CN116244894B - Power system transient simulation method and system based on large step length - Google Patents
Power system transient simulation method and system based on large step length Download PDFInfo
- Publication number
- CN116244894B CN116244894B CN202211580935.2A CN202211580935A CN116244894B CN 116244894 B CN116244894 B CN 116244894B CN 202211580935 A CN202211580935 A CN 202211580935A CN 116244894 B CN116244894 B CN 116244894B
- Authority
- CN
- China
- Prior art keywords
- simulation
- module
- step length
- power system
- time constant
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
- G06F17/13—Differential equations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Geometry (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Operations Research (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The disclosure belongs to the technical field of power systems, and in particular relates to a power system transient simulation method and system based on a large step length, comprising the following steps: acquiring a time constant and a preset simulation step length of a power system module; judging the magnitude relation between the acquired time constant and a preset simulation step length, and determining the actual simulation step length of the power system module; according to the time constant, the preset simulation step length and the actual simulation step length, completing transient simulation of the power system; the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method.
Description
Technical Field
The disclosure belongs to the technical field of power systems, and particularly relates to a power system transient simulation method and system based on a large step size.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the increase of the scale and the change of the structure of the power system, the operation characteristics of the power system are more complex, the generated accidents are more and more difficult to predict by the traditional analysis method, the simulation technology of the power system is also continuously changed, and the characteristics and the emphasis of different simulation technologies are different.
The power system is a complex large-scale nonlinear multi-time scale system, and comprises a large number of variables with different time constants, wherein some variables have quick change characteristics, and some variables have slow change characteristics; in particular, for high-proportion power electronic equipment with small time constant and fast dynamic process, the simulation method which only adopts large-step simulation to realize accurate and clear simulation of the fast dynamic process and takes slow dynamics such as frequency as the dominant process has important significance.
The mathematical model of the transient simulation of the power system is a set of nonlinear rigid differential algebraic equations (differential algebraic equation, DAE), and the numerical integration algorithm is a core for solving the time domain calculation of the nonlinear rigid DAE equation and is also a basis for constructing an efficient solving algorithm. Therefore, the solving method of the differential equation is of great importance, and the research of the numerical integration method in the transient simulation of the power system is of great importance.
The current numerical integration calculation method applied to solving differential equations is mainly divided into two types, one type is a classical calculation method, such as the most common four-order Dragon-Gregorian method, euler method and deformation thereof, trapezoidal method and deformation thereof, linear multi-step method and the like, and has been widely applied to the field of electric power system simulation in China. The novel integration algorithm is improved on the basis of the classical integration algorithm or combined with other calculation methods, and new ideas are provided, such as a fine integration method, a matrix index method, a point matching method and the like.
The trapezoidal integral method has second-order precision and symmetrical A stability (symmetrical A stability), the original unstable mode in the system can be expressed, so that the problem of hyperstability is avoided, the calculation efficiency is high, the floating point number calculation amount when solving the network equation is equivalent to that of the backward Euler method, the trapezoidal integral method has strong adaptability to a rigid system, is very suitable for transient simulation of an electric power system, and is widely applied to practical simulation programs. PSD and PSASP developed by Chinese electric department adopts a fixed-step trapezoidal integration method, the common simulation step is 0.01s, and the calculation result is stable and reliable.
In recent years, aiming at the characteristics of large-scale multi-time scale of the power system, a numerical integration method such as a fine integration method, a multi-step Taylor series expansion method, a multi-rate method and the like also appears, and the transient simulation efficiency of the power system can be effectively improved. The fine integration method allows the adoption of larger step length by numerical simulation, and has the advantages of high calculation speed, high simulation precision and the like; according to the multi-step Taylor series expansion method for expanding different orders according to the integration time and the state variable types, the transient simulation efficiency of the power system can be effectively improved; the multi-rate method is to topologically divide the system according to the local truncation error or the physical characteristics of the system, and to simulate and analyze the divided variables by different methods, thereby improving the simulation efficiency.
The inventor finds that at least the following defects exist in the large-step transient simulation of the existing large-scale power system:
(1) For multi-rate simulation methods, the premise is that all variables must be properly grouped according to local truncation errors or physical characteristics of the system prior to simulation. However, no standard is formed in the aspects of the division criteria of the fast-varying component and the slow-varying component, the selection of the global step length and the local step length, the selection of the error range and the like, and the difficulty is brought to the transient simulation calculation of the power system.
