Stability detection method, device and electronic equipment for generator set in power system

Abstract

The present invention provides a stability detection method, device and electronic equipment for a generator set in an electric power system, the method comprising: determining a target matrix based on a state space matrix corresponding to data of a phasor measurement device PMU using the Lyapunov direct method; obtaining a state deviation corresponding to the PMU data and an oscillation curve corresponding to the state deviation when the power system is determined to be in a stable state according to the target matrix; determining the extreme point value corresponding to the oscillation curve at each oscillation; and evaluating the working state of the generator set in the electric power system according to the extreme point value. The method is used to solve the defect that the existing process of determining the stability of an electric power system is relatively complicated, which easily leads to the inability of electronic equipment to accurately determine the stability of the electric power system, and enables the electronic equipment to accurately determine the stability of the electric power system based on PMU data with a large amount of data using the Lyapunov direct method.

Description

Technical Field

[0001] The present invention relates to the technical field of power system detection, and in particular to a stability detection method, device and electronic equipment for a generator set in a power system. Background Art

[0002] With the development of power electronics in core equipment in power systems and the rapid transformation of new energy power generation, the current power system presents a "double high" development trend of a high proportion of renewable energy and a high proportion of power electronic equipment. At the same time, due to the continuous promotion of high-voltage and large-capacity converters in the transmission network and the widespread application of power electronics technology on the distribution side, the "double high" characteristics of the power system are more significant. In addition, the "double high" feature has gradually become an important technical feature of the new generation of power systems. Therefore, research on the small disturbance stability of the "double high" power system has gradually become necessary.

[0003] In this "double-high" power system, large synchronous generators are replaced by small power sources, and massive distributed power sources, electric vehicles, distributed energy storage and other new devices with power electronics interfaces are connected to the power system from the medium and low voltage sides. This means that the number of dynamic elements that need to be considered in stability analysis may reach hundreds of thousands to millions, and the dynamic characteristics of various types of generators vary relatively greatly, showing a high degree of heterogeneity.

[0004] In the prior art, when analyzing the small disturbance stability of the above-mentioned "double-high" power system, electronic equipment will encounter severe challenges such as computational burden and communication burden due to the high data dimension. In addition, due to the volatility caused by the supply of new energy and the frequent switching of a large number of power electronic equipment and the high-speed changes in the system topology, the operating position of the power system will also change rapidly. In summary, since the existing process of determining the stability of the power system is relatively complicated, it is easy for electronic equipment to be unable to accurately judge the stability of the power system. Summary of the invention

[0005] The present invention provides a stability detection method, device and electronic equipment for a generator set in an electric power system, so as to solve the defect that the existing process of determining the stability of the electric power system is relatively complicated, which easily leads to the inability of the electronic equipment to accurately judge the stability of the electric power system. The electronic equipment can accurately determine the stability of the electric power system based on PMU data with a large amount of data and using the Lyapunov direct method.

[0006] The present invention provides a method for detecting stability of a generator set in an electric power system, comprising:

[0007] Based on the state space matrix corresponding to the data of the phasor measurement device PMU, the target matrix is ​​determined using the Lyapunov direct method;

[0008] When it is determined that the power system is in a stable state according to the target matrix, a state deviation corresponding to the PMU data and an oscillation curve corresponding to the state deviation are obtained;

[0009] Determine the extreme point value corresponding to each oscillation of the oscillation curve;

[0010] According to the extreme point value, the working status of the generator set in the power system is evaluated.

[0011] According to a stability detection method for a generator set in an electric power system provided by the present invention, a state space matrix corresponding to the phasor measurement device PMU data is determined by using the Lyapunov direct method to determine a target matrix, including: determining the state space matrix based on the generator state space model according to the acquired phasor measurement device PMU data; and analyzing the state space matrix by using the Lyapunov direct method to determine the target matrix.

[0012] According to a method for detecting the stability of a generator set in an electric power system provided by the present invention, the electric power system is determined to be in a stable state based on the target matrix, including: determining that the electric power system is in a stable state when the target matrix is ​​determined to be a positive definite matrix.

[0013] According to a stability detection method for a generator set in an electric power system provided by the present invention, the determination of the extreme point value corresponding to the oscillation curve at each oscillation includes: using a gradient descent method to determine the first extreme point value corresponding to the crest and the second extreme point value corresponding to the trough of the oscillation curve at each oscillation.

[0014] According to a stability detection method for a generator set in an electric power system provided by the present invention, the working state of the generator set in the electric power system is evaluated based on the extreme value point value, including: performing weighted summation on each extreme value point data to obtain an extreme value deviation; and evaluating the working state of the generator set in the electric power system based on the extreme value deviation.

[0015] According to a stability detection method for a generator set in an electric power system provided by the present invention, the working state of the generator set in the electric power system is evaluated based on the extreme value deviation, including: when the extreme value deviation is less than a preset deviation threshold, determining that the oscillation degree of the generator set in the electric power system is not severe; when the extreme value deviation is greater than or equal to the preset deviation threshold, determining that the oscillation degree of the generator set is severe.

[0016] According to a stability detection method for a generator set in an electric power system provided by the present invention, a state space matrix is ​​determined based on the generator state space model according to the acquired phasor measurement device PMU data, including: summarizing the acquired phasor measurement device PMU data to obtain power grid data; performing dimensionality reduction preprocessing on the power grid data to obtain a data matrix; and determining the state space matrix based on the generator state space model according to the data matrix.

