CN115085275A - PID speed regulator parameter optimization method for wind power participating in frequency modulation - Google Patents
PID speed regulator parameter optimization method for wind power participating in frequency modulation Download PDFInfo
- Publication number
- CN115085275A CN115085275A CN202210890283.6A CN202210890283A CN115085275A CN 115085275 A CN115085275 A CN 115085275A CN 202210890283 A CN202210890283 A CN 202210890283A CN 115085275 A CN115085275 A CN 115085275A
- Authority
- CN
- China
- Prior art keywords
- frequency
- wind power
- frequency modulation
- dead zone
- speed regulator
- 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.)
- Pending
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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- 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
- H02J3/241—The oscillation concerning frequency
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/06—Wind turbines or wind farms
-
- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Evolutionary Computation (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Power Engineering (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Computational Linguistics (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Physiology (AREA)
- Genetics & Genomics (AREA)
- Computer Hardware Design (AREA)
- Geometry (AREA)
- Control Of Eletrric Generators (AREA)
Abstract
The invention discloses a PID speed regulator parameter optimization method for wind power participation frequency modulation, which adopts a small signal analysis method to construct a frequency response model for wind power participation frequency modulation; secondly, linearizing non-linear links such as wind power and hydropower dead zones by adopting a description function method, constructing a wind power participation frequency modulation frequency model containing a dead zone of a speed regulator, and equivalently simplifying the model according to an equivalent transformation rule; thirdly, according to the influence of the main parameters in the frequency response model on the frequency stability, constructing a primary frequency modulation performance index and a system damping index, and establishing a multi-objective optimization model; and finally, searching and updating PID speed regulator parameters by adopting an intelligent optimization algorithm, providing a method for inhibiting ultralow frequency oscillation by considering dead zone wind power participation frequency modulation, and effectively shortening the regulation time and inhibiting the ultralow frequency oscillation.
Description
Technical Field
The invention relates to the technical field of power grid safety and stability control, in particular to a PID speed regulator parameter optimization method for wind power participating in frequency modulation.
Background
The oscillation problem is the most important content in the small disturbance stability research of the power system. The traditional low-frequency oscillation is that continuous relative swing between the rotors of the motor is caused due to insufficient damping, the oscillation frequency is generally between 0.1 and 2.5Hz, and the oscillation is also called electromechanical oscillation. But in recent years some oscillation events with frequencies below the above range have occurred in real grids. The oscillation with oscillation periods of 10s and 14s respectively occurs in Tianguang direct current and Jinsu direct current island tests, the frequency fluctuation is obvious, the fluctuation amplitude respectively reaches +/-0.23 Hz and +/-0.26 Hz, and analysis shows that the event is the oscillation caused by the instability of a speed regulator link in a direct current island sending system of a hydroelectric power plant. With the development and construction of power grids in China, operating modes such as direct current transmission end islands and regional power grid asynchronous interconnection appear in a power system, the problem of frequency stability becomes a main risk threatening the safe and stable operation of the power grids, and in 2016 years of asynchronous networking tests of a Yunnan power grid and a southern power grid main grid, ultralow-frequency oscillation with oscillation frequency of about 0.05Hz and amplitude of +/-0.1 Hz appears in the Yunnan power grid, and the power grids at the transmission ends are seriously threatened. The ultralow frequency oscillation of the power system belongs to the problem of small disturbance frequency stability, is obviously lower than the electromechanical oscillation range of 0.1-2.5Hz, and is represented by the homodyne change of the rotating speed of all generators, the integral oscillation of the frequency of the whole network and not the relative motion among clusters in the network.
With the increase of grid-connected wind power capacity, wind power permeability is continuously improved, and a series of challenges are brought to safe and stable operation of a power system including frequency stability. In order to ensure the stable frequency of the high-permeability wind power accessed to the power grid, some recently published power grid guide rules of countries such as Germany, Canada, Ireland, Denmark, Spain, UK and the like clearly suggest that the wind turbine generator set should have similar inertial response and primary frequency modulation capability as the traditional synchronous generator set. The national standard GB/T published in 2011 of China, 19963 plus 2011 of technical provision for accessing wind power plants to a power system clearly indicates that a wind power generation unit has the capability of participating in primary frequency modulation of a power grid, so that wind power participation in frequency control is necessary requirement for future power grid development; however, the ultra-low frequency oscillation of the power system is affected by the high-permeability wind power integration considering the auxiliary frequency modulation function. The existing research on the ultra-low frequency oscillation suppression measure by wind power frequency modulation does not consider the influence of wind power frequency modulation on the ultra-low frequency oscillation by combining the primary frequency modulation performance and the system damping level under the conditions of wind power and water power occupation ratio and dynamic change of dead zone in the wind power frequency modulation process.
Disclosure of Invention
In order to solve the technical problems, the invention comprehensively considers the wind power participating primary frequency modulation characteristic and the influence of the dead zone link of the speed regulator on the frequency stability of the system, optimizes the main control parameters of the speed regulator by adopting a cuckoo intelligent optimization algorithm, and provides a PID speed regulator parameter optimization method for wind power participating in frequency modulation.
