CN115733149A - Wind power system reactive power optimization method considering alternative solution of DFIG output range - Google Patents

Wind power system reactive power optimization method considering alternative solution of DFIG output range Download PDF

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CN115733149A
CN115733149A CN202211591476.8A CN202211591476A CN115733149A CN 115733149 A CN115733149 A CN 115733149A CN 202211591476 A CN202211591476 A CN 202211591476A CN 115733149 A CN115733149 A CN 115733149A
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dfig
active
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power
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李生虎
常雅玲
李璐璐
陈东
汪壮
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Hefei University of Technology
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Abstract

The invention disclosesA wind power system reactive power optimization method considering alternative solution of a DFIG output range is provided, and comprises the following steps: 1. establishing a DFIG internal power flow model of the doubly-fed induction motor, and setting a Q according to a DFIG reactive power set value DFIG,set Calculating the upper limit of active power output P DFIG,max (ii) a Based on internal constraint of DFIG, obtaining DFIG reactive output Q DFIG A range; 2. establishing an active output lower limit model of the DFIG and calculating to obtain P DFIG A range; 3. the DFIG model is merged into a power grid to obtain a DFIG model of the wind power system, and P after grid connection is calculated DFIG A range; 4. computing post-grid Q DFIG Performing iterative calculation to obtain a DFIG output range after grid connection; 5. establishing a reactive power optimization model of the wind power system alternately solved by the output range of the DFIG; 6. and solving the reactive power optimization model by using a PSO-GWOO algorithm. The invention can effectively consider the influence of each factor on the DFIG output range, performs reactive power optimization on the power grid, reduces the voltage fluctuation of the power grid, reduces the grid loss and improves the stability of the power grid operation on the basis of quantifying the DFIG operation range.

Description

Wind power system reactive power optimization method considering alternative solution of DFIG output range
Technical Field
The invention relates to the technical field of power systems, in particular to a reactive power optimization method for calculating the alternative solution of the active/reactive power output range of a DFIG (doubly Fed Induction Generator) system.
Background
With the shortage of fossil energy, environmental pollution and greenhouse effect pressure, the wind power capacity of China is rapidly increased. In 2020, the national wind power installed capacity 28153 ten thousand kW accounts for 12.79% of the total installed capacity, and the wind power generation capacity accounts for 30.09% of the total renewable energy generation capacity, and the method is a non-negligible power generation form in a power grid. Because of the low cost of double-fed induction generator (DFIG), it is widely used.
The fluctuation and randomness caused by wind power generation can affect the stability of a power grid and reduce the quality of electric energy, wherein the reactive voltage problem of a wind power plant is one of the most outstanding problems. With the continuous increase of the wind power capacity, in order to ensure the balance of the power grid source and the load and low wind power pollution, only a method that partial thermal power generating units are forced to operate in a derating mode or even stop operation can be selected. From the perspective of safe operation of a power grid, the wind turbine generator is required to participate in active scheduling and frequency adjustment. The wind turbine generator can maintain the reactive balance of a power grid, the wind power plant can realize the voltage control, and when the power grid is disturbed, the wind power plant needs to inject reactive power into the power grid as soon as possible, so that the influence of faults on the power grid is reduced, and the system stability is improved. Therefore, the active/reactive adjustable range of the DFIG needs to be determined, and the operation safety of the power grid is guaranteed. When the system has enough reactive power, the reactive power optimization of the power grid containing the wind power system is needed, and the voltage fluctuation generated during the wind power integration is reduced.
In the existing research, when aiming at a reactive Power optimization problem, in a model constraint condition, the active output of the DFIG is generally set from 0 to the Maximum output, and the reactive output of the DFIG is generally set to a reactive output range obtained in a single machine Maximum Power Point Tracking (MPPT) mode. However, like a synchronous motor, the DFIG also has a lower active output limit, and the output range of the DFIG should be from the lower active output limit to the maximum output at the current wind speed, so that the DFIG cannot regard its active output as a parameter that continuously changes from 0. The magnitude of the reactive power of the DFIG depends on the real power, so that the range of the reactive power is affected when the real output of the DFIG changes. The calculation of the active power of the DFIG needs to provide a reactive set value to solve the active power, so that the reactive power output of the DFIG can also influence the active power of the DFIG.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a reactive power optimization method for a wind power system, which takes the DFIG output range into consideration and alternatively solves the problems, so that the mutual influence between the DFIG output powers can be considered, and the active/reactive power output range of the DFIG can be accurately calculated, thereby obtaining a better reactive power optimization effect and improving the operation stability of a power grid.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention relates to a wind power system reactive power optimization method considering alternative solving of a DFIG output range, which is characterized by comprising the following steps of:
s1, establishing maximum workAn internal power flow model of the doubly-fed induction machine DFIG in the MPPT mode is tracked through the rate point, and the reactive power set value Q of the doubly-fed induction machine DFIG is obtained DFIG,set Calculating the upper limit of active power output;
based on internal constraint of the DFIG of the doubly-fed induction motor, calculating the upper limit Q of reactive power output of the DFIG in the MPPT mode by using the upper limit of active power output DFIG,max And lower limit of reactive power Q DFIG,min Thereby obtaining the reactive output Q of the DFIG DFIG A range;
s2, establishing an active power lower limit model of the DFIG of the doubly-fed induction motor, and calculating an active power lower limit, so that an active power output range of the DFIG is obtained according to the active power upper limit and the active power lower limit;
