A PID speed regulator parameter optimization method for wind power frequency regulation

Abstract

The present invention discloses a method for optimizing parameters of a PID speed regulator with wind power participating in frequency modulation, adopts a small signal analysis method to construct a frequency response model of wind power participating in frequency modulation; then adopts a describing function method to linearize nonlinear links such as wind power and hydropower dead zones, constructs a frequency model of wind power participating in frequency modulation containing a speed regulator dead zone, and performs equivalent simplification on the model according to an equivalent transformation rule; thirdly, according to the influence of main parameters in the frequency response model on frequency stability, a primary frequency modulation performance index and a system damping index are constructed, and a multi-objective optimization model is established; finally, an intelligent optimization algorithm is adopted to search and update PID speed regulator parameters, and a method for suppressing ultra-low frequency oscillation by wind power participating in frequency modulation considering the dead zone is given, which can more effectively shorten the regulation time and suppress ultra-low frequency oscillation.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid safety and stability control, and in particular to a method for optimizing parameters of a PID speed regulator in which wind power participates in frequency regulation. Background Art

[0002] Oscillation is the most important content in the study of small disturbance stability of power systems. Traditional low-frequency oscillation refers to the continuous relative swing between motor rotors caused by insufficient damping. The oscillation frequency is generally between 0.1-2.5Hz, also known as electromechanical oscillation. However, in recent years, some oscillation events with frequencies lower than the above range have appeared in actual power grids. In the Tianguang DC and Jinsu DC island tests, oscillations with oscillation periods of 10s and 14s respectively occurred, with obvious frequency fluctuations and fluctuation amplitudes of ±0.23Hz and ±0.26Hz respectively. Analysis shows that the above events are oscillations caused by the instability of the governor link in the DC island transmission system of the hydropower plant. With the development and construction of my country's power grid, DC sending-end islands and asynchronous interconnection of regional power grids have appeared in the power system. Frequency stability issues have become the main risk threatening the safe and stable operation of the power grid. In the asynchronous interconnection test between the Yunnan power grid and the main grid of the Southern Power Grid in 2016, the Yunnan power grid experienced ultra-low frequency oscillations with an oscillation frequency of about 0.05Hz and an amplitude of ±0.1Hz, posing a major threat to the sending-end power grid. Ultra-low frequency oscillations in power systems are small-disturbance frequency stability issues, which are significantly lower than the electromechanical oscillation range of 0.1-2.5 Hz. They manifest themselves as synchronous changes in the speed of all generators and overall oscillations of the entire network frequency, rather than relative movement between groups within the network.

[0003] With the increase of wind power capacity connected to the grid, the penetration rate of wind power continues to increase, which brings a series of challenges to the safe and stable operation of the power system, including frequency stability. In order to ensure the frequency stability of high-penetration wind power connected to the grid, some grid guidelines recently issued by countries such as Germany, Canada, Ireland, Denmark, Spain and the United Kingdom have clearly stated that wind turbines should have inertial response and primary frequency regulation capabilities similar to traditional synchronous generators. my country's national standard GB / T, 19963-2011 "Technical Regulations for Wind Farm Access to Power System" issued at the end of 2011 clearly pointed out that wind turbines should have the ability to participate in the primary frequency regulation of the grid. Therefore, wind power participation in frequency control is an inevitable requirement for the future development of the power grid; however, high-penetration wind power grid connection taking into account the auxiliary frequency regulation function has brought an impact on the ultra-low frequency oscillation of the power system. The existing research on the suppression measures of wind power participation in frequency regulation on ultra-low frequency oscillation has not considered the impact of wind power participation in frequency regulation on ultra-low frequency oscillation under the dynamic changes of wind power and hydropower proportions and dead zone size during wind power frequency regulation, combined with primary frequency regulation performance and system damping level. Summary of the invention

[0004] In order to solve the above technical problems, the present invention comprehensively considers the influence of wind power participating in primary frequency regulation and the dead zone of the speed regulator on the system frequency stability, adopts the cuckoo intelligent optimization algorithm to optimize the main control parameters of the speed regulator, and proposes a PID speed regulator parameter optimization method for wind power participating in frequency regulation.

