CN112448400A - Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve - Google Patents
Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve Download PDFInfo
- Publication number
- CN112448400A CN112448400A CN201910822800.4A CN201910822800A CN112448400A CN 112448400 A CN112448400 A CN 112448400A CN 201910822800 A CN201910822800 A CN 201910822800A CN 112448400 A CN112448400 A CN 112448400A
- Authority
- CN
- China
- Prior art keywords
- scene
- wind power
- day
- power output
- output
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Control Of Eletrric Generators (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a robust optimal scheduling method and a robust optimal scheduling system for determining wind power primary frequency modulation reserve, which comprise the following steps: establishing primary frequency modulation standby constraint of a synchronous generator and a wind turbine generator based on the slope climbing rate of a speed regulator; establishing a two-stage economic optimization robust scheduling model containing primary frequency modulation standby constraints of the synchronous generator and the wind turbine generator; and screening out a key scene set in the wind power output scene set in a day, solving the robust optimization scheduling model aiming at the key scene set and determining the wind power primary frequency modulation standby. The method provided by the invention effectively reduces the calculation difficulty and can more accurately formulate the primary frequency modulation standby strategy.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a robust optimal scheduling method and system for determining wind power primary frequency modulation standby.
Background
With the rapid development of power systems and the improvement of environmental protection requirements of various countries in the world, renewable energy power generation represented by wind power and photovoltaic is more and more emphasized. It is worth noting that access to a large amount of renewable energy in a power system presents challenges to system frequency stabilization. Taking wind power which cannot be scheduled as an example, the influence of the wind power on system frequency control is mainly embodied in the following two points: (1) the converter decouples the frequency of a generator rotor and an electric power system, namely decoupling the mechanical power of a wind turbine generator and the electromagnetic power of the electric power system, so that a fan has no inertial response capability, and the wind turbine generator usually runs in a maximum power tracking mode and cannot reserve primary frequency modulation for standby; (2) wind power large-scale grid connection replaces part of traditional synchronous generator sets with frequency modulation capacity, when frequency fluctuation is generated due to faults and the like of the system, inertia of the wind power generator sets is 0 and standby cannot be provided, and inertia response capacity and frequency modulation standby capacity of the system are reduced.
Part of scholars and engineering experts provide a virtual synchronous machine technology, and links such as a motion equation, primary frequency modulation and the like of a rotor of a simulated synchronous generator are introduced into a power supply controller containing a power electronic converter, so that a new energy source unit adopting the device for grid connection has the characteristics of inertia, damping, frequency modulation, voltage regulation and the like of grid connection operation of the synchronous generator. The comparison shows that the virtual synchronous machine technology can provide larger inertia and system frequency stability compared with the droop control. Therefore, the virtual synchronous generator of the wind turbine generator has the capacity of participating in frequency modulation in the system operation process, researches on the participation of the wind turbine generator in the primary frequency modulation response of the power system, and has important significance in coordinating with other synchronous generator sets in the system to reserve primary frequency modulation for later use.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a robust optimal scheduling method and a robust optimal scheduling system for determining wind power primary frequency modulation reserve, the virtual synchronous generator technology is utilized to enable a wind power generator set to have frequency modulation capacity, the primary frequency modulation reserve of the synchronous generator set in the wind power and power system is determined through robust optimal scheduling, the frequency modulation capacity of the wind power is fully utilized, and the frequency stability of the system is improved.
In order to achieve the above purpose, the invention adopts the following technical scheme: a robust optimization scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps:
screening out a key scene set in the daily wind power output scene set;
solving a pre-established two-stage economic optimization robust scheduling model aiming at a key scene set of the wind power output in the day to obtain the output of a traditional synchronous generator set based on a wind power prediction expected value in the day, the unbalance reserve left for dealing with the error between the wind power output in the day and the prediction expected value, the output regulated again by the traditional synchronous generator set in the day, the primary frequency modulation reserve capacity and the load shedding capacity of the wind power generator set in the day and the traditional synchronous generator set;
the two-stage economic optimization robust scheduling model is obtained according to pre-established primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator and primary frequency modulation standby constraint of the wind generating set;
the intra-day wind power output scene is data of active output power of the wind driven generators in a preset time period, and the intra-day wind power output scene set is a set of active output power data of a plurality of groups of wind driven generators in the preset time period; the intra-day wind power output key scene set represents a set of scenes in which the intra-day wind power output and the prediction deviation before the day in the intra-day wind power output scene set exceed a set threshold value.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the synchronous generator primary frequency modulation standby constraint based on the slope climbing rate of the speed regulator is specifically as follows:
wherein:
for the primary frequency modulation standby of the conventional synchronous generator set i, PlossFor reduced active power output caused by a fault in a unit in an electric power system, CiFor the i speed regulator of the synchronous generator set, MHIs a transient time constant, f, of the power system0For the initial normal operating frequency, f, of the power systemdRepresenting the frequency of the dead zone, fMRepresenting the lowest point of the power system frequency for the case where the governor is at the maximum ramp rate.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the primary frequency modulation standby constraint of the wind turbine generator is as follows:
in the formula:
for primary frequency modulation standby of wind turbine generatorAnd epsilon is the coefficient, P, for improving the active power output of the wind turbineNRated installed capacity for wind turbine generator, CWFor the speed regulator climbing rate after the wind turbine generator is simulated by the virtual synchronous generator set MHIs a transient time constant, f, of the power system0For the initial normal operating frequency, f, of the power systemdRepresenting the frequency of the dead zone, fMRepresenting the lowest point of the frequency of the power system with the speed regulator at the maximum ramp rate, PlossFor reduced active power contribution due to a group fault in the power system,
and
the actual wind power output and the wind power output in the maximum power tracking mode are respectively.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the two-stage economic optimization robust scheduling model specifically comprises the following steps:
the first stage is day-ahead economic optimization scheduling, and the output and power imbalance reserve of the traditional synchronous generator set under the wind power output expected value is determined; the second stage is a day-in stage, the minimum balance cost in a given wind power output scene set omega is taken as a target, the wind power output before the day is expressed by an expected value and is taken as a basic scene, the wind power output before the day is expressed by an superscript 0, and the day-in scene is expressed by an superscript s;
