A dynamic evaluation method for control parameters of new energy stations

Abstract

The present application provides a method for dynamically evaluating the control parameters of a new energy station, including: according to the frequency dynamic response process after the system is disturbed, retaining the nonlinear links and corresponding parameters that affect the frequency in each unit of the multi-heterogeneous frequency regulation resources and constructing a system multi-machine frequency response model; based on the system multi-machine frequency response model, determining the frequency change rate at the moment the system is disturbed; based on the frequency change rate, determining the virtual inertia control parameters of the new energy station; based on the virtual inertia control parameters and the system multi-machine frequency response model, determining the maximum frequency deviation after the system is disturbed; based on the maximum frequency deviation and the virtual inertia control parameters, determining the primary frequency regulation control parameters of the new energy station. The evaluation results can provide engineering guidance for the configuration of control parameters of new energy stations, support the optimization of controllers and the implementation of active support strategies, and improve frequency response under various working conditions, thereby enhancing the safety and stability of the system.

Description

Technical Field

[0001] The present application relates to the technical field of dynamic evaluation of power systems, and in particular to a method for dynamic evaluation of control parameters of new energy stations. Background Art

[0002] With the continuous optimization of the global energy structure, the proportion of renewable energy access in power systems continues to increase. In particular, the proportion of new energy sources such as wind power and photovoltaics has increased rapidly, gradually replacing traditional synchronous generators based on thermal power. While this trend has effectively promoted the process of clean energy and reduced greenhouse gas emissions, it has also posed unprecedented challenges to the safe and stable operation of power systems. Due to the high proportion of renewable energy access, the proportion of traditional synchronous generators in power systems has continued to decline, the system inertia level has been significantly reduced, the primary frequency regulation capability has been weakened, and the power fluctuation range has increased, posing severe challenges to frequency stability. Under the same disturbance scenario, the frequency change rate and frequency fluctuation amplitude increase, resulting in an increase in the probability of low-frequency load shedding and high-frequency generator tripping protection. Frequency safety issues have become a major threat that cannot be ignored in systems with a high proportion of converters, and it is urgent to address them through technological upgrades and the introduction of new control measures.

[0003] Under conventional control methods, renewable energy generation is primarily connected to the system through power electronic converters. These converters lack rotating mass support and are unable to provide traditional inertia support, resulting in a significant decrease in the overall inertia level of the power system. Furthermore, converters typically operate in maximum power point tracking (MPPT) mode, prioritizing maximum energy output. These converters lack the ability to sense and respond to grid frequency fluctuations, further weakening the system's dynamic regulation capabilities, particularly at the primary frequency regulation level. Currently, newly released domestic and international guidelines have established clear requirements for renewable energy participation in grid inertia response and primary frequency regulation, aiming to address the system support gap caused by the retirement of synchronous generators, thereby improving system stability and security and ensuring that renewable energy stations can effectively participate in the dispatch and operation of the power system.

[0004] However, in actual applications, different power system topologies, load characteristics, and disturbance types place diverse demands on the response capabilities of new energy stations to system frequency disturbances. Current mainstream research focuses on evaluating the frequency support capabilities that new energy stations can provide by identifying their existing control parameters, such as virtual inertia coefficient and frequency regulation coefficient. This type of approach emphasizes the identification and modeling of existing control strategies, and is more focused on the perspective of "how much support can be provided" rather than the system frequency security requirements, which in turn infers "how much support should be provided" by new energy stations. Therefore, in the context of responding to a high proportion of new energy access and the continuous decline in power system inertia, existing methods find it difficult to accurately assess the inertia and frequency regulation capabilities required of new energy stations under different operating conditions, making it difficult to effectively support the optimal configuration of frequency control strategies and the quantitative management of active support capabilities, becoming one of the key factors restricting the actual promotion and implementation of new energy active support strategies. Summary of the Invention

[0005] In order to overcome the above technical deficiencies, this application provides a method for dynamically evaluating the control parameters of a new energy station. To achieve the above objectives, this application is implemented according to the following technical solutions:

[0006] This application provides a method for dynamically evaluating control parameters of a new energy station, including:

[0007] Step S101: According to the frequency dynamic response process after the system is disturbed, retain the nonlinear links and corresponding parameters that affect the frequency in each unit of the multi-heterogeneous frequency modulation resources and build a system multi-machine frequency response model;

[0008] Step S102: determining the frequency change rate of the system at the moment of disturbance based on the system multi-machine frequency response model;

[0009] Step S103: determining a virtual inertia control parameter of the new energy station based on the frequency change rate;

[0010] Step S104: determining the maximum frequency deviation of the system after being disturbed based on the virtual inertia control parameter and the system multi-machine frequency response model;

[0011] Step S105: Determine the primary frequency regulation control parameters of the new energy station based on the maximum frequency deviation and the virtual inertia control parameters.

[0012] Optionally, the multi-heterogeneous frequency regulation resources include hydropower units, thermal power units, gas turbines, direct current transmission, and new energy stations.

[0013] Optionally, according to the frequency dynamic response process after the system is disturbed, retaining the nonlinear links and corresponding parameters that affect the frequency in each unit of the multi-heterogeneous frequency modulation resources and constructing the system multi-machine frequency response model includes:

[0014] The frequency dynamic response process of the system after being disturbed can be expressed as:

[0015] ;

[0016] Where, is the equivalent inertia constant of the system, is the maximum frequency deviation, is the sum of the primary frequency regulation powers of all synchronous generator sets; The power released by DC participating in FLC control; Provide fast frequency modulation power for new energy stations; is the equivalent damping coefficient of the system, is the fault disturbance amount;

[0017] Aggregate the inertia constant of the new energy station with the inertia constant of the synchronous unit to determine the equivalent inertia constant of the system:

[0018] ;

[0019] Where, represents the inertia constant of the thermal power unit, represents the inertia constant of the hydropower unit, represents the gas turbine inertia constant, is the virtual inertia control constant of the new energy station;

[0020] Based on the equivalent inertia constant of the system and the frequency dynamic response process of the system after being disturbed, the nonlinear links and corresponding parameters affecting the frequency in each unit of the multi-heterogeneous frequency regulation resources are retained and a system multi-machine frequency response model is constructed.

[0021] Optionally, determining the frequency change rate of the system at the moment of disturbance based on the system multi-machine frequency response model includes:

[0022] Step S401: setting the fault magnitude, setting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables to zero, and then substituting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables into the system multi-machine frequency response model;

[0023] Step S402: simulating the system multi-machine frequency response model to obtain the frequency change rate during the frequency response process;

[0024] The determining of the virtual inertia control parameter of the new energy station based on the frequency change rate includes:

[0025] Step S403: Determine whether the flag variable is 1;

[0026] If not, proceed to step S404;

[0027] If so, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, the simulation ends, and step S104 is executed;

[0028] Step S404: determining whether the frequency change rate is at a critical position of the constraint condition;

[0029] If so, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, the simulation ends, and step S104 is executed;

[0030] If not, the virtual inertia control parameter is corrected using the Brent iteration algorithm, and then step S402 is executed.

[0031] Optionally, the adopting the Brent iteration algorithm to correct the virtual inertia control parameter includes:

[0032] Step S501: determining whether the difference between the frequency change rate and a set frequency change rate target value is less than zero;

[0033] If so, the following formula is used to update the current first evaluation interval range;

[0034] ;

[0035] Where, is the virtual inertia control parameter, is the minimum value of the current first evaluation range, The maximum value of the current first evaluation range;

[0036] If not, the following formula is used to update the current first evaluation interval range:

[0037] ;

[0038] Step S502: determining whether the length of the updated current first evaluation interval is greater than a first preset value, and whether the difference between the frequency change rate and the set frequency change rate target value is also greater than a first accuracy value;

[0039] If yes, update the dynamic switching condition parameter to 0 and execute step S503;

[0040] If not, update the dynamic switching condition parameter to 1 and execute step S503;

[0041] Step S503: Determine whether the dynamic switching condition parameter is 1;

[0042] If not, proceed to step S504;

[0043] If yes, execute step S505;

[0044] Step S504: using a dichotomy method to correct the virtual inertia control parameter;

[0045] ;

[0046] Step S505: Correct the virtual inertia control parameters using the secant method:

[0047] ;

[0048] Where, The updated maximum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed, The updated minimum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed, is the set frequency change rate target value;

[0049] Step S506: determining whether the virtual inertia control parameter corrected by the secant method is within the updated current first evaluation interval;

[0050] If not, proceed to step S504;

[0051] If so, execute step S402.

[0052] Optionally, after the step of correcting the virtual inertia control parameter using the dichotomy method, the method further includes:

[0053] Determining whether the updated length of the current first evaluation interval is less than the second precision value;

[0054] If yes, update the flag variable to 1 and execute step S402;

[0055] If not, update the flag variable to 0 and execute step S402.

[0056] Optionally, determining the maximum frequency deviation of the system after being disturbed based on the virtual inertia control parameter and the system multi-machine frequency response model includes:

[0057] Step S701: Substituting the initial values ​​of the virtual inertia control parameter and the primary frequency modulation control parameter, and the flag variable into the system multi-machine frequency response model;

[0058] Step S702: simulating the system multi-machine frequency response model to obtain the maximum frequency deviation after the system is disturbed;

[0059] The determining of the primary frequency regulation control parameter of the new energy station based on the maximum frequency deviation and the virtual inertia control parameter includes:

[0060] Step S703: Determine whether the flag variable is 1;

[0061] If not, proceed to step S704;

[0062] If yes, the current primary frequency modulation control parameter value corresponding to the frequency change rate is used as the primary frequency modulation control parameter, and the simulation and evaluation are terminated;

[0063] Step S704: determining whether the maximum frequency deviation is at a critical position of the constraint condition;

[0064] If yes, the current primary frequency modulation control parameter value corresponding to the frequency change rate is used as the primary frequency modulation control parameter, and the simulation and evaluation are terminated;

[0065] If not, the Brent iteration algorithm is used to modify the primary frequency modulation control parameter, and then step S702 is executed.

[0066] Optionally, the adopting the Brent iterative algorithm to correct the primary frequency modulation control parameter includes:

[0067] Step S801: determining whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is less than zero;

[0068] If so, the following formula is used to update the current second evaluation interval range:

[0069] ;

[0070] Where, is the primary frequency modulation control parameter, is the minimum value of the current second evaluation range, The maximum value of the current second evaluation range;

[0071] If not, update the current second evaluation interval range in the following manner:

[0072] ;

[0073] Step S802: determining whether the updated length of the current second evaluation interval is greater than the first preset value, and whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is also greater than the first accuracy value;

[0074] If yes, update the dynamic switching condition parameter to 0 and execute step S803;

[0075] If not, update the dynamic switching condition parameter to 1 and execute step S803;

[0076] Step S803: Determine whether the dynamic switching condition parameter is 1;

[0077] If not, proceed to step S804;

[0078] If yes, execute step S805;

[0079] Step S804: using a binary method to modify the primary frequency modulation control parameters;

[0080] ;

[0081] Step S805: the secant method is used to correct the primary frequency modulation control parameters:

[0082] ;

[0083] Where, The updated maximum value of the current second evaluation interval The corresponding maximum frequency deviation of the system after being disturbed, The updated minimum value of the current second evaluation interval The corresponding maximum frequency deviation of the system after being disturbed, is the set maximum frequency deviation target value;

[0084] Step S806: determining whether the primary frequency modulation control parameter corrected by the secant method is within the updated current second evaluation interval;

[0085] If not, proceed to step S804;

[0086] If so, execute step S702.

[0087] Optionally, after the step of correcting the primary frequency modulation control parameter using the dichotomy method, the method further includes:

[0088] Determining whether the updated length of the current second evaluation interval is less than the second precision value;

[0089] If yes, update the flag variable to 1 and execute step S702;

[0090] If not, update the flag variable to 0, and then execute step S702.

[0091] This application has the following beneficial effects:

[0092] The method proposed in this application takes the system frequency safety constraint as the core, comprehensively considers key indicators such as the maximum frequency change rate and the minimum frequency, and effectively reversely infers the minimum virtual inertia and primary frequency regulation capabilities required by the new energy station under different disturbance conditions, thereby ensuring frequency stability from the source and improving safety adaptability. Based on the multi-machine system frequency response model, the coupling effect of inertia response and primary frequency regulation is fully considered. The method has good dynamics and universality and is applicable to a variety of power system structures and operating scenarios. The evaluation results can provide engineering guidance for the configuration of control parameters of new energy stations, support the optimization of controllers and the implementation of active support strategies, and improve frequency response under various working conditions to enhance the safety and stability of the system.

[0093] In addition to the above-described purposes, features and advantages, the present application also has other purposes, features and advantages. The present application will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0095] Figure 1 This is a flow chart of a method for dynamically evaluating control parameters of a new energy station provided in an embodiment of the present application;

[0096] Figure 2 is a schematic diagram of a multi-machine frequency response model framework provided in an embodiment of the present application;

[0097] Figure 3 is a flow chart of a virtual inertia control parameter evaluation framework provided in an embodiment of the present application;

[0098] Figure 4 1 is a flow chart of correcting virtual inertia control parameters using the Brent iteration algorithm provided in an embodiment of the present application;

[0099] Figure 5 This is a flow chart of a primary frequency modulation control parameter evaluation framework provided by an embodiment of the present application;

[0100] Figure 6 This is a flow chart of correcting a primary frequency modulation control parameter using a Brent iteration algorithm according to an embodiment of the present application;

[0101] Figure 7 This is a schematic diagram of the structure of the improved IEEE-39 node calculation example provided in the experimental verification phase of the embodiment of the present application;

[0102] Figure 8This is a schematic diagram of the comparison results of the frequency curves before and after adding the new energy station control in the working condition 1 provided in the experimental verification stage of the embodiment of the present application;

[0103] Figure 9 This is a schematic diagram of the frequency curve comparison results before and after adding new energy station control in working condition 2 provided in the experimental verification stage of this application. DETAILED DESCRIPTION

[0104] The embodiments of the present application are described in detail below with reference to the accompanying drawings, but the present application can be implemented in many different ways as defined and covered by the claims.

[0105] Therefore, in order to solve the above problems, Figure 1 As shown, this application proposes a method for dynamic evaluation of control parameters of new energy stations, including:

[0106] Step S101: According to the frequency dynamic response process of the system after being disturbed, retain the nonlinear links and corresponding parameters that affect the frequency response of each unit of the multi-heterogeneous frequency modulation resources and build a system multi-machine frequency response model;

[0107] In power systems, a system disturbance refers to a process in which normal system operation is disrupted due to various internal and external factors, leading to a disruption in active power, reactive power, or frequency / voltage balance. Such disturbances can trigger chain reactions, threaten system stability, and even cause power outages. System disturbances disrupt the active power balance and trigger dynamic frequency responses (such as frequency fluctuations and generator speed governors operating to adjust power). These two processes form a causal relationship: "disturbance triggers response, and response suppresses the impact of disturbances."

[0108] When constructing a multi-machine frequency response model for a system, the purpose of retaining nonlinear links and their corresponding parameters is to truly depict the complex characteristics of the system's frequency dynamic response after a disturbance, and to avoid analytical distortion caused by simplifying the model. The following is a detailed description of this construction process:

[0109] The frequency dynamic response process of the system after being disturbed can be expressed as:

[0110] (1)

[0111] Where, is the equivalent inertia constant of the system, is the maximum frequency deviation, is the sum of the primary frequency regulation powers of all synchronous generator sets; The power released by DC participating in FLC control; Provide fast frequency modulation power for new energy stations; is the equivalent damping coefficient of the system, is the fault disturbance amount;

[0112] Aggregate the inertia constant of the new energy station with the inertia constant of the synchronous unit to determine the equivalent inertia constant of the system:

[0113] (2)

[0114] Where, represents the inertia constant of the thermal power unit, represents the inertia constant of the hydropower unit, represents the gas turbine inertia constant, is the virtual inertia control constant of the new energy station;

[0115] According to the above-mentioned system equivalent inertia constant and the frequency dynamic response process after the system is disturbed, that is, the nonlinear links and corresponding parameters that affect the frequency response in each unit of the multi-heterogeneous frequency regulation resources, a system multi-machine frequency response model is constructed. Taking into account the multi-heterogeneous frequency regulation resources such as hydropower units, thermal power units, gas turbines, DC transmission, and new energy stations, a multi-machine system frequency response model is constructed. The model completely retains the nonlinear links and related parameters that affect the frequency response of the units and DC systems, including the frequency regulation dead zone, speed deviation amplification factor, speed threshold limit, system time constant and power limit, etc. The block diagram of the constructed multi-machine frequency response model is as follows Figure 2 As shown:

[0116] For synchronous units: is the capacity ratio of the i-th thermal power unit, The upper and lower limits of the output of the i-th thermal power unit, is the capacity ratio coefficient of the i-th hydropower unit, The upper and lower limits of the output of the i-th hydropower unit, is the capacity ratio of the i-th gas turbine, The upper and lower limits of the output of the i-th gas turbine, The upper and lower limits of DC output for frequency modulation, The upper and lower output limits of new energy stations participating in frequency regulation. is the regulation coefficient of the i-th high-pressure steam turbine; is the power proportional coefficient of the i-th high-pressure steam turbine; is the reheat time constant; is the speed regulator time constant; is the steam capacity time constant; is the regulation coefficient of the i-th turbine; is the response time constant of the servomotor; is the inertia time constant of water flow; is the transient droop time constant of the turbine governor; Reset time for turbine governor; is the regulation coefficient of the i-th gas turbine; and is the coefficient of the transfer function of the valve positioner in the fuel system of the i-th unit; is the lead time constant of the governor section; is the lag time constant of the speed regulator part; is the combustion reaction delay time constant; is the fuel system time constant; is the compression displacement time constant. In the DC frequency modulation model: is the capacity ratio of DC; is the DC equivalent regulation coefficient; is the delay constant of the measurement link; is the proportional gain; is the time constant of the integral link. For the control link of the new energy station: is the capacity ratio of the station; Characterize the virtual control response delay of the station; is the filter parameter of the station unit; is the equivalent primary frequency regulation control coefficient of the station unit, is the Laplace operator.

[0117] Step S102: determining the frequency change rate of the system at the moment of disturbance based on the system multi-machine frequency response model;

[0118] After obtaining the system multi-machine frequency response model, determine the frequency change rate of the system at the moment of disturbance, and then determine the virtual inertia control parameters based on the frequency change rate, such as Figure 3 As shown, the specific process is as follows:

[0119] Step S401: setting the fault magnitude, setting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables to zero, and substituting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables into the system multi-machine frequency response model;

[0120] Because at the beginning, the virtual inertia control parameters of the new energy station corresponding to the current system and primary frequency modulation control parameters The actual value of is unknown. Therefore, the fault magnitude is first set. The initial values ​​of the new energy station's virtual inertia control parameters, the initial values ​​of the primary frequency modulation control parameters, and the flag scalar are all set to zero. This is then substituted into the system's multi-machine frequency response model. The flag variable is used during the correction process when using the dichotomy method to correct the virtual inertia control parameters. Its specific application will be explained in detail later.

[0121] Step S402: simulating the system multi-machine frequency response model to obtain the frequency change rate during the frequency response process;

[0122] After substituting the initial values ​​of the virtual inertia control parameters of the new energy station and the initial values ​​of the primary frequency modulation control parameters, as well as the zero sign variable into the system multi-machine frequency response model, the simulation is started to obtain the frequency change rate in the current process frequency response process. .

[0123] Step S103: determining a virtual inertia control parameter of the new energy station based on the frequency change rate;

[0124] Step S403: Determine whether the flag variable is 1;

[0125] At this point, if the aforementioned binary method is used to correct the virtual inertia control parameter, the value of the flag variable will be updated in real time. Therefore, it is necessary to first judge the flag scalar. If the judgment result is negative, step S404 is executed. If the judgment result is 1, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, ending the simulation and executing step S104. Since the primary frequency modulation parameters will need to be corrected later, after the virtual inertia parameters are corrected, the flag variable is updated to zero and subsequent operations are executed.

[0126] Step S404: determining whether the frequency change rate is at a critical position of the constraint condition;

[0127] After obtaining the corresponding frequency change rate, the frequency change rate Whether it is in the critical position of the constraint is determined. If so, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, the simulation ends, and step S104 is executed.

[0128] If the result of step S404 is negative, the virtual inertia control parameter is corrected using the Brent iteration algorithm, and then step S402 is executed. Since the frequency change rate is only affected by the virtual inertia control parameter, it is necessary to substitute the corrected virtual inertia control parameter into the system multi-machine frequency response model after obtaining it, perform a simulation, and obtain the frequency change rate corresponding to the corrected virtual inertia control parameter, and then re-evaluate the frequency change rate.

[0129] like Figure 4 As shown in Figure 2, the specific process of using the Brent iterative algorithm to correct the virtual inertia control parameters is as follows:

[0130] Step S501: Determine whether the difference between the frequency change rate and the set frequency change rate target value is less than zero; that is:

[0131] (3)

[0132] Where, is the set frequency change rate target value;

[0133] If so, the following formula is used to update the current first evaluation interval range;

[0134] (4)

[0135] If not, the following formula is used to update the current first evaluation interval range;

[0136] (5)

[0137] Where, is the minimum value of the current first evaluation range, The maximum value of the current first evaluation range;

[0138] Step S502: When determining whether the length of the updated current first evaluation interval is greater than the first preset value, and whether the difference between the frequency change rate and the set frequency change rate target value is also greater than the first accuracy value; that is:

[0139] (6)

[0140] and (7)

[0141] Where, is the first precision value, is the first preset value;

[0142] If yes, update the dynamic switching condition parameter use_secent to 0 and execute step S503;

[0143] If not, the dynamic switching condition parameter is updated to 1, and step S503 is also executed;

[0144] Step S503: Determine whether the dynamic switching condition parameter is 1;

[0145] If not, proceed to step S504;

[0146] If yes, execute step S505;

[0147] Step S504: using a dichotomy method to correct the virtual inertia control parameter;

[0148] (8)

[0149] After the virtual inertia control parameter is corrected by the dichotomy method, it is determined whether the length of the updated current first evaluation interval is less than the second precision value. ,Right now:

[0150] (9)

[0151] If so, the flag variable is updated to 1 and step S402 is executed; if not, the flag variable is updated to 0 and step S402 is executed.

[0152] Step S505: Correct the virtual inertia control parameters using the secant method:

[0153] (10)

[0154] Where, The updated maximum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed, The updated minimum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed;

[0155] Step S506: determining whether the virtual inertia control parameter corrected by the secant method is within the updated current first evaluation interval;

[0156] If not, proceed to step S504;

[0157] If so, execute step S402.

[0158] Step S104: determining the maximum frequency deviation of the system after being disturbed based on the virtual inertia control parameter and the system multi-machine frequency response model;

[0159] After determining the virtual inertia control parameters, the system maximum frequency deviation can be determined based on the virtual inertia control parameters and the system multi-machine frequency response model, and then the primary frequency modulation control parameters can be determined based on the system maximum frequency deviation, such as Figure 5 The specific process is as follows:

[0160] Step S701: Substituting the initial values ​​of the virtual inertia control parameter and the primary frequency modulation control parameter, and the flag variable into the system multi-machine frequency response model;

[0161] The maximum frequency deviation after the system is disturbed , will be affected by the frequency modulation control parameters and virtual inertia control parameters After step S103, the most suitable virtual inertia control parameters for the current system can be determined, and then the maximum frequency deviation after the system is disturbed can be used to calculate the virtual inertia control parameters. , determining the most appropriate primary frequency modulation control parameters for the current system. Since the previous steps did not involve changes to the primary frequency modulation control parameters, their initial values ​​remain unchanged at zero. Since the primary frequency modulation parameters will be corrected using the dichotomy method later, the subsequent correction process requires adjusting the flag variables. The initial values ​​of the primary frequency modulation parameters, the virtual inertia control parameters, and the flag variables are then substituted into the system's multi-machine frequency response model.

[0162] Step S702: simulating the system multi-machine frequency response model to obtain the maximum frequency deviation after the system is disturbed;

[0163] By simulating the multi-machine frequency response model of the system, the maximum frequency deviation after the system is disturbed can be obtained. .

[0164] Step S105: Determine the primary frequency regulation control parameters of the new energy station based on the maximum frequency deviation and the virtual inertia control parameters.

[0165] Step S703: Determine whether the flag variable flag is 1;

[0166] If not, execute step S704; if so, use the current primary frequency modulation control parameter value corresponding to the frequency change rate as the primary frequency modulation control parameter, and end the simulation and evaluation;

[0167] Step S704: determining whether the maximum frequency deviation is at a critical position of the constraint condition;

[0168] After obtaining the maximum frequency deviation, it is judged whether the maximum frequency deviation is at the critical position of the constraint condition. If so, it represents the current primary frequency modulation control parameter, that is, the most suitable inertia parameter for the current operation of the system. At this time, the current primary frequency modulation control parameter value corresponding to the current frequency change rate is used as the primary frequency modulation control parameter to be sought, and the simulation and evaluation are ended.

[0169] If it is not within the critical position of the constraint condition, the Brent iteration algorithm is used to correct the primary frequency modulation control parameter, and then the corrected primary frequency modulation control parameter is used to execute step S702 and make another judgment.

[0170] like Figure 6 As shown in Figure 2, the specific process of using the Brent iterative algorithm to correct the primary frequency modulation control parameters is as follows:

[0171] Step S801: Determine whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is less than zero; that is:

[0172] (11)

[0173] Where, is the set maximum frequency deviation target value;

[0174] If so, the following formula is used to update the current second evaluation interval range:

[0175] (12)

[0176] Where, is the primary frequency modulation control parameter, is the minimum value of the current second evaluation range, The maximum value of the current second evaluation range;

[0177] If not, update the current second evaluation interval range in the following manner:

[0178] (13)

[0179] Step S802: When determining whether the length of the updated current second evaluation interval is greater than the first preset value, and whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is also greater than the first accuracy value; that is:

[0180] (14)

[0181] and (15)

[0182] If yes, update the dynamic switching condition parameter use_secent to 0 and execute step S803;

[0183] If not, update the dynamic switching condition parameter to 1 and execute step S803;

[0184] Step S803: Determine whether the dynamic switching condition parameter is 1;

[0185] If not, proceed to step S804;

[0186] If yes, execute step S805;

[0187] Step S804: using a binary method to modify the primary frequency modulation control parameters;

[0188] (16)

[0189] After the step of correcting the frequency modulation control parameter once by using the binary method, it is necessary to determine whether the length of the updated current second evaluation interval range is less than the second precision value. ;Right now:

[0190] (17)

[0191] If so, the flag variable is updated to 1 and step S702 is executed; if not, the flag variable is updated to 0 and step S702 is executed.

[0192] Step S805: the secant method is used to correct the primary frequency modulation control parameters:

[0193] (18)

[0194] Where, is the maximum frequency deviation of the system after being disturbed, corresponding to the maximum value Kmax of the current evaluation range. The maximum frequency deviation after the system is disturbed, corresponding to the minimum value Kmin of the current evaluation range;

[0195] Step S806: determining whether the primary frequency modulation control parameter corrected by the secant method is within the updated current second evaluation interval;

[0196] If not, execute step S804; if so, execute step S702.

[0197] Experimental simulation stage

[0198] In order to verify the effectiveness of the evaluation method of this application, the following verification method is used:

[0199] Simulation conditions and configuration: The computer used was configured with an Intel Core i5 CPU and 16GB of memory. The proposed dynamic evaluation method for control parameters of renewable energy stations adapted to system frequency safety constraints was implemented in MATLAB software, and simulation calculations were completed using MATLAB / Simulink.

[0200] like Figure 7As shown, the accuracy of the proposed method for dynamic evaluation of control parameters of a new energy station described above is verified based on an improved IEEE-39 node calculation system. In the improved IEEE-39 node calculation system, nodes 31, 34, 36, 38, and 39 are connected to thermal power generators with steam turbines as prime movers, nodes 32 and 33 are connected to hydropower generators with water turbines as prime movers, nodes 30 and 37 are connected to gas turbines, node 21 is connected to a DC transmission line via a converter, and node 35 is connected to a new energy station. All synchronous generator sets are equipped with speed regulators to participate in primary frequency regulation response, and the DC transmission lines are equipped with DC modulation capabilities. The unit information for each of the above nodes is shown in Table 1.

[0201] Table 1 Unit information of each node

[0202] ;

[0203] Table 2 Main parameters of the tested new energy power system

[0204] ;

[0205] Please refer to Table 2 for