[0017] The present invention also provides a generator set stability detection device, comprising:

[0018] The data processing module is used to determine the target matrix based on the state space matrix corresponding to the phasor measurement device PMU data by using the Lyapunov direct method; when it is determined that the power system is in a stable state according to the target matrix, obtain the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation; determine the extreme point value corresponding to the oscillation curve at each oscillation;

[0019] The stability determination module is used to evaluate the working state of the generator set in the power system according to the extreme value point value.

[0020] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a stability detection method for a generator set in an electric power system as described in any one of the above methods is implemented.

[0021] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for detecting the stability of a generator set in an electric power system as described in any one of the above is implemented.

[0022] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for detecting the stability of a generator set in an electric power system.

[0023] The stability detection method, device and electronic device of the generator set in the power system provided by the present invention determine the target matrix by using the Lyapunov direct method based on the state space matrix corresponding to the PMU data of the phasor measurement device; when it is determined that the power system is in a stable state according to the target matrix, the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation are obtained; the extreme point value corresponding to the oscillation curve at each oscillation is determined; and the working state of the generator set in the power system is evaluated according to the extreme point value. This method is used to solve the defect that the existing process of determining the stability of the power system is relatively complicated, which easily leads to the inability of the electronic device to accurately judge the stability of the power system, and realizes that the electronic device can accurately determine the stability of the power system based on the PMU data with a large amount of data by using the Lyapunov direct method. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 It is a flow chart of a method for detecting the stability of a generator set in a power system provided by the present invention;

[0026] Figure 2a It is a power angle oscillation curve diagram corresponding to each generator set in the simulation system provided by the present invention when the damping stability controller PSS is not configured;

[0027] Figure 2b It is an oscillation curve diagram corresponding to different power units in the power system without the damping stability controller PSS provided by the present invention;

[0028] Figure 2c These are oscillation curve diagrams corresponding to power systems equipped with different damping stability controllers PSS provided by the present invention;

[0029] Figure 3 It is a structural schematic diagram of a generator set stability detection device provided by the present invention;

[0030] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] It should be noted that the electronic device involved in the embodiment of the present invention may be a power system, or may be a terminal device associated with the power system (hereinafter referred to as an associated device), which is not specifically limited here.

[0033] The power system may be a "double-high" power system, which refers to a system with a high proportion of renewable energy sources and a high proportion of power electronic equipment.

[0034] Optionally, in the case where the electronic device is a terminal device associated with the power system, the electronic device may include but is not limited to: a computer, a mobile terminal, a wearable device, etc.

[0035] Optionally, the associated equipment and the power system can be connected via wireless communication technology, which may include but is not limited to one of the following: the 4th Generation mobilecommunication technology (4G), the 5th Generation mobilecommunication technology (5G) and wireless fidelity technology (WiFi), etc.

[0036] It should be noted that the execution subject involved in the embodiment of the present invention may be a generator set stability detection device or an electronic device. The embodiment of the present invention will be further described below using the electronic device as an example.

[0037] like Figure 1 FIG. 1 is a flow chart of a method for detecting the stability of a generator set in a power system provided by the present invention, which may include:

[0038] 101. Based on the state space matrix corresponding to the PMU data of the phasor measurement device, the target matrix is ​​determined using the Lyapunov direct method.

[0039] Among them, the phasor measurement device (Power Management Unit, PMU) data refers to the data obtained by the electronic equipment using the PMU to measure the generator set in the power system during operation, that is, the power system data monitored by the PMU in real conditions;

[0040] The state space matrix refers to the matrix corresponding to the PMU data obtained by the electronic equipment based on the generator state space model, which can be represented by A;

[0041] The target matrix refers to the matrix obtained by the electronic device after performing a series of operations on the above state space matrix, which can be represented by P;

[0042] Lyapunov's direct method, also known as Lyapunov's second method, refers to the direct inference of the stability problem of the power system by using the Lyapunov energy function and the sign property of the derivative of the energy function along the trajectory calculated according to the differential equation.

[0043] Optionally, the PMU data may include, but is not limited to: a speed increment, a power angle increment, an electromagnetic power increment, a damping torque constant and an inertia time constant corresponding to the generator set.

[0044] After acquiring the PMU data in real time, the electronic device may perform a series of operations on the state space matrix corresponding to the PMU data to obtain a target matrix corresponding to the PMU data.

[0045] It should be noted that for the unified inertia center of the entire power system, when oscillation occurs in a certain area of ​​the power system, there will always be a deceleration and acceleration unit that manifests as a relative swing between two generator sets. The two generator sets can be simplified into an equivalent power system consisting of two equivalent generator sets interconnected.

[0046] In some embodiments, the electronic device determines the target matrix based on the state space matrix corresponding to the phasor measurement device PMU data using the Lyapunov direct method, which may include: the electronic device determines the state space matrix based on the generator state space model according to the acquired phasor measurement device PMU data; the electronic device uses the Lyapunov direct method to analyze the state space matrix to determine the target matrix.

[0047] The generator state space model refers to a second-order model obtained by reducing the order of the synchronous generator model by the electronic device, and the second-order model corresponds to the rotor motion equations of two equivalent generator sets.

[0048] The electronic equipment can accurately obtain the target matrix corresponding to the PMU data based on the generator state space model and Lyapunov direct method.