s3, merging the internal power flow model and the active power output lower limit model of the DFIG of the doubly-fed induction motor into the power grid to obtain a DFIG grid-connected power flow model and an active power output lower limit model of the wind power system, and calculating an active power output upper limit P after grid connection DFIG,max And the lower limit P of active power output after grid connection DFIG,min Obtaining the active power output range of the DFIG after grid connection;
s4, calculating the reactive power output range of the DFIG after grid connection by using the active power output range of the DFIG after grid connection, and thus iteratively calculating to obtain the DFIG power output range after grid connection;
s4.1, setting the iteration precision to be epsilon, defining the current iteration frequency to be k, and initializing k =1;
defining the upper limit of the reactive power output of the DFIG of the k-1 iteration as
Figure BDA0003994667080000021
And initialize
Figure BDA0003994667080000022
Defining the upper limit of the active output of the DFIG of the k-1 iteration as
Figure BDA0003994667080000023
And initialize
Figure BDA0003994667080000024
S4.2, according to the active output upper limit of the DFIG of the k-1 iteration
Figure BDA0003994667080000025
Calculating the upper limit of the reactive power output of the DFIG of the kth iteration in the wind power system
Figure BDA0003994667080000026
Limiting the upper limit of the reactive power output of the DFIG of the k iteration
Figure BDA0003994667080000027
Substituting for reactive set value Q in DFIG grid-connected power flow model and active output lower limit model DFIG,set And then, calculating the upper limit of the DFIG reactive power output of the wind power system of the (k + 1) th iteration
Figure BDA0003994667080000028
And upper limit of reactive power
Figure BDA0003994667080000029
Thereby obtaining the DFIG active output range of the wind power system of the (k + 1) th iteration;
s4.3, utilizing the upper limit of the active power output of the DFIG of the (k + 1) th iteration
Figure BDA00039946670800000210
Calculating the upper limit of the DFIG reactive power output of the wind power system of the (k + 1) th iteration
Figure BDA00039946670800000211
And upper limit of reactive power
Figure BDA00039946670800000212
Thereby obtaining the reactive power output range of the DFIG of the wind power system after the k +1 th iteration;
s4.4, calculating the DFIG active output upper limit of the wind power system of the (k + 2) th iteration according to the process of the step S4.2
Figure BDA00039946670800000213
S4.5, calculating the difference value of the upper limit of the active power output of the DFIG of the wind power system by using the formula (1)
Figure BDA00039946670800000214
Figure BDA00039946670800000215
S4.6, if
Figure BDA0003994667080000031
Assigning k +1 to k, returning to the step S4.2 for sequential execution, otherwise, obtaining the active output range and the reactive output range of the DFIG in the wind power system of the (k + 1) th iteration, and recording the reactive output range of the DFIG as a first reactive output range;
s4.7, defining the lower limit of the active output of the DFIG of the k-1 iteration as
Figure BDA0003994667080000032
And initialize
Figure BDA0003994667080000033
Obtaining the reactive power output range of the DFIG in the wind power system of the (k + 1) th iteration according to the process from S4.2 to S4.6, and recording the reactive power output range as a second reactive power output range;
s4.8, taking the first reactive power output range and the second reactive power output range as a reactive power output range of the DFIG in the wind power system after merging;
s5, establishing a reactive power optimization model of the wind power system for alternately solving the output range of the DFIG, wherein the model comprises the following steps: the method comprises the following steps of (1) operating constraint conditions of the wind power system and a target function considering the active power network loss of the wind power system;
the objective function is a function with minimum active network loss of the power network, and the operation constraint conditions include: a constraint equation of node power balance, a constraint equation of active and reactive power output ranges of the DFIG, a constraint equation of node voltage amplitude and phase angle, a constraint equation of transformer transformation ratio and a constraint equation of parallel capacitor capacity;
and S6, solving a reactive power optimization model of the wind power system by utilizing a particle swarm optimization-Hui wolf algorithm PSO-GWOO, and outputting an optimal node voltage and active network loss.
The wind power system reactive power optimization method considering the alternative solution of the DFIG output range is also characterized in that the step S1 comprises the following steps:
s1.1, constructing a DFIG internal power flow model in the MPPT mode by using the formula (2):
Figure BDA0003994667080000034
in formula (2): delta Q s For the reactive equilibrium equation of the stator, Δ P m And Δ Q m For the active and reactive equilibrium equations of the excitation circuit, Δ P g And Δ Q g For the active and reactive balance equations of the converter, Δ T is the balance torque equation, Q DFIG,set Is the reactive set point, Q, of the DFIG sm Reactive power, Q, for stator flow excitation sg For reactive power of the stator flowing to the converter, P ms And Q ms Active and reactive power, P, flowing to the stator for excitation mr And Q mr Active and reactive power, Q, flowing to the rotor for excitation mm For reactive power in the excitation circuit, P rm Active power, P, for rotor flow direction excitation gs And Q gs For active and reactive power, Q, flowing to the stator of the converter g,set For the reactive setting of the grid-side converter, P wt Capturing power for wind turbines, P em The electromagnetic power of the DFIG is shown, and s is slip;
s1.2, according to a reactive set value Q of the DFIG of the doubly-fed induction motor DFIG,set Calculating the upper limit P of active power output of the DFIG DFIG,max ；
S1.3, constructing stator current constraint by using an equation (3):
Figure BDA0003994667080000041
in formula (3): u shape s Is the stator voltage, I s Is stator current, I s,max Is the maximum stator current, r s Radius of the reactive power output range at the stator side;
s1.4, constructing rotor current constraint by using an equation (4):
Figure BDA0003994667080000042
in formula (4): x s 、X m Respectively stator side reactance and excitation reactance, I r Is the rotor current, I r,max At maximum rotor current, r r Radius of the rotor side reactive power output range;
s1.5, constructing an operation range considering slip power by using an equation (6):
Figure BDA0003994667080000043
in formula (5): p DFIG Is the active power of DFIG, and P sm ＝P DFIG /(1-s)；
S1.6, constructing the capacity constraint of the grid-side converter by using the formula (7):
Figure BDA0003994667080000044
in formula (6): q DFIG For reactive power, S, of DFIG GSC,N The rated capacity of the grid-side converter;
s1.7, obtaining the reactive power operation range of the doubly-fed induction machine DFIG in the tracking MPPT mode by using the formula (7):
Figure BDA0003994667080000045
in formula (7): q DFIG,max Upper limit of reactive power, Q, of DFIG DFIG,min Is the lower reactive power limit of the DFIG.