the two-stage economic optimization robust scheduling model objective function is specifically as follows:
in the formula: t is a scheduling time interval, and T is 1-T; n is a radical ofG、NWAnd NBThe number of power nodes of the traditional synchronous generator set, the wind turbine generator set and the system is respectively 1-NG；k＝1～(NG+Nw)；m＝1～NB；
And
the method comprises the steps that an active output and an unbalanced power of a traditional synchronous generator set i in a t period in a basic scene are respectively reserved up and down in a unit MW; cG,i、
And
the active output cost, the power imbalance upper standby cost and the lower standby cost coefficient of the traditional synchronous generator set i are respectively calculated;
and
adjusting values of the active output of a traditional synchronous generator set i on the basis of the output of the generator set in a basic scene at t in a daily scene s;
is a primary standby of a traditional synchronous generator set or a wind turbine set k under a time t in a day scene s,
the primary standby cost coefficient of the traditional synchronous generator set or the wind turbine set k;
is the load shedding quantity, C, of the node m of the power system at the moment tL,mCutting a load cost coefficient for a power system node m;
in the day-ahead scheduling, a wind power output predicted expected value is used as a basic scene, a scheduling strategy with the minimum output and unbalanced standby cost of the traditional synchronous generator set is searched, and scheduling constraints are as follows:
in the formula: i belongs to m, w belongs to m and l belongs to m and respectively represents a traditional synchronous generator set i, a wind turbine generator set w and a line l which are connected with a power system node m;
the expected output of the wind turbine generator w at t time in the basic scene; pL,m,tThe load on the node m of the power system is t;
the transmission power of a line l connecting nodes m and n of the power system at t in a basic scene;
and
the phase angles of the nodes m and n of the power system at t time in the basic scene are respectively; x is the number ofmnReactance of the line connecting the nodes m, n of the power system;
and PG,iThe output of the traditional synchronous generator set i is respectively the upper limit and the lower limit;
the active output of a traditional synchronous generator set i in a t-1 time period in a basic scene; rU,iAnd RD,iRespectively an upper limit and a lower limit of the climbing of a traditional synchronous generator set i;
and Pl mnThe upper limit and the lower limit of the transmission power of a line l connected with nodes m and n of the power system are respectively set;
and
the lower limits of the upper standby and the lower standby of the traditional synchronous generator set i with unbalanced power in the period t are respectively set;
the method comprises the following steps of performing synchronous generator set output adjustment on each scene in a wind power output scene set omega during daily operation of a power system, and searching for the most serious scene adjustment cost, wherein the most serious scene represents the highest optimized scheduling cost in the scene, and the corresponding constraints are as follows:
in the formula: s represents the s-th scene in the wind power output scene set omega, and the total number of scenes corresponding to s is the number of scenes in the wind power output scene set;
the actual output of the wind turbine generator w at the s day scene t;
representing the load on the power system node m at t;
is the most importantLarge cuttable load;
the method is characterized in that primary frequency modulation standby of a traditional synchronous generator set or a wind turbine set y at the t moment of the s-th day scene is represented, and y is 1 to (N)G+Nw-1)；CyRepresenting the climbing rate of a speed regulator of a traditional synchronous generator set or a wind turbine generator set y;
representing the primary frequency modulation standby of the wind turbine generator w at the t moment of the s day scene;
and representing the wind power output of the wind turbine generator in the maximum power tracking mode at the t moment of the s-th intraday scene.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the method for screening out the key scene set with the concentrated wind power output scene in the day specifically comprises the following steps:
the method comprises the steps of calculating difference values between a predicted wind power output expected value in a preset time period before the day and wind power output in the preset time period contained in a given wind power output scene set in the day, summing the difference values, sorting the sum of the difference values obtained in all the scenes in a descending order, intercepting the previous x values according to a given threshold value, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
and representing the wind power output corresponding to the sx day scene.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the method comprises the following steps of solving a two-stage economic optimization robust scheduling model aiming at a key scene set of wind power output in a day, obtaining output of a traditional synchronous generator set based on a wind power prediction expected value in the day, reserving unbalanced standby reserved for dealing with errors existing between the wind power output in the day and the prediction expected value, adjusting output of the traditional synchronous generator set in the day again, primary frequency modulation standby capacity and load shedding of the wind power generator set and the traditional synchronous generator set, and further obtaining total scheduling economic cost in the day before the day, wherein the specific steps comprise:
1) for a set of key scenes omegamSolving the simplified objective function represented by the formula (29) to obtain the output of the traditional synchronous generator set based on the wind power prediction expected value in the basic scene in the day-ahead
And reserve power imbalance for error between the wind power output and the predicted expected value in the day
For later use
Form a scheduling policy X of day aheadmAt the same time, the key set omega is obtained by adding the constraint formula (30)mCorresponding second stage regulation costs, including output readjustment costs of the conventional generator set in the day
Primary frequency modulation spare cost of all units
And load shedding cost
Selecting the maximum adjusting cost corresponding to the key set as betaM；
Beta is the adjustment cost of the second-stage day-inside operation stage, and the formula (29) is the simplification of the formula (11):
the β includes the following constraints:
2) aiming at a scene set omega \ omegamEach scene in (a) calculates the following objective function:
βsremove the critical scene set omega from the scene set omegamThe objective function value corresponding to the external scene set is as shown in formula (31), the objective function of formula (31) needs to satisfy the constraints shown in formulas (19) - (28), and the objective function is specific to the scene set omega \ omegamThe objective function value obtained by calculating each scene in the sequence is arranged to be the maximum value
The wind power output of the scene s' corresponding to the maximum objective function value is recorded as
Wherein: omega/omegamRepresenting the key scene set omega in the scene set omegamAn outer set of scenes;
denotes the maximum objective function value β'sWind power output under the corresponding s' th real-time scene;
3) if beta'S＞βMThen, then
The newly found maximum objective function value beta 'in the third step'sWind power output under corresponding s' th real-time scene
Added to the original key scene set omegamTurning to step 1); otherwise, outputting the scheduling strategy X of the step 1)mAnd the scheduling strategy of the step 2) and the total optimized scheduling cost in the day before, wherein the scheduling strategy of the step 2) is an upper adjustment value of the active output of the traditional synchronous generator set in the day on the basis of the output of the generator set in the basic scene
Lower adjustment value
Primary standby of wind turbine generator and traditional synchronous generator set
And load shedding amount of power system node
And ending the iteration.
The robust optimal scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps of: the preset time period is 24 time periods.