(2) When some parameters or structures in the simulation process of the power system are changed, the tolerance of the existing numerical integration method to the simulation step length is small, and the problems that the numerical value is unstable, can not be converged even under a large step length and the like can occur; therefore, in the actual power system simulation, it is difficult to satisfy the requirement that the user obtains a process dominated by slow variables only by using large-step simulation.
(3) In the actual power system simulation, when faults occur and control is applied, small step-size simulation is required to be performed in a fast dynamic process, and if fixed step-size simulation is adopted, the whole simulation step size is limited to be very small, and the time is very long.
Disclosure of Invention
In order to solve the problems, the disclosure provides a large-step-size-based power system transient simulation method and a large-step-size-based power system transient simulation system, which can meet the requirement that a user expects to accurately and rapidly obtain a process taking a slow-change component as a dominant component by adopting only large-step-size simulation, ensure the calculation precision of the large-scale power system transient simulation under the large step size, and improve the overall calculation efficiency.
According to some embodiments, a first scheme of the present disclosure provides a power system transient simulation method based on a large step size, which adopts the following technical scheme:
a power system transient simulation method based on a large step length comprises the following steps:
acquiring a time constant and a preset simulation step length of a power system module;
judging the magnitude relation between the acquired time constant and a preset simulation step length, and determining the actual simulation step length of the power system module;
according to the time constant, the preset simulation step length and the actual simulation step length, completing transient simulation of the power system;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method.
As a further technical limitation, the time constant T is respectively judged by the obtained relation between the preset simulation step length and the time constant i Alpha times the time constant T i The size between beta times of the power system and a preset simulation step length H is selected to be used for actual simulation calculation in a small module of the power system, wherein alpha and beta both represent time constant setting parameters, and alpha is smaller than beta; namely:
when H < alpha T i When the method is used, H is used as an actual simulation step length in the small module to calculate an integral step length, and an implicit trapezoidal integral method is adopted to calculate and solve;
when alpha T i ≤H≤βT i When the simulation step size is preset, an improved implicit trapezoidal integration method is adopted for calculation and solution;
when H > beta T i And when the simulation step length is preset, calculating and solving by adopting an approximation processing method with a large step length.
Furthermore, in the process of calculating and solving by adopting the improved implicit trapezoidal integral method, small step processing is needed, namely, the preset simulation step H is divided into n i The actual integration step h is multiplied by i Repeating n within each small module i Iterative computation of the implicit trapezoidal method.
Furthermore, in the process of calculating and solving by adopting the approximation processing method with large step length, H is used as the integral step length of the actual simulation calculation in the small module, and the approximation processing method of different small modules under the simulation of large step length is considered.
Further, the approximation method adopting the large step length comprises approximation of a first-order inertia module, approximation of a differential module and approximation of a lead-lag module; the approximation processing of the first-order inertia module is direct static processing, and a linear result is output; the approximation processing of the differential module can be equivalent to the series connection of a pure differential module and a first-order inertia module, and linear output results are obtained through superposition by considering all attenuation before each moment at the moment.
Furthermore, the approximation processing of the lead-lag module can be equivalent to the parallel connection of the first-order inertia module and the differential module, the two modules are respectively processed in a large step size, and the large step size output result of the lead-lag module is obtained through the accumulation and summation of the two modules.
As a further technical limitation, the simulation is performed by adopting a large step length when the power system has no fault, the transient simulation is performed by adopting a small step length when the power system has no fault, the small step length is still adopted after the control is applied, but the large step length simulation is adopted after the power system is transited to a more stable state.
According to some embodiments, a second aspect of the present disclosure provides a large-step-size-based power system transient simulation system, which adopts the following technical scheme:
a large step size based power system transient simulation system comprising:
the acquisition module is configured to acquire a time constant and a preset simulation step length of the power system module;
the judging module is configured to judge the magnitude relation between the acquired time constant and a preset simulation step length and determine the actual simulation step length of the power system module;
the simulation module is configured to complete transient simulation of the power system according to the time constant, the preset simulation step length and the actual simulation step length;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method.
According to some embodiments, a third aspect of the present disclosure provides a computer-readable storage medium, which adopts the following technical solutions:
a computer readable storage medium having stored thereon a program which when executed by a processor implements the steps in a large step size based power system transient simulation method according to the first aspect of the present disclosure.