The step S2 includes:
s2.1, establishing an active power lower limit model of the doubly-fed induction motor DFIG by using the formula (8):
Figure BDA0003994667080000051
in formula (8): s RSC,N Rated capacity, U, of rotor-side converter RSC r Is the rotor voltage, U m To the excitation voltage, [ theta ] rm Is rotor to excitation phase difference, R r And X r Is a rotor resistance and a rotor reactance, and has:
Figure BDA0003994667080000052
equation (9) is the capacity constraint of the rotor side converter RSC;
and S2.2, calculating the lower active output limit of the DFIG according to the lower active output limit model of the DFIG of the doubly-fed induction motor, so that the upper active output limit and the lower active output limit of the DFIG form the active output range of the DFIG.
The S3 comprises the following steps:
s3.1, respectively establishing a DFIG active output upper limit model and a DFIG active output lower limit model of the wind power system by using the formula (10) and the formula (11);
Figure BDA0003994667080000053
Figure BDA0003994667080000061
in formulae (10) and (11): delta P sys 、ΔQ sys Respectively the active and reactive unbalance of the grid node, delta theta sys 、ΔU sys Correction of phase angle and voltage for grid nodes, J sys Matrix for the derivation of node parameters of a wind power system from nodes of the wind power system, J sys,DFIG Matrix for derivation of DFIG node parameters for wind power system nodes，J DFIG,sys Matrix for derivation of node parameters of wind power system for DFIG nodes, J DFIG A matrix for deriving the DFIG node parameters for the DFIG node;
s3.2, calculating the upper limit P of the active output of the DFIG of the wind power system DFIG,max And DFIG active power lower limit P DFIG,min 。
Calculating the node voltage influenced by the power flow of the wind power system by using the formula (12), and obtaining the stator node voltage U of the DFIG of the wind power system by using the formula (13) s ：
Figure BDA0003994667080000062
U s ＝f(ΔU sys ) (13)。
The S6 comprises the following steps:
s6.1, initializing a Huilus wolf population parameter: setting the maximum iteration number as N, the current iteration number as m, initializing m =1, setting the grey wolf individual position as W, and setting the position of each grey wolf as a parameter in the target function of the step S5;
s6.2, calculating the fitness value of each wolf individual in the mth generation wolf population, and setting the first 3 optimal fitness values as the optimal wolf individual alpha in the mth generation wolf population m 、β m 、λ m And their corresponding position is correspondingly noted
Figure BDA0003994667080000063
S6.3, determining the ith grey wolf individual and the optimal grey wolf individual alpha in the mth grey wolf generation population by using the formula (14) m 、β m 、λ m Is a distance of
Figure BDA0003994667080000064
Then, updating each wolf generation in the mth generation wolf population at the optimal wolf generation wolf individual alpha by using the formula (15) m 、β m 、λ m Post-guided position W 1 m 、W 2 m 、W 3 m ；
Figure BDA0003994667080000071
Figure BDA0003994667080000072
In the formula (14), C 1 、C 2 、C 3 Is a wobble factor and is [0,1]A random number in between;
in the formula (15), A 1 、A 2 、A 3 Is a convergence factor;
s6.4, obtaining the position W of the ith grey wolf individual after updating in the mth grey wolf population by using the formula (16) i m ；
Figure BDA0003994667080000073
S6.4, updating the moving speed V of the ith grey wolf individual in the mth grey wolf generation population by using a formula (17) i m And position W i m Thereby obtaining the moving speed V of the wolf individuals in the m +1 th generation wolf population i m+1 And position W i m+1 ；
Figure BDA0003994667080000074
In the formula (17), c 1 、c 2 、c 3 As a learning factor, rand 3 Is [0,1 ]]A random number in between;
s6.5, calculating the position of each wolf generation m +1 wolf population according to the steps S6.2-S6.4 and forming a m +1 wolf generation position vector W m+1
S6.5, after m +1 is assigned to m, m is judged>N is established, if it is, the m-th generation optimum wolf direction vector W is output m And is used as the optimal solution of the target function, otherwise, the step S6.2 is returned to for execution in sequence;
and S6.6, calculating the optimal node voltage and the active network loss according to the optimal solution of the objective function.