A robust optimization scheduling system for determining wind power primary frequency modulation reserve is characterized by comprising:
the system comprises a daily wind power output key scene set screening module, a daily wind power output key scene set screening module and a daily wind power output key scene set screening module, wherein the daily wind power output key scene set screening module is used for screening a key scene set in a daily wind power output scene set;
the method comprises the steps of solving a pre-established two-stage economic optimization robust scheduling model module, solving a pre-established two-stage economic optimization robust scheduling model aiming at a key scene set of the wind power output in the day, and obtaining the output of a traditional synchronous generator set based on a wind power prediction expected value in the day, unbalanced standby reserved for dealing with errors existing between the wind power output in the day and the prediction expected value, the output of readjustment of the traditional synchronous generator set in the day, the primary frequency modulation standby capacity and the load shedding capacity of the wind power generator set in the day and the traditional synchronous generator set;
the two-stage economic optimization robust scheduling model is obtained according to pre-established primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator and primary frequency modulation standby constraint of the wind generating set;
the intra-day wind power output scene is data of active output power of the wind driven generators in a preset time period, and the intra-day wind power output scene set is a set of active output power data of a plurality of groups of wind driven generators in the preset time period; the intra-day wind power output key scene set represents a set of scenes in which the intra-day wind power output and the prediction deviation before the day in the intra-day wind power output scene set exceed a set threshold value.
The robust optimization scheduling system for determining wind power primary frequency modulation reserve is characterized in that: further comprising: a model building module; the model building module comprises:
the synchronous generator primary frequency modulation standby model establishing unit is used for establishing primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator;
the wind turbine generator primary frequency modulation standby constraint establishing unit is used for establishing primary frequency modulation standby constraints of the wind turbine generator;
the two-stage robust optimization scheduling model establishing unit is used for establishing a two-stage robust optimization scheduling model containing primary frequency modulation standby constraint of the synchronous generator and primary frequency modulation standby constraint of the wind generating set;
the robust optimization scheduling system for determining wind power primary frequency modulation reserve is characterized in that: the day wind power output key scene set screening module comprises:
the processing unit is used for making difference values between the wind power output expected value of the predicted preset time period in the day and the wind power output of the preset time period contained in the given wind power output scene set in the day, summing the difference values, and sequencing the sum of the difference values obtained in all the scenes in a descending order;
a screening unit for intercepting the previous x values according to a given threshold value, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
and representing the wind power output corresponding to the sx day scene.
Has the advantages that: on the basis of the related technical criteria of the virtual synchronous machine, the primary wind power frequency modulation standby constraint of the day-internal operation time scale is established, day-ahead and day-internal operation is coordinated, the problem of power imbalance caused by large-scale wind power grid connection is solved through robust optimization, wherein the primary frequency modulation standby capacity of a wind power unit and a synchronous generator adopting the virtual synchronous generator technology is calculated in the day-internal operation stage, the system frequency falling process is not out of limit after the synchronous generator unit fails, the wind power unit has the capability of quick response under the emergency conditions of unit failure, direct current blocking and the like, and enough primary standby can be reserved by fully utilizing the characteristics of the wind power unit to obtain the starting time for other frequency modulation measures of the system; in order to solve the problem, a key scene set is screened out, so that the calculation difficulty is reduced, and the model calculation efficiency is improved.
Drawings
FIG. 1 is a flow chart of a scheduling method according to an embodiment of the present invention;
FIG. 2 is a graph of governor power versus frequency for one embodiment of the present invention;
fig. 3 is a wind power primary frequency modulation standby explanatory diagram according to an embodiment of the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are intended to be purely exemplary and are not intended to limit the scope of the invention, as various equivalent modifications of the invention will occur to those skilled in the art upon reading the present disclosure and fall within the scope of the appended claims.
In the case of the example 1, the following examples are given,
as shown in fig. 1, a robust optimal scheduling method for determining wind power primary frequency modulation backup specifically includes the following steps:
step 2, the wind turbine generator has primary frequency modulation capability after using the virtual synchronous machine technology, and primary frequency modulation standby constraint of the wind turbine generator is established based on the primary frequency modulation capability;
step 3, aiming at uncertain natural characteristics of wind power output prediction, establishing a two-stage economic optimization robust scheduling model containing primary frequency modulation standby constraint of the synchronous generator and primary frequency modulation standby constraint of the wind power generator set;
and 4, screening out key scenes in the wind power output scene set, and solving the two-stage economic optimization robust scheduling model aiming at the key scene set to obtain the total optimization scheduling cost in the day before, the primary wind power reserve capacity in the day and the primary reserve capacity of the traditional generator.
The step 1, when the power system is scheduled day ahead, based on the synchronous generator dynamic process during primary frequency modulation, establishes the primary frequency modulation standby constraint of the synchronous generator based on the ramp rate of the speed regulator, and the specific steps include:
1.1 when the power system has reduced active output, the power system frequency is reduced, at the moment, the speed regulator responds in the standby range, and the mechanical power of the power system is increased to enable the mechanical power and the electromagnetic power to reach balance again. Neglecting load damping, the power system frequency variation versus power is as follows:
wherein: mHIs a transient time constant of the power system; f (t) is the power system frequency at time t; delta P is the deviation of the active output and the active load of the power system; pm(t) and Pe(t) electrical power system mechanical power and electromagnetic power, respectively;
1.2 the two-sided integration of equation (1) yields:
wherein: f. ofNThe frequency of the lowest point after the generator set is in fault; f. of0The initial normal operation frequency of the power system; t is tNThe time to reach the lowest point frequency in the process of frequency descending;
1.3 from the graph of the power-frequency variation of the governor of fig. 2, the above equation (2) can be equivalently in the form:
wherein: plossReduced active power output for a unit fault in the power system; t is tdIs the time to reach the dead band frequency during the frequency descent; cNThe slope climbing rate of the speed regulator.
In fig. 2: plRepresents tdAnd tNThe change quantity of the difference value of the mechanical power and the electromagnetic power of the electric power system between the moments; f. ofdRepresents a dead band frequency;
representing the primary frequency modulation standby of a traditional synchronous generator set i, wherein i is less than or equal to the total number of the synchronous generator sets;
1.4 hypothesis that there is a maximum governor ramp rate CM，fMCorresponds to CMRepresenting the lowest point of the frequency of the power system when the speed governor is at the maximum climbing rate, f in the formula (3)NAnd CNFrom CMAnd fMInstead, then:
wherein:
is electricityForce system transient time constant calculation equation.
Because of the dead zone of the frequency modulation of the speed regulator, the power fluctuation of the system is supported by inertia in a short time, so that the system can pass through
Representing the power system transient time constant.
1.5 when only synchronous generator sets in the system are considered, P is lost for a unit faultlossAfter active power output, the primary backup of the power system should satisfy the following constraints:
wherein: ciThe slope climbing rate of a speed regulator of the synchronous generator set i;
the method is used for standby primary frequency modulation of the traditional synchronous generator set i.