[0049] Optionally, the electronic device determines the state space matrix based on the acquired phasor measurement device PMU data and the generator state space model, which may include: the electronic device determines the state space matrix based on the acquired phasor measurement device PMU data and the rotor motion equations in the generator state space model.

[0050] The rotor motion equations are:

[0051] represents the first speed increment corresponding to the first generator set; Δω1 represents the first power angle increment corresponding to the first generator set; represents the second speed increment corresponding to the second generator set; Δω2 represents the second power angle increment corresponding to the second generator set; Indicates the equivalent power angle increment corresponding to the first generator set; ΔP 1e represents the first electromagnetic power increment corresponding to the first generator set; D1 represents the first damping torque constant corresponding to the first generator set; M1 represents the first inertia time constant corresponding to the first generator set; Indicates the equivalent power angle increment corresponding to the second generator set; ΔP 2e represents the second electromagnetic power increment corresponding to the second generator set; D2 represents the second damping torque constant corresponding to the second generator set; M2 represents the second inertia time constant corresponding to the second generator set.

[0052] The state space matrix

[0053] In the state space matrix A,

[0054] The electromagnetic power equation can be expressed as:

[0055] The dynamic active power of the wind farm is expressed as:

[0056] K 12 represents the first target constant, k1 represents the first sub-constant, k2 represents the second sub-constant, K 13 represents the second target constant, k3 represents the third sub-constant, k4 represents the fourth sub-constant, Δδ1 represents the first speed increment, Δδ2 represents the second speed increment, Δδ w Indicates the third speed increment, ΔP w1 Indicates the first dynamic active power, ΔP w2 Indicates the second dynamic active power.

[0057] After acquiring the PMU data, the electronic device accurately determines the state space matrix corresponding to the PMU data based on the rotor motion equations in the generator state space model.

[0058] It should be noted that the rotor motion equations are obtained by reducing the order of the electronic device based on the formulas in the synchronous generator model. The specific reduction process is as follows: the formulas in the synchronous generator model include: the voltage equation of the f winding, the voltage equation of the g winding, the voltage equation of the D winding, the voltage equation of the Q winding and the first motion equation of the rotor;

[0059] Among them, the voltage equation of the f winding is:

[0060] T′ d0 represents the inertia time constant corresponding to the f winding, p represents the number of pole pairs corresponding to the f winding, E′ q It represents the transient no-load potential corresponding to the f winding, E f represents the excitation potential, X d represents the first steady-state reactance corresponding to the f winding, X′ d represents the transient reactance corresponding to the f winding, X1 represents the second steady-state reactance corresponding to the f winding, E″ q Indicates the sub-transient no-load potential corresponding to the f winding, X″ d represents the subtransient reactance corresponding to the f winding, i d Indicates the AC component corresponding to the f winding;

[0061] The voltage equation of the g winding is:

[0062] T′ q0 represents the inertia time constant corresponding to the g winding, X q represents the steady-state reactance corresponding to the g winding, X′ q Indicates the transient parameter reactance corresponding to the g winding, X″ q represents the subtransient reactance corresponding to the g winding, i q Indicates the AC component corresponding to the g winding;

[0063] The voltage equation of the D winding is: T″ d0 It represents the inertia time constant corresponding to the D winding;

[0064] The voltage equation of the Q winding is: T″ q0 It represents the inertia time constant corresponding to the Q winding;

[0065] The first equation of motion of the rotor is: T J Indicates the inertia time constant corresponding to the rotor, T m represents the first time constant corresponding to the rotor, ω represents the power angle corresponding to the rotor, also called angular velocity, δ represents the rotational speed of the rotor, and t represents the movement time of the rotor.

[0066] Then, when the electronic device analyzes the small disturbance stability of the power system, that is, the stability of the motor components in the power system, in order to reduce the order of the state equation group in the power system to avoid the problem of inaccurate stability judgment due to too high an order, since the time constant of each rotor damping winding is small, the electronic device can appropriately ignore the windings corresponding to these rotor damping windings in the actual application analysis. When the electronic device ignores the effects of the equivalent D-axis, Q-axis and g-axis of the damping winding, and only considers the transient process of the excitation winding and the third-order model of the rotor dynamics, the system where the excitation winding is located can be represented by a first-order linear link. At this time, the electronic device can reduce the above-mentioned synchronous generator model to a third-order model. The state quantities in the third-order model are the transient no-load potential E′ q , angular velocity ω and rotation speed δ, the third-order model may include: generator excitation winding equation, stator voltage equation and the second motion equation of the rotor;

[0067] Among them, the generator excitation winding equation is: T′ d0 pE′ q =E f -E′ q -(X d -X′ d )i d ;

[0068] Stator voltage equation: U d =X q i q -r a i d , U q =E′ q -X′ d i d -r a i q , U d Indicates the first voltage corresponding to the stator, U q represents the second voltage corresponding to the stator, r a Indicates the resistance corresponding to the stator;

[0069] The second equation of motion of the rotor:

[0070] Next, the electronic device can further ignore the transient process of the f winding and reduce the above third-order model to a classic second-order practical model of the generator, which can also be called a constant impedance model for the load, as follows:

[0071]

[0072] Finally, when the electronic device adopts the classical second-order practical model of the generator, the aforementioned process can be equivalent to a set of rotor motion equations of two equivalent generator sets, that is, the aforementioned process can be equivalent to a generator state space model.