The technical scheme adopted by the invention is as follows: the invention relates to a PID speed regulator parameter optimization method for wind power participating in frequency modulation, which comprises the following steps:
step 1: a small signal analysis method is adopted to construct a frequency response model of wind power participating in frequency modulation, a virtual inertia control strategy, an overspeed control strategy and a pitch angle control strategy are selected, and the influence of the wind power frequency modulation on the ultralow frequency oscillation is analyzed;
and 2, step: nonlinear links such as wind power and hydropower dead zones are linearized by a descriptive function method, a wind power participation frequency modulation frequency model containing a speed regulator dead zone is constructed, and the model is equivalently simplified by moving a comparison point according to an equivalent transformation rule;
and step 3: according to the influence of the main parameters in the frequency model in the step 2 on the frequency stability, constructing a primary frequency modulation performance index A (K) and a system damping index B (K), and establishing a multi-target optimization model C (K) ═ a A (K) + bB (K);
and 4, step 4: searching by adopting intelligent optimization algorithmNew coefficient of proportionality K P Integral coefficient K I Differential coefficient K D The PID speed regulator parameters formed by parallel connection provide a method for restraining ultralow frequency oscillation by wind power participation frequency modulation considering dead zones.
Further, in step 1, in the actual operation of the power grid, a frequency response model of a traditional unit and transfer functions of a water turbine, a steam turbine and a generator are established by taking a thermal power generating unit and a hydroelectric power generating unit as typical prime systems:
in the formula: g ht And G st Transfer functions of water turbines and turbines, G hgov And Gs gov The transfer function of its corresponding PID regulator; delta omega is the variation of the rotating speed of the generator, and delta mu is the variation of the opening of the guide vane; t is W Is the water flow inertia time constant, B p Is the coefficient of variation, K P 、K I 、K D The proportional, integral and differential coefficients of the speed regulator are respectively; f HP Is the percentage of the steady state output power of the high pressure cylinder to the total output power of the steam turbine, T RH Is the intermediate reheat steam volume effect time constant, T CH Is the main air intake volume effect time constant; t is a unit of G Is a servo system time constant, and R is a primary frequency modulation droop system of the speed regulator; t is a unit of J Is the moment of inertia of the generator, Δ P m As a change in mechanical power, Δ P e The variable quantity of the electromagnetic power is D, and the damping coefficient of the generator is D; d is partial derivative, s is differential operator;
then, the system phase lag and the damping deterioration caused by the unreasonable water hammer effect of the hydroelectric generating set and the parameter setting of the PID speed regulator are analyzed, so that the ultralow frequency oscillation phenomenon in the high-proportion hydroelectric generating set is avoided, the wind power participation frequency modulation is considered on the basis of a traditional set frequency response model, a small signal analysis method is adopted to construct a wind power participation frequency modulation system frequency response model, and the mechanical power change of the wind power is expressed by a wind turbine model:
where ρ is the air density, C P The coefficient is the wind energy capture efficiency, lambda is the tip speed ratio, beta is the pitch angle, A is the blade wind energy capture area, and v is the wind speed;
and virtual inertia control, overspeed control and pitch angle control strategies are selected, and the influence of wind power participating in frequency modulation on ultralow frequency oscillation is analyzed.
Further, in the step 2, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone by analyzing the characteristics of the primary frequency modulation dead zone:
in the formula: x is the input of the dead zone, namely the frequency deviation value delta f of the system, y is the output of the dead zone, and a is the critical threshold of the dead zone;
on the basis of an original system model, dead zone links corresponding to a water turbine, a speed regulator of the water turbine and a wind power frequency modulation module are respectively considered, and a system frequency model containing the dead zone of the speed regulator is established; the original system model refers to a system frequency stability analysis model without considering dead zone links;
in view of the characteristics of ultralow frequency oscillation and the homodyne of all generators, local and regional oscillation does not exist, all generators are equivalent to a unit with an inertia center, water, electricity and wind power dead zones are equivalent according to an equivalent transformation rule, and a system is represented as a simplified system frequency analysis model with two parts of linearity and nonlinearity by moving comparison points;
the nonlinear dead zone link is linearized by adopting a function description method, the open loop part of the system is the series connection of a nonlinear link N (A) and a linear link G(s), and the closed loop frequency characteristic of the system is as follows:
the characteristic equation is as follows:
1+ n (a) G (j ω) ═ 0 (7):
G(jω)＝﹣1/N(A) (8)
the system stability is analyzed through the relative position between a G (j omega) curve and a-1/N (A) curve on a complex plane, namely a negative falling characteristic, and the influence of a dead zone on the system frequency stability is further analyzed.
Further, analyzing the influence of the dead zone on the frequency stability of the system includes the following two cases:
1) the system without considering the dead zone is stable, according to the Nyquist stability criterion, if the linear system is stable, the G (j ω) curve does not surround the point (-1, 0), the-1/n (a) curve is always positioned at the left side of the G (j ω) curve, and is not surrounded by the G (j ω) curve, so the nonlinear system with considering the dead zone is also stable;
2) the system without considering the dead zone is unstable, the G (j omega) curve surrounds a point (-1, 0) and forms an intersection with the-1/N (A) curve, and the corresponding amplitude at the intersection is set as A lim The dynamic behavior of the system has 2 situations: a) if the initial amplitude A < A lim If the working point is positioned on the left side of the intersection point and is not surrounded by the G (j omega) curve, the system is stable, the oscillation attenuation enables the A to be reduced, and the working point moves to the left until the oscillation is settled and tends to be stable; b) if the initial amplitude A > A lim If the working point is located on the right of the intersection point and is surrounded by the G (j omega) curve, the system is unstable, the oscillation diverges to increase A, the working point moves to the right, and the oscillation continuously diverges.
Further, in step 3, according to the simplified frequency model of the system with the dead zone, the analysis is not carried out under the strategies of virtual inertia control, overspeed control and pitch angle control respectivelyThe influence of the same parameter on the frequency stability of the system comprises the following steps: firstly, when wind power does not participate in frequency modulation, different wind power occupation ratios have influence on damping torque coefficients of a frequency response part of a system, and when the wind power participates in frequency modulation, different wind power occupation ratios have influence on damping torque coefficients of the frequency response part of the system; ② different water hammer time constants T W Influence on the damping characteristics of wind power and a water turbine; thirdly, the wind power participates in the change of the root track of the system before and after frequency modulation; fourthly, changing root tracks of different wind power ratio systems after the wind power participates in frequency modulation; different PID governor parameters, i.e. proportionality coefficient K P Integral coefficient K I Differential coefficient K D The effect on system frequency oscillation; sixthly, the influence of the wind power and hydropower dead zone size on the ultralow frequency oscillation;
in view of the influence of the different parameters on the frequency stability of the system, a performance index function A (K) reflecting the primary frequency modulation of the system is constructed:
A(K)＝∑k 1 T 0.9 +k 2 T s +k 3 P f (9)
in the formula: t is 0.9 The rising time T from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit reaches the target value of 90 percent s Represents the time from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit is stabilized, P f Representing the inverse modulation power, k 1 、k 2 、k 3 Weight coefficients respectively representing the parameters;
constructing an index B (K) of the damping level of the reaction system:
in the formula: d (f) is the algebraic sum of damping coefficients of an open-loop system transfer function consisting of the speed regulator, the water turbine and the wind turbine generator set under the concerned frequency band;
the two are combined to calculate and consider the comprehensive indexes of the primary frequency modulation performance and the ultra-low frequency band damping, and a multi-objective optimization function is constructed, namely
C(K)＝a A(K)+b B(K) (11)
Wherein a and b are the weight coefficients of A (K) and B (K), respectively.
Further, in step 4, a cuckoo optimization algorithm is adopted, and the nest positions are initialized by setting the nest number and the search space dimension:
according to the random walk mode and the principle of saving, safety and eliminating danger, the positions of the nests are updated, and the positions of the nests are reserved or changed according to the found probability, so that a group of optimal nest positions are obtained
Wherein:
in the formula, alpha is step length control quantity, and Levy is a random walk path; by searching for an optimal nest sequence, the PID speed regulator control parameters are updated iteratively, the current optimal nest position is reserved, a group of PID speed regulator control parameters which give consideration to primary frequency modulation and ultralow frequency oscillation suppression are obtained, and further, a method for suppressing ultralow frequency oscillation by wind power participation frequency modulation considering the dead zone of the speed regulator is provided.
The invention has the beneficial effects that:
1) on the basis of a traditional frequency stability analysis model, the method establishes a wind power grid frequency stability analysis model based on virtual inertia control, overspeed load shedding control and pitch angle control; the influence of the dead zone link of the hydroelectric and wind speed regulators is considered, and the analysis model is equivalently simplified according to the transformation rule;
2) in order to overcome the problem of nonlinearity of an analysis model, a description function method is applied to a wind power grid frequency stability analysis model; in order to analyze the stability of the wind power generation power system, a critical disturbance amplitude that triggers system frequency oscillations in the wind power control strategy is calculated.
3) And properly setting the dead zone changes of the hydroelectric and wind speed regulators and the wind power with different proportions to verify the analysis result. Establishing an optimization objective function based on the genetic algorithm, and finally calculating the optimal parameters of the PID through the internal continuous iteration of the genetic algorithm and the selection, crossing and variation of the population;
4) and comparing the performance of inhibiting ultralow frequency oscillation by different PID parameters under the condition that the hydropower dead zone is larger than the wind power dead zone. Simulation examples show that the large-scale wind power participating in frequency regulation can improve the damping characteristic of the system, and the provided optimal PID parameter setting measure based on the intelligent optimization algorithm can effectively shorten the regulation time and inhibit the ultralow frequency oscillation.
Drawings
FIG. 1 is a schematic flow chart of the method of the present invention
FIG. 2 is a schematic diagram of a frequency response model of a wind power-participating frequency modulation system;
FIG. 3 is a schematic diagram of a frequency model of a system with dead zones;
FIG. 4 is a simplified system frequency analysis model diagram;
FIG. 5 is a schematic diagram of a system open loop frequency characteristic, wherein (a) a small graph is the system open loop frequency characteristic of initial system instability; (b) the small graph is a stable system open loop frequency characteristic curve of an initial system;
FIG. 6 is a schematic diagram of a system frequency oscillation curve, wherein (a) the small graph is a system frequency oscillation curve with an amplitude greater than a critical amplitude; (b) the small graph is a system frequency oscillation curve with the amplitude smaller than the critical amplitude;
FIG. 7 is a diagram of a system frequency oscillation curve with amplitude much greater than the critical amplitude.
Detailed Description
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
As shown in FIG. 1, the PID speed regulator parameter optimization method for wind power participating in frequency modulation comprises the following steps:
step 1: a small signal analysis method is adopted to construct a frequency response model of wind power participating in frequency modulation, typical wind power control strategies such as virtual inertia control are selected, and the influence of wind power frequency modulation on ultralow frequency oscillation is analyzed. By analyzing the water hammer effect of the hydroelectric generating set, the phase lag and the damping deterioration of the system are caused, on the basis of a traditional high-proportion hydroelectric system frequency response model, a frequency stability analysis model of wind power participation frequency modulation is constructed by considering wind power participation frequency modulation, a virtual inertia control strategy, an overspeed control strategy and a pitch angle control strategy are selected, and the influence of the wind power participation frequency modulation on ultralow frequency oscillation is analyzed.
Step 2: nonlinear links such as wind power and hydropower dead zones are linearized by a description function method, a wind power participation frequency modulation frequency model containing a dead zone of a speed regulator is constructed, and the model is equivalently simplified by moving a comparison point according to an equivalent transformation rule. Analyzing the characteristic of a primary frequency modulation dead zone, linearizing a nonlinear link of the dead zone of the speed regulator by adopting a description function method, establishing a wind power participation frequency modulation frequency stability analysis model containing the dead zone of the speed regulator, carrying out equivalence on a hydroelectric power region and a wind power dead zone according to an equivalent transformation rule in view of the mechanism characteristic of ultralow frequency oscillation, simplifying the model by moving a comparison point, and constructing a single-machine equivalent model containing the dead zone of the wind power region and the dead zone of the hydroelectric power region.
And step 3: according to the influence of main parameters in the frequency response model on the frequency stability, a primary frequency modulation performance index A (K) and a system damping index B (K) are established, and a multi-objective optimization model is established. Selecting virtual inertia control, overspeed control and pitch angle control strategies, constructing a performance index of primary frequency modulation of the reaction system and an index of damping level of the reaction system, and combining different parameters (water hammer time constant T) W Proportional coefficient K of PID speed regulator P Integral coefficient K I Differential coefficient K D The dead zone size and the wind power ratio) on ultralow frequency oscillation, calculating and considering the comprehensive indexes of a primary frequency modulation performance index function A (K) and an ultralow frequency band damping level index B (K), and constructing a multi-target optimization model C (K) of a A (K) + b B (K).
And 4, step 4: searching and updating the scaling coefficient K by adopting an intelligent optimization algorithm P Integral coefficient K I Differential coefficient K D The PID speed regulator parameters formed by parallel connection provide a method for restraining ultralow frequency oscillation by wind power participation frequency modulation considering dead zones. According to the primary frequency modulation performance index and the index of the damping level of the reaction system, a cuckoo optimization algorithm is adopted, the PID speed regulator control parameter which gives consideration to the primary frequency modulation performance and the ultra-low frequency oscillation suppression is obtained by searching and updating the PID speed regulator parameter through searching the optimal nest sequence and reserving or changing the nest position according to the probability, and further, the method for suppressing the ultra-low frequency oscillation by the wind power participation frequency modulation considering the dead zone of the speed regulator is provided.
Further, in step 1, firstly, in the actual operation of the power grid, a thermal power generating unit and a hydroelectric generating unit are taken as typical prime systems, and a traditional unit frequency response model and transfer functions of a water turbine, a steam turbine and a generator are established:
in the formula: t is W Is the water flow inertia time constant, B p To adjust the difference coefficient, K P 、K I 、K D The proportional, integral and differential coefficients of the speed regulator are respectively; f HP Is the percentage of the steady state output power of the high pressure cylinder to the total output power of the steam turbine, T RH Is the intermediate reheat steam volume effect time constant; t is J Is the moment of inertia of the generator, Δ P m As a change in mechanical power, Δ P e D is the damping coefficient of the generator.
And then analyzing the system phase lag and damping deterioration caused by the unreasonable water hammer effect of the hydroelectric generating set and the parameter setting of the PID speed regulator, so that the ultralow frequency oscillation phenomenon including the mechanism and the characteristics of the ultralow frequency oscillation in the high-proportion hydroelectric generating set is generated, and on the basis of a traditional set frequency response model, considering the wind power participation frequency modulation, and constructing a wind power participation frequency modulation system frequency response model, as shown in figure 2. The mechanical power change of the wind power is represented by a wind turbine model:
in the formula: t is J Is the moment of inertia of the generator, Δ P m As a change in mechanical power, Δ P e D is the damping coefficient of the generator.
In the step 2, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone by analyzing the characteristics of the primary frequency modulation dead zone:
in the formula: x is the input of the dead zone, i.e. the frequency deviation value Δ f of the system, y is the output of the dead zone, and a is the critical threshold of the dead zone.