Equations (5) and (6) represent the primary frequency modulation standby constraint of the synchronous generator based on the ramp rate of the speed governor.
Step 2, establishing primary frequency modulation standby constraint of the wind turbine generator, specifically comprising the following steps:
2.1 the existing virtual synchronous machine control makes the wind generating set have the similar frequency modulation characteristic with the synchronous generating set, when the frequency deviation of the power system is more than fdAnd when the active output of the virtual synchronous machine is more than 20% of the rated installed capacity of the wind turbine generator, the active output of the virtual synchronous machine can be adjusted to participate in primary frequency modulation of the power system. When the frequency of the power system drops, the active output of the virtual synchronous machine is increased, the maximum value of the active output improvement is at least 10% of the rated installed capacity of the wind turbine generator, but the value of the virtual synchronous machine is not too large in order to ensure the sufficient generated energy of the wind power plant.
2.2 if the condition of reserving the primary frequency modulation reserve is met, determining the primary frequency modulation reserve constraint of the wind turbine generator according to the primary frequency modulation reserve constraint of the synchronous generator, and the method comprises the following steps:
wherein:
the method is used for primary frequency modulation standby of the wind turbine generator; cWThe climbing rate of the speed regulator after the wind turbine generator is simulated by the virtual synchronous generator set;
2.3 determining primary frequency modulation standby constraint of the wind turbine generator according to the technical requirements of the virtual synchronous machine, as follows:
wherein: epsilon is a coefficient which can improve the active output of the wind turbine generator and is generally a numerical value larger than 10%; pNRated installed capacity of the wind turbine;
2.4 as shown in fig. 3, combining the primary frequency modulation standby constraint of the synchronous generator and the primary frequency modulation standby determined by the technical requirement of the virtual synchronous machine to obtain the primary frequency modulation standby constraint finally applicable to the wind turbine generator, as follows:
in the formula:
and
respectively the actual wind power output and the maximum powerWind power output in a rate tracking mode.
In step 3, the two-stage economic optimization robust scheduling model is established as follows:
in the optimization scheduling process, uncertainty of wind power output cannot be ignored, and day-ahead power imbalance reserve needs to be considered (for the day-ahead wind power output and prediction, adjustable reserve, namely day-ahead power imbalance reserve, is reserved for a traditional unit in the day), so the invention provides a day-ahead and day-ahead two-stage economic optimization robust scheduling model. Assuming that the load prediction is a determined value, under the wind power prediction expected value, the method determines the output and power imbalance reserve of the traditional synchronous generator set through day-ahead scheduling so as to deal with the error between the wind power output and the wind power prediction during real-time operation. Under the intra-day scale, 50 groups of wind power output in different days are set according to the fact that the deviation between the upper deviation and the lower deviation of the predicted wind power output value in the day ahead is within 15%, under the given different wind power output, the output of the traditional synchronous generator set needs to be adjusted again within the constraint range of output and power unbalance reserve determined in the day ahead, and on the basis, the traditional synchronous generator set and the wind power generator set need to be reserved for primary frequency modulation reserve and need to be subjected to load shedding if necessary.
3.1 in an optimized dispatching model, in the first stage, the day-ahead economic optimized dispatching is carried out, and the output and the power imbalance of the traditional synchronous generator set under the expected value of the wind power output (namely the wind power output predicted day-ahead) are determined for standby; the second stage is an intraday stage, uncertainty is represented by a plurality of given wind power output scenes, a scene set containing all the given wind power output scenes is represented by omega, the wind power output scenes are data of active output power of the wind driven generators in 24 time periods, and the scene set of the wind power output scenes is a set of the active output power data of a plurality of groups of wind driven generators in 24 time periods; the method aims at minimizing the balance standby cost in the wind power output scene set omega, and considers the output readjustment of the traditional units, the primary frequency modulation standby of all the units and the load shedding under the wind power output scene s in a day. In the model, the day-ahead wind power output is expressed by a prediction expected value, namely a wind power output basic scene, which is expressed by an upper standard 0, and a day-in wind power output scene is expressed by an upper standard s. The specific mathematical expression of the objective function of the two-stage economic optimization robust scheduling model is as follows, and the objective function is obtained as the total optimization scheduling cost in the day before:
in the formula: t is a scheduling time interval, and 24h, T is 1-T; n is a radical ofG、NWAnd NBThe number of power nodes of the traditional synchronous generator set, the wind turbine generator set and the system is respectively 1-NG；k＝1～(NG+Nw)；m＝1～NB；
And
the method comprises the steps that an active output and an unbalanced power of a traditional synchronous generator set i in a t period in a basic scene are respectively reserved up and down in a unit MW; cG,i、
And
the active output cost, the power imbalance upper standby cost and the lower standby cost coefficient of the traditional synchronous generator set i are respectively calculated;
and
adjusting values of the active output of a traditional synchronous generator set i on the basis of the output of the generator set in a basic scene at t in a daily scene s;
is a primary standby of a traditional synchronous generator set or a wind turbine set k under a time t in a day scene s,
the primary standby cost coefficient of the traditional synchronous generator set or the wind turbine set k;
is the load shedding quantity, C, of the node m of the power system at the moment tL,mCutting a load cost coefficient for a power system node m;
3.2 for the objective function of the above formula (11), the day-ahead scheduling takes the predicted expected value of wind power output as a basic scene, and a scheduling strategy with the minimum output and unbalanced standby cost of the traditional synchronous generator set is searched, wherein the scheduling constraint is as follows:
in the formula: i ∈ m, w ∈ m, and l ∈ m denote ANDThe system comprises a traditional synchronous generator set i, a wind turbine generator set w and a line l which are connected with a node m of the power system;
the expected output of the wind turbine generator w at t time in the basic scene; pL,m,tThe load on the node m of the power system is t;
the transmission power of a line l connecting nodes m and n of the power system at t in a basic scene;
and
the phase angles of the nodes m and n of the power system at t time in the basic scene are respectively; x is the number ofmnReactance of the line connecting the nodes m, n of the power system; pG,iAnd PG,iThe output of the traditional synchronous generator set i is respectively the upper limit and the lower limit;
the active output of a traditional synchronous generator set i in a t-1 time period in a basic scene; rU,iAnd RD,iRespectively an upper limit and a lower limit of the climbing of a traditional synchronous generator set i;
and Pl mnThe upper limit and the lower limit of the transmission power of a line l connected with nodes m and n of the power system are respectively set;
and
the lower limits of the upper standby and the lower standby of the traditional synchronous generator set i with unbalanced power in the period t are respectively set;
3.3 when the power system operates in the day, the traditional generating set output adjustment is carried out on each scene in the wind power output scene set omega, the most serious scene adjustment cost is searched, the most serious scene adjustment cost comprises the traditional generating set output readjustment cost, the primary frequency modulation standby cost of all the generating sets and the load shedding cost, the most serious scene represents that the optimal scheduling cost is the highest under the scene, and the corresponding constraints are as follows:
in the formula: s represents the s-th scene in the wind power output scene set omega, and the total number of scenes corresponding to s is the number of scenes in the wind power output scene set;
the wind turbine generator w outputs power at the t-th day scene;
representing the load on the power system node m at t;
the maximum cutting load;
the method is characterized in that primary frequency modulation standby of a traditional synchronous generator set or a wind turbine set y at the t moment of the s-th day scene is represented, and y is 1 to (N)G+Nw-1)；CyRepresenting the climbing rate of a speed regulator of a traditional synchronous generator set or a wind turbine generator set y;
representing the primary frequency modulation standby of the wind turbine generator w at the t moment of the s day scene;
representing the wind power output of the wind turbine generator in the maximum power tracking mode at the t moment of the s-th real-time scene; the other variables have the same meaning as the variables in step 3.2, with the superscript s being the s-th day scene.