[0073] Optionally, the electronic device uses Lyapunov direct method to analyze the state space matrix and determine the target matrix, which may include: the electronic device substitutes the state space matrix into the linear steady-state system state equation and matrix formula in Lyapunov direct method to obtain the target matrix.

[0074] Among them, the state equation of the linear steady-state system is

[0075] The matrix formula is A T P+PA=-Q;

[0076] represents the equilibrium point; x represents the equilibrium state point; A represents the state space matrix; A T represents the transpose of the state space matrix A; Q represents the preset positive definite matrix in Lyapunov's direct method.

[0077] Optionally, the preset positive definite matrix Q is an arbitrary real symmetric matrix. In order to simplify the process of determining the target matrix, the preset positive definite matrix Q can be set to the unit matrix I.

[0078] In some embodiments, the electronic device determines the state space matrix based on the acquired phasor measurement device PMU data and the generator state space model, which may include: the electronic device summarizes the acquired phasor measurement device PMU data to obtain power grid data; the electronic device performs dimensionality reduction preprocessing on the power grid data to obtain a data matrix; the electronic device determines the state space matrix based on the generator state space model according to the data matrix.

[0079] The dimension reduction preprocessing refers to the process in which the electronic device reduces the first dimension of the power grid data to obtain a data matrix of the second dimension, where the first dimension is greater than the second dimension.

[0080] After acquiring the PMU data in real time, the electronic device can first summarize the PMU data to form power grid data, that is, obtain an initial data matrix corresponding to the PMU data; then, the electronic device performs dimensionality reduction preprocessing on the power grid data to obtain the data matrix required by the generator state space model; finally, the electronic device can accurately obtain the state space matrix A corresponding to the PMU data based on the data matrix and the generator state space model.

[0081] 102. When it is determined that the power system is in a static stable state according to the target matrix, a state deviation corresponding to the PMU data and an oscillation curve corresponding to the state deviation are obtained.

[0082] Among them, the state deviation can be understood as the deviation of the oscillation curve at a certain moment relative to the stable equilibrium point. It is not used in the qualitative determination stage of the power system stability. It is mainly used to quantitatively describe the oscillation amplitude and oscillation duration of a certain monitored state quantity of the electronic device relative to the balance point of the electronic device after the electronic device is determined to be stable, that is, it can be regarded as the severity of the oscillation of the power system;

[0083] The oscillation curve refers to the curve corresponding to when the generator set oscillates during operation, and the curve may include peaks and troughs.

[0084] After obtaining the target matrix, the electronic device can determine whether the power system is in a static stable state based on the target matrix; when the electronic device determines that the power system is in a static stable state based on the target matrix, it can obtain the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation, thereby determining the dynamic stable state of the power system.

[0085] Optionally, before or after step 102, the method may further include: when the electronic device determines, based on the target matrix, that the power system is not in a static stable state, it may output a first prompt message, and the first prompt message is used to prompt the user that the power system is unstable. In this way, the user can promptly know that the power system is not stable enough and take corresponding measures to make the power system tend to stabilize. At this time, the electronic device can obtain the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation.

[0086] Optionally, the electronic device obtaining the state deviation corresponding to the PMU data may include: the electronic device obtaining the state variable integral value of the i-th state deviation corresponding to the PMU data based on an integral value formula.

[0087] The integral value formula is:

[0088] J represents the state variable integral value of the i-th state deviation; x T represents the transpose of the equilibrium point x; Q J =diag(q1,…,q j ,…,q n ), represents the diagonal matrix corresponding to the PMU data, q j represents the jth element, the diagonal matrix Q J Only the corresponding diagonal matrix elements are set to 1, and the rest are set to 0, for example: Q J =diag(1,…,1,0,…,0).

[0089] In order to simplify the determination process of the integral value of the state variable of the entire i-th state deviation, the electronic device can bring the unit matrix I into Q J ,get Then we get J = x T P J x,P J Represents the target matrix corresponding to the i-th state deviation.

[0090] In this way, the electronic device can obtain the state variable integral value corresponding to at least one state deviation based on the above integral value formula, that is, obtain at least one state variable integral value.

[0091] It should be noted that the integral value J of the state variable can reflect the dynamic stability state of the state deviation of the power system, that is, the dynamic stability; the smaller the integral value J of the state variable is, the faster the state deviation decays and the smaller the oscillation amplitude of the oscillation curve is, the shorter the duration of the entire dynamic stability process is, and the better the small disturbance stability of the power system is; conversely, it means that the slower the state deviation decays and the larger the oscillation amplitude of the oscillation curve is, the longer the duration of the entire dynamic stability process is, and the worse the small disturbance stability of the power system is.

[0092] In some embodiments, the electronic device determines that the power system is in a static stable state according to the target matrix, which may include: the electronic device determines that the power system is in a static stable state when determining that the target matrix is ​​a positive definite matrix.

[0093] Among them, a positive definite matrix refers to a matrix whose eigenvalues ​​are all positive, whose principal minors of all orders are positive, and which is equivalent to the unit matrix.

[0094] After obtaining the target matrix, the electronic device can determine whether the target matrix is ​​a positive definite matrix; when the electronic device determines that the eigenvalues ​​of the target matrix are all positive, the principal minors of each order of the target matrix are all positive, and the target matrix is ​​the same as the unit matrix, it can determine that the target matrix is ​​a positive definite matrix. At this time, the electronic device can accurately determine that the power system is in a static stable state.

[0095] 103. Determine the value of the extreme point corresponding to each oscillation of the oscillation curve.

[0096] The extreme value point value refers to the first extreme value point value corresponding to the peak generated by the oscillation curve during oscillation and the second extreme value point value corresponding to the trough generated.

[0097] The oscillation curve will produce peaks and troughs during oscillation, and the electronic device only needs to obtain the first extreme value point value corresponding to the peak and the second extreme value point value corresponding to the trough generated during each oscillation.

[0098] In some embodiments, the electronic device determines the extreme point value corresponding to the oscillation curve at each oscillation, which may include: the electronic device uses a gradient descent method to determine the first extreme point value corresponding to the peak and the second extreme point value corresponding to the trough of the oscillation curve at each oscillation.

[0099] Among them, the gradient descent method refers to a time-weighted value based on the gradient descent deviation of the oscillation curve, which is used to describe the low-frequency oscillation process of a single state deviation. It can analyze and evaluate the dynamic process of the state deviation, and can also analyze the dynamic stability process of the power system.

[0100] When analyzing each generator set in the power system, in order to simplify the calculation process and achieve an effect similar to the above-mentioned state deviation, the electronic device can use the gradient descent method to determine the first extreme point value corresponding to the peak and the second extreme point value corresponding to the trough of the oscillation curve during each oscillation.

[0101] After obtaining the oscillation curve, the electronic device can use the oscillation curve as the objective function in the gradient descent method, and the objective function is x(t)=[x(t1), ..., x(t m ), …, x(t n )],x(t m ) represents the mth independent variable corresponding to the oscillation curve; then, the electronic device performs a gradient descent iteration process on the objective function as follows. When θ>0, the electronic device can obtain the following iteration formula: θ represents the number of iterations, and η represents the iteration constant; during the entire gradient descent iteration process, when the iteration reaches the convergence condition, that is, when the extreme value corresponding to the zero point is obtained when the gradient is zero, the electronic device no longer performs gradient descent iteration on the objective function. From these iterative formulas of the gradient descent method, the selection of the next time point is related to the position of the current time point and the gradient of the current time point. If the electronic device wants to calculate the maximum value of the objective function, it can move in the opposite direction of the time gradient; then, the electronic device repeats the gradient descent iteration process to determine the first extreme point value corresponding to the peak of the oscillation curve and the second extreme point value corresponding to the trough at each oscillation.

[0102] In addition, from the above-mentioned entire process of obtaining the extreme point value, whether the electronic device determines the maximum value or the minimum value of the objective function, it is necessary to construct the following iterative relationship: g(t)=t-ηf(t).

[0103] In this way, after the electronic device determines that the power system is in a static stable state according to the target matrix, it can record the time corresponding to the entire oscillation curve during the oscillation process in real time; then, the electronic device uses the gradient descent method on the oscillation curve to accurately determine the extreme point value corresponding to the oscillation curve at each oscillation.

[0104] 104. Evaluate the working status of the generator set in the power system based on the extreme point values.

[0105] In some embodiments, the electronic device evaluates the working status of the generator set in the power system based on the extreme point values, which may include: the electronic device performs weighted summation on each extreme point data to obtain the extreme value deviation; the electronic device evaluates the working status of the generator set in the power system based on the extreme value deviation.

[0106] Different extreme points correspond to different weights. After obtaining the extreme point values, the electronic device can perform weighted summation of each extreme point value and the weight corresponding to each extreme point value to obtain the extreme deviation corresponding to the generator set, that is, the extreme deviation of the oscillation curve during the oscillation process can be determined; then, the electronic device determines the oscillation severity of the generator set in the power system based on the extreme deviation, thereby determining the stability of the generator set. In other words, the electronic device can determine whether the generator set in the power system is stable or unstable based on the size of the extreme deviation, which is not specifically limited here.

[0107] In addition, the extreme deviation of the state variable of the electronic device, that is, the extreme deviation difference of the oscillation curve obtained by the electronic device using the gradient descent method is different from the state deviation integral value (J), and is mainly used to evaluate the oscillation amplitude of the state variable of the electronic device more quickly and efficiently through calculation.

[0108] In some embodiments, the electronic device evaluates the working state of the generator set in the power system based on the extreme value deviation, which may include: the electronic device determines that the oscillation degree of the generator set in the power system is not severe when the extreme value deviation is less than a preset deviation threshold; the electronic device determines that the oscillation degree of the generator set is severe when the extreme value deviation is greater than or equal to the preset deviation threshold.

[0109] The preset deviation threshold may be set before the electronic device leaves the factory, or may be obtained by the user based on a large amount of simulation experiment data, and is not specifically limited here.

[0110] When the electronic device determines the working state of the generator set in the power system based on the extreme value deviation, the extreme value deviation can be compared with the preset deviation: when the extreme value deviation is less than the preset deviation threshold, it means that the extreme value deviation is small, and at this time, it can be determined that the oscillation degree of the generator set is not severe; when the extreme value deviation is greater than or equal to the preset deviation threshold, it means that the extreme value deviation is large, and at this time, it can be determined that the oscillation degree of the generator set is severe.

[0111] Optionally, after the electronic device determines that the oscillation degree of the generator set is severe, the method may also include: the electronic device outputs a second prompt information, and the second prompt information is used to prompt the user that the generator set in the power system is unstable. In this way, the user can promptly obtain information that the generator set is not stable enough and take corresponding measures for the generator set, for example, adding a damping stability controller (Power System Stabilizer, PSS) to the generator set, so that the generator set can tend to stabilize during operation, thereby effectively ensuring that the power system is in a dynamically stable state.

[0112] In an embodiment of the present invention, based on the state space matrix corresponding to the data of the phasor measurement device PMU, the target matrix is ​​determined by using the Lyapunov direct method; when it is determined that the power system is in a stable state according to the target matrix, the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation are obtained; the extreme point value corresponding to the oscillation curve at each oscillation is determined; and the working state of the generator set in the power system is evaluated according to the extreme point value. This method is used to solve the defect that the existing process of determining the stability of the power system is relatively complicated, which easily leads to the inability of electronic equipment to accurately judge the stability of the power system, and realizes that the electronic equipment can accurately determine the stability of the power system based on the PMU data with a large amount of data by using the Lyapunov direct method.

[0113] For example, according to Figure 1 The stability detection method of the generator set in the power system shown in the figure simulates the generator set of the power system, and the process is as follows:

[0114] In the process of performing a small disturbance stability direct method calculation example analysis on the power system, the electronic device uses the PMU data obtained after actual measurement of the existing New England system, specifically, the current and voltage amplitudes and phase angles collected when the corresponding time length of the PMU data is 0 seconds (s) to 1.179s; then, the electronic device summarizes and pre-processes the PMU data to obtain the data matrix required by the generator state space model; then, the electronic device brings the data matrix into the state space matrix A, and uses the IEEE 10-machine 39-node New England system as the simulation system, and uses the Lyapunov direct method to perform small disturbance stability analysis and calculation on the simulation system. Optionally, during the simulation process, the electronic device uses MATLAB to design an algorithm program for stability determination and calculation of the index function value. Then, the electronic device uses the above algorithm steps to apply the eigenvalue method and the Lyapunov direct method to the WSCC 3-machine system, the China Electric Power Research Institute 6-machine system and the New England 10-machine system for stability determination, and the stability determination results of different simulation systems are shown in Table 1:

[0115] Table 1

[0116]

[0117] Among them, the eigenvalue method refers to judging the stability of the power system by analyzing the relationship between the eigenvalue and the state variable. The electronic device can calculate the eigenvalue and eigenvector of the matrix corresponding to the power system based on the linearized model of the power system in the form of a state equation. Then, the electronic device determines the stability of the power system based on the eigenvalue and the eigenvector.

[0118] It can be seen from Table 1 that the electronic device obtains the same results whether it applies the eigenvalue method or the Lyapunov direct method. Therefore, the Lyapunov direct method involved in the present invention can accurately and reliably determine the stability of different power systems, and the results obtained by the two judgment methods will not be inconsistent due to the omission of certain parameters.

[0119] In the process of analyzing the low-frequency oscillation example of the state deviation square integral value of the power system by the electronic device, the minimum damping ratio of the electromechanical mode is often used as an evaluation index of the low-frequency oscillation when a small disturbance occurs in the power system. In the prior art, there are electronic devices that can configure the damping stability controller PSS of the power system according to the dynamic minimum damping ratio configuration criterion, and give the minimum damping ratio obtained by the eigenvalue method. The power system dynamic deviation square integral value method involved in the present invention is to establish the Lyapunov equation group using the state space matrix A, call the Lyapunov equation function in MATLAB to solve the target matrix P, determine the positive definiteness of the target matrix P, and then use the Lyapunov direct method to judge the stability of the power system. According to the dynamic deviation value method mentioned above, the electronic device obtains the index function value with the help of the Lyapunov equation, that is, obtains the weighted square integral value of each state deviation in the oscillation curve of the power system, and the weighted square integral value can reflect the dynamic performance of the extreme deviation of the power system. As shown in Table 2, it is a relationship table between the unit equipped with PSS provided by the present invention and the minimum damping ratio and the square integral value of the dynamic deviation:

[0120] Table 2

[0121] Units equipped with PSS Minimum damping ratio 1，2 0.0243 1，2，9， 0.0245 1，2，9，7， 0.0272 1，2，9，7，4 0.0288 1，2，9，7，4，5 0.0654 1，2，9，7，4，5，3 0.0916 1，2，9，7，4，5，3，8 0.0963 1，2，9，7，4，5，3，8，10 0.1057

[0122] It can be seen from Table 2 that the minimum damping ratio can be regarded as a performance indicator of the power system, and the square integral value of the dynamic deviation can also be regarded as a performance indicator of the power system. As the number of PSSs configured in the power system increases, the minimum damping ratio becomes larger and larger, and the square integral value of the dynamic deviation becomes smaller and smaller, which shows that the stability of the power system becomes better and better with the increase in the number of PSSs in the power system.

[0123] In the process of configuring the PSS of the power system according to the dynamic deviation value of the time-weighted gradient of the state variable curve, the electronic device verifies the stability of the power system based on the Lyapunov direct method for the low-frequency oscillations generated by small disturbances. In the prior art, the 6# unit of the New England 10-machine 39-node system is an equivalent machine and does not need to be configured with PSS. The dynamic damping ratio configuration method can be used to determine the location of the PSS configuration, thereby achieving the purpose of optimizing the small disturbance stability of the power system. In the present invention, the electronic device uses MATLAB software Simulink to build a simulation system corresponding to the New England 10-machine 39-node system, and constructs a small disturbance signal module for the 6# unit in the simulation system to simulate the low-frequency oscillation of the simulation system when it is subjected to small disturbances, thereby analyzing the small disturbance stability of the simulation system.

[0124] The electronic device involved in the present invention uses the obtained time-weighted gradient dynamic deviation value of the state variable curve to describe the low-frequency oscillation dynamic process of the generator set after the simulation system is subjected to a small disturbance, and by comparing the low-frequency oscillation dynamic deviation values ​​of different units in the simulation system, the PSS is configured for the units with large oscillation amplitude and long oscillation time in the simulation system. Next, in order to further verify the feasibility and effectiveness of the above-mentioned time-weighted gradient dynamic deviation value of the state variable curve for PSS configuration, the electronic device configures the PSS of the simulation system according to the square integral value of the power angle dynamic deviation obtained by the Lyapunov direct method.

[0125] As shown in Table 3, it is a table of the time-weighted gradient deviation of the state curve of each generator set in the simulation system provided by the present invention. Figure 2a As shown, it is a power angle oscillation curve diagram corresponding to each generator set in the simulation system provided by the present invention when the PSS is not configured;

[0126] Table 3:

[0127] Generator set number State curve gradient dynamic deviation value 1# 0.03569 2# 0.02602 3# 0.03271 4# 0.07179 5# 0.08368 7# 0.05546 8# 0.06102 9# 0.04219 10# 0.04847

[0128] It can be seen from Table 3 that the time-weighted gradient deviation of the state curve corresponding to different generator sets is different. The generator sets configured with PSS in the power system should be No. 4#, No. 5#, No. 7#, No. 8# and No. 10# respectively; at the same time, the electronic device can compare the configuration of PSS for the generator sets according to the dynamic minimum damping ratio configuration criterion. The method for configuring a damping stability controller in a simulation system provided by the present invention can improve the small disturbance stability of the simulation system. In addition, different PSS configuration schemes are adopted for the same simulation system, and the oscillation curves obtained by the different PSS configuration schemes can intuitively reflect the dynamic process of the oscillation, and can effectively improve the small disturbance stability of the simulation system.

[0129] from Figure 2a It can be seen from the figure that the power angle oscillation curves corresponding to different generator sets are also different when they are not equipped with a damping stability controller PSS.

[0130] like Figure 2b As shown, it is the oscillation curve diagram corresponding to different power units in the power system without the damping stability controller PSS provided by the present invention; Figure 2c These are oscillation curve diagrams corresponding to power systems configured with different damping stability controllers PSS provided by the present invention.

[0131] through Figure 2b and Figure 2cBy comparison, it can be seen that the stability of the power system after PSS is configured is higher than that of the power system without PSS, and the power angle fluctuation degree of the power system after PSS is configured is significantly smaller than that of the power system without PSS, indicating that the configuration method of electronic equipment based on dynamic damping ratio and the configuration method based on time-weighted deviation value of state curve have certain effectiveness.

[0132] In addition, the time-weighted value of the power angle deviation can effectively reflect the oscillation amplitude of all generator sets in the time interval, thereby more comprehensively reflecting the dynamic process of the power system during operation. Figure 2b Oscillation curve diagram, based on Figure 2c The oscillation curve of the power system with PSS configuration in which the electronic equipment is based on the time-weighted deviation of the state curve is significantly shortened, and the oscillation amplitude is effectively reduced.

[0133] In summary, the PSS configuration method of the electronic device according to the time-weighted deviation of the state curve involved in the present invention is effective and feasible in certain circumstances.

[0134] The generator set stability detection device provided by the present invention is described below. The generator set stability detection device described below and the generator set stability detection method in the power system described above can be referred to each other.

[0135] like Figure 3 FIG. 1 is a schematic diagram of the structure of the generator set stability detection device provided by the present invention, which may include:

[0136] The data processing module 301 is used to determine the target matrix based on the state space matrix corresponding to the phasor measurement device PMU data by using the Lyapunov direct method; when it is determined that the power system is in a static stable state according to the target matrix, obtain the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation; determine the extreme point value corresponding to the oscillation curve at each oscillation;

[0137] The stability determination module 302 is used to evaluate the working state of the generator set in the power system according to the extreme value point value.

[0138] Optionally, the data processing module 301 is specifically used to determine the state space matrix according to the acquired phasor measurement device PMU data and based on the generator state space model; and analyze the state space matrix using the Lyapunov direct method to determine the target matrix.

[0139] Optionally, the stability determination module 302 is specifically configured to determine whether the power system is in a static stable state when it is determined that the target matrix is ​​a positive definite matrix.

[0140] The gradient descent method is used to determine the first extreme point value corresponding to the peak and the second extreme point value corresponding to the trough of the oscillation curve during each oscillation.

[0141] Optionally, the stability determination module 302 is specifically used to perform weighted summation on each of the extreme value point data to obtain an extreme value deviation; and evaluate the working state of the generator set in the power system based on the extreme value deviation.

[0142] Optionally, the stability determination module 302 is specifically used to determine that the oscillation degree of the generator set in the power system is not severe when the extreme value deviation is less than a preset deviation threshold; and to determine that the oscillation degree of the generator set is severe when the extreme value deviation is greater than or equal to the preset deviation threshold.

[0143] Optionally, the stability determination module 302 is specifically used to summarize the acquired phasor measurement device PMU data to obtain power grid data; perform dimensionality reduction preprocessing on the power grid data to obtain a data matrix; and determine the state space matrix based on the generator state space model according to the data matrix.

[0144] like Figure 4 As shown, it is a structural schematic diagram of an electronic device provided by the present invention, and the electronic device may include: a processor (processor) 410, a communication interface (Communications Interface) 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 complete mutual communication through the communication bus 440. The processor 410 can call the logic instructions in the memory 430 to execute the stability detection method of the generator set in the power system, and the method includes: based on the state space matrix corresponding to the phasor measurement device PMU data, using the Lyapunov direct method, determining the target matrix; when it is determined that the power system is in a static stable state according to the target matrix, obtaining the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation; determining the extreme point value corresponding to the oscillation curve at each oscillation; and evaluating the working state of the generator set in the power system according to the extreme point value.

[0145] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0146] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the stability detection method of the generator set in the power system provided by the above-mentioned methods, and the method includes: based on the state space matrix corresponding to the phasor measurement device PMU data, using the Lyapunov direct method, determining the target matrix; when it is determined that the power system is in a static stable state according to the target matrix, obtaining the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation; determining the extreme point value corresponding to the oscillation curve at each oscillation; and evaluating the working state of the generator set in the power system according to the extreme point value.

[0147] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the stability detection method of a generator set in an electric power system provided by the above-mentioned methods, the method comprising: determining a target matrix by using the Lyapunov direct method based on a state space matrix corresponding to the data of a phasor measurement device PMU; when it is determined according to the target matrix that the electric power system is in a static stable state, obtaining a state deviation corresponding to the PMU data and an oscillation curve corresponding to the state deviation; determining the extreme point value corresponding to the oscillation curve at each oscillation; and evaluating the working state of the generator set in the electric power system according to the extreme point value.

[0148] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0149] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the stability of a generator set in an electric power system, characterized in that: include: Based on the state space matrix corresponding to the data of the phasor measurement device PMU, the target matrix is ​​determined using the Lyapunov direct method; When it is determined that the power system is in a stable state according to the target matrix, obtaining a state deviation corresponding to the PMU data and an oscillation curve corresponding to the state deviation; Determine the extreme point value corresponding to each oscillation of the oscillation curve; According to the extreme value point value, evaluating the working state of the generator set in the power system; The step of evaluating the working state of the generator set in the power system according to the extreme value point comprises: Performing weighted summation on each extreme value point data to obtain an extreme value deviation; According to the extreme value deviation, evaluating the working state of the generator set in the power system; The step of evaluating the working state of the generator set in the power system according to the extreme value deviation comprises: When the extreme value deviation is less than a preset deviation threshold, determining that the oscillation degree of the generator set in the power system is not severe; When the extreme value deviation is greater than or equal to the preset deviation threshold, it is determined that the oscillation degree of the generator set is severe.

2. The method according to claim 1, characterized in that The state space matrix corresponding to the phasor measurement device PMU data is determined by using the Lyapunov direct method to determine the target matrix, including: According to the acquired phasor measurement device PMU data, based on the generator state space model, a state space matrix is ​​determined; The state space matrix is ​​analyzed by using Lyapunov direct method to determine the target matrix.

3. The method according to claim 1 or 2, characterized in that: Determining, according to the target matrix, that the power system is in a stable state comprises: When it is determined that the target matrix is ​​a positive definite matrix, it is determined that the power system is in a stable state.

4. The method according to claim 3, characterized in that The determining of the extreme point value corresponding to each oscillation of the oscillation curve comprises: The gradient descent method is used to determine the first extreme point value corresponding to the peak and the second extreme point value corresponding to the trough of the oscillation curve during each oscillation.

5. The method according to claim 2, characterized in that: Determining the state space matrix based on the generator state space model according to the acquired phasor measurement device PMU data includes: Summarize the acquired phasor measurement device PMU data to obtain power grid data; Performing dimension reduction preprocessing on the power grid data to obtain a data matrix; According to the data matrix, a state space matrix is ​​determined based on a generator state space model.

6. A generator set stability detection device, characterized in that: include: A data processing module is used to determine a target matrix based on a state space matrix corresponding to the PMU data of the phasor measurement device using the Lyapunov direct method; When it is determined that the power system is in a stable state according to the target matrix, the state deviation corresponding to the PMU data and the oscillation curve corresponding to the state deviation are obtained; and the extreme value corresponding to each oscillation of the oscillation curve is determined; A stability determination module, used for evaluating the working state of the generator set in the power system according to the extreme value point value; The stability determination module is specifically used for: Performing weighted summation on each extreme value point data to obtain an extreme value deviation; According to the extreme value deviation, evaluating the working state of the generator set in the power system; The stability determination module is specifically used for: When the extreme value deviation is less than a preset deviation threshold, determining that the oscillation degree of the generator set in the power system is not severe; When the extreme value deviation is greater than or equal to the preset deviation threshold, it is determined that the oscillation degree of the generator set is severe.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for detecting the stability of a generator set in a power system according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for detecting the stability of a generator set in a power system according to any one of claims 1 to 5 is implemented.

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