On the basis of an original system model, dead zone links corresponding to a water turbine, a speed regulator of the water turbine and a wind power frequency modulation module are respectively considered, and a system frequency model containing the dead zone is established as shown in figure 3. In view of the characteristics of ultra-low frequency oscillation and the homoordination of all generators, local and regional oscillation does not exist, all generators are equivalent to a unit with an inertia center, the water, electricity and wind dead zones are equivalent according to an equivalent transformation rule, and by moving a comparison point, a system can be represented as a simplified system frequency analysis model with two parts, namely linearity and nonlinearity, as shown in fig. 3. The nonlinear dead zone link is linearized by adopting a function description method, the open loop part of the system is the series connection of a nonlinear link N (A) and a linear link G(s), and the closed loop frequency characteristic of the system is as follows:
the characteristic equation is as follows:
1+ n (a) G (j ω) 0 (7) then:
G(jω)＝﹣1/N(A) (8)
analyzing the system stability through the relative position between a G (j omega) curve and a-1/N (A) curve (called negative inverted characteristic) on a complex plane, and further analyzing the influence of a dead zone on the system frequency stability, wherein the method comprises the following two conditions: 1) the system without regard to dead zone is stable. According to the Nyquist stability criterion, if the linear system is stable, the G (j omega) curve does not surround the point (-1, 0), the-1/N (A) curve is always positioned on the left side of the G (j omega) curve and is not surrounded by the G (j omega) curve, and the nonlinear system considering the dead zone is also stable; 2) a system that does not take into account dead zones is unstable. The G (j omega) curve surrounds a point (-1, 0), an intersection point appears with the-1/N (A) curve, and the corresponding amplitude at the intersection point is set as A lim The dynamic behavior of the system has 2 conditions: a) if the initial amplitude A < A lim If the working point is positioned on the left side of the intersection point and is not surrounded by the G (j omega) curve, the system is stable, the oscillation attenuation enables the A to be reduced, and the working point moves to the left until the oscillation is settled and tends to be stable; b) if the initial amplitude A > A lim If the working point is located on the right of the intersection point and is surrounded by the G (j omega) curve, the system is unstable, the oscillation diverges to increase A, the working point moves to the right, and the oscillation continuously diverges.
Further, in the step 3 and the step 4, according to the simplified system frequency model including the dead zone, the influence of different parameters on the system frequency stability is analyzed under the virtual inertia control, the overspeed control and the pitch angle control strategies respectively. Which comprises the following steps: firstly, when wind power does not participate in frequency modulation, the influence of different wind power proportions on the damping torque coefficient of the frequency response part of the system and the influence of different wind power proportions on the damping torque coefficient of the frequency response part of the system when the wind power participates in frequency modulation are realized; ② different water hammer time constants T W Influence on the damping characteristics of wind power and a water turbine; thirdly, the wind power participates in the change of the root track of the system before and after frequency modulation; fourthly, changing root tracks of different wind power ratio systems after the wind power participates in frequency modulation;different PID governor parameters (proportionality coefficient K) P Integral coefficient K I Differential coefficient K D ) The effect on system frequency oscillation; and sixthly, the influence of the wind power and hydropower dead zone size on the ultra-low frequency oscillation.
Now, taking the virtual inertia control strategy as an example, the above impact analysis mechanism is simulated and verified. If the initial system is unstable, set the damping coefficient D s The characteristic value of the oscillation mode of the system frequency without taking the dead zone into account is 0.0282+0.2700j, and the damping ratio is-0.1040. Considering the dead zone element, curves G (j ω) and-1/N (A) will have an intersection, as shown in the small graph of FIG. 5 (a). The amplitude at the intersection point is the critical amplitude, and the critical amplitude A is obtained lim 0.0024. If the initial system is stable, set D s The characteristic value of the oscillation mode of the system frequency without considering the dead zone is-0.0096 +0.2730j, and the damping ratio is 0.0350. For the dead zone characteristic, the curves have no intersection point regardless of the variation in the oscillation amplitude, as shown in the small graph (b) in fig. 5.
For the small graph (a) in fig. 5, when the system is unstable without considering the influence of the dead zone, the critical amplitude a is calculated lim Considering that the oscillation amplitude is greater than or less than the critical amplitude, if the amplitude a is set to 0.0026, the amplitude is greater than the critical amplitude a lim Considering the system oscillation curve before and after the dead zone, it is shown as a small graph (a) in fig. 6. From the simulation results, it can be seen that: considering that a system is unstable before and after a dead zone, oscillation in a dynamic process is dispersed, an open-loop frequency characteristic curve passes through a linear system equivalent to a nonlinear part, and along with the oscillation dispersion, the oscillation amplitude A of the system is continuously increased and finally reaches a limit position. If the set amplitude A is 0.0022, it is smaller than the critical amplitude A lim Considering the system oscillation curve before and after the dead zone, it is shown as a small graph (b) in fig. 6. From the simulation results, it can be seen that: the system instability before the dead zone is considered, the oscillation convergence of the dynamic process of the system is considered after the dead zone, the open-loop frequency characteristic curve does not pass through the linear system equivalent to the nonlinear part, and the closed-loop system is stable.
For the small graph (b) in fig. 6, when the influence of the dead zone is not considered and the system is stable, if the oscillation amplitude a is set to 0.1, it is much larger than the critical amplitude a lim Considering dead zoneThe front and rear system oscillation curves are shown in fig. 7 below. From the simulation results, it can be seen that: the system is stable before and after the dead zone is considered, the open loop frequency characteristic curve does not pass through the linear system equivalent to the nonlinear part, and the oscillation of the system in the dynamic process is converged.
In view of the influence of the different parameters on the frequency stability of the system, a performance index function A (K) reflecting the primary frequency modulation of the system is constructed:
A(K)＝∑k 1 T 0.9 +k 2 T s +k 3 P f (9)
in the formula: t is 0.9 And the rising time from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit reaches a target value of 90 percent is represented. T is s Represents the time from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit is stabilized, P f Representing the inverse modulation power, k 1 、k 2 、k 3 Each represents a weight coefficient of each parameter.
Constructing an index B (K) of the damping level of the reaction system:
in the formula: the damping coefficient algebraic sum of the open-loop system transfer function composed of the governor, the hydraulic turbine and the wind generating set under the concerned frequency band.
The two are combined to calculate and consider the comprehensive indexes of the primary frequency modulation performance and the ultra-low frequency band damping, and a multi-objective optimization function is constructed, namely
C(K)＝a A(K)+b B(K) (11)
The cuckoo optimization algorithm is adopted, and the nest positions are initialized by setting the nest number and searching space dimensions:
according to the random walk mode and the principle of saving, safety and going to risk, the position of the bird nest is updated according to the probability of being foundRetaining or changing the position of the nest to obtain a set of superior nest point positions
Wherein:
in the formula, α is a step control amount, and Levy is a random walk path. By searching for an optimal nest sequence, the PID speed regulator control parameters are updated iteratively, the current optimal nest position is reserved, a group of PID speed regulator control parameters which give consideration to primary frequency modulation and ultralow frequency oscillation suppression are obtained, and further, a method for suppressing ultralow frequency oscillation by wind power participation frequency modulation considering the dead zone of the speed regulator is provided.
According to the method, the influence of the hydropower and wind power dead zones on the stability of the system is considered, a system frequency model is constructed, and the convergence and divergence of system frequency oscillation before and after the dead zones are analyzed and considered by adopting a description function method through setting different oscillation amplitudes aiming at three typical wind power control strategies. The influence of important influence factors on the stability of the system is analyzed by setting two different scenes that the hydropower dead zone is smaller than the wind power dead zone and the hydropower dead zone is larger than the wind power dead zone, and different oscillation amplitudes and dead zone values, and the PID speed regulator parameters are optimized through an intelligent algorithm to inhibit ultralow frequency oscillation.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and all equivalent variations made by using the contents of the present specification and the drawings are within the protection scope of the present invention.
Claims (6)
1. A PID speed regulator parameter optimization method for wind power participating in frequency modulation is characterized by comprising the following steps:
step 1: a small signal analysis method is adopted to construct a frequency response model of wind power participating in frequency modulation, a virtual inertia control strategy, an overspeed control strategy and a pitch angle control strategy are selected, and the influence of the wind power frequency modulation on the ultralow frequency oscillation is analyzed;
step 2: nonlinear links such as wind power and hydropower dead zones are linearized by a descriptive function method, a wind power participation frequency modulation frequency model containing a speed regulator dead zone is constructed, and the model is equivalently simplified by moving a comparison point according to an equivalent transformation rule;
and step 3: according to the influence of parameters in the model in the step 2 on the frequency stability, constructing a primary frequency modulation performance index A (K) and a system damping index B (K), and establishing a multi-objective optimization model C (K) ═ a A (K) + b B (K);
and 4, step 4: searching and updating the scaling coefficient K by adopting an intelligent optimization algorithm P Integral coefficient K I Differential coefficient K D The PID speed regulator parameters formed by parallel connection provide a method for restraining ultralow frequency oscillation by wind power participation frequency modulation considering dead zones.
2. The PID speed regulator parameter optimization method for wind power participating in frequency modulation according to claim 1, characterized in that: in the step 1, firstly, a frequency response model of a traditional unit and transfer functions of a water turbine, a steam turbine and a generator are established by taking a thermal power generating unit and a hydroelectric generating unit as typical prime systems in the actual operation of a power grid:
in the formula: g ht And G st Transfer functions of water turbines and turbines, G hgov And Gs gov The transfer function of its corresponding PID regulator; delta omega is the variation of the rotating speed of the generator, and delta mu is the variation of the opening of the guide vane;T W is the water flow inertia time constant, B p To adjust the difference coefficient, K P 、K I 、K D The proportional, integral and differential coefficients of the speed regulator are respectively; f HP Is the percentage of the steady state output power of the high pressure cylinder to the total output power of the steam turbine, T RH Is the intermediate reheat steam volume effect time constant, T CH Is the main air intake volume effect time constant; t is G Is a servo system time constant, and R is a primary frequency modulation droop system of the speed regulator; t is J Is the moment of inertia of the generator, Δ P m As a change in mechanical power, Δ P e The variable quantity of the electromagnetic power is D, and the damping coefficient of the generator is D; d is partial derivative, s is differential operator;
then, the system phase lag and the damping deterioration caused by the unreasonable water hammer effect of the hydroelectric generating set and the parameter setting of the PID speed regulator are analyzed, so that the ultralow frequency oscillation phenomenon in the high-proportion hydroelectric generating set is avoided, the wind power participation frequency modulation is considered on the basis of a traditional set frequency response model, a small signal analysis method is adopted to construct a wind power participation frequency modulation system frequency response model, and the mechanical power change of the wind power is expressed by a wind turbine model:
where ρ is the air density, C P The coefficient is the wind energy capture efficiency, lambda is the tip speed ratio, beta is the pitch angle, A is the blade wind energy capture area, and v is the wind speed;
and virtual inertia control, overspeed control and pitch angle control strategies are selected, and the influence of wind power participating in frequency modulation on ultralow frequency oscillation is analyzed.
3. The PID speed regulator parameter optimization method for wind power participating in frequency modulation according to claim 1, characterized in that: in the step 2, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone by analyzing the characteristics of the primary frequency modulation dead zone:
in the formula: x is the input of the dead zone, namely the frequency deviation value delta f of the system, y is the output of the dead zone, and a is the critical threshold of the dead zone;
on the basis of an original system model, dead zone links corresponding to a water turbine, a speed regulator of the water turbine and a wind power frequency modulation module are respectively considered, and a system frequency model containing the dead zone of the speed regulator is established;
in view of the characteristics of ultralow frequency oscillation and the homodyne of all generators, local and regional oscillation does not exist, all generators are equivalent to a unit with an inertia center, water, electricity and wind power dead zones are equivalent according to an equivalent transformation rule, and a system is represented as a simplified system frequency analysis model with two parts of linearity and nonlinearity by moving comparison points;
the nonlinear dead zone link is linearized by adopting a function description method, the open loop part of the system is the series connection of a nonlinear link N (A) and a linear link G(s), and the closed loop frequency characteristic of the system is as follows:
the characteristic equation is as follows:
1+N(A)G(jω)＝0 (7)
then:
G(jω)＝﹣1/N(A) (8)
the system stability is analyzed through the relative position between a G (j omega) curve and a-1/N (A) curve on a complex plane, namely a negative falling characteristic, and the influence of a dead zone on the system frequency stability is further analyzed.
4. The PID speed regulator parameter optimization method for wind power participating in frequency modulation according to claim 3, characterized in that: analyzing the influence of the dead zone on the frequency stability of the system, including the following two cases:
1) the system without considering the dead zone is stable, according to the Nyquist stability criterion, if the linear system is stable, the G (j ω) curve does not surround the point (-1, 0), the-1/n (a) curve is always on the left side of the G (j ω) curve, and is not surrounded by the G (j ω) curve, so the nonlinear system with considering the dead zone is also stable;
2) the system without considering the dead zone is unstable, the G (j omega) curve surrounds a point (-1, 0) and forms an intersection with the-1/N (A) curve, and the corresponding amplitude at the intersection is set as A lim The dynamic behavior of the system has 2 conditions: a) if the initial amplitude A < A lim If the working point is positioned on the left side of the intersection point and is not surrounded by the G (j omega) curve, the system is stable, the oscillation attenuation enables the A to be reduced, and the working point moves to the left until the oscillation is settled and tends to be stable; b) if the initial amplitude A > A lim If the working point is located on the right of the intersection point and is surrounded by the G (j omega) curve, the system is unstable, the oscillation diverges to increase A, the working point moves to the right, and the oscillation continuously diverges.
5. The PID speed regulator parameter optimization method for wind power participating in frequency modulation according to claim 1, characterized in that: in step 3, according to the simplified frequency model of the system with the dead zone, the influence of different parameters on the frequency stability of the system is analyzed under the strategies of virtual inertia control, overspeed control and pitch angle control, wherein the method comprises the following steps: firstly, when wind power does not participate in frequency modulation, different wind power occupation ratios have influence on damping torque coefficients of a frequency response part of a system, and when the wind power participates in frequency modulation, different wind power occupation ratios have influence on damping torque coefficients of the frequency response part of the system; ② different water hammer time constants T W Influence on the damping characteristics of wind power and a water turbine; thirdly, the wind power participates in the change of the root track of the system before and after frequency modulation; fourthly, changing root tracks of different wind power ratio systems after the wind power participates in frequency modulation; different PID governor parameters, i.e. proportionality coefficient K P Integral coefficient K I Differential coefficient K D The effect on system frequency oscillation; sixthly, the influence of the wind power and hydropower dead zone size on the ultralow frequency oscillation;
in view of the influence of the different parameters on the frequency stability of the system, a performance index function A (K) reflecting the primary frequency modulation of the system is constructed:
A(K)＝∑k 1 T 0.9 +k 2 T s +k 3 P f (9)
in the formula: t is 0.9 The rising time T from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit reaches the target value of 90 percent s Represents the time from the time when the frequency difference exceeds the primary frequency modulation dead zone to the time when the active power of the unit is stabilized, P f Representing the inverse modulation power, k 1 、k 2 、k 3 Weight coefficients representing the respective parameters;
constructing an index B (K) of the damping level of the reaction system:
in the formula: d (f) is the algebraic sum of damping coefficients of an open-loop system transfer function consisting of the speed regulator, the water turbine and the wind generating set under the concerned frequency band;
the two are combined to calculate and consider the comprehensive indexes of the primary frequency modulation performance and the ultra-low frequency band damping, and a multi-objective optimization function is constructed, namely
C(K)＝a A(K)+b B(K) (11)
Wherein a and b are the weight coefficients of A (K) and B (K), respectively.
6. The PID speed regulator parameter optimization method for wind power participating in frequency modulation according to claim 5, characterized in that: in step 4, a cuckoo optimization algorithm is adopted, and the nest positions are initialized by setting the nest number and searching space dimensions:
according to the random walk mode and the principle of saving, safety and eliminating danger, the positions of the nests are updated, and the positions of the nests are reserved or changed according to the found probability, so that a group of optimal nest positions are obtained
Wherein:
in the formula, alpha is step length control quantity, and Levy is a random walk path; by searching for an optimal nest sequence, the PID speed regulator control parameters are updated iteratively, the current optimal nest position is reserved, a group of PID speed regulator control parameters which give consideration to primary frequency modulation and ultralow frequency oscillation suppression are obtained, and further, a method for suppressing ultralow frequency oscillation by wind power participation frequency modulation considering the dead zone of the speed regulator is provided.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890283.6A CN115085275A (en) | 2022-07-27 | 2022-07-27 | PID speed regulator parameter optimization method for wind power participating in frequency modulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210890283.6A CN115085275A (en) | 2022-07-27 | 2022-07-27 | PID speed regulator parameter optimization method for wind power participating in frequency modulation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115085275A true CN115085275A (en) | 2022-09-20 |
Family
ID=83242084
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210890283.6A Pending CN115085275A (en) | 2022-07-27 | 2022-07-27 | PID speed regulator parameter optimization method for wind power participating in frequency modulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115085275A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115663844A (en) * | 2022-11-02 | 2023-01-31 | 西南交通大学 | Analysis method for ultralow frequency oscillation stability margin of hydroelectric generating set |
| CN116436042A (en) * | 2023-06-13 | 2023-07-14 | 昆明理工大学 | Wind-water-fire system stability analysis method considering wind turbine frequency modulation dead zone |
-
2022
- 2022-07-27 CN CN202210890283.6A patent/CN115085275A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115663844A (en) * | 2022-11-02 | 2023-01-31 | 西南交通大学 | Analysis method for ultralow frequency oscillation stability margin of hydroelectric generating set |
| CN115663844B (en) * | 2022-11-02 | 2023-08-22 | 西南交通大学 | Analysis method for ultralow frequency oscillation stability margin of hydroelectric generating set |
| CN116436042A (en) * | 2023-06-13 | 2023-07-14 | 昆明理工大学 | Wind-water-fire system stability analysis method considering wind turbine frequency modulation dead zone |
| CN116436042B (en) * | 2023-06-13 | 2023-08-15 | 昆明理工大学 | Wind-water-fire system stability analysis method considering wind turbine frequency modulation dead zone |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115085275A (en) | PID speed regulator parameter optimization method for wind power participating in frequency modulation | |
| Guo et al. | Hydropower system operation stability considering the coupling effect of water potential energy in surge tank and power grid | |
| Lescher et al. | Switching LPV controllers for a variable speed pitch regulated wind turbine | |
| CN107800146A (en) | Take into account the governor parameter optimization method that primary frequency modulation and ultra-low frequency oscillation suppress | |
| CN112564127B (en) | Photovoltaic grid-connected power system frequency transient stability analysis method | |
| Muhando et al. | Disturbance rejection by dual pitch control and self-tuning regulator for wind turbine generator parametric uncertainty compensation | |
| CN115663844B (en) | Analysis method for ultralow frequency oscillation stability margin of hydroelectric generating set | |
| CN115459303A (en) | Self-adaptive control method for participating in primary frequency modulation of power grid by battery energy storage | |
| CN110445194B (en) | Primary frequency modulation capability optimization method based on different proportions of hydroelectric power and thermal power | |
| Ahmed et al. | An efficient coordinated strategy for frequency stability in hybrid power systems with renewables considering interline power flow controller and redox flow battery | |
| CN103606939B (en) | Based on the wind bavin hybrid power system LOAD FREQUENCY control method that sliding formwork controls | |
| Zhou et al. | Research on control methods and technology for reduction of large-scale wind turbine blade vibration | |
| Magdy et al. | Renewable power systems dynamic security | |
| CN115102193B (en) | System frequency secondary falling event prediction method considering wind power participation frequency modulation | |
| Metwally et al. | A genetic algorithm for optimum design of PID controller in multi area load frequency control for Egyptian electrical grid | |
| AlSoud et al. | Linear parameter varying robust control for wind turbine power regulation | |
| CN114285037A (en) | Method for determining control parameter stability region of regional electricity-gas integrated energy system | |
| Eide et al. | Control design methodologies for vibration mitigation on wind turbine systems | |
| Schlipf | Prospects of multivariable feedforward control of wind turbines using lidar | |
| Jin et al. | The impact research of delay time in steam turbine DEH on power grid | |
| Li et al. | Optimal control strategy of turbine governor parameters based on improved beetle antennae search algorithm | |
| Xu et al. | Process control optimization for hydroelectric power based on neural network algorithm | |
| Li et al. | Nonlinear state feedback-synergetic control for low frequency oscillation suppression in grid-connected pumped storage-wind power interconnection system | |
| Dao et al. | An intelligent CPSOGSA-based mixed H2/H∞ robust controller for the multi-hydro-turbine governing system with sharing common penstock | |
| Wang et al. | Frequency Control Strategy of Wind Turbines Based on Reduced-order Frequency Response Model |
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 |