrm{kj}}{\mathrm{\ΔP}}_k^w\≤\stackrel{\‾}{T_j}-T_j,j\∈M_{\mathrm{tie}}& \left(c\right)\\ & \mathrm{\Δ}{\underset{\‾}{P}}_i\≤{\mathrm{\ΔP}}_i\≤\mathrm{\Δ}{\stackrel{\‾}{P}}_i,i\∈N_G^{\mathrm{rt}}& \left(d\right)\\ & {\mathrm{\ΔP}}_j^w\≥0& \end{array}\right.$

Wherein, r _iBe that the current generating unit of conventional electric generators i adjusts cost; w _jBe that wind energy turbine set j abandons wind power cost, abandon wind, general w in order to reduce _j〉=100r _i

Δ P is next adjusting total amount of exerting oneself constantly of Real-Time Scheduling unit;

Δ P _iBe the adjustment amount of next period Real-Time Scheduling unit i,

Number for the Real-Time Scheduling unit of the whole network except that the wind-powered electricity generation unit;

Be the wind-powered electricity generation power of abandoning of wind energy turbine set j, the wind-powered electricity generation that it equals next prediction period predicted value of exerting oneself

With next period Real-Time Scheduling planned value

Difference;

Current value of exerting oneself for wind energy turbine set j;

S _IjGenerated output is to the sensitivity of section;

(c) M in _TieThe set of expression power grid security power delivery section,

Be the power delivery upper limit of section, this value reads T from described historical load database _jBe the current through-put power of section, this inequality constraints guarantees transmission section nonoverload;

Adopt simplex method to find the solution the Real-Time Scheduling model, draw the adjustment amount Δ P of Real-Time Scheduling unit i _iThe wind-powered electricity generation power of abandoning with next scheduling slot initial time wind energy turbine set j

(7) will plan in real time to issue, the fired power generating unit in the Real-Time Scheduling unit be provided the adjustment amount Δ P of next scheduling slot initial time _i, wind energy turbine set j is provided maximum planned value of exerting oneself of next scheduling slot initial time

After wind energy turbine set receives the maximum planned value of exerting oneself, formulate the generation schedule in this wind energy turbine set; Simultaneously, wind energy turbine set is sent to the control centre in real time with the electric parameters in this wind field field, fan operation state etc.

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