The two-stage economic optimization robust scheduling model is as follows: formulas (11) to (28).
In the step 4, a wind power output key scene is screened to obtain a robust optimal scheduling strategy considering wind power primary frequency modulation standby, and the specific steps are as follows:
4.1 solving the two-stage economic optimization robust scheduling model established by the invention directly has higher difficulty, and aiming at the min-max-min problem, the adjusting cost auxiliary variable beta of the second-stage daily operation stage can be introduced to replace the internal max-min problem, namely, the formula (11) is simplified as follows:
4.2 at the same time, add the following constraints:
the two-stage robust optimization scheduling model after the auxiliary variable beta is introduced is equivalent to the model before the change, and the min-max-min three-layer optimization problem represented by the formula (11) becomes a single-layer optimization problem, but if all scenes in the scene set omega are considered at the same time, each scene corresponds to a series of real-time operation constraints, the problem scale is huge and is difficult to solve. Therefore, the invention provides an iteration method, which comprises two layers of problems, namely, a key scene set omega in a scene set omega is searched through a lower layer of problemsmAnd the upper layer problem only aims at the key scene set omegamThe objective function represented by equation (29) is solved. Key scene set omegamRepresenting a set of scenes with the most serious deviation between the wind power output in the day and the prediction in the day before in the scene set omega, wherein the upper layer problem aims at the key scene set omegamThe calculated active power output of the traditional synchronous generator set can be readjusted within the standby constraint range in any scene at the daytime stage, as shown in a formula (24). The specific process is as follows:
1) the first step is as follows: the method comprises the steps of performing difference on wind power output expected values in a preset time period (for example, 24 time periods) predicted in the day ahead and wind power output in the preset time period contained in a scene set, summing the difference values, sequencing the sum of the difference values obtained in all the scenes in a descending order, intercepting the first x values according to a given threshold, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
representing the wind power output corresponding to the sx day scene;
2) the second step is that: for a set of key scenes omegamSolving the simplified objective function represented by the formula (29) to obtain the output of the traditional synchronous generator set based on the wind power prediction expected value in the basic scene in the day-ahead
And reserve power imbalance for error between the wind power output and the predicted expected value in the day
For later use
Form a scheduling policy X of day aheadmMeanwhile, the key set omega at the moment is obtained by adding the constraint formula (30)mAnd the corresponding second-stage adjusting cost is as follows: beta is a1，…，βxIncluding the output readjustment cost of the conventional generator set in the day
Primary frequency modulation spare cost of all units
And load shedding cost
Selecting the maximum adjusting cost corresponding to the key set as betaM；
3) The third step: aiming at the scene set omega \ omega, the day-ahead scheduling strategy obtained by the second stepmEach scene in (a) calculates the following objective function:
βsremove the critical scene set omega from the scene set omegamThe objective function value corresponding to the external scene set is as shown in formula (31), the objective function of formula (31) needs to satisfy the constraints shown in formulas (19) - (28), and the objective function is specific to the scene set omega \ omegamThe objective function value obtained by calculating each scene in the sequence is arranged to be the maximum value
The wind power output of the scene s' corresponding to the maximum objective function value is recorded as
Wherein: omega/omegamRepresenting the key scene set omega in the scene set omegamAn outer set of scenes;
denotes the maximum objective function value β'sWind power output under the corresponding s' th real-time scene; one scene in the wind power output scene set omega is a preset time period output condition of one wind power generator;
4) if beta'S＞βMIf the key set screened out before is not representative of the most serious situation in the scene, then
Namely the newly found maximum objective function value beta 'in the third step'sWind power output under corresponding s' th real-time scene
Added to the original key scene set omegamTurning to step 2); otherwise, outputting the scheduling strategy X of the second stepmAnd the scheduling strategy and the total optimized scheduling cost in the day before are used as the scheduling strategy in the third step, namely the active output of the traditional synchronous generator set in the dayAdjusting value on the basis of output of the unit in basic scene
Lower adjustment value
Primary standby of wind turbine generator and traditional synchronous generator set
And load shedding amount of power system node
And ending the iteration.
In the case of the example 2, the following examples are given,
a robust optimization scheduling system for determining wind power primary frequency modulation reserve is characterized by comprising:
the system comprises a daily wind power output key scene set screening module, a daily wind power output key scene set screening module and a daily wind power output key scene set screening module, wherein the daily wind power output key scene set screening module is used for screening a key scene set in a daily wind power output scene set;
the method comprises the steps of solving a pre-established two-stage economic optimization robust scheduling model module, solving a pre-established two-stage economic optimization robust scheduling model aiming at a key scene set of the daily wind power output to obtain the output of a traditional synchronous generator set based on a wind power prediction expected value, and reserving unbalanced standby for dealing with errors existing between the daily wind power output and the prediction expected value, and readjusting the output of the traditional synchronous generator set in the day, the primary frequency modulation standby capacity and the load shedding capacity of the wind power generator set in the day and the traditional synchronous generator set;
the two-stage economic optimization robust scheduling model is obtained according to pre-established primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator and primary frequency modulation standby constraint of the wind generating set;
the intra-day wind power output scene is data of active output power of the wind driven generators in a preset time period, and the intra-day wind power output scene set is a set of active output power data of a plurality of groups of wind driven generators in the preset time period; the intra-day wind power output key scene set represents a set of scenes in which the intra-day wind power output and the prediction deviation before the day in the intra-day wind power output scene set exceed a set threshold value.
The system also includes a model building module; the model building module comprises:
the synchronous generator primary frequency modulation standby model establishing unit is used for establishing primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator;
the wind turbine generator primary frequency modulation standby constraint establishing unit is used for establishing primary frequency modulation standby constraints of the wind turbine generator;
the two-stage robust optimization scheduling model establishing unit is used for establishing a two-stage robust optimization scheduling model containing primary frequency modulation standby constraint of the synchronous generator and primary frequency modulation standby constraint of the wind generating set;
the day wind power output key scene set screening module comprises:
the processing unit is used for making difference values between the wind power output expected value of the predicted preset time period in the day and the wind power output of the preset time period contained in the given wind power output scene set in the day, summing the difference values, and sequencing the sum of the difference values obtained in all the scenes in a descending order;
a screening unit for intercepting the previous x values according to a given threshold value, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
and representing the wind power output corresponding to the sx day scene.
The invention adopts a modified model and algorithm provided by IEEE57 node arithmetic test, wherein the unit on the node 3 is a wind turbine with the rated capacity of 140MW, the total installed capacity of the system is about 2000MW, and the arithmetic adopts 50 wind power output scenes to represent uncertain information. According to the China power grid operation standard, the rated frequency of a power grid is 50Hz, and the lowest limit of the frequency is 49.8 Hz.
The large-scale wind power integration causes the shutdown of part of traditional synchronous generator sets to meet the wind power consumption, and the method for replacing the synchronous generator by the wind power set is adopted to simulate the shutdown. The capacity of the fault unit is 20MW, and the initial frequency of the system is 50 Hz.
The method screens out the scene serial number [6 ] corresponding to the key scene set by an iteration method; 49], i.e. scenario 6 and 49. The cost of primary backup is not considered to be 5375256$, the cost is considered to be 5508326 $whenprimary frequency modulation backup is considered but wind power does not participate, and the cost is considered to be 5508085 $whenwind power participates. At the moment, the dispatching cost of the large-scale wind power system is obviously increased after the frequency response is considered for one time, and the increased cost is mainly the one-time standby or load shedding cost. The wind power scene set [ 6; 49], the scheduling cost in the day and the future under the same condition is basically the same, and the scheduling cost comprises the output cost of the generator set and the reserved unbalanced power standby cost corresponding to the wind power prediction error.
The method screens out wind power key scenes, reduces the calculation difficulty, improves the model calculation efficiency, and obtains the primary reserve capacity of the wind generation set with better economy based on the related technical criteria of the virtual synchronizer.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A robust optimization scheduling method for determining wind power primary frequency modulation reserve is characterized by comprising the following steps:
screening out a key scene set in the daily wind power output scene set;
solving a pre-established two-stage economic optimization robust scheduling model aiming at a key scene set of the wind power output in the day to obtain the output of a traditional synchronous generator set based on a wind power prediction expected value in the day, the unbalance reserve left for dealing with the error between the wind power output in the day and the prediction expected value, the output regulated again by the traditional synchronous generator set in the day, the primary frequency modulation reserve capacity and the load shedding capacity of the wind power generator set in the day and the traditional synchronous generator set;
the two-stage economic optimization robust scheduling model is obtained according to pre-established primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator and primary frequency modulation standby constraint of the wind generating set;
the intra-day wind power output scene is data of active output power of the wind driven generators in a preset time period, and the intra-day wind power output scene set is a set of active output power data of a plurality of groups of wind driven generators in the preset time period; the intra-day wind power output key scene set represents a set of scenes in which the intra-day wind power output and the prediction deviation before the day in the intra-day wind power output scene set exceed a set threshold value.
2. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 1, characterized in that: the synchronous generator primary frequency modulation standby constraint based on the slope climbing rate of the speed regulator is specifically as follows:
wherein:
for the primary frequency modulation standby of the conventional synchronous generator set i, PlossFor reduced active power output caused by a fault in a unit in an electric power system, CiFor the i speed regulator of the synchronous generator set, MHIs a transient time constant, f, of the power system0For the initial normal operating frequency, f, of the power systemdRepresenting the frequency of the dead zone, fMRepresenting the lowest point of the power system frequency for the case where the governor is at the maximum ramp rate.
3. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 1, characterized in that: the primary frequency modulation standby constraint of the wind turbine generator is as follows:
in the formula:
for the primary frequency modulation standby of the wind turbine generator, epsilon is the coefficient, P, for the active power output of the wind turbine generatorNRated installed capacity for wind turbine generator, CWFor the speed regulator climbing rate after the wind turbine generator is simulated by the virtual synchronous generator set MHIs a transient time constant, f, of the power system0For the initial normal operating frequency, f, of the power systemdRepresenting the frequency of the dead zone, fMRepresenting the lowest point of the frequency of the power system with the speed regulator at the maximum ramp rate, PlossFor reduced active power contribution due to a group fault in the power system,
and
the actual wind power output and the wind power output in the maximum power tracking mode are respectively.
4. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 1, characterized in that: the two-stage economic optimization robust scheduling model specifically comprises the following steps:
the first stage is day-ahead economic optimization scheduling, and the output and power imbalance reserve of the traditional synchronous generator set under the wind power output expected value is determined; the second stage is a day-in stage, the minimum balance cost in a given wind power output scene set omega is taken as a target, the wind power output before the day is expressed by an expected value and is taken as a basic scene, the wind power output before the day is expressed by an superscript 0, and the day-in scene is expressed by an superscript s;
the two-stage economic optimization robust scheduling model objective function is specifically as follows:
in the formula: t is a scheduling time interval, and T is 1-T; n is a radical ofG、NWAnd NBThe number of power nodes of the traditional synchronous generator set, the wind turbine generator set and the system is respectively 1-NG；k＝1～(NG+Nw)；m＝1～NB；
And
the method comprises the steps that an active output and an unbalanced power of a traditional synchronous generator set i in a t period in a basic scene are respectively reserved up and down in a unit MW; cG,i、
And
the active output cost, the power imbalance upper standby cost and the lower standby cost coefficient of the traditional synchronous generator set i are respectively calculated;
and
adjusting values of the active output of a traditional synchronous generator set i on the basis of the output of the generator set in a basic scene at t in a daily scene s;
is a primary standby of a traditional synchronous generator set or a wind turbine set k under a time t in a day scene s,
the primary standby cost coefficient of the traditional synchronous generator set or the wind turbine set k;
is the load shedding quantity, C, of the node m of the power system at the moment tL,mCutting a load cost coefficient for a power system node m;
in the day-ahead scheduling, a wind power output predicted expected value is used as a basic scene, a scheduling strategy with the minimum output and unbalanced standby cost of the traditional synchronous generator set is searched, and scheduling constraints are as follows:
in the formula: i belongs to m, w belongs to m and l belongs to m and respectively represents a traditional synchronous generator set i, a wind turbine generator set w and a line l which are connected with a power system node m;
the expected output of the wind turbine generator w at t time in the basic scene; pL,m,tThe load on the node m of the power system is t;
the transmission power of a line l connecting nodes m and n of the power system at t in a basic scene;
and
of nodes m and n of power system at time t in basic sceneA phase angle; x is the number ofmnReactance of the line connecting the nodes m, n of the power system;
andP G,ithe output of the traditional synchronous generator set i is respectively the upper limit and the lower limit;
the active output of a traditional synchronous generator set i in a t-1 time period in a basic scene; rU,iAnd RD,iRespectively an upper limit and a lower limit of the climbing of a traditional synchronous generator set i;
andP l mnthe upper limit and the lower limit of the transmission power of a line l connected with nodes m and n of the power system are respectively set;
and
the lower limits of the upper standby and the lower standby of the traditional synchronous generator set i with unbalanced power in the period t are respectively set;
the method comprises the following steps of performing synchronous generator set output adjustment on each scene in a wind power output scene set omega during daily operation of a power system, and searching for the most serious scene adjustment cost, wherein the most serious scene represents the highest optimized scheduling cost in the scene, and the corresponding constraints are as follows:
in the formula: s represents the s-th scene in the wind power output scene set omega, and the total number of scenes corresponding to s is the number of scenes in the wind power output scene set;
the actual output of the wind turbine generator w at the s day scene t;
representing t-hour electricityLoad cutting on a force system node m;
the maximum cutting load;
the method is characterized in that primary frequency modulation standby of a traditional synchronous generator set or a wind turbine set y at the t moment of the s-th day scene is represented, and y is 1 to (N)G+Nw-1)；CyRepresenting the climbing rate of a speed regulator of a traditional synchronous generator set or a wind turbine generator set y;
representing the primary frequency modulation standby of the wind turbine generator w at the t moment of the s day scene;
and representing the wind power output of the wind turbine generator in the maximum power tracking mode at the t moment of the s-th intraday scene.
5. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 1, characterized in that: the method for screening out the key scene set with the concentrated wind power output scene in the day specifically comprises the following steps:
the method comprises the steps of calculating difference values between a predicted wind power output expected value in a preset time period before the day and wind power output in the preset time period contained in a given wind power output scene set in the day, summing the difference values, sorting the sum of the difference values obtained in all the scenes in a descending order, intercepting the previous x values according to a given threshold value, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
and representing the wind power output corresponding to the sx day scene.
6. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 4, characterized in that: the method comprises the following steps of solving a two-stage economic optimization robust scheduling model aiming at a key scene set of wind power output in a day, obtaining output of a traditional synchronous generator set based on a wind power prediction expected value in the day, reserving unbalanced standby reserved for dealing with errors existing between the wind power output in the day and the prediction expected value, adjusting output of the traditional synchronous generator set in the day again, primary frequency modulation standby capacity and load shedding of the wind power generator set and the traditional synchronous generator set, and further obtaining total scheduling economic cost in the day before the day, wherein the specific steps comprise:
1) for a set of key scenes omegamSolving the simplified objective function represented by the formula (29) to obtain the output of the traditional synchronous generator set based on the wind power prediction expected value in the basic scene in the day-ahead
And reserve power imbalance for error between the wind power output and the predicted expected value in the day
For later use
Form a scheduling policy X of day aheadmAt the same time, the key set omega is obtained by adding the constraint formula (30)mCorresponding second stage regulation costs, including output readjustment costs of the conventional generator set in the day
Primary frequency modulation spare cost of all units
And load shedding cost
Selecting the maximum adjusting cost corresponding to the key set as betaM；
Beta is the adjustment cost of the second-stage day-inside operation stage, and the formula (29) is the simplification of the formula (11):
the β includes the following constraints:
2) aiming at a scene set omega \ omegamEach scene in (a) calculates the following objective function:
βsremove the critical scene set omega from the scene set omegamThe objective function value corresponding to the external scene set is as shown in formula (31), the objective function of formula (31) needs to satisfy the constraints shown in formulas (19) - (28), and the objective function is specific to the scene set omega \ omegamThe objective function value obtained by calculating each scene in the sequence is arranged to be the maximum value
The wind power output of the scene s' corresponding to the maximum objective function value is recorded as
Wherein: omega/omegamRepresenting the key scene set omega in the scene set omegamAn outer set of scenes;
denotes the maximum objective function value β'SWind power output under the corresponding s' th real-time scene;
3) if beta'S＞βMThen, then
The newly found maximum objective function value beta 'in the third step'SWind power output under corresponding s' th real-time scene
Added to the original key scene set omegamTurning to step 1); otherwise, outputting the scheduling strategy X of the step 1)mAnd the scheduling strategy of the step 2) and the total optimized scheduling cost in the day before, wherein the scheduling strategy of the step 2) is an upper adjustment value of the active output of the traditional synchronous generator set in the day on the basis of the output of the generator set in the basic scene
Lower adjustment value
Primary standby of wind turbine generator and traditional synchronous generator set
And load shedding amount of power system node
And ending the iteration.
7. The robust optimal scheduling method for determining wind power primary frequency modulation backup according to claim 1, characterized in that: the preset time period is 24 time periods.