The invention relates to an electronic device, which comprises a memory and a processor, wherein the memory is used for storing a program for supporting the processor to execute the wind power system reactive power optimization method, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, executes the steps of the method for reactive power optimization of a wind power system.
Compared with the prior art, the invention has the beneficial effects that:
firstly, establishing DFIG initial value analytic expression in a rotor overspeed active standby mode, adding RSC capacity constraint on the basis, and establishing a DFIG active lower limit solving algorithm; on the basis of considering the current constraint of the stator and the rotor and the capacity constraint of the grid-side converter, the influence of the active output of the DFIG on the reactive output is also considered, and the obtained active output is substituted into a DFIG reactive operation range calculation formula, so that more accurate Q can be obtained DFIG A range; a DFIG output iterative algorithm is provided, and a reactive power optimization model is established on the basis, so that the active power network loss on the power grid side can be effectively reduced, and the method has the advantages of ensuring the stability and safety of the operation of a power system.
Drawings
FIG. 1 is a block diagram of a prior art DFIG;
FIG. 2 shows the present invention P DFIG And Q DFIG A flow chart of steps of simultaneous iterations.
Detailed Description
In this embodiment, a wind power system reactive power optimization method considering alternative solutions of a DFIG output range includes the following steps:
s1, establishing an internal power flow model of the DFIG of the doubly-fed induction motor in a Maximum Power Point Tracking (MPPT) mode by using the graph 1, and setting a reactive power set value Q of the DFIG according to the Maximum Power Point Tracking (MPPT) mode DFIG,set Calculating the upper limit P of active power output DFIG,max ；
Based on internal constraint of DFIG (doubly-fed induction generator), active power output upper limit P is utilized DFIG,max Calculating the upper limit Q of reactive power output of DFIG in the MPPT mode DFIG,max And lower limit of reactive power Q DFIG,min Obtaining the reactive power output range of the DFIG;
s1.1, constructing a DFIG internal power flow model in the MPPT mode by using the formula (1):
Figure BDA0003994667080000081
in formula (1): delta Q s For the reactive equilibrium equation of the stator, Δ P m And Δ Q m For the active and reactive equilibrium equations, Δ P, of the excitation loop g And Δ Q g For the active and reactive balance equations of the converter, Δ T is the balance torque equation, Q DFIG,set For reactive setting of DFIG, Q sm Reactive power, Q, for stator flow to excitation sg For reactive power of the stator flowing to the converter, P ms And Q ms Active and reactive power, P, flowing to the stator for excitation mr And Q mr Active and reactive power, Q, flowing to the rotor for excitation mm For reactive power in the excitation circuit, P rm Active power for rotor flow direction excitation, P gs And Q gs For active and reactive power, Q, flowing to the stator of the converter g,set For the reactive setting of the grid-side converter, P wt Capturing power for wind turbines, P em The electromagnetic power of the DFIG is shown, and s is slip;
s1.2, according to a reactive set value Q of the DFIG of the doubly-fed induction motor DFIG,set Calculating the active power upper limit P of the DFIG DFIG,max ；
S1.3, constructing stator current constraint by using an equation (2):
Figure BDA0003994667080000091
in the formula (2): u shape s Is the stator voltage, I s Is stator current, I s,max Is the maximum stator current, r s Radius of the reactive power output range at the stator side;
s1.4, constructing rotor current constraint by using an equation (3):
Figure BDA0003994667080000092
in formula (3): x s 、X m Respectively stator side reactance and excitation reactance, I r Is the rotor current, I r,max Is the maximum rotor current, r r Radius of the rotor side reactive power output range;
s1.5, constructing an operation range considering slip power by using an equation (4):
Figure BDA0003994667080000093
in formula (4): p DFIG Is the active power of DFIG, and P sm ＝P DFIG /(1-s)；
S1.6, constructing the capacity constraint of the grid-side converter by using the formula (5):
Figure BDA0003994667080000094
in formula (5): q DFIG Is the reactive power, S, of the DFIG GSC,N The rated capacity of the grid-side converter;
s1.7, obtaining the reactive power operation range of the doubly-fed induction machine DFIG in the tracking MPPT mode by using the formula (6):
Figure BDA0003994667080000095
in formula (6): q DFIG,max Is the upper limit of reactive power output, Q, of the DFIG DFIG,min Is the lower reactive power output limit of the DFIG.
S2, establishing an active power output lower limit model of the DFIG of the doubly-fed induction motor, and calculating an active power output lower limit P DFIG,min Thereby coming out according to the real powerThe upper limit and the lower limit of the force are obtained to obtain the active force range of the DFIG;
s2.1, establishing an active power lower limit model of the doubly-fed induction motor DFIG by using the formula (7):
Figure BDA0003994667080000101
in formula (7): s RSC,N Rated capacity, U, of rotor-side converter RSC r Is the rotor voltage, U m To the excitation voltage, [ theta ] rm Is rotor to excitation phase difference, R r And X r Is a rotor resistance and a rotor reactance, and has:
Figure BDA0003994667080000102
equation (8) is the capacity constraint of the rotor side converter RSC;
and S2.2, calculating the lower active output limit of the DFIG according to the lower active output limit model of the DFIG of the doubly-fed induction motor, so that the upper active output limit and the lower active output limit of the DFIG form the active output range of the DFIG.