According to some embodiments, a fourth aspect of the present disclosure provides an electronic device, which adopts the following technical solutions:
an electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, the processor implementing steps in a large step size based power system transient simulation method according to the first aspect of the present disclosure when the program is executed.
Compared with the prior art, the beneficial effects of the present disclosure are:
the method and the device provide an optimization strategy of the self-adaptive integral step length, based on an implicit trapezoidal integral algorithm, a large step length set by a user is automatically converted into a small step length relative to a module with a smaller time constant, n times of repeated iterative computation are carried out, the computation error of the module with the smaller time constant in each iteration is reduced, and a proper integral step length is selected for simulation computation relative to a slow dynamic module with a larger time constant, so that the computation precision of all modules under large step length simulation is ensured. The optimization strategy of the self-adaptive integral step length is beneficial to accurately and clearly simulating the fast dynamic process of the fast-varying component with small time constant, and further improves the overall calculation accuracy in large-step simulation.
The present disclosure proposes an approximation strategy, a large step simulation processing technique that includes three modules: firstly, the first-order inertial module under a large step length is directly subjected to static treatment and is subjected to linear output; secondly, the differential module under the large step length can be equivalently connected in series between the pure differential module and the first-order inertial module, and the output at each moment is obtained by superposing all attenuation before each moment in consideration of the attenuation at the moment; and thirdly, the lead-lag module under the large step length can be equivalently connected in parallel with the first-order inertia module and the differential module, the two modules are respectively processed in the large step length, and finally, the sum is carried out to obtain the large step length output of the final lead-lag module. For a module with a small time constant, an approximate processing strategy is adopted under large-step simulation, so that the calculation efficiency is high, and the simulation precision meets the requirement of dynamic simulation. The tolerance of the approximate processing strategy to the simulation step length is higher, and the numerical stability is higher; the processing skills of the large-step simulation calculation on different small modules are provided, the calculation efficiency of the large-step simulation can be ensured while the simulation precision meets the requirement of dynamic simulation, and the tolerance and the numerical stability of the simulation step are improved.
The simulation method framework for autonomously setting the variable step length in the transient simulation of the actual power system is designed based on two strategies of the small time constant module. Compared with fixed-step simulation, the framework of the simulation method for autonomously setting the variable step can improve the overall calculation efficiency on the basis of ensuring the calculation precision in the actual power system simulation process, and can well meet the requirement that a user expects to accurately and rapidly obtain the simulation result taking the slow variable component as the dominant process by adopting only large-step simulation.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate and explain the exemplary embodiments of the disclosure and together with the description serve to explain the disclosure, and do not constitute an undue limitation on the disclosure.
FIG. 1 is a flow chart of a large step size based power system transient simulation method in a first embodiment of the present disclosure;
FIG. 2 is a flow chart of an adaptive integration step optimization method in accordance with a first embodiment of the present disclosure;
FIG. 3 is a flow chart of the approximation process of the module at large step in one embodiment of the present disclosure;
FIG. 4 is a flow chart of a simulation method of autonomously setting a variable step in a first embodiment of the present disclosure;
fig. 5 is a block diagram of a large step size based power system transient simulation system in a second embodiment of the disclosure.
Detailed Description
The disclosure is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.
Example 1
The embodiment of the disclosure first introduces a power system transient simulation method based on large step sizes.
The large-step-size-based power system transient simulation method as shown in fig. 1 comprises the following steps:
acquiring a time constant and a preset simulation step length of a power system module;
judging the magnitude relation between the acquired time constant and a preset simulation step length, and determining the actual simulation step length of the power system module;
according to the time constant, the preset simulation step length and the actual simulation step length, completing transient simulation of the power system;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method.
According to the relation between the module dynamics and the dominant dynamics expected to be observed by the user, the method selects an optimization strategy or an approximate processing strategy for adopting self-adaptive integral step length for different small time constant modules; and combining with an actual simulation process of the power system, adopting a simulation method for autonomously setting a variable step length.
As one or more embodiments, the time constant T is respectively judged according to the obtained relation between the preset simulation step length and the time constant i Alpha times the time constant T i The size between beta times of the power system and a preset simulation step length H is selected to be used for the actual simulation calculation inside a small module of the power system, wherein alpha and beta are bothRepresenting a time constant setting parameter, wherein alpha < beta; namely:
when H < alpha T i When the method is used, H is used as an actual simulation step length in the small module to calculate an integral step length, and an implicit trapezoidal integral method is adopted to calculate and solve;
when alpha T i ≤H≤βT i When the simulation step size is preset, an improved implicit trapezoidal integration method is adopted for calculation and solution;
when H > beta T i When the simulation step length is preset, calculating and solving by adopting an approximation processing method of a large step length
In the present embodiment, takeBeta=2; as shown in fig. 2, the process of the adaptive integral step optimization strategy is:
by acquiring simulation step length H set by a user and time constants T of i dynamic modules i Selecting a suitable integration step h i The method is used for actual simulation calculation inside the small module. And if the simulation step length set by the user is determined to be larger, performing small step length processing, and improving the traditional implicit trapezoidal algorithm.
The specific method comprises determining the value of local step length, and setting simulation step length H and small module time constant T by user i 1/4 and 2 times of (a):
when (when)When the simulation step length set by the user is considered to be very small, H is used as the integration step length of the actual simulation calculation in the small module, and the implicit trapezoidal integration method is adopted, so that the calculation accuracy is still very high;
when (when)In order to improve the simulation precision of the traditional implicit trapezoidal integral algorithm, the simulation step length set by the user is processed in a small step length, in particular to divide the simulation step length H set by the user into n i Double actualIntegration step h i Repeating n within each small module i Iterative computation of a subspecies trapezoidal method; the specific details are shown in a small-step calculation formula shown in a formula (1) and a formula (2):
when H > 2T i At this time, the simulation step length set by the user is very large, H is used as the integration step length of the actual simulation calculation in the small module, and the approximate processing method of different small modules under the large step length simulation is considered.
As one or more embodiments, as shown in fig. 3, the approximation strategy of the small module at large steps includes: the approximate processing method of the first-order inertia, differentiation and lead-lag module comprises the following specific steps:
(1) For the first-order inertial module, k in the formula (3) is the amplification factor, and T is the time constant of the first-order inertial module. When the time constant is very small, namely T-0, the module is statically processed, and the linear output shown in the formula (4) is achieved;
y＝kx (4)
(2) For the differential module, the serial connection of the pure differential module and the first-order inertial module can be equivalently used, as shown in formula (5), k is a proportionality coefficient of the differential module, and T is a time constant of the differential module.
Knowing the initial t 0 The input of time is x 0 When the large step-size simulation is carried out until the time t, the large step-size simulation process of the differential module is obtained by adopting the approximate processing of the module, and the specific steps are as follows:
(1) in the first step, since the differentiating module reflects the rate of change of the input signal, it is necessary to determine at the next time t 1 ＝t 0 Input x of +H acquisition 1 Whether or not at last moment x 0 Equal. If yes, the next time t 1 Output value y of (2) 1 Directly setting to 0; if not, the estimated initial value y of the pure differential module at the next moment is required to be obtained 1 micro : order theAnd as an integral step length in the differential module, performing iterative calculation under a small step length.
(2) The series connection of the pure differential module and the first-order inertial module in the differential link can be regarded as that the input signal firstly passes through the pure differential module to obtain an estimated output value, and then passes through a low-pass filtering link to enable the estimated output value at the moment to be processedTo obtain the next time t 1 Output value y of (2) 1 As shown in equation (6).
(3) To get the next time t 2 ＝t 1 And (3) repeating steps (1) - (2) according to the output value of +H, and considering the influence of the last moment and output. Although the output at the previous time decays exponentially, there is still output at that time, i.e. the output at the previous time decays to a value of that timeTherefore, considering the output attenuation amount at the previous time, the final output at that time is obtained as:
(4) to get t n ＝t 0 The output value at +nH time is taken into consideration by the output attenuation amount at each time before the time, i.e., t 1 ～t n-1 Output of time of day versus t n The influence of time isThus, t is obtained n The final output at time is:
(3) For the lead-lag module, it can be equivalent to the parallel connection of the first-order inertial module and the differential module, as shown in formula (9), where k is a proportionality coefficient, T 1 、T 2 Time constants of the lead and lag portions, respectively.
As shown in equation (10), the output of the lead-lag module at large steps is a superposition of the two module outputs, where y lead_lag 、y first_order 、y washout The output values of the lead-lag module, the first-order inertia module and the differential module in a large step length are respectively. The first-order inertia module under the large step length is statically processed, and the differential module performs the approximation processing, specifically as shown in a formula (11) and a formula (12).
y lead_lag ＝y first_order +y washout (10)
y first_order ＝kx (11)
As one or more embodiments, as shown in fig. 4, the autonomous variable step-size simulation method includes the following steps:
according to the relation between the module dynamics and the dominant dynamics expected to observe by a user, a strategy adopted for the small time constant module is selected, and in combination with the step of power system analysis, an autonomous setting variable step-size simulation method is adopted in the actual power system simulation, so that the proper step-size is adopted for simulation calculation in the fast dynamic process and the steady state process. Specifically, large step length is adopted in fault-free simulation, small step length is adopted in fault time to perform transient simulation, small step length is still adopted after control is applied, but large step length simulation is adopted after transition to a more stable state.
Aiming at the characteristics of multiple time scales of a large-scale power system, the embodiment aims at accurately and rapidly obtaining the simulation result taking the slow variable component as the dominant process by using only large-step simulation expected by a user, and is different from a multi-rate simulation method, and step adjustment is directly performed on the level of a bottom mathematical module. And selecting a proper processing strategy for the fast-changing component according to the simulation process of the actual power system, and adopting an autonomous setting variable step-length simulation method to ensure the calculation accuracy of the transient simulation of the large-scale power system under a large step length and improve the calculation efficiency.
Example two
The second embodiment of the disclosure introduces a power system transient simulation system based on a large step size.
A large step size based power system transient simulation system as shown in fig. 5, comprising:
the acquisition module is configured to acquire a time constant and a preset simulation step length of the power system module;
the judging module is configured to judge the magnitude relation between the acquired time constant and a preset simulation step length and determine the actual simulation step length of the power system module;
the simulation module is configured to complete transient simulation of the power system according to the time constant, the preset simulation step length and the actual simulation step length;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method.
The detailed steps are the same as those of the power system transient simulation method based on the large step size provided in the first embodiment, and will not be described herein.
Example III
A third embodiment of the present disclosure provides a computer-readable storage medium.
A computer readable storage medium having stored thereon a program which when executed by a processor performs steps in a large step size based power system transient simulation method according to an embodiment of the present disclosure.
The detailed steps are the same as those of the power system transient simulation method based on the large step size provided in the first embodiment, and will not be described herein.
Example IV
The fourth embodiment of the disclosure provides an electronic device.
An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, the processor implementing the steps in a large step size based power system transient simulation method according to embodiment one of the present disclosure when the program is executed.
The detailed steps are the same as those of the power system transient simulation method based on the large step size provided in the first embodiment, and will not be described herein.
The foregoing description of the preferred embodiments of the present disclosure is provided only and not intended to limit the disclosure so that various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
While the specific embodiments of the present disclosure have been described above with reference to the drawings, it should be understood that the present disclosure is not limited to the embodiments, and that various modifications and changes can be made by one skilled in the art without inventive effort on the basis of the technical solutions of the present disclosure while remaining within the scope of the present disclosure.
Claims (5)
1. The power system transient simulation method based on the large step length is characterized by comprising the following steps of:
acquiring a time constant and a preset simulation step length of a power system module;
judging the magnitude relation between the acquired time constant and a preset simulation step length, and determining the actual simulation step length of the power system module;
according to the time constant, the preset simulation step length and the actual simulation step length, completing transient simulation of the power system;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method;
by the obtained relation between the preset simulation step length and the time constant, namely respectively judging the time constant T i Alpha times the time constant T i The magnitude between beta times and the preset simulation step length H, selecting a proper integration step length for the actual simulation calculation inside the small module of the power system, wherein alpha and beta both represent time constant setting parameters, and alpha is<Beta; namely:
when H is<αT i When the method is used, H is used as an actual simulation step length in the small module to calculate an integral step length, and an implicit trapezoidal integral method is adopted to calculate and solve;
when alpha T i ≤H≤βT i When the simulation step size is preset, an improved implicit trapezoidal integration method is adopted for calculation and solution;
when H is>βT i When the simulation step length is preset, calculating and solving by adopting an approximation processing method with a large step length;
in the process of calculating and solving by adopting the improved implicit trapezoidal integration method, small step processing is needed, namely, the preset simulation step length H is divided into n i The actual integration step h is multiplied by i Repeating n within each small module i Iterative computation of a subspecies trapezoidal method;
in the process of calculating and solving by adopting a large-step approximation method, H is used as an integral step length of actual simulation calculation in a small module, and the approximation method of different small modules under large-step simulation is considered;
the approximation processing method adopting the large step length comprises approximation processing of a first-order inertia module, approximation processing of a differential module and approximation processing of a lead-lag module; the approximation processing of the first-order inertia module is direct static processing, and a linear result is output; the approximation processing of the differential module can be equivalent to the series connection of a pure differential module and a first-order inertia module, and linear output results are obtained through superposition by considering all attenuation before each moment;
the approximation processing of the lead-lag module can be equivalent to the parallel connection of the first-order inertia module and the differential module, the two modules are respectively processed in large step length, and the large step length output result of the lead-lag module is obtained through the accumulation summation of the two modules.
2. A large step size based power system transient simulation method as claimed in claim 1, wherein the simulation is performed with a large step size when the power system is fault-free, with a small step size when the power system is fault-free, and with a small step size after the control is applied, but with a large step size after the transition to a more stable state.
3. A large step-size based power system transient simulation system, comprising:
the acquisition module is configured to acquire a time constant and a preset simulation step length of the power system module;
the judging module is configured to judge the magnitude relation between the acquired time constant and a preset simulation step length and determine the actual simulation step length of the power system module;
the simulation module is configured to complete transient simulation of the power system according to the time constant, the preset simulation step length and the actual simulation step length;
the transient simulation of the power system comprises an adaptive integral step optimization method and an approximation processing method;
by the obtained relation between the preset simulation step length and the time constant, namely respectively judging the time constant T i Alpha times the time constant T i Beta times and pre-forms of (2)Setting the size between simulation step sizes H, and selecting a proper integration step size for practical simulation calculation in a small module of the power system, wherein alpha and beta both represent time constant setting parameters, wherein alpha<Beta; namely:
when H is<αT i When the method is used, H is used as an actual simulation step length in the small module to calculate an integral step length, and an implicit trapezoidal integral method is adopted to calculate and solve;
when alpha T i ≤H≤βT i When the simulation step size is preset, an improved implicit trapezoidal integration method is adopted for calculation and solution;
when H is>βT i When the simulation step length is preset, calculating and solving by adopting an approximation processing method with a large step length;
in the process of calculating and solving by adopting the improved implicit trapezoidal integration method, small step processing is needed, namely, the preset simulation step length H is divided into n i The actual integration step h is multiplied by i Repeating n within each small module i Iterative computation of a subspecies trapezoidal method;
in the process of calculating and solving by adopting a large-step approximation method, H is used as an integral step length of actual simulation calculation in a small module, and the approximation method of different small modules under large-step simulation is considered;
the approximation processing method adopting the large step length comprises approximation processing of a first-order inertia module, approximation processing of a differential module and approximation processing of a lead-lag module; the approximation processing of the first-order inertia module is direct static processing, and a linear result is output; the approximation processing of the differential module can be equivalent to the series connection of a pure differential module and a first-order inertia module, and linear output results are obtained through superposition by considering all attenuation before each moment;
the approximation processing of the lead-lag module can be equivalent to the parallel connection of the first-order inertia module and the differential module, the two modules are respectively processed in large step length, and the large step length output result of the lead-lag module is obtained through the accumulation summation of the two modules.
4. A computer readable storage medium having stored thereon a program, which when executed by a processor implements the steps of the large step size based power system transient simulation method of any of claims 1-2.
5. An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, wherein the processor implements the steps of the large step size based power system transient simulation method of any of claims 1-2 when the program is executed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211580935.2A CN116244894B (en) | 2022-12-09 | 2022-12-09 | Power system transient simulation method and system based on large step length |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211580935.2A CN116244894B (en) | 2022-12-09 | 2022-12-09 | Power system transient simulation method and system based on large step length |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116244894A CN116244894A (en) | 2023-06-09 |
| CN116244894B true CN116244894B (en) | 2023-09-15 |
Family
ID=86630327
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211580935.2A Active CN116244894B (en) | 2022-12-09 | 2022-12-09 | Power system transient simulation method and system based on large step length |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116244894B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102609575A (en) * | 2012-01-19 | 2012-07-25 | 浙江大学 | Power system transient stability simulating method based on implicit numerical integration |
| CN103700036A (en) * | 2013-12-19 | 2014-04-02 | 天津大学 | Transient stability projection integral method suitable for multi-time scale of electrical power system |
| CN106295001A (en) * | 2016-08-10 | 2017-01-04 | 华北电力大学 | The quasi-steady state variable step emulation mode of long time scale be applicable to power system |
| CN111881541A (en) * | 2020-06-03 | 2020-11-03 | 东南大学 | Electric power system transient stability simulation algorithm based on discontinuous Galerkin method |
| CN113158447A (en) * | 2021-04-07 | 2021-07-23 | 清华大学 | Large-step-length frequency-shift electromagnetic transient simulation method and system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113094887B (en) * | 2021-03-31 | 2024-05-03 | 清华大学 | Optimization method and device for frequency-shifting electromagnetic transient simulation and electronic equipment |
-
2022
- 2022-12-09 CN CN202211580935.2A patent/CN116244894B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102609575A (en) * | 2012-01-19 | 2012-07-25 | 浙江大学 | Power system transient stability simulating method based on implicit numerical integration |
| CN103700036A (en) * | 2013-12-19 | 2014-04-02 | 天津大学 | Transient stability projection integral method suitable for multi-time scale of electrical power system |
| CN106295001A (en) * | 2016-08-10 | 2017-01-04 | 华北电力大学 | The quasi-steady state variable step emulation mode of long time scale be applicable to power system |
| CN111881541A (en) * | 2020-06-03 | 2020-11-03 | 东南大学 | Electric power system transient stability simulation algorithm based on discontinuous Galerkin method |
| CN113158447A (en) * | 2021-04-07 | 2021-07-23 | 清华大学 | Large-step-length frequency-shift electromagnetic transient simulation method and system |
Non-Patent Citations (2)
| Title |
|---|
| Effectiveness indexes of numerical simulation for power system transient stability;Zhang Ning, et al.;DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS;全文 * |
| 电力系统全过程动态仿真的组合数值积分算法研究;宋新立，等;中国电机工程学报;第29卷(第28期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116244894A (en) | 2023-06-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109255160B (en) | Neural network-based unit delay prediction method and unit delay sensitivity calculation method | |
| CN113489014B (en) | Quick and flexible full-pure embedded power system optimal power flow evaluation method | |
| CN105938578A (en) | Large-scale photovoltaic power station equivalent modeling method based on clustering analysis | |
| CN112287605B (en) | Power flow checking method based on graph convolution network acceleration | |
| CN109599866B (en) | Prediction-assisted power system state estimation method | |
| Wang et al. | A two-stage method for assessment of voltage stability in power system with renewable energy | |
| CN113406503A (en) | Lithium battery SOH online estimation method based on deep neural network | |
| Guo et al. | An adaptive approach for battery state of charge and state of power co-estimation with a fractional-order multi-model system considering temperatures | |
| CN113791351B (en) | Lithium battery life prediction method based on transfer learning and difference probability distribution | |
| CN116667816A (en) | High-precision nonlinear Kalman filter design method based on neural network | |
| CN112946480B (en) | Lithium battery circuit model simplification method for improving SOC estimation real-time performance | |
| CN116244894B (en) | Power system transient simulation method and system based on large step length | |
| CN105677936B (en) | The adaptive recurrence multistep forecasting method of electromechanical combined transmission system demand torque | |
| CN112000004A (en) | Sewage treatment concentration control method utilizing iterative quadratic heuristic programming | |
| CN116148666A (en) | Battery SOC signal processing method, device, vehicle, computer readable storage medium and computer program product | |
| CN115859891A (en) | Method for determining simulation parameters of electrolytic aluminum electrolysis cell | |
| CN110034559B (en) | Power system fusion state estimation method based on switching system model | |
| CN110619147B (en) | Second-order and multi-order battery equivalent circuit model construction method applied to constant-voltage working condition | |
| CN109390946B (en) | Optimal probability load flow rapid calculation method based on multi-parameter planning theory | |
| CN107065557B (en) | Finite field filter design method with random filter gain variation | |
| CN112667957A (en) | Intelligent electric energy meter failure rate prediction method based on deep neural network | |
| CN108491606B (en) | A kind of strength of materials distribution acquiring method | |
| CN112949240B (en) | Multi-physical field coupling simulation method for centralized parameter model | |
| CN115883408B (en) | Multi-rate complex network state estimation method based on compensation | |
| CN113447818B (en) | Identification method and system of battery equivalent circuit model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |