A minimum inertia demand evaluation method and system for a new energy power system

Abstract

The application discloses a kind of minimum inertia demand evaluation method and system for new energy power system, the present application includes obtaining the source data and load data of new energy power system;Fitting construction synchronous unit low-order transfer function, new energy field station transfer function and load low-order transfer function;The frequency response model of power system is constructed, open loop processing establishes equation group containing the time point corresponding to the maximum deviation of system frequency, frequency maximum deviation constraint and minimum inertia time constant;Solve equation group to calculate the total equivalent kinetic energy of system that meets the minimum inertia demand of system.The present application aims to realize the minimum inertia demand evaluation of system considering the maximum deviation of frequency constraint, can be used as the data support of the virtual inertia control parameter setting of new energy field station, such as the support ability size of each new energy field station is combined to set virtual inertia control parameter, so that system frequency stability is improved, the anti-interference ability of system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system dispatching, and in particular to a minimum inertia requirement assessment method and system for a new energy power system. Background Art

[0002] Traditional thermal power plants are being gradually retired, and the proportion of renewable energy integration in provincial power grids is increasing. This has led to a decrease in the grid's equivalent inertia and primary frequency regulation capacity, weakening the system's ability to resist disturbances and accidents. In the face of incidents such as DC line double-lockouts and large-scale renewable energy outages, insufficient grid frequency stability can lead to rapid frequency drops, potentially impacting the grid's three defense lines and potentially causing severe consequences such as large-scale load loss. To better analyze system frequency stability under large-scale renewable energy integration, while also factoring in the response characteristics of the load side, a more comprehensive system frequency response model is needed. To address the issue of declining grid inertia, a method for assessing the system's minimum inertia requirement, which considers the maximum frequency deviation constraint, is needed. The results can serve as data support for tuning the virtual inertia control parameters of renewable energy stations. By evaluating the minimum inertia requirement and considering the supporting capacity of each renewable energy station, the virtual inertia control parameters can be adjusted, ultimately improving system frequency stability and enhancing the system's resistance to disturbances. Summary of the Invention

[0003] Technical problem to be solved by the present invention: In response to the above-mentioned problems in the prior art, a method and system for evaluating the minimum inertia requirement of a new energy power system are provided. The present invention aims to realize the system minimum inertia requirement evaluation considering the maximum frequency deviation constraint, which can serve as data support for the adjustment of virtual inertia control parameters of new energy stations. For example, the virtual inertia control parameters can be adjusted in combination with the support capacity of each new energy station to improve the system frequency stability and enhance the system's anti-interference ability.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A minimum inertia requirement assessment method for a new energy power system, comprising:

[0006] Obtain source data and load data of new energy power systems;

[0007] Combine source data and load data to fit and construct the low-order transfer function of synchronous units, construct the transfer function of new energy stations, and fit and construct the low-order transfer function of loads;

[0008] The power system frequency response model is constructed by combining the low-order transfer functions of synchronous units, renewable energy stations, and loads. Assuming that the primary frequency regulation power of the renewable energy power system is a linear function of time, the power system frequency response model is open-loop processed to establish a set of equations including the time point corresponding to the maximum system frequency deviation, the maximum frequency deviation constraint, and the minimum inertia time constant.

[0009] The equations are solved according to a given maximum frequency deviation constraint to calculate the total equivalent kinetic energy of the system requiring the minimum inertia of the system to satisfy the given maximum frequency deviation constraint.

[0010] Optionally, when obtaining the source data and load data of the new energy power system, the source data obtained include the synchronous unit rotational inertia and installed capacity data, the synchronous unit speed regulator-prime mover specific model and parameter data, the synchronous unit start-up and shutdown plan data, and the new energy station grid-connected control parameter data; the load data obtained is the power load level data of the entire network.

[0011] Optionally, the function expression of the low-order transfer function of the synchronous unit is:

[0012] ,

[0013] In the above formula, is the low-order transfer function of the synchronous unit of the i-th synchronous unit, 、 、 and are all coefficients of the low-order transfer function of the synchronous unit; the functional expression of the new energy station transfer function is:

[0014] ,

[0015] In the above formula, For the i The new energy station transfer function of each new energy station, is the virtual inertia coefficient, is the virtual droop coefficient; the function expression of the load low-order transfer function is:

[0016] ,

[0017] In the above formula, For the i The load low-order transfer function of a load, 、 、 and are the coefficients of the load low-order transfer function.

[0018] Optionally, the fitting and constructing of the low-order transfer function of the synchronous unit includes:

[0019] Based on a set time interval ,according to The low-order transfer function of the synchronous unit is converted from s domain to z Transformation z The low-order transfer function of the synchronous generator in the domain is:

[0020] ,

[0021] In the above formula, is the i-th synchronous unit z The low-order transfer function of the synchronous generator in the domain, 、 、 and These are parameters to be identified;

[0022] According to the specific model and parameters of the speed regulator-prime mover in the source data, a complete full-order speed regulation system model of each synchronous unit is built. A frequency step disturbance experiment is performed on the full-order speed regulation system model of each unit. A frequency step signal of a preset size is applied to the input port of the speed regulation system to obtain a standardized response power signal; the frequency step signal is set to a discrete sequence with a specified step length to obtain a discrete sequence of frequency step signals. , and obtain the corresponding output power signal discrete sequence ; According to the discrete sequence of frequency step signal , power signal discrete sequence Combined with the low-order transfer function of the synchronous unit and z The transformation principle establishes the relationship shown below:

[0023] ,

[0024] ,

[0025] ,

[0026] In the above formula, 、 and are discrete sequences of power signals The kth, k-1th and k-2th power signals in and are discrete sequences of frequency step signals The kth and k-1th frequency step signals in, is the observation sequence, is the parameter matrix to be identified;

[0027] The least squares method is used to identify the parameter matrix Perform parameter identification, and for input sequence length N In the case of The accuracy is given by the square of the error and To measure:

[0028] ,

[0029] And the error square sum The conditions for having a minimum value are:

[0030] ,

[0031] In the above formula, is the sum of the squares of the errors About the parameter matrix to be identified The partial derivative of is the matrix composed of power signals, is the matrix of the observation sequence, and has:

[0032] ,

[0033] ,

[0034] exist When the rank is full, the parameter matrix to be identified is obtained The least squares solution of is: .

[0035] Optionally, the function expression of the power system frequency response model is:

[0036]

[0037] In the above formula, is the system inertia time constant, is the frequency change at time t, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load, is the damping coefficient, is the system active power shortage at time t, and:

[0038] ,

[0039] In the above formula, is the number of synchronous units in the new energy power system, For the i The time constant of the synchronous unit, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, No. i The damping coefficient of the synchronous unit.

[0040] Optionally, the functional expression of the equation group including the time point corresponding to the maximum system frequency deviation, the maximum frequency deviation constraint, and the minimum inertia time constant is:

[0041] ,

[0042] In the above formula, To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, The time point corresponding to the maximum deviation of the system frequency of the new energy power system The system equivalent transfer function is is the active energy missing from the system, is the frequency reference value, is the maximum deviation constraint for a given frequency, where and is an unknown quantity, where the functional expression of the system equivalent transfer function is:

[0043] ,

[0044] In the above formula, is the system equivalent transfer function, is the equivalent transfer function of the system's additional power, which includes the frequency response model transfer functions of synchronous units, new energy stations, and loads, and has:

[0045] ,

[0046] In the above formula, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load.

[0047] Optionally, the function expression of the total equivalent kinetic energy of the system that meets the minimum inertia requirement of the system that meets the given maximum frequency deviation constraint is:

[0048] ,

[0049] In the above formula, The total equivalent kinetic energy of the system to meet the minimum inertia requirement of the system with a given maximum frequency deviation constraint is: To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of a new energy station.

[0050] In addition, the present invention also provides a minimum inertia requirement assessment system for a new energy power system, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the minimum inertia requirement assessment method for the new energy power system.

[0051] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system through a processor.

[0052] In addition, the present invention also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system through a processor.

[0053] Compared with the prior art, the present invention mainly has the following advantages: the present invention reduces the order of the speed control system model of the synchronous generator in the power system based on the parameter identification algorithm. The obtained low-order model can effectively reduce the amount of calculation, and takes into account the grid-connected control of the new energy station and the frequency response characteristics of the load side, and constructs a system frequency response model that includes the frequency response characteristics of both the source and the load. In terms of the minimum inertia demand evaluation, the present invention proposes a frequency response open-loop processing method, which obtains the system minimum inertia demand by solving a set of equations. The method proposed in the present invention can be well applied to the grid scenario with a high proportion of new energy access, and can accurately realize the system minimum inertia demand evaluation considering the maximum frequency deviation constraint. It can be used as data support for the virtual inertia control parameter adjustment of the new energy station. For example, the virtual inertia control parameters can be adjusted in combination with the support capacity of each new energy station to improve the system frequency stability and enhance the system's anti-interference ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0055] Figure 1 Schematic diagram of the basic process of the method of the embodiment of the present invention.

[0056] Figure 2 Schematic diagram of the system structure of the power system frequency response model in an embodiment of the present invention.

[0057] Figure 3 This is a topology diagram of the IEEE39 node test system used in the embodiment of the present invention.

[0058] Figure 4 3 is a comparison diagram of the frequency response curves of the time domain simulation and the low-order model in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0060] The minimum inertia requirement assessment method for new energy power systems of the present invention is designed to take into account the detailed frequency response characteristics of new energy units in new power systems with large-scale new energy access, and to achieve rapid and accurate calculation of the lowest point of the system frequency. Compared with time domain simulation calculations, it has higher efficiency and lower error. Figure 1 As shown, the minimum inertia requirement assessment method for a new energy power system in this embodiment includes:

[0061] S1, obtain source data and load data of the new energy power system;

[0062] S2, combining source data and load data to fit and construct the low-order transfer function of synchronous units, construct the transfer function of new energy stations, and fit and construct the low-order transfer function of loads;

[0063] S3: Construct a power system frequency response model by combining the low-order transfer functions of synchronous units, renewable energy station transfer functions, and loads. Assuming that the primary frequency regulation power of the renewable energy power system is a linear function of time, perform open-loop processing on the power system frequency response model and establish a set of equations including the time point corresponding to the maximum frequency deviation of the system, the maximum frequency deviation constraint, and the minimum inertia time constant.

[0064] S4, solving the equation group according to the given maximum frequency deviation constraint, and calculating the total equivalent kinetic energy of the system that satisfies the given minimum inertia requirement of the system.

[0065] When obtaining the source data and load data of the new energy power system in step S1 of this embodiment, the source data obtained include the synchronous unit rotational inertia and installed capacity scale data, the synchronous unit speed regulator-prime mover specific model and parameter data, the synchronous unit start-up and shutdown plan data, and the new energy station grid-connected control parameter data; the load data obtained is the power load level data of the entire network, among which the synchronous unit rotational inertia and installed capacity scale data refer to the rotor rotational kinetic energy and installed capacity data of all synchronous units including thermal power and hydropower in the power system, the new energy station grid-connected control parameters refer to the virtual inertia control parameters and virtual droop control parameters of each new energy station, and the load level data includes the total power load of the entire network and the proportion of constant impedance, constant current, and constant power loads.

[0066] The function expression of the low-order transfer function of the synchronous generator set constructed by fitting in step S2 of this embodiment is:

[0067] ,

[0068] In the above formula, is the low-order transfer function of the synchronous unit of the i-th synchronous unit, 、 、 and are all coefficients of the low-order transfer function of the synchronous unit; the functional expression of the new energy station transfer function is:

[0069] ,

[0070] In the above formula, For the i The new energy station transfer function of each new energy station, is the virtual inertia coefficient, is the virtual droop coefficient; the function expression of the load low-order transfer function is:

[0071] ,

[0072] In the above formula, For the i The load low-order transfer function of a load, 、 、 and are the coefficients of the load low-order transfer function.

[0073] In step S2 of this embodiment, fitting and constructing the low-order transfer function of the synchronous generator set includes:

[0074] 1) Based on a set time interval , using the backward difference method to s Domain transfer function z Transformation, that is, according to The low-order transfer function of the synchronous unit is converted from s domain to z Transformation z The low-order transfer function of the synchronous generator in the domain is:

[0075] ,

[0076] In the above formula, is the i-th synchronous unit z The low-order transfer function of the synchronous generator in the domain, 、 、 and These are parameters to be identified;

[0077] 2) Based on the specific model and parameters of the speed regulator-prime mover in the source data, a complete full-order speed regulation system model of each synchronous unit is constructed, and a frequency step disturbance experiment is performed on the full-order speed regulation system model of each unit. A frequency step signal of a preset size (which can be selected according to actual needs, for example, 1% in this embodiment) is applied to the input port of the speed regulation system to obtain a standardized response power signal; the frequency step signal is set to a discrete sequence with a specified step size (which can be selected according to actual needs, for example, 0.01s in this embodiment) to obtain a discrete sequence of frequency step signals , and obtain the corresponding output power signal discrete sequence ; According to the discrete sequence of frequency step signal , power signal discrete sequence Combined with the low-order transfer function of the synchronous unit and z The transformation principle establishes the relationship shown below:

[0078] ,

[0079] ,

[0080] ,

[0081] In the above formula, 、 and are discrete sequences of power signals The kth, k-1th and k-2th power signals in and are discrete sequences of frequency step signals The kth and k-1th frequency step signals in, is the observation sequence, is the parameter matrix to be identified;

[0082] 3) Use the least squares method to identify the parameter matrix Parameter identification is performed. Since the parameter identification method used in this embodiment is mainly used for offline modeling of the speed governor-prime mover, the influence of signal transmission noise or data abnormality that needs to be considered in online monitoring calculation is not considered in this embodiment. N In the case of The accuracy is given by the square of the error and To measure:

[0083] ,

[0084] And the error square sum The conditions for having a minimum value are:

[0085] ,

[0086] In the above formula, is the sum of the squares of the errors About the parameter matrix to be identified The partial derivative of is the matrix composed of power signals, is the matrix of the observation sequence, and has:

[0087] ,

[0088] ,

[0089] exist When the rank is full, the parameter matrix to be identified is obtained The least squares solution of is: .

[0090] Obtain the parameters to be identified in the second-order identification model of the synchronous unit speed governor-prime mover, and then bring the parameters into the function expression of the load low-order transfer function and perform inverse transformation to obtain s Domain transfer function, so far the low-order equivalent model of the speed governor-prime mover of all synchronous units can be obtained.

[0091] Static loads include constant impedance loads, constant current loads, and constant power loads. Since constant current loads account for a small proportion in actual power systems and can be ignored, the response model between their active power, voltage, and frequency can be simplified to the following form:

[0092] ,

[0093] In the above formula, is the per-unit value of load active power; is the proportion of constant impedance load in the system; is the load active frequency characteristic coefficient; is the frequency change; is the load voltage; is the rated voltage. Since the voltage change mechanism after the system accident is relatively complex, the least squares method is also used here to identify the load. The low-order load transfer is shown as follows:

[0094] ,

[0095] In the above formula, For the i The load low-order transfer function of a load, 、 、 and are the coefficients of the load low-order transfer function.

[0096] The power system frequency response model is constructed by combining the obtained unit speed governor-prime mover model and the system inertia level and load level data. In step S3 of this embodiment, the function expression of the constructed power system frequency response model is:

[0097] ,

[0098] In the above formula, is the system inertia time constant, is the frequency change at time t, 、 and are the sum of the additional power generated by all synchronous units at time t, the sum of the additional power generated by all new energy stations, and the sum of the changes in all load power. is the system active power shortage at time t, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load, is the damping coefficient, and:

[0099] ,

[0100] In the above formula, is the number of synchronous units in the new energy power system, For the i The time constant of the synchronous unit, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, No. i The damping coefficient of the synchronous unit, the above power system frequency response model can be graphically represented as follows Figure 2 As shown, Figure 2 In:

[0101]

[0102] Represents the inertia and damping components of the frequency swing equation; Laplace transforming the function expression of the power system frequency response model yields:

[0103] ,

[0104] In the above formula, It is the system active power shortage, which can usually be regarded as a step signal in the scenario of large power disturbance.

[0105] When the total additional power of the system is equal to the active power deficit, the system frequency deviation is the largest. Therefore, it is assumed that before this, the total additional power of the system is in the form of a linear function, as shown in the following formula:

[0106] ,

[0107] In the above formula, The time domain expression of the system's additional power; is the time point corresponding to the maximum deviation of the system frequency; is the active energy missing from the system, and its value is The step amount of the above is introduced into the function expression of the power system frequency response model:

[0108] ,

[0109] When the system active power deficit is the amount of active power missing from the system When = When:

[0110] ,

[0111] Therefore, when When:

[0112] ,

[0113] In the above formula, is the frequency at the time point corresponding to the maximum deviation of the system frequency, is the frequency reference value.

[0114] Will = The Laplace transform of the relationship is:

[0115] ,

[0116] In the above formula, The equivalent transfer function of the system's additional power includes the frequency response model transfer functions of synchronous units, new energy stations, and loads; is the equivalent transfer function of the system, and:

[0117] ,

[0118] In the above formula, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load.

[0119] Therefore, when When = The result of Laplace transform of the relationship when is inverse Laplace transform, we have:

[0120] ,

[0121] At this time, the maximum deviation constraint of the given system frequency , assuming that the minimum inertia time constant of the system that satisfies this constraint is , then the above equation and the frequency at the time point corresponding to the maximum deviation of the system frequency are combined The function expression of the equation group including the time point corresponding to the maximum frequency deviation of the system, the maximum frequency deviation constraint, and the minimum inertia time constant established in step S3 of this embodiment is obtained as follows:

[0122] ,

[0123] In the above formula, To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, The time point corresponding to the maximum deviation of the system frequency of the new energy power system The system equivalent transfer function is is the active energy missing from the system, is the frequency reference value, is the maximum deviation constraint for a given frequency, where and is an unknown quantity, where the functional expression of the system equivalent transfer function is:

[0124] .

[0125] In step S3 of this embodiment, the function expression of the total equivalent kinetic energy of the system that meets the system minimum inertia requirement of the given maximum frequency deviation constraint is:

[0126] ,

[0127] In the above formula, The total equivalent kinetic energy of the system to meet the minimum inertia requirement of the system with a given maximum frequency deviation constraint is: To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of a new energy station.

[0128] In order to verify the feasibility and effectiveness of the above-mentioned system frequency response model and the frequency minimum point calculation method provided in this embodiment, an IEEE 39-bus system was built on the DIgSILENT PowerFactory 2022 software platform and a specific implementation example analysis was carried out. Among them, the calculation program was compiled using MATLAB on the computer. Application Example: Taking the IEEE standard 30-bus system as the test system, Figure 3 As shown, wind turbines with a rated output of 2.5*30MW are connected to nodes 6, 22, 27, and 28 respectively. The wind power penetration rate is about 43%, and the power factor is constant at -0.98. The constant impedance load accounts for 50% of the total system load. The MATLAB platform is used for data modeling and calculation. First, the accuracy of the constructed system frequency response model considering the source-load double-sided response characteristics is verified. In order to simplify the complexity of the model, this embodiment aggregates all the low-order models of synchronous generators in the system into a whole according to their capacity, and sets the system to a 5% load surge. In order to verify the feasibility of the method of this embodiment, the initial inertia time constant of the system is set to 4.1592s, which is converted into kinetic energy of 35770 The frequency minimum point constraint is set to 49.60Hz, that is, the maximum frequency deviation is less than or equal to 0.4Hz, and the system frequency minimum point in the initial state is 49.4971Hz. The frequency minimum point time and the minimum inertia time constant solved by the method of this embodiment are 6.79s and 8.93s, which are converted to kinetic energy form as 76798 , which verifies the feasibility of the method of this embodiment. Figure 4 The time domain simulation results of the software platform (simulation platform results) and the simulation curve of the frequency response model established in this embodiment (proposed model results) show that the two curves are basically consistent before reaching the lowest frequency point, which can meet the calculation requirements of the method of this embodiment. In addition, the accuracy of the lowest frequency point of the proposed model also reaches 0.3348%.

[0129] In summary, the minimum inertia requirement assessment method for a new energy power system in this embodiment reduces the order of the speed control system model of the synchronous generator in the power system based on a parameter identification algorithm. The resulting low-order model can effectively reduce the amount of calculation, and takes into account the grid-connected control of the new energy station and the frequency response characteristics of the load side, constructing a system frequency response model that includes the frequency response characteristics of both the source and the load. In terms of minimum inertia requirement assessment, this embodiment proposes a frequency response open-loop processing method to obtain the system minimum inertia requirement by solving a set of equations. The method proposed in this embodiment can be well applied to power grid scenarios with a high proportion of new energy access, and can accurately implement the system minimum inertia requirement assessment considering the maximum frequency deviation constraint. It can serve as data support for the virtual inertia control parameter adjustment of new energy stations. For example, the virtual inertia control parameters can be adjusted in combination with the support capacity of each new energy station to improve the system frequency stability and enhance the system's anti-interference ability. The advantages of this embodiment's method are: ① The frequency response model takes into account the characteristics of synchronous units, renewable energy stations, and load response, effectively describing the characteristics of the frequency response of today's power systems; ② The closed-loop frequency response model is processed in an open-loop manner, avoiding the need to solve time-domain equations for complex closed-loop systems. Therefore, the model and calculation method proposed in this embodiment are highly adaptable and flexible, and can theoretically be applied to power grids of any size, providing real-time minimum inertia requirement information to grid operators and regulators.

[0130] In addition, this embodiment also provides a minimum inertia requirement assessment system for a new energy power system, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system.

[0131] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program or instructions, and the computer program or instructions are programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system through a processor.

[0132] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system through a processor.

[0133] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions described in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including the instruction device, which implements the function specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0134] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for evaluating minimum inertia requirements for a new energy power system, characterized in that: include: Obtain source data and load data of new energy power systems; Combine source data and load data to fit and construct the low-order transfer function of synchronous units, construct the transfer function of new energy stations, and fit and construct the low-order transfer function of loads; The power system frequency response model is constructed by combining the low-order transfer functions of synchronous units, renewable energy stations, and loads. Assuming that the primary frequency regulation power of the renewable energy power system is a linear function of time, the power system frequency response model is open-loop processed to establish a set of equations including the time point corresponding to the maximum system frequency deviation, the maximum frequency deviation constraint, and the minimum inertia time constant. Solving the set of equations according to a given maximum frequency deviation constraint to calculate the total equivalent kinetic energy of the system requiring the minimum inertia of the system to satisfy the given maximum frequency deviation constraint; The functional expression of the equation group including the time point corresponding to the maximum system frequency deviation, the maximum frequency deviation constraint, and the minimum inertia time constant is: ， In the above formula, To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, The time point corresponding to the maximum deviation of the system frequency of the new energy power system The system equivalent transfer function is is the active energy missing from the system, is the frequency reference value, is the maximum deviation constraint for a given frequency, where and is an unknown quantity, where the functional expression of the system equivalent transfer function is: ， In the above formula, is the system equivalent transfer function, is the equivalent transfer function of the system's additional power, which includes the frequency response model transfer functions of synchronous units, new energy stations, and loads, and has: ， In the above formula, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load, is the low-order transfer function of the synchronous unit of the i-th synchronous unit, For the i The new energy station transfer function of each new energy station.

2. The minimum inertia requirement assessment method for a new energy power system according to claim 1, characterized in that: When obtaining the source data and load data of the new energy power system, the source data obtained include the rotational inertia and installed capacity data of the synchronous unit, the specific model and parameter data of the synchronous unit speed regulator-prime mover, the start-up and shutdown plan data of the synchronous unit, and the grid-connected control parameter data of the new energy station; the load data obtained is the power load level data of the entire network.

3. The minimum inertia requirement assessment method for a new energy power system according to claim 1, characterized in that: The functional expression of the low-order transfer function of the synchronous unit is: ， In the above formula, is the low-order transfer function of the synchronous unit of the i-th synchronous unit, 、 、 and are all coefficients of the low-order transfer function of the synchronous unit; the functional expression of the new energy station transfer function is: ， In the above formula, For the i The new energy station transfer function of each new energy station, is the virtual inertia coefficient, is the virtual droop coefficient; the function expression of the load low-order transfer function is: ， In the above formula, For the i The load low-order transfer function of a load, 、 、 and are the coefficients of the load low-order transfer function.

4. The minimum inertia requirement assessment method for a new energy power system according to claim 3, characterized in that: The fitting and construction of the low-order transfer function of the synchronous unit includes: Based on a set time interval ,according to The low-order transfer function of the synchronous unit is converted from s domain to z Transformation z The low-order transfer function of the synchronous generator in the domain is: ， In the above formula, is the i-th synchronous unit z The low-order transfer function of the synchronous generator in the domain, 、 、 and These are parameters to be identified; According to the specific model and parameters of the speed regulator-prime mover in the source data, a complete full-order speed regulation system model of each synchronous unit is built. A frequency step disturbance experiment is performed on the full-order speed regulation system model of each unit. A frequency step signal of a preset size is applied to the input port of the speed regulation system to obtain a standardized response power signal; the frequency step signal is set to a discrete sequence with a specified step length to obtain a discrete sequence of frequency step signals. , and obtain the corresponding output power signal discrete sequence ; According to the discrete sequence of frequency step signal , power signal discrete sequence Combined with the low-order transfer function of the synchronous unit and z The transformation principle establishes the relationship shown below: ， ， ， In the above formula, 、 and are discrete sequences of power signals The kth, k-1th and k-2th power signals in and are discrete sequences of frequency step signals The kth and k-1th frequency step signals in, is the observation sequence, is the parameter matrix to be identified; The least squares method is used to identify the parameter matrix Perform parameter identification, and for input sequence length N In the case of The accuracy is given by the square of the error and To measure: ， And the error square sum The conditions for having a minimum value are: ， In the above formula, is the sum of the squares of the errors About the parameter matrix to be identified The partial derivative of is the matrix composed of power signals, is the matrix of the observation sequence, and has: ， ， exist When the rank is full, the parameter matrix to be identified is obtained The least squares solution of is: .

5. The method for evaluating minimum inertia requirements for a new energy power system according to claim 1, wherein: The functional expression of the power system frequency response model is: In the above formula, is the system inertia time constant, is the frequency change at time t, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, is the number of loads in the renewable energy power system, For the i The load low-order transfer function of a load, is the damping coefficient, is the system active power shortage at time t, and: ， In the above formula, is the number of synchronous units in the new energy power system, For the i The time constant of the synchronous unit, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of new energy stations, No. i The damping coefficient of the synchronous unit.

6. The method for evaluating minimum inertia requirements for a new energy power system according to claim 1, wherein: The functional expression of the total equivalent kinetic energy of the system that meets the minimum inertia requirement of the system that meets the given maximum frequency deviation constraint is: ， In the above formula, The total equivalent kinetic energy of the system to meet the minimum inertia requirement of the system with a given maximum frequency deviation constraint is: To satisfy the minimum inertia time constant of the maximum frequency deviation constraint of the system, is the number of synchronous units in the new energy power system, For the i Rated capacity of synchronous units, is the number of new energy stations in the new energy power system, For the i The rated capacity of a new energy station.

7. A minimum inertia requirement assessment system for a new energy power system, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system according to any one of claims 1 to 6 through a processor.

9. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the minimum inertia requirement assessment method for a new energy power system according to any one of claims 1 to 6 through a processor.

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