A method for establishing a frequency response model of a power system including photovoltaic power generation

Abstract

The present invention discloses a method for establishing a frequency response model of a power system containing photovoltaic power generation, comprising the following steps: S1, establishing a model of a conventional unit prime mover-speed regulator; S2, establishing a model of photovoltaic power generation participating in frequency control; S3, establishing an improved SFR model of a power system containing photovoltaic power generation according to the models in S1 and S2; S4, estimating the parameters in the S3 model framework, wherein some parameters are directly obtained by weighted calculation of each unit information, and the remaining parameters are obtained by identification according to constraint conditions; S5, substituting the parameters obtained in S4 into the S3 model, and predicting the frequency of the system after the disturbance by sensing the power system disturbance event. The model established by this method can predict the system frequency response, and accurately grasp the maximum frequency deviation, the lowest frequency point time, the steady-state frequency deviation and other information that may exist after the system is disturbed.

Description

Technical Field

[0001] The invention belongs to the technical field of power system frequency analysis, and relates to a method technology for establishing a frequency response model of a power system including photovoltaic power generation. Background Art

[0002] The frequency of the power system reflects the active power balance of the system. Once the active power balance disturbance occurs in the power system, the system frequency will deviate. If the system frequency regulation capability is insufficient, it may trigger the low-frequency load reduction protection action. In severe cases, it will cause the system to be disconnected, resulting in large economic losses. With the increase in the proportion of photovoltaic power generation, high-proportion photovoltaic power generation grid connection is one of the typical operating scenarios. After large-scale photovoltaic power generation is connected to the grid, it will significantly affect the frequency characteristics of the power grid. Therefore, it is necessary to study and analyze the frequency dynamic response characteristics of photovoltaic power generation grid-connected power systems.

[0003] The main methods for analyzing the frequency response characteristics of power systems include full-time domain simulation, frequency response calculation based on artificial intelligence algorithms, and frequency response models (SFR, System Frequency Response). Full-time domain simulation solves differential equations to obtain the frequency response information after the system disturbance based on the establishment of detailed models of each component of the power system. It has high accuracy, but the required amount of calculation and calculation time field are large, making it difficult to apply in real time. Frequency response calculation based on artificial intelligence algorithms has good prediction accuracy and speed, but the physical meaning of the model is unclear, and it is difficult to provide guidance for the optimization of actual system parameters. The SFR model has the advantages of low order, analyzability, and fast calculation, and is widely used in power system frequency stability analysis. However, the traditional SFR model only considers thermal power units and ignores the impact of frequency regulation dead zones. It will not be suitable for scenarios with a high proportion of photovoltaic access, and will directly cause errors between simulation analysis and actual measurement results.

[0004] Therefore, the present invention proposes a method for establishing a frequency response model of a power system containing photovoltaic power generation. The model takes into account the impact of photovoltaic frequency modulation and frequency modulation dead zone on frequency response, and provides a parameter calculation and identification method for the corresponding model. Based on the perception of disturbance events, the model established by the present invention can predict the system frequency response, providing a basis for further research on the frequency response control strategy of power systems containing a high proportion of photovoltaic power generation. Summary of the invention

[0005] Technical problem: After large-scale photovoltaic grid connection, it will significantly affect the frequency characteristics of the power grid. When the system is disturbed, there may be risks such as rapid frequency drop or surge, excessive frequency difference, etc., which will trigger the action of the system protection device and make the system face the risk of large-scale machine and load shedding. To solve such problems, the present invention proposes an improved frequency response model, which can quickly predict the system frequency response and provide guidance for ensuring the safe and stable operation of the power system.

[0006] Technical solution: A method for establishing a frequency response model of a power system including photovoltaic power generation, the specific steps are as follows:

[0007] S1: Establish the model of prime mover-speed governor of conventional unit. The conventional unit type is reheat steam turbine unit, and its prime mover-speed governor improved model consists of primary frequency regulation dead zone, regulation difference coefficient R H , equivalent speed regulator time constant T G , reheat time constant T RH , high pressure cylinder work ratio F HP composition.

[0008] When the system experiences power disturbance and the frequency deviation exceeds the primary frequency regulation dead zone of the steam turbine, the power change caused by the action of the steam turbine governor is as shown in formula (1):

[0009]

[0010] Where Δf is the system frequency deviation, s is the Laplace operator, and d H K is the primary frequency regulation dead zone of the steam turbine unit, H It is the proportion of thermal power units participating in primary frequency regulation in the total installed capacity of the system.

[0011] S2: Establish a model for photovoltaic power generation to participate in frequency control. Some photovoltaic stations provide frequency support to the power grid through functional transformation. The frequency control framework consists of a primary frequency regulation dead zone and a frequency difference coefficient R. R composition.

[0012] When the system experiences power disturbance and the frequency variation exceeds the primary frequency regulation dead zone of the photovoltaic station, the power variation caused by the speed regulator is shown in formula (2):

[0013]

[0014] Where, d R is the primary frequency regulation dead zone of the photovoltaic station, K R It is the proportion of photovoltaic power generation participating in primary frequency regulation in the system output.

[0015] S3: Based on the models in S1 and S2, an improved SFR model of the power system including photovoltaic power generation is established.

[0016] When the system generates power △P d After the disturbance, the system frequency response is shown in formula (3):

[0017]

[0018] Where H is the equivalent inertia constant of the system, and D is the equivalent damping coefficient of the load in the system.

[0019] S4: Estimate the parameters in the S3 model framework, where some parameters are directly calculated by weighting the information of each unit, and the remaining parameters are obtained through identification based on the constraints obtained from the S4 analysis.

[0020] There are 11 parameters in the S3 model, namely H, D, d H d R , K H , K R , R H , R R 、F HP , T RH , T G , where d H d R According to empirical values, the primary frequency regulation dead zone of thermal power units is 0.033Hz, and the primary frequency regulation dead zone of photovoltaic power generation is 0.05Hz.

[0021] K H , K R They are the ratios of the total installed capacity of thermal power and photovoltaic power participating in primary frequency regulation to the total installed capacity of the system.

[0022]

[0023]

[0024] In the formula, S Hi , S Ri are the installed capacities of thermal power and photovoltaic units in the system, m and n are the numbers of thermal power and photovoltaic units, k and l are the numbers of thermal power and photovoltaic units participating in primary frequency regulation, where k≤m, l≤n.

[0025] H is the system equivalent inertia constant. At present, it presents weak inertia or no inertia to the power grid. The inertia time constant of the photovoltaic unit can be considered to be 0. Therefore, the calculation formula of the system equivalent inertia time constant is:

[0026]

[0027] In the formula, H Hi is the inertia constant of the i-th thermal power unit;

[0028] F HP , T RH , R H The corresponding coefficient information of each thermal power unit participating in frequency regulation is obtained by weighting, that is,

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] Where: K Hi is the ratio of the installed capacity of the i-th thermal power unit to the total installed capacity of the system, R Hi is the adjustment coefficient of the i-th thermal power unit, F HPi is the reheating time constant of the i-th thermal power unit, F HPi is the work ratio of the high-pressure cylinder of the i-th thermal power unit;

[0035] By identifying the load equivalent damping coefficient D and the photovoltaic power generation adjustment coefficient R R And the equivalent speed regulator time constant T G to obtain it.

[0036] According to formula (3), when t→∞, the system steady-state frequency deviation can be obtained as:

[0037]

[0038] According to formula (12), we can know that D and R R There is an equality constraint between them. After identifying D, R can be directly solved. R ;

[0039]

[0040] Where E is the error function, f SFR is the equivalent model output frequency, f act is the actual system measurement frequency, θ=[D,T G ] T is the independent variable.

[0041] According to formula (13), the equivalent model output frequency f SFR Compared with the actual system measurement frequency f act The arithmetic square root of the sum of squares of the errors between them is the error function, and the particle swarm algorithm is used to minimize the error function to optimize D and T. G To identify.

[0042] S5: Substitute the parameters obtained in S4 into the S3 model, and predict the frequency of the system after the disturbance by sensing the power system disturbance event.

[0043] In addition, the present invention also discloses a computer-readable storage medium storing instructions, which can implement any of the above-mentioned methods when executed.

[0044] Beneficial effects:

[0045] The present invention provides a method for establishing a frequency response model of an electric power system including photovoltaic power generation. Based on the perceived disturbance event, the system frequency response can be predicted, and the maximum frequency deviation, the frequency minimum point time, the steady-state frequency deviation and other information after the disturbance occurs can be accurately predicted. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a block diagram of the frequency response model of a power system including photovoltaic power generation;

[0047] Figure 2 This is the control block diagram of the IEEE-G1 steam turbine speed control system;

[0048] Figure 3 The system frequency curve under different disturbances when the photovoltaic penetration rate is 10%;

[0049] Figure 4 The system frequency curve under different disturbances when the photovoltaic penetration rate is 20%;

[0050] Figure 5 This is the system frequency curve under different disturbances when the photovoltaic penetration rate is 35%. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the present invention, and thus to more clearly define the scope of the present invention, the present invention is described in detail with respect to some specific embodiments of the present invention. It should be noted that the following are only some specific implementation methods of the present invention, wherein the specific and direct description of the relevant structure is only for the convenience of understanding the present invention, and each specific feature does not naturally and directly limit the scope of implementation of the present invention.

[0052] The present invention is described in further detail below. However, the present invention is not limited to the examples given.

[0053] A method for establishing a frequency response model of a power system including photovoltaic power generation, the specific steps are as follows: S1: Establishing a model of a prime mover-speed governor of a conventional unit. The conventional unit type is a reheat steam turbine unit, and its prime mover-speed governor improved model consists of a primary frequency regulation dead zone, a regulation coefficient R H , equivalent speed regulator time constant T G , reheat time constant T RH , high pressure cylinder work ratio F HP composition.

[0054] When the system experiences power disturbance and the frequency variation exceeds the primary frequency regulation dead zone of the steam turbine, the power variation caused by the action of the steam turbine governor is as shown in formula (1):

[0055]

[0056] Where Δf is the system frequency deviation, s is the Laplace operator, and d H is the primary frequency regulation dead zone of the steam turbine unit, K H It is the proportion of the output of thermal power units participating in primary frequency regulation in the system.

[0057] S2: Establish a model for photovoltaic power generation to participate in frequency control. Some photovoltaic units provide frequency support to the power grid through functional transformation. The frequency control framework consists of a primary frequency regulation dead zone and a frequency difference coefficient R R composition.

[0058] When the system experiences power disturbance and the frequency change exceeds the primary frequency regulation dead zone of the photovoltaic generator set, the power change caused by the speed regulator action is shown in formula (2):

[0059]

[0060] Where, d R is the primary frequency regulation dead zone of photovoltaic power generation, K R It is the proportion of the output of photovoltaic power generation units participating in primary frequency regulation in the system.

[0061] S3: Based on the models in S1 and S2, an improved SFR model of the power system including photovoltaic power generation is established. The model framework is as follows: Figure 1 shown.

[0062] When the system generates power △P d After the disturbance, the system frequency response is shown in formula (3):

[0063]

[0064] Where H is the equivalent inertia constant of the system, and D is the equivalent damping coefficient of the load in the system.

[0065] S4: Estimate the parameters in the S3 model framework, where some parameters are directly calculated by weighting the information of each unit, and the remaining parameters are obtained through identification based on the constraints obtained from the S4 analysis.

[0066] There are 11 parameters in the S3 model, namely H, D, d H d R , K H , K R , R H , R R 、F HP , T RH , T G , where d H d R According to empirical values, the primary frequency regulation dead zone of thermal power units is 0.033Hz, and the primary frequency regulation dead zone of photovoltaic power generation is 0.05Hz.

[0067] K H , K R They are the ratios of the total installed capacity of thermal power and photovoltaic power participating in primary frequency regulation to the total installed capacity of the system.

[0068]

[0069]

[0070] In the formula, S Hi , S Ri are the installed capacities of thermal power and photovoltaic units in the system, m and n are the numbers of thermal power and photovoltaic units, k and l are the numbers of thermal power and photovoltaic units participating in primary frequency regulation, where k≤m, l≤n.

[0071] H is the system equivalent inertia constant. At present, it presents weak inertia or no inertia to the power grid. The inertia time constant of the photovoltaic unit can be considered to be 0. Therefore, the calculation formula of the system equivalent inertia time constant is:

[0072]

[0073] In the formula, H Hi is the inertia constant of the i-th thermal power unit;

[0074] F HP , T RH , R H The corresponding coefficient information of each thermal power unit participating in frequency regulation is obtained by weighting, that is,

[0075]

[0076]

[0077]

[0078]

[0079]

[0080] Where: K Hi is the ratio of the installed capacity of the i-th thermal power unit to the total installed capacity of the system, R Hi is the adjustment coefficient of the i-th thermal power unit, F HPi is the reheating time constant of the i-th thermal power unit, F HPi is the work ratio of the high-pressure cylinder of the i-th thermal power unit;

[0081] Due to the large number of photovoltaic units, its adjustment coefficient is difficult to obtain, and the equivalent damping coefficient D includes the generator damping coefficient and the load frequency factor, which is difficult to calculate directly. Therefore, the load equivalent damping coefficient D and the adjustment coefficient R of photovoltaic power generation are identified. R And the equivalent speed regulator time constant T G to obtain it.

[0082] According to formula (3), when t→∞, the system steady-state frequency deviation can be obtained as:

[0083]

[0084] According to formula (12), we can know that D and R R There is an equality constraint between them. After identifying D, R can be directly solved. R .

[0085]

[0086] Where E is the error function, f SFR is the equivalent model output frequency, f act is the actual system measurement frequency, θ=[D,T G ] T is the independent variable.

[0087] According to formula (13), the equivalent model output frequency f SFR Compared with the actual system measurement frequency f act The arithmetic square root of the sum of squares of the errors between them is the error function, and the particle swarm algorithm is used to minimize the error function to optimize D and T. G To identify.

[0088] S5: Substitute the parameters obtained in S4 into the S3 model, and predict the frequency of the system after the disturbance by sensing the power system disturbance event.

[0089] In order to further understand the present invention, a simulation analysis of a frequency response model of a power system including photovoltaic power generation is performed based on the DIgSILENT / PowerFactory simulation platform to explain the practical application of the present invention.

[0090] The example is the improved New England 10-machine 39 power saving system. Without loss of generality, the speed governor control system of the thermal power unit adopts the following Figure 2The IEEE-G1 speed control system shown in the figure adopts the photovoltaic model of the general electromechanical transient model of photovoltaic power generation proposed by the Western Electricity Coordinating Committee and the Electric Power Research Institute of the United States. A 2% load disturbance is set for parameter calculation, and a 5% load disturbance is used to verify the improved frequency response model and parameter calculation method. Simulation analysis is performed when the photovoltaic penetration rate is 10%, 20%, and 35%. The parameter calculation results are shown in Table 1-3, and the simulation results are shown in Table 1-3. Figure 3-5 shown.

[0091] Table 1 Model parameters when photovoltaic penetration is 10%

[0092]

[0093] Table 2 Model parameters when photovoltaic penetration is 20%

[0094]

[0095] Table 3 Model parameters when the photovoltaic penetration rate is 35%

[0096]

[0097] Depend on Figure 3-5 It can be seen that under different photovoltaic penetration rates, the initial frequency drop, the lowest frequency drop point and its corresponding time, and the frequency steady-state value, the improved SFR model and the time domain simulation have a high degree of consistency, indicating that the weighted equivalent inertia constant H and the turbine reheating time constant T RH , Steam turbine adjustment coefficient R H The effectiveness of the speed regulator parameters T G , Photovoltaic regulation coefficient R R In addition, Figure 3-5 It can be seen that when the parameters calculated by 2% load disturbance are subjected to 5% load disturbance, the improved SFR model and the frequency response curve obtained by time domain simulation have a high degree of fit. The results show that the improved SFR model and parameter calculation method have good adaptability. That is, when the system installation does not change significantly, the parameter calculation and identification results under one working condition are applicable to other working conditions. Therefore, the system frequency response can be predicted by sensing the disturbance event, and the maximum frequency deviation, the lowest frequency point time, the steady-state frequency deviation and other information that may exist after the disturbance occurs can be accurately grasped.

[0098] In summary, under different photovoltaic penetration rates and different disturbance conditions, the improved SFR model can quickly and accurately reflect the dynamic frequency of the system after the disturbance, and grasp the information such as the maximum frequency deviation, the lowest frequency point time, and the steady-state frequency deviation that may exist after the disturbance occurs.

[0099] In some examples of the present invention, there is also a computer-readable storage medium storing instructions. When the instructions are executed, the above-mentioned method for suppressing transient overvoltage indicators of the AC system at the sending end can be implemented. More specifically, the instructions can be a computer-readable language. The above-mentioned computer can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer can be a desktop computer, a portable computer, a network server, a PDA (Personal Digital Assistant), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The storage medium can be any available medium that can be accessed by the computer or a data storage device such as a server or a data center that includes one or more available media. For example, the storage medium is, for example, but not limited to, a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a digital versatile disc (DVD)), or a semiconductor medium (for example, a solid-state drive (SSD)).

[0100] The above describes the specific implementation of the present invention. It should be understood that the present invention is not limited to the above specific implementation, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for establishing a frequency response model of a power system including photovoltaic power generation, characterized in that: The following steps are involved: S1: Establish the model of prime mover-speed governor of conventional unit. The conventional unit type is reheat steam turbine unit. Its prime mover-speed governor improved model consists of primary frequency regulation dead zone, regulation coefficient R H , equivalent speed regulator time constant T G , reheat time constant T RH , high pressure cylinder work ratio F HP composition; When the system experiences power disturbance and the frequency variation exceeds the primary frequency regulation dead zone of the steam turbine, the power variation caused by the action of the steam turbine governor is as shown in formula (1): Where Δf is the system frequency deviation, s is the Laplace operator, and d H is the primary frequency regulation dead zone of the steam turbine unit, K H The proportion of thermal power units participating in primary frequency regulation in the system output; S2: Establish a model for photovoltaic power generation to participate in frequency control; some photovoltaic units provide frequency support to the power grid through functional transformation, and its frequency control framework is composed of the primary frequency regulation dead zone and the differential coefficient R R composition; When the system experiences power disturbance and the frequency change exceeds the primary frequency regulation dead zone of the photovoltaic generator set, the power change caused by the speed regulator action is shown in formula (2): Where, d R is the primary frequency regulation dead zone of photovoltaic power generation, K R The proportion of the output of photovoltaic power generation units participating in primary frequency regulation in the system; S3: Based on the models in S1 and S2, an improved SFR model of the power system including photovoltaic power generation is established; When the system generates power △P d After the disturbance, the system frequency response is shown in formula (3): In the formula, H is the equivalent inertia constant of the system, and D is the equivalent damping coefficient of the load in the system; S4: Estimate the parameters in the S3 model framework, where some parameters are directly calculated by weighting the information of each unit, and the remaining parameters are obtained by identification based on the constraints obtained from the S4 analysis; S5: Substitute the parameters obtained in S4 into the S3 model, and predict the frequency of the system after the disturbance by sensing the power system disturbance event; S4 specifically includes the following steps: There are 11 parameters in the S3 model, namely H, D, d H d R , K H , K R , R H , R R 、F HP , T RH , T G , where d H d R According to the empirical value, the dead zone of primary frequency regulation of thermal power units is 0.033Hz, and the dead zone of primary frequency regulation of photovoltaic power generation is 0.05Hz; K H , K R They are the ratios of the total installed capacity of thermal power and photovoltaic power participating in primary frequency regulation to the total installed capacity of the system; In the formula, S Hi , S Rj are the installed capacity of each thermal power and photovoltaic unit in the system, m and n are the number of thermal power and photovoltaic units, k and l are the number of thermal power and photovoltaic units participating in primary frequency regulation, where k≤m, l≤n; H is the system equivalent inertia constant. At present, it presents weak inertia or no inertia to the power grid. The inertia time constant of the photovoltaic unit can be considered to be 0. Therefore, the calculation formula of the system equivalent inertia time constant is: In the formula, H Hi is the inertia constant of the i-th thermal power unit; F HP 、T RH , R H The corresponding coefficient information of each thermal power unit participating in frequency regulation is obtained by weighting, that is, Where: K Hi is the ratio of the installed capacity of the i-th thermal power unit to the total installed capacity of the system, R Hi is the adjustment coefficient of the i-th thermal power unit, F HPi is the reheating time constant of the i-th thermal power unit, F HPi is the work ratio of the high-pressure cylinder of the i-th thermal power unit; By identifying the load equivalent damping coefficient D and the photovoltaic power generation adjustment coefficient R R And the equivalent speed regulator time constant T G To obtain; According to formula (3), when t→∞ When , the system steady-state frequency deviation can be obtained as: According to formula (12), we can know that D and R R There is an equality constraint between them. After identifying D, R can be directly solved. R ; Where E is the error function, f SFR is the equivalent model output frequency, f act is the actual system measurement frequency, θ=[D,T G ] T is the independent variable; According to formula (13), the equivalent model output frequency f SFR Compared with the actual system measurement frequency f act The arithmetic square root of the sum of squares of the errors between them is the error function, and the particle swarm algorithm is used to minimize the error function to optimize D and T. G To identify.

2. A computer-readable storage medium storing instructions, which, when executed, are used to implement the method of claim 1.

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