S3, after an internal power flow model and an active power output lower limit model of the DFIG of the doubly-fed induction motor are merged into a power grid, a DFIG grid-connected power flow model and an active power output lower limit model of the wind power system are obtained, and an active power output range of the DFIG after grid connection is calculated;
s3.1, respectively establishing a DFIG active output upper limit model and a DFIG active output lower limit model of the wind power system by using the formulas (9) and (10);
Figure BDA0003994667080000103
Figure BDA0003994667080000111
in formulae (9) and (10): delta P sys 、ΔQ sys Active and inactive respectively of grid nodesAmount of work unbalance, Δ θ sys 、ΔU sys For the correction of the phase angle and voltage of the grid node, J sys Matrix for the derivation of the node parameters of the wind power system for the nodes of the wind power system, J sys,DFIG Matrix for derivation of DFIG node parameters for the wind power system node, J DFIG,sys Matrix for derivation of node parameters of wind power system for DFIG nodes, J DFIG A matrix for deriving the DFIG node parameters for the DFIG node;
s3.2, calculating the upper limit P of the active output of the DFIG of the wind power system DFIG,max And DFIG active power lower limit P DFIG,min ；
S3.3, calculating the node voltage influenced by the power flow of the wind power system by using the formula (10), and obtaining the stator node voltage U of the DFIG of the wind power system by using the formula (11) s ：
Figure BDA0003994667080000112
U s ＝f(ΔU sys ) (12)
S4, calculating the reactive power output range of the DFIG after grid connection by using the active power output range of the DFIG after grid connection, and performing iterative calculation to obtain the output range of the DFIG after grid connection, wherein the iterative flow is shown in FIG. 2;
s4.1, setting the iteration precision to be epsilon, defining the current iteration frequency to be k, and initializing k =1;
defining the upper limit of the reactive power output of the DFIG of the k-1 iteration as
Figure BDA0003994667080000113
And initialize
Figure BDA0003994667080000114
Defining the upper limit of the active output of the DFIG of the k-1 iteration as
Figure BDA0003994667080000115
And initialize
Figure BDA0003994667080000116
S4.2, according to the active output upper limit of the DFIG of the k-1 iteration
Figure BDA0003994667080000117
Calculating the upper limit of the reactive power output of the DFIG of the kth iteration in the wind power system
Figure BDA0003994667080000118
The upper limit of the reactive power output of the DFIG of the k iteration is calculated by using the formula (13)
Figure BDA0003994667080000119
Substituting for a reactive set value Q in a DFIG grid-connected power flow model and an active output lower limit model DFIG,set And then, calculating the upper limit of the DFIG reactive power output of the wind power system of the (k + 1) th iteration
Figure BDA00039946670800001110
And upper limit of reactive power
Figure BDA00039946670800001111
Thereby obtaining the DFIG active output range of the wind power system of the (k + 1) th iteration;
Figure BDA0003994667080000121
in the formula (13), the reaction mixture is,
Figure BDA0003994667080000122
for the reactive balance equation of the stator after the kth iteration,
Figure BDA0003994667080000123
for the reactive power of the stator flow to the excitation after the kth iteration,
Figure BDA0003994667080000124
the reactive power of the stator flowing to the converter after the kth iteration is obtained;
s4.3, utilizing the DFIG active power output of the k +1 th iterationLimit for
Figure BDA0003994667080000125
Calculating the upper limit of the DFIG reactive power output of the wind power system of the (k + 1) th iteration
Figure BDA0003994667080000126
And upper limit of reactive power
Figure BDA0003994667080000127
Thereby obtaining the reactive power output range of the DFIG of the wind power system after the k +1 th iteration;
s4.4, calculating the upper limit of the active output of the DFIG of the wind power system of the (k + 2) th iteration according to the process of the step S4.2
Figure BDA0003994667080000128
S4.5, calculating the difference value of the DFIG active output upper limit of the wind power system by using the formula (1)
Figure BDA0003994667080000129
Figure BDA00039946670800001210
S4.6, if Δ P DFIG >If epsilon is not higher than epsilon, the value of k +1 is assigned to k, the step S4.2 is returned to be executed in sequence, otherwise, the active output range and the reactive output range of the DFIG in the wind power system of the k +1 th iteration are obtained, and the reactive output range of the DFIG is marked as a first reactive output range;
s4.7, defining the lower limit of the active output of the DFIG of the k-1 iteration as
Figure BDA00039946670800001211
And initialize
Figure BDA00039946670800001212
According to the process from S4.2 to S4.6, the lower limit of active power output after grid connection
Figure BDA00039946670800001213
Processing to obtain a reactive power output range of the DFIG in the wind power system of the (k + 1) th iteration, and recording the reactive power output range as a second reactive power output range;
s4.8, taking the first reactive power output range and the second reactive power output range as a reactive power output range of the DFIG in the wind power system after merging;
s5, establishing a reactive power optimization model of the wind power system alternately solved by the DFIG output range, wherein the reactive power optimization model comprises the following steps: the method comprises the following steps of (1) operating constraint conditions of the wind power system and a target function considering the active power network loss of the wind power system;
Figure BDA00039946670800001214
in formula (15): p loss For line active network loss, N is the number of nodes, G ij For the conductance between nodes i and j, U i And theta i The voltage amplitude and phase angle, U, of node i, respectively j And theta j Respectively, the voltage magnitude and phase angle of node j.
The objective function is a function with minimum active network loss of the power grid, and the operation constraint conditions comprise: a constraint equation of node power balance, a constraint equation of active and reactive power output ranges of the DFIG, a constraint equation of node voltage amplitude and phase angle, a constraint equation of transformer transformation ratio and a constraint equation of parallel capacitor capacity;
grid node balance constraints
Figure BDA0003994667080000131
In formula (16): delta P i 、ΔQ i Respectively, the power unbalance amount at the node i; p is Gi 、Q Gi Respectively providing active power and reactive power for the thermal power generating unit at the node i; p Li 、Q Li Is the load power; p is i 、Q i Power is injected for the node.
And (3) DFIG operation range constraint:
Figure BDA0003994667080000132
node voltage amplitude and phase angle constraints:
Figure BDA0003994667080000133
transformer transformation ratio constraint:
T min ≤T≤T max (19)
in formula (19): t is min 、T max The lower limit and the upper limit of the adjustable transformer are respectively, and T is the gear of the adjustable transformer.
Capacity constraint of the parallel capacitor:
Q c,min ≤Q c ≤Q c,max (20)
in formula (20): q c,min 、Q c,max Lower and upper limits of the parallel capacitor capacity, Q, respectively c Is the parallel capacitor capacity.
And S6, solving a reactive power optimization model of the wind power system by utilizing a particle swarm optimization-gray wolf algorithm PSO-GWOO, and outputting the optimal node voltage and the active network loss.
S6.1, initializing a Huilus wolf population parameter: setting the maximum iteration number as N, the current iteration number as m, initializing m =1, setting the individual positions of the grey wolfs as W, and setting the position of each grey wolf as a parameter in the target function in the step S5;
s6.2, calculating the fitness value of each wolf generation population, and setting the first 3 optimal fitness values as the optimal wolf generation population alpha m 、β m 、λ m And the corresponding position is correspondingly recorded as
Figure BDA0003994667080000134
S6.3, determining the ith grey wolf individual and the optimal grey wolf individual alpha in the mth grey wolf population by using the formula (14) m 、β m 、λ m Is a distance of
Figure BDA0003994667080000135
Then, updating each wolf generation in the mth generation wolf population at the optimal wolf generation wolf individual alpha by using the formula (15) m 、β m 、λ m Post-guided position W 1 m 、W 2 m 、W 3 m ；
Figure BDA0003994667080000136
Figure BDA0003994667080000141
In the formula (14), C 1 、C 2 、C 3 Is a wobble factor and is [0,1]A random number in between;
in the formula (15), A 1 、A 2 、A 3 Is a convergence factor;
s6.4, obtaining the position W of the updated ith grey wolf individual in the mth grey wolf generation population by using the formula (16) i m ；
Figure BDA0003994667080000142
S6.4, updating the moving speed V of the ith grey wolf individual in the mth grey wolf generation population by using the formula (17) i m And position W i m Thereby obtaining the moving speed V of the wolf individuals in the m +1 th generation wolf population i m+1 And position W i m+1 ；
Figure BDA0003994667080000143
In the formula (17), c 1 、c 2 、c 3 As learning factor, rand 3 Is [0,1 ]]A random number in between;
s6.5, according to the steps S6.2-S6.4 calculating the position of each wolf individual in the m +1 generation wolf population and forming the m +1 generation wolf position vector W m+1
S6.5, after m +1 is assigned to m, m is judged>N is established, if it is, the m-th generation optimum wolf direction vector W is output m And the solution is used as the optimal solution of the objective function, otherwise, the step S6.2 is returned to be executed in sequence.
And S6.6, calculating the optimal node voltage and the active network loss according to the optimal solution of the objective function.
In this embodiment, an electronic device includes a memory and a processor, where the memory is used to store a program that supports the processor to execute the wind power system reactive power optimization method, and the processor is configured to execute the program stored in the memory.
In this embodiment, a computer-readable storage medium stores a computer program thereon, and the computer program is executed by a processor to perform the steps of the method for reactive power optimization of the wind power system.

Claims (8)

1. A wind power system reactive power optimization method considering alternative solving of a DFIG output range is characterized by comprising the following steps of:
s1, establishing an internal power flow model of the double-fed induction motor DFIG in a maximum power point tracking MPPT mode, and setting a reactive power set value Q of the double-fed induction motor DFIG DFIG,set Calculating the upper limit of active power output;
based on internal constraint of the DFIG of the doubly-fed induction motor, calculating the upper limit Q of reactive power output of the DFIG in the MPPT mode by using the upper limit of active power output DFIG,max And lower limit of reactive power Q DFIG,min Thereby obtaining the reactive output Q of the DFIG DFIG A range;
s2, establishing an active power lower limit model of the DFIG of the doubly-fed induction motor, and calculating an active power lower limit, so that an active power output range of the DFIG is obtained according to the active power upper limit and the active power lower limit;
s3, after the internal power flow model and the active power output lower limit model of the DFIG of the doubly-fed induction motor are merged into the power grid, the DFI of the wind power system is obtainedG grid-connected power flow model and active power output lower limit model, and calculating active power output upper limit P after grid connection DFIG,max And the lower limit P of active power output after grid connection DFIG,min Obtaining the active power output range of the DFIG after grid connection;
s4, calculating the reactive power output range of the DFIG after grid connection by using the active power output range of the DFIG after grid connection, and thus obtaining the DFIG output range after grid connection through iterative calculation;
s4.1, setting the iteration precision to be epsilon, defining the current iteration frequency to be k, and initializing k =1;
defining the upper limit of the reactive power output of the DFIG of the k-1 iteration as
Figure FDA0003994667070000011
And initialize
Figure FDA0003994667070000012
Defining the upper limit of the active output of the DFIG of the k-1 iteration as
Figure FDA0003994667070000013
And initialize
Figure FDA0003994667070000014
S4.2, according to the active output upper limit of the DFIG of the k-1 iteration
Figure FDA0003994667070000015
Calculating the upper limit of the reactive power output of the DFIG of the kth iteration in the wind power system
Figure FDA0003994667070000016
Limiting the DFIG reactive power output upper limit of the kth iteration
Figure FDA0003994667070000017
Substituting for reactive set value Q in DFIG grid-connected power flow model and active output lower limit model DFIG,set Then, calculate the firstDFIG (doubly Fed Induction Generator) reactive power output upper limit of k +1 iteration wind power system
Figure FDA0003994667070000018
And upper limit of reactive power output
Figure FDA0003994667070000019
Thereby obtaining the DFIG active output range of the wind power system of the (k + 1) th iteration;
s4.3, utilizing the active output upper limit of the DFIG of the (k + 1) th iteration
Figure FDA00039946670700000110
Calculating the upper limit of the DFIG reactive power output of the wind power system of the (k + 1) th iteration
Figure FDA00039946670700000111
And upper limit of reactive power output
Figure FDA00039946670700000112
Thereby obtaining the reactive power output range of the DFIG of the wind power system after the k +1 th iteration;
s4.4, calculating the upper limit of the active output of the DFIG of the wind power system of the (k + 2) th iteration according to the process of the step S4.2
Figure FDA00039946670700000113
S4.5, calculating the difference value of the DFIG active output upper limit of the wind power system by using the formula (1)
Figure FDA00039946670700000114
Figure FDA0003994667070000021
S4.6, if
Figure FDA0003994667070000022
Then k +1 is assigned toAfter k, returning to the step S4.2 for sequential execution, otherwise, representing that the active output range and the reactive output range of the DFIG in the wind power system of the (k + 1) th iteration are obtained, and recording the reactive output range of the DFIG as a first reactive output range;
s4.7, defining the lower limit of the active output of the DFIG of the k-1 iteration as
Figure FDA0003994667070000023
And initialize
Figure FDA0003994667070000024
Obtaining the reactive power output range of the DFIG in the wind power system of the (k + 1) th iteration according to the process from S4.2 to S4.6, and recording the reactive power output range as a second reactive power output range;
s4.8, taking the first reactive power output range and the second reactive power output range as a reactive power output range of the DFIG in the wind power system after merging;
s5, establishing a reactive power optimization model of the wind power system for alternately solving the output range of the DFIG, wherein the model comprises the following steps: the method comprises the following steps of (1) operating constraint conditions of the wind power system and an objective function considering the active network loss of the wind power system;
the objective function is a function with minimum active network loss of the power network, and the operation constraint conditions include: a constraint equation of node power balance, a constraint equation of active and reactive power output ranges of the DFIG, a constraint equation of node voltage amplitude and phase angle, a constraint equation of transformer transformation ratio and a constraint equation of parallel capacitor capacity;
and S6, solving the reactive power optimization model of the wind power system by utilizing a particle swarm optimization-gray wolf algorithm PSO-GWOO, and outputting the optimal node voltage and the active network loss.
2. The wind power system reactive power optimization method taking the DFIG output range alternative solution into account as set forth in claim 1, wherein the step S1 includes:
s1.1, constructing a DFIG internal power flow model in the MPPT mode by using the formula (2):
Figure FDA0003994667070000025
in formula (2): delta Q s For the reactive equilibrium equation of the stator, Δ P m And Δ Q m For the active and reactive equilibrium equations of the excitation circuit, Δ P g And Δ Q g For the active and reactive balance equations of the converter, Δ T is the balance torque equation, Q DFIG,set Is the reactive set point, Q, of the DFIG sm Reactive power, Q, for stator flow excitation sg For reactive power of the stator flowing to the converter, P ms And Q ms Active and reactive power, P, flowing to the stator for excitation mr And Q mr Active and reactive power, Q, flowing to the rotor for excitation mm For reactive power in the excitation circuit, P rm Active power, P, for rotor flow direction excitation gs And Q gs For active and reactive power, Q, flowing to the stator of the converter g,set For the reactive set-point, P, of the network-side converter wt Capturing power, P, for wind turbines em Is the electromagnetic power of the DFIG, and s is the slip;
s1.2, according to a reactive set value Q of the DFIG of the doubly-fed induction motor DFIG,set Calculating the upper limit P of active power output of the DFIG DFIG,max ；
S1.3, constructing stator current constraint by using an equation (3):
Figure FDA0003994667070000031
in formula (3): u shape s Is the stator voltage, I s Is stator current, I s,max Is the maximum stator current, r s Radius of the reactive power output range at the stator side;
s1.4, constructing rotor current constraint by using an equation (4):
Figure FDA0003994667070000032
in formula (4): x s 、X m Stator side reactance and excitation respectivelyMagnetic reactance, I r Is the rotor current, I r,max Is the maximum rotor current, r r Radius of the rotor side reactive power output range;
s1.5, constructing an operation range considering slip power by using an equation (6):
Figure FDA0003994667070000033
in formula (5): p DFIG Is the active power of DFIG, and P sm ＝P DFIG /(1-s)；
S1.6, constructing the capacity constraint of the grid-side converter by using the formula (7):
Figure FDA0003994667070000034
in formula (6): q DFIG Is the reactive power, S, of the DFIG GSC,N The rated capacity of the grid-side converter;
s1.7, obtaining the reactive operation range of the doubly-fed induction machine DFIG in the tracking MPPT mode by using the formula (7):
Figure FDA0003994667070000035
in formula (7): q DFIG,max Is the upper limit of reactive power output, Q, of the DFIG DFIG,min Is the lower reactive power output limit of the DFIG.
3. The wind power system reactive power optimization method taking into account alternative solutions of DFIG output ranges according to claim 2, wherein said step S2 includes:
s2.1, establishing an active output lower limit model of the doubly-fed induction machine DFIG by using the formula (8):
Figure FDA0003994667070000041
in formula (8): s. the RSC,N Rated capacity, U, of rotor-side converter RSC r Is the rotor voltage, U m To the excitation voltage, θ rm Is rotor to excitation phase difference, R r And X r Is a rotor resistance and a rotor reactance, and has:
Figure FDA0003994667070000042
equation (9) is the capacity constraint of the rotor side converter RSC;
and S2.2, calculating the lower active output limit of the DFIG according to the lower active output limit model of the DFIG of the doubly-fed induction motor, so that the upper active output limit and the lower active output limit of the DFIG form the active output range of the DFIG.
4. The wind power system reactive power optimization method taking into account DFIG output range alternation solution according to claim 3, wherein the S3 comprises:
s3.1, respectively establishing a DFIG active output upper limit model and a DFIG active output lower limit model of the wind power system by using the formula (10) and the formula (11);
Figure FDA0003994667070000043
Figure FDA0003994667070000051
in formulae (10) and (11): delta P sys 、ΔQ sys Respectively the active and reactive unbalance, delta theta, of the grid node sys 、ΔU sys For the correction of the phase angle and voltage of the grid node, J sys Matrix for the derivation of the node parameters of the wind power system for the nodes of the wind power system, J sys,DFIG Matrix for derivation of DFIG node parameters for the wind power system node, J DFIG,sys Matrix for derivation of node parameters of wind power system for DFIG nodes, J DFIG A matrix for deriving the DFIG node parameters for the DFIG node;
s3.2, calculating the upper limit P of the active output of the DFIG of the wind power system DFIG,max And DFIG active power lower limit P DFIG,min 。
5. The wind power system reactive power optimization method considering DFIG output range alternative solution as claimed in claim 4, wherein the node voltage after wind power system load flow influence is calculated by using equation (12), and stator node voltage U of DFIG of wind power system is obtained by using equation (13) s ：
Figure FDA0003994667070000052
U s ＝f(ΔU sys ) (13)。
6. The wind power system reactive power optimization method taking into account DFIG output range alternation solution as recited in claim 1, wherein said S6 comprises:
s6.1, initializing a wolf population parameter: setting the maximum iteration number as N, the current iteration number as m, initializing m =1, setting the grey wolf individual position as W, and setting the position of each grey wolf as a parameter in the target function of the step S5;
s6.2, calculating the fitness value of each wolf generation population, and setting the first 3 optimal fitness values as the optimal wolf generation population alpha m 、β m 、λ m And the corresponding position is correspondingly recorded as
Figure FDA0003994667070000053
S6.3, determining the ith grey wolf individual and the optimal grey wolf individual alpha in the mth grey wolf generation population by using the formula (14) m 、β m 、λ m Is a distance of
Figure FDA0003994667070000054
Rear, utilization type (15)Updating each wolf generation gray wolf population in the optimal wolf generation gray wolf individual alpha m 、β m 、λ m Post-guided position W 1 m 、
Figure FDA0003994667070000055
Figure FDA0003994667070000061
Figure FDA0003994667070000062
In the formula (14), C 1 、C 2 、C 3 Is a wobble factor and is [0,1]A random number in between;
in the formula (15), A 1 、A 2 、A 3 Is a convergence factor;
s6.4, obtaining the position W of the updated ith grey wolf individual in the mth grey wolf generation population by using the formula (16) i m ；
Figure FDA0003994667070000063
S6.4, updating the moving speed V of the ith grey wolf individual in the mth grey wolf generation population by using a formula (17) i m And position W i m Thereby obtaining the moving speed V of the wolf individuals in the m +1 th generation wolf population i m+1 And position W i m+1 ；
Figure FDA0003994667070000064
In the formula (17), c 1 、c 2 、c 3 As learning factor, rand 3 Is [0,1 ]]A random number in between;
s6.5, according to the stepsS6.2-S6.4 calculate the position of each individual wolf in the m +1 th generation wolf population and form an m +1 th generation wolf position vector W m+1
S6.5, assigning m +1 to m, and then judging m>If N is true, outputting the direction vector W of the mth generation of the optimal wolf individual m And is used as the optimal solution of the target function, otherwise, the step S6.2 is returned to be executed in sequence;
and S6.6, calculating the optimal node voltage and the active network loss according to the optimal solution of the objective function.
7. An electronic device comprising a memory and a processor, wherein the memory is used for storing a program for supporting the processor to execute the wind power system reactive power optimization method according to any one of claims 1 to 6, and the processor is configured to execute the program stored in the memory.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, performs the steps of the method for reactive power optimization of a wind power system according to any of claims 1 to 6.
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