[0005] The technical solution adopted by the present invention is: a PID speed regulator parameter optimization method for wind power participating in frequency regulation described in the present invention comprises the following steps:

[0006] Step 1: Use the small signal analysis method to build a frequency response model of wind power frequency modulation, select the virtual inertia control strategy, overspeed control strategy and pitch angle control strategy, and analyze the impact of wind power frequency modulation on ultra-low frequency oscillation;

[0007] Step 2: Use the describing function method to linearize the nonlinear links such as wind power and hydropower dead zones, build a frequency model of wind power participating in frequency regulation including the dead zone of the speed regulator, and simplify the model by moving the comparison point according to the equivalent transformation rule;

[0008] Step 3: According to the influence of the main parameters in the frequency model described in step 2 on the frequency stability, the primary frequency modulation performance index A(K) and the system damping index B(K) are constructed, and a multi-objective optimization model C(K)=aA(K)+bB(K) is established;

[0009] Step 4: Use intelligent optimization algorithm to search and update the proportional coefficient K P , integral coefficient K I , differential coefficient K D The parameters of the PID speed regulator composed of parallel connections are given, and a method for suppressing ultra-low frequency oscillation by wind power participating in frequency regulation considering the dead zone is given.

[0010] Furthermore, in step 1, firstly, in the actual operation of the power grid, taking thermal power units and hydropower units as typical prime movers, a frequency response model of a traditional unit and transfer functions of a turbine, a steam turbine and a generator are established:

[0011]

[0012]

[0013]

[0014] Where: G ht and G st are the transfer functions of the water turbine and steam turbine respectively, G hgov and Gs gov is the transfer function of the corresponding PID speed regulator; Δω is the change in generator speed, Δμ is the change in guide vane opening; T Wis the water flow inertia time constant, B p is the adjustment coefficient, K P , K I , K D They are the proportional, integral and differential coefficients of the speed regulator respectively; F HP is the percentage of the high pressure cylinder steady state output power to the total turbine output power, T RH is the time constant of volume effect of intermediate reheat steam, T CH T is the time constant of the main intake volume effect; G is the servo system time constant, R is the speed regulator primary frequency droop system; T J is the moment of inertia of the generator, ΔP m is the mechanical power change, ΔP e is the change of electromagnetic power, D is the generator damping coefficient; d is the partial derivative, s is the differential operator;

[0015] Then, the ultra-low frequency oscillation phenomenon in high-proportion hydropower units due to the water hammer effect of the hydropower units and the unreasonable setting of PID speed regulator parameters is analyzed. On the basis of the traditional unit frequency response model, the frequency response model of the wind power participating in the frequency regulation is considered, and the small signal analysis method is used to construct the frequency response model of the wind power participating in the frequency regulation system. The mechanical power change of wind power is represented by the wind turbine model:

[0016]

[0017] Where ρ is the air density, C P is the wind energy capture efficiency coefficient, λ is the tip speed ratio, β is the pitch angle, A is the blade wind energy capture area, and v is the wind speed;

[0018] The virtual inertia control, overspeed control and pitch angle control strategies are selected to analyze the impact of wind power participation in frequency regulation on ultra-low frequency oscillation.

[0019] Furthermore, in step 2, by analyzing the primary frequency modulation dead zone characteristics, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone:

[0020]

[0021] Where: x is the input of the dead zone, that is, the frequency deviation value Δf of the system, y is the output of the dead zone, and a is the critical threshold of the dead zone;

[0022] On the basis of the original system model, the dead zone links corresponding to the turbine and its speed governor, and the wind power frequency regulation module are considered respectively, and a system frequency model including the speed governor dead zone is established; the original system model refers to the system frequency stability analysis model without considering the dead zone link;

[0023] In view of the characteristics of ultra-low frequency oscillation and the synchronization of all generators, there is no local and inter-regional oscillation. All generators are equivalent to a unit with an inertia center, and according to the equivalent transformation rule, the dead zones of hydropower and wind power are equivalent. By moving the comparison point, the system is represented as a simplified system frequency analysis model with linear and nonlinear parts.

[0024] The nonlinear dead zone link is linearized by using the function description method. The open-loop part of the system is the series connection of the nonlinear link N(A) and the linear link G(s). The closed-loop frequency characteristic of the system is:

[0025]

[0026] The characteristic equation is:

[0027] 1+N(A)G(jω)=0 (7) Then:

[0028] G(jω)=﹣1 / N(A) (8)

[0029] The system stability is analyzed by the relative position of the G(jω) curve and the -1 / N(A) curve on the complex plane, that is, the negative inverse characteristic, and then the influence of the dead zone on the system frequency stability is analyzed.

[0030] Further, the impact of the dead zone on the system frequency stability is analyzed, including the following two cases:

[0031] 1) The system without considering the dead zone is stable. According to the Nyquist stability criterion, if the linear system is stable, the G(jω) curve does not surround the point (-1, 0), then the -1 / N(A) curve is always on the left side of the G(jω) curve and is not surrounded by the G(jω) curve. Therefore, the nonlinear system considering the dead zone is also stable;

[0032] 2) The system without considering the dead zone is unstable. The G(jω) curve surrounds the point (-1, 0) and intersects with the -1 / N(A) curve. Let the corresponding amplitude at the intersection be A. lim , the system dynamic behavior has two situations: a) If the initial amplitude A<A lim , then the operating point is located to the left of the intersection, not surrounded by the G(jω) curve, the system is stable, the oscillation decays so that A decreases, and the operating point moves to the left until the oscillation subsides and becomes stable; b) If the initial amplitude A>A lim , then the operating point is located to the right of the intersection and is surrounded by the G(jω) curve. The system is unstable, the oscillation diverges, causing A to increase, the operating point moves to the right, and the oscillation continues to diverge.

[0033] Furthermore, in step 3, according to the simplified frequency model of the system with dead zone, the influence of different parameters on the system frequency stability is analyzed under the virtual inertia control, overspeed control, and pitch angle control strategies, including: ① the influence of different wind power proportions on the damping torque coefficient of the system frequency response part when wind power does not participate in frequency regulation, and the influence of different wind power proportions on the damping torque coefficient of the system frequency response part when wind power participates in frequency regulation; ② different water hammer time constants T W Impact on the damping characteristics of wind power and turbines; ③ Changes in the root locus of the system before and after wind power participates in frequency modulation; ④ Changes in the root locus of the system with different wind power proportions after wind power participates in frequency modulation; ⑤ Different PID speed regulator parameters, i.e., the proportional coefficient K P , integral coefficient K I , differential coefficient K D Impact on system frequency oscillation;⑥ Impact of wind power and hydropower dead zone size on ultra-low frequency oscillation;

[0034] In view of the influence of the above-mentioned different parameters on the system frequency stability, the performance index function A(K) of the primary frequency modulation of the reaction system is constructed:

[0035] A(K)=∑k1T 0.9 +k2T s +k3P f (9)

[0036] Where: T 0.9 It indicates the rising time from the time when the frequency difference exceeds the primary frequency regulation dead zone to the time when the unit active power reaches 90% of the target value, T s It indicates the time from when the frequency difference exceeds the frequency regulation dead zone to when the unit active power reaches stability, P f represents the reverse modulation power, k1, k2, k3 represent the weight coefficients of each parameter respectively;

[0037] Construct the index B(K) of the damping level of the reaction system:

[0038]

[0039] Where: D(f) is the algebraic sum of the damping coefficients of the open-loop system transfer function consisting of the governor, turbine and wind turbine in the frequency band of interest;

[0040] Combining the two calculations to consider the comprehensive index of primary frequency modulation performance and ultra-low frequency damping, a multi-objective optimization function is constructed, namely:

[0041] C(K)=aA(K)+bB(K) (11)

[0042] Where a and b are the weight coefficients of A(K) and B(K) respectively.

[0043] Furthermore, in step 4, the cuckoo optimization algorithm is used to initialize the nest position by setting the number of nests and the search space dimension:

[0044]

[0045] According to the random walk method and the principle of keeping safety and removing danger, the location of the bird's nest is updated, and the location of the bird's nest is retained or changed according to the probability of being discovered, so as to obtain a set of optimal nest locations. in:

[0046]

[0047] In the formula, α is the step size control variable, and Levy is the random walk path. By searching the optimal bird nest sequence, iteratively updating the PID speed regulator control parameters, and retaining the current optimal bird nest position, a set of PID speed regulator control parameters that take into account both primary frequency regulation and ultra-low frequency oscillation suppression are obtained, and then a method for suppressing ultra-low frequency oscillation by wind power participating in frequency regulation considering the dead zone of the speed regulator is given.

[0048] The beneficial effects of the present invention are:

[0049] 1) Based on the traditional frequency stability analysis model, the method of the present invention establishes a wind power grid frequency stability analysis model based on virtual inertia control, overspeed load reduction control and pitch angle control; considering the influence of the dead zone of hydropower and wind power governors, the analysis model is equivalently simplified according to the transformation rules;

[0050] 2) In order to overcome the nonlinear problem of the analysis model, the describing function method is applied to the wind power grid frequency stability analysis model; in order to analyze the stability of the wind power generation power system, the critical disturbance amplitude that triggers the system frequency oscillation in the wind power control strategy is calculated.

[0051] 3) Properly set the dead zone changes of hydropower and wind power governors and different proportions of wind power to verify the analysis results. And establish the optimization objective function based on the genetic algorithm, and finally calculate the optimal parameters of PID through the internal continuous iteration of the genetic algorithm, as well as the selection, crossover and mutation of the population;

[0052] 4) When the dead zone of hydropower is larger than the dead zone of wind power, the performance of suppressing ultra-low frequency oscillation with different PID parameters is compared. The simulation example shows that large-scale wind power participation in frequency regulation can improve the damping characteristics of the system, and the proposed optimal PID parameter setting measures based on intelligent optimization algorithm can more effectively shorten the regulation time and suppress ultra-low frequency oscillation. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 Schematic diagram of the process of the present invention

[0054] Figure 2 This is a schematic diagram of the frequency response model of the frequency regulation system with wind power participating;

[0055] Figure 3 It is a schematic diagram of the frequency model of the system including dead zone;

[0056] Figure 4 To simplify the schematic diagram of the system frequency analysis model;

[0057] Figure 5 Schematic diagram of the system open-loop frequency characteristic curve, wherein (a) is the system open-loop frequency characteristic curve when the initial system is unstable; (b) is the system open-loop frequency characteristic curve when the initial system is stable;

[0058] Figure 6 Schematic diagram of system frequency oscillation curve, where (a) is a system frequency oscillation curve with an amplitude greater than the critical amplitude; (b) is a system frequency oscillation curve with an amplitude less than the critical amplitude;

[0059] Figure 7 Schematic diagram of the system frequency oscillation curve with an amplitude much larger than the critical amplitude. DETAILED DESCRIPTION

[0060] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0061] like Figure 1 As shown, the method for optimizing parameters of a PID speed regulator for wind power frequency modulation described in the present invention comprises the following steps:

[0062] Step 1: Use the small signal analysis method to build a frequency response model of wind power participating in frequency modulation, select typical wind power control strategies such as virtual inertia control, and analyze the impact of wind power frequency modulation on ultra-low frequency oscillation. By analyzing the water hammer effect of hydropower units, which leads to system phase lag and damping deterioration, based on the traditional high-ratio hydropower system frequency response model, consider wind power participating in frequency modulation, build a frequency stability analysis model of wind power participating in frequency modulation, select virtual inertia control, overspeed control and pitch angle control strategies, and analyze the impact of wind power participating in frequency modulation on ultra-low frequency oscillation.

[0063] Step 2: Use the describing function method to linearize the nonlinear links such as wind power and hydropower dead zones, build a frequency model of wind power participating in frequency regulation including the speed regulator dead zone, and simplify the model by moving the comparison point according to the equivalent transformation rule. Analyze the characteristics of the primary frequency regulation dead zone, use the describing function method to linearize the nonlinear links of the speed regulator dead zone, establish a frequency stability analysis model of wind power participating in frequency regulation including the speed regulator dead zone, and in view of the mechanism characteristics of ultra-low frequency oscillation, according to the equivalent transformation rule, make the hydropower and wind power dead zones equivalent, simplify the model by moving the comparison point, and build a single-machine equivalent model including wind power dead zones and hydropower dead zones.

[0064] Step 3: According to the influence of the main parameters in the frequency response model on the frequency stability, the primary frequency regulation performance index A(K) and the system damping index B(K) are constructed, and a multi-objective optimization model is established. The virtual inertia control, overspeed control and pitch angle control strategies are selected to construct the performance index of the primary frequency regulation of the reaction system and the index of the damping level of the reaction system. W 、Proportional coefficient K of PID speed regulator P , integral coefficient K I , differential coefficient K D The influence of the primary frequency regulation performance index function A(K) and the ultra-low frequency damping level index B(K) is calculated, and a multi-objective optimization model C(K)=a A(K)+b B(K) is constructed.

[0065] Step 4: Use intelligent optimization algorithm to search and update the proportional coefficient K P , integral coefficient K I , differential coefficient K D The PID speed regulator parameters composed of parallel connections are given, and the method of suppressing ultra-low frequency oscillation by wind power participating in frequency modulation considering the dead zone is given. According to the primary frequency regulation performance index and the index of the damping level of the reaction system, the cuckoo optimization algorithm is used to search for the optimal bird nest sequence, retain or change the bird nest position according to the probability, search and update the PID speed regulator parameters, and obtain the PID speed regulator control parameters that take into account the primary frequency regulation performance and ultra-low frequency oscillation suppression. Then, the method of suppressing ultra-low frequency oscillation by wind power participating in frequency modulation considering the dead zone of the speed regulator is given.

[0066] Furthermore, in step 1, firstly, in the actual operation of the power grid, taking thermal power units and hydropower units as typical prime movers, a frequency response model of a traditional unit and transfer functions of a turbine, a steam turbine and a generator are established:

[0067]

[0068]

[0069]

[0070] Where: T W is the water flow inertia time constant, B p is the adjustment coefficient, K P , K I , K D They are the proportional, integral and differential coefficients of the speed regulator respectively; F HP is the percentage of the high pressure cylinder steady state output power to the total turbine output power, T RH is the time constant of volume effect of intermediate reheat steam; T J is the moment of inertia of the generator, ΔP m is the mechanical power change, ΔP e is the change of electromagnetic power, and D is the damping coefficient of the generator.

[0071] Then, the ultra-low frequency oscillation phenomenon in high-proportion hydropower units due to the water hammer effect of the hydropower units and the unreasonable setting of PID speed regulator parameters is analyzed, including the mechanism and characteristics of ultra-low frequency oscillation. On the basis of the traditional unit frequency response model, the frequency response model of the wind power participating in frequency regulation is constructed by considering the participation of wind power in frequency regulation. Figure 2 The mechanical power variation of wind power is represented by the wind turbine model:

[0072]

[0073] Where: T J is the moment of inertia of the generator, ΔP m is the mechanical power change, ΔP e is the change of electromagnetic power, and D is the damping coefficient of the generator.

[0074] In step 2, by analyzing the primary frequency modulation dead zone characteristics, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone:

[0075]

[0076] Where: x is the input of the dead zone, that is, the frequency deviation value Δf of the system, y is the output of the dead zone, and a is the critical threshold of the dead zone.

[0077] On the basis of the original system model, the dead zone links corresponding to the turbine and its speed regulator and the wind power frequency modulation module are considered respectively, and the system frequency model with dead zone is established as follows: Figure 3As shown. In view of the characteristics of ultra-low frequency oscillation and the synchronization of all generators, there is no local and inter-regional oscillation. All generators are equivalent to a unit with an inertia center, and according to the equivalent transformation rule, the dead zones of hydropower and wind power are equivalent. By moving the comparison point, the system can be expressed as a simplified system frequency analysis model with linear and nonlinear parts, as shown in Figure 3 The function description method is used to linearize the nonlinear dead zone link. The open-loop part of the system is the series connection of the nonlinear link N(A) and the linear link G(s). The closed-loop frequency characteristic of the system is:

[0078]

[0079] The characteristic equation is:

[0080] 1+N(A)G(jω)=0 (7) Then:

[0081] G(jω)=﹣1 / N(A) (8)

[0082] The system stability is analyzed by the relative position between the G(jω) curve and the -1 / N(A) curve (called the negative inverse characteristic) on the complex plane, and then the influence of the dead zone on the system frequency stability is analyzed, 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(jω) curve does not surround the point (-1, 0), then the -1 / N(A) curve is always on the left side of the G(jω) curve and is not surrounded by the G(jω) curve, then the nonlinear system considering the dead zone is also stable; 2) The system without considering the dead zone is unstable. The G(jω) curve surrounds the point (-1, 0) and has an intersection with the -1 / N(A) curve. Let the corresponding amplitude at the intersection be A lim , the system dynamic behavior has two situations: a) If the initial amplitude A<A lim , then the operating point is located to the left of the intersection, not surrounded by the G(jω) curve, the system is stable, the oscillation decays so that A decreases, and the operating point moves to the left until the oscillation subsides and becomes stable; b) If the initial amplitude A>A lim , then the operating point is located to the right of the intersection and is surrounded by the G(jω) curve. The system is unstable, the oscillation diverges, causing A to increase, the operating point moves to the right, and the oscillation continues to diverge.

[0083] Furthermore, in step 3 and step 4, according to the simplified system frequency model with dead zone, the influence of different parameters on the system frequency stability is analyzed under virtual inertia control, overspeed control, and pitch angle control strategies. These include: ① When wind power does not participate in frequency regulation, the influence of different wind power proportions on the damping torque coefficient of the system frequency response part, and when wind power participates in frequency regulation, the influence of different wind power proportions on the damping torque coefficient of the system frequency response part; ② Different water hammer time constants T WThe impact on the damping characteristics of wind power and turbines; ③ The changes in the root locus of the system before and after wind power participates in frequency modulation; ④ The changes in the root locus of the system with different wind power proportions after wind power participates in frequency modulation; ⑤ Different PID speed regulator parameters (proportional coefficient K P , integral coefficient K I , differential coefficient K D ) The impact of wind power and hydropower dead zone size on ultra-low frequency oscillation.

[0084] 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 =0.4, the characteristic value of the system frequency oscillation mode without considering the dead zone is 0.0282+0.2700j, and the damping ratio is -0.1040. Considering the dead zone link, the curve G(jω) and -1 / N(A) will have an intersection point, such as Figure 5 As shown in the small figure (a) in the figure. The amplitude at the intersection is the critical amplitude, and the critical amplitude A is obtained lim =0.0024. If the initial system is stable, set D s =1.25, the characteristic value of the system frequency oscillation mode without considering the dead zone is -0.0096+0.2730j, and the damping ratio is 0.0350. For the dead zone characteristics, no matter how the oscillation amplitude changes, the curve has no intersection, such as Figure 5 As shown in the sub-figure (b).

[0085] for Figure 5 In the (a) panel, when the dead zone is not considered, the system is unstable. According to the calculated critical amplitude A lim , consider the two cases where the oscillation amplitude is greater than or less than the critical amplitude. If the amplitude A is set to 0.0026, it is greater than the critical amplitude A lim , considering the system oscillation curve before and after the dead zone Figure 6 As shown in the small figure (a) in the figure. From the simulation results, it can be seen that the system is unstable before and after the dead zone, the dynamic process oscillates and diverges, and the open-loop frequency characteristic curve passes through the linear system equivalent to the nonlinear part. As the oscillation diverges, the system oscillation amplitude A continues to increase and eventually reaches the limit position. If the amplitude A is set to 0.0022, which is less than the critical amplitude A lim , considering the system oscillation curve before and after the dead zone Figure 6 As shown in the sub-figure (b) in the figure. From the simulation results, it can be seen that: before the dead zone, the system is unstable, but after the dead zone, the system dynamic process oscillates and converges, 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.

[0086] for Figure 6 In the (b) panel, when the dead zone does not affect the stability of the system, if the oscillation amplitude A is set to 0.1, it is much larger than the critical amplitude A.lim , considering the system oscillation curve before and after the dead zone is as follows Figure 7 From the simulation results, it can be seen that the system is stable before and after the dead zone, the open-loop frequency characteristic curve does not pass through the linear system equivalent to the nonlinear part, and the system dynamic process oscillates and converges.

[0087] In view of the influence of the above-mentioned different parameters on the system frequency stability, the performance index function A(K) of the primary frequency modulation of the reaction system is constructed:

[0088] A(K)=∑k1T 0.9 +k2T s +k3P f (9)

[0089] Where: T 0.9 It indicates the rising time from the time when the frequency difference exceeds the primary frequency regulation dead zone to the time when the unit active power reaches 90% of the target value. s It indicates the time from when the frequency difference exceeds the frequency regulation dead zone to when the unit active power reaches stability, P f represents the reverse modulation power, and k1, k2, and k3 represent the weight coefficients of each parameter respectively.

[0090] Construct the index B(K) of the damping level of the reaction system:

[0091]

[0092] Where: is the algebraic sum of the damping coefficients of the open-loop system transfer function consisting of the governor, turbine and wind turbine in the frequency band of interest.

[0093] Combining the two calculations to consider the comprehensive index of primary frequency modulation performance and ultra-low frequency damping, a multi-objective optimization function is constructed, namely:

[0094] C(K)=aA(K)+bB(K) (11)

[0095] Using the cuckoo optimization algorithm, the nest position is initialized by setting the number of nests and the search space dimension:

[0096]

[0097] According to the random walk method and the principle of keeping safety and removing danger, the location of the bird's nest is updated, and the location of the bird's nest is retained or changed according to the probability of being discovered, so as to obtain a set of better nest locations. in:

[0098]

[0099] In the formula, α is the step size control variable, and Levy is the random walk path. By searching for the optimal bird nest sequence, iteratively updating the PID speed regulator control parameters, and retaining the current optimal bird nest position, a set of PID speed regulator control parameters that take into account both primary frequency regulation and ultra-low frequency oscillation suppression are obtained, and then a method for suppressing ultra-low frequency oscillation by wind power participating in frequency regulation considering the dead zone of the speed regulator is given.

[0100] The method described in the present invention constructs a system frequency model by considering the influence of hydropower and wind power dead zones on system stability. For three typical wind power control strategies, different oscillation amplitudes are set and the describing function method is used to analyze the convergence and divergence of system frequency oscillation before and after the dead zones. By setting two different scenarios, where 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, the influence of important influencing factors on system stability is analyzed, and the PID speed regulator parameters are optimized by intelligent algorithms to suppress ultra-low frequency oscillations.

[0101] The above description is only a preferred embodiment of the present invention and is not intended to be a further limitation of the present invention. All equivalent changes made using the contents of the present specification and drawings are within the protection scope of the present invention.

Claims

1. A method for optimizing parameters of a PID speed regulator for wind power frequency modulation, characterized in that: The method comprises the following steps: Step 1: Use the small signal analysis method to build a frequency response model of wind power frequency modulation, select the virtual inertia control strategy, overspeed control strategy and pitch angle control strategy, and analyze the impact of wind power frequency modulation on ultra-low frequency oscillation; Step 2: Use the describing function method to linearize the nonlinear links such as wind power and hydropower dead zones, build a frequency model of wind power participating in frequency regulation including the dead zone of the speed regulator, and simplify the model by moving the comparison point according to the equivalent transformation rule; Step 3: According to the influence of the parameters in the model described in step 2 on the frequency stability, the primary frequency modulation performance index A(K) and the system damping index B(K) are constructed, and a multi-objective optimization model C(K)=a A(K)+b B(K) is established; Step 4: Use intelligent optimization algorithm to search and update the proportional coefficient K P , integral coefficient K I , differential coefficient K D The parameters of the PID speed regulator formed in parallel are given, and the method of suppressing ultra-low frequency oscillation by wind power participating in frequency regulation considering the dead zone is given; In step 1, firstly, in the actual operation of the power grid, the thermal power unit and the hydropower unit are taken as typical prime mover systems, and the frequency response model of the traditional unit and the transfer functions of the turbine, steam turbine and generator are established: Where: G ht and G st are the transfer functions of the water turbine and steam turbine respectively, G hgov and Gs gov is the transfer function of the corresponding PID speed regulator; Δω is the change in generator speed, Δμ is the change in guide vane opening; T W is the water flow inertia time constant, B p is the adjustment coefficient, K P , K I , K D They are the proportional, integral and differential coefficients of the speed regulator respectively; F HP is the percentage of the high pressure cylinder steady state output power to the total turbine output power, T RH is the time constant of volume effect of intermediate reheat steam, T CH T is the time constant of the main intake volume effect; G is the servo system time constant, R is the speed regulator primary frequency droop system; T J is the moment of inertia of the generator, ΔP m is the mechanical power change, ΔP e is the change of electromagnetic power, D is the generator damping coefficient; d is the partial derivative, s is the differential operator; Then, the ultra-low frequency oscillation phenomenon in high-proportion hydropower units due to the water hammer effect of the hydropower units and the unreasonable setting of PID speed regulator parameters is analyzed. On the basis of the traditional unit frequency response model, the frequency response model of the wind power participating in the frequency regulation is considered, and the small signal analysis method is used to construct the frequency response model of the wind power participating in the frequency regulation system. The mechanical power change of wind power is represented by the wind turbine model: Where ρ is the air density, C P is the wind energy capture efficiency coefficient, λ is the tip speed ratio, β is the pitch angle, A is the blade wind energy capture area, and v is the wind speed; The virtual inertia control, overspeed control and pitch angle control strategies are selected to analyze the impact of wind power participation in frequency regulation on ultra-low frequency oscillation.

2. The method for optimizing parameters of a PID speed regulator for wind power frequency modulation according to claim 1, characterized in that: In step 2, by analyzing the primary frequency modulation dead zone characteristics, a common dead zone is selected to perform mathematical modeling on the input and output of the dead zone: Where: x is the input of the dead zone, that is, the frequency deviation value Δf 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 the original system model, the dead zone links corresponding to the turbine and its speed governor, and the wind power frequency regulation module are considered respectively, and a frequency model of the system with the speed governor dead zone is established. In view of the characteristics of ultra-low frequency oscillation and the synchronization of all generators, there is no local and inter-regional oscillation. All generators are equivalent to a unit with an inertia center, and according to the equivalent transformation rule, the dead zones of hydropower and wind power are equivalent. By moving the comparison point, the system is represented as a simplified system frequency analysis model with linear and nonlinear parts. The nonlinear dead zone link is linearized by using the function description method. The open-loop part of the system is the series connection of the nonlinear link N(A) and the linear link G(s). The closed-loop frequency characteristic of the system is: The characteristic equation is: 1+N(A)G(jω)=0 (7) but: G(jω)=﹣1 / N(A) (8) The system stability is analyzed by the relative position of the G(jω) curve and the -1 / N(A) curve on the complex plane, that is, the negative inverse characteristic, and then the influence of the dead zone on the system frequency stability is analyzed.

3. The method for optimizing parameters of a PID speed regulator for wind power frequency modulation according to claim 2 is characterized in that: Analysis of the impact of dead zone on system frequency stability 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(jω) curve does not surround the point (-1, 0), then the -1 / N(A) curve is always on the left side of the G(jω) curve and is not surrounded by the G(jω) curve. Therefore, the nonlinear system considering the dead zone is also stable; 2) The system without considering the dead zone is unstable. The G(jω) curve surrounds the point (-1, 0) and intersects with the -1 / N(A) curve. Let the corresponding amplitude at the intersection be A. lim , the system dynamic behavior has two situations: a) If the initial amplitude A<A lim , then the operating point is located to the left of the intersection, not surrounded by the G(jω) curve, the system is stable, the oscillation decays so that A decreases, and the operating point moves to the left until the oscillation subsides and becomes stable; b) If the initial amplitude A>A lim , then the operating point is located to the right of the intersection, surrounded by the G(jω) curve, the system is unstable, the oscillation diverges, causing A to increase, the operating point moves to the right, and the oscillation continues to diverge.

4. The method for optimizing parameters of a PID speed regulator for wind power frequency modulation according to claim 1, characterized in that: In step 3, according to the simplified frequency model of the system with dead zone, the influence of different parameters on the system frequency stability is analyzed under the virtual inertia control, overspeed control and pitch angle control strategies, including: ① the influence of different wind power proportions on the damping torque coefficient of the system frequency response part when wind power does not participate in frequency regulation, and the influence of different wind power proportions on the damping torque coefficient of the system frequency response part when wind power participates in frequency regulation; ② different water hammer time constants T W Impact on the damping characteristics of wind power and turbines; ③ Changes in the root locus of the system before and after wind power participates in frequency modulation; ④ Changes in the root locus of the system with different wind power proportions after wind power participates in frequency modulation; ⑤ Different PID speed regulator parameters, i.e., the proportional coefficient K P , integral coefficient K I , differential coefficient K D Impact on system frequency oscillation;⑥ Impact of wind power and hydropower dead zone size on ultra-low frequency oscillation; In view of the influence of the above-mentioned different parameters on the system frequency stability, the performance index function A(K) of the primary frequency modulation of the reaction system is constructed: A(K)=∑k1T 0.9 +k2T s +k3P f (9) Where: T 0.9 It indicates the rising time from the time when the frequency difference exceeds the primary frequency regulation dead zone to the time when the unit active power reaches 90% of the target value, T s It indicates the time from when the frequency difference exceeds the frequency regulation dead zone to when the unit active power reaches stability, P f represents the reverse modulation power, k1, k2, k3 represent the weight coefficients of each parameter respectively; Construct the index B(K) of the damping level of the reaction system: Where: D(f) is the algebraic sum of the damping coefficients of the open-loop system transfer function consisting of the governor, turbine and wind turbine in the frequency band of interest; Combining the two calculations to consider the comprehensive index of primary frequency modulation performance and ultra-low frequency damping, a multi-objective optimization function is constructed, namely: C(K)=aA(K)+bB(K) (11) Where a and b are the weight coefficients of A(K) and B(K) respectively.

5. The method for optimizing parameters of a PID speed regulator for wind power frequency modulation according to claim 4 is characterized in that: In step 4, the cuckoo optimization algorithm is used to initialize the nest position by setting the number of nests and the search space dimension: P0=[x1 (t) ,x2 (t) ,…,x n (t) ] (12) According to the random walk method and the principle of keeping safety and removing danger, the location of the bird's nest is updated, and the location of the bird's nest is retained or changed according to the probability of being discovered, so as to obtain a set of optimal nest locations g t =[x1 (t) , x2 (t) , …, x n (t) ],in: In the formula, α is the step size control variable, and Levy is the random walk path. By searching the optimal bird nest sequence, iteratively updating the PID speed regulator control parameters, and retaining the current optimal bird nest position, a set of PID speed regulator control parameters that take into account both primary frequency regulation and ultra-low frequency oscillation suppression are obtained, and then a method for suppressing ultra-low frequency oscillation by wind power participating in frequency regulation considering the dead zone of the speed regulator is given.

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