8. A robust optimization scheduling system for determining wind power primary frequency modulation reserve is characterized by comprising:
the system comprises a daily wind power output key scene set screening module, a daily wind power output key scene set screening module and a daily wind power output key scene set screening module, wherein the daily wind power output key scene set screening module is used for screening a key scene set in a daily wind power output scene set;
the method comprises the steps of solving a pre-established two-stage economic optimization robust scheduling model module, solving a pre-established two-stage economic optimization robust scheduling model aiming at a key scene set of the wind power output in the day, and obtaining the output of a traditional synchronous generator set based on a wind power prediction expected value in the day, unbalanced standby reserved for dealing with errors existing between the wind power output in the day and the prediction expected value, the output of readjustment of the traditional synchronous generator set in the day, the primary frequency modulation standby capacity and the load shedding capacity of the wind power generator set in the day and the traditional synchronous generator set;
the two-stage economic optimization robust scheduling model is obtained according to pre-established primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator and primary frequency modulation standby constraint of the wind generating set;
the intra-day wind power output scene is data of active output power of the wind driven generators in a preset time period, and the intra-day wind power output scene set is a set of active output power data of a plurality of groups of wind driven generators in the preset time period; the intra-day wind power output key scene set represents a set of scenes in which the intra-day wind power output and the prediction deviation before the day in the intra-day wind power output scene set exceed a set threshold value.
9. The robust optimized scheduling system for determining wind power primary frequency modulation backup as claimed in claim 8, wherein: further comprising: a model building module; the model building module comprises:
the synchronous generator primary frequency modulation standby model establishing unit is used for establishing primary frequency modulation standby constraint of the synchronous generator based on the slope climbing rate of the speed regulator;
the wind turbine generator primary frequency modulation standby constraint establishing unit is used for establishing primary frequency modulation standby constraints of the wind turbine generator;
and the two-stage robust optimization scheduling model establishing unit is used for establishing a two-stage robust optimization scheduling model containing the primary frequency modulation standby constraint of the synchronous generator and the primary frequency modulation standby constraint of the wind generating set.
10. The robust optimized scheduling system for determining wind power primary frequency modulation backup as claimed in claim 8, wherein: the day wind power output key scene set screening module comprises:
the processing unit is used for making difference values between the wind power output expected value of the predicted preset time period in the day and the wind power output of the preset time period contained in the given wind power output scene set in the day, summing the difference values, and sequencing the sum of the difference values obtained in all the scenes in a descending order;
a screening unit for intercepting the previous x values according to a given threshold value, and forming an initial key scene set by the corresponding x scenes
Representing the wind power output corresponding to the s1 th intraday scene,
and representing the wind power output corresponding to the sx day scene.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910822800.4A CN112448400B (en) | 2019-09-02 | 2019-09-02 | Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910822800.4A CN112448400B (en) | 2019-09-02 | 2019-09-02 | Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112448400A true CN112448400A (en) | 2021-03-05 |
| CN112448400B CN112448400B (en) | 2022-08-23 |
Family
ID=74734771
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910822800.4A Active CN112448400B (en) | 2019-09-02 | 2019-09-02 | Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112448400B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113112063A (en) * | 2021-04-07 | 2021-07-13 | 国网新疆电力有限公司经济技术研究院 | Multi-scene robust scheduling method and device containing wind power system |
| CN117422183A (en) * | 2023-12-18 | 2024-01-19 | 国网四川省电力公司 | Unit overhaul optimization method, device, equipment and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107039977A (en) * | 2017-06-03 | 2017-08-11 | 广东博慎智库能源科技发展有限公司 | With the uncertain collection construction method of the power system Robust Scheduling of the minimum target of integrated cost |
-
2019
- 2019-09-02 CN CN201910822800.4A patent/CN112448400B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107039977A (en) * | 2017-06-03 | 2017-08-11 | 广东博慎智库能源科技发展有限公司 | With the uncertain collection construction method of the power system Robust Scheduling of the minimum target of integrated cost |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113112063A (en) * | 2021-04-07 | 2021-07-13 | 国网新疆电力有限公司经济技术研究院 | Multi-scene robust scheduling method and device containing wind power system |
| CN117422183A (en) * | 2023-12-18 | 2024-01-19 | 国网四川省电力公司 | Unit overhaul optimization method, device, equipment and storage medium |
| CN117422183B (en) * | 2023-12-18 | 2024-03-19 | 国网四川省电力公司 | Unit overhaul optimization method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112448400B (en) | 2022-08-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | A coordinated dispatch method with pumped-storage and battery-storage for compensating the variation of wind power | |
| Toma et al. | On the virtual inertia provision by BESS in low inertia power systems | |
| Sedaghat et al. | Design of a multilevel control strategy for integration of stand-alone wind/diesel system | |
| Zografos | Power system inertia estimation and frequency response assessment | |
| CN110350589B (en) | Renewable energy and energy storage scheduling model and scheduling method | |
| CN109992818B (en) | Unit combination model with large-scale wind power participating primary frequency modulation and solving method | |
| CN107800153B (en) | Electric heat energy rolling robust scheduling method for electric heat storage and wind power consumption | |
| CN113193547A (en) | Day-ahead-day cooperative scheduling method and system for power system considering uncertainty of new energy and load interval | |
| CN105207259A (en) | Energy-management-based micro-grid system dispatching method in grid connection state | |
| CN112448400B (en) | Robust optimal scheduling method and system for determining wind power primary frequency modulation reserve | |
| CN114725926A (en) | Toughness-improvement-oriented black start strategy for distributed resource-assisted main network key nodes | |
| El-Bahay et al. | Computational methods to mitigate the effect of high penetration of renewable energy sources on power system frequency regulation: a comprehensive review | |
| CN105207207A (en) | Energy-management-based micro-grid system dispatching method in isolated grid state | |
| Anderson et al. | Distributed wind-hybrid microgrids with autonomous controls and forecasting | |
| CN112039126B (en) | Multi-time-scale coordinated scheduling method and system for power distribution network containing distributed power supply | |
| Zhang et al. | Research on frequency regulation strategy based on model predictive control for wind-hydro-storage complementary microgrid | |
| Dahmane et al. | Control of wind conversion system used in autonomous system | |
| Hosseini et al. | Coordinating demand response and wind turbine controls for alleviating the first and second frequency dips in wind-integrated power grids | |
| CN107069810B (en) | Cope with the intermittent fired power generating unit built-up pattern building of wind-powered electricity generation and analysis method | |
| Gonzalez-Longatt et al. | Flexible automatic generation control system for embedded HVDC links | |
| CN115603308A (en) | Source network coordination planning method and system considering demand response substitution benefit | |
| Dai et al. | Multilevel dispatch and control for grid interconnected wind-CAES hybrid systems | |
| ZHANG et al. | A Robust Reserve Scheduling Method Considering Wind Turbine Generator’s De-loading Control | |
| Azizipanah-Abarghooee et al. | Integration of wind and solar energies with battery energy storage systems into 36-zone Great Britain power system for frequency regulation studies | |
| CN117578467B (en) | Electric quantity weight-based micro-grid cluster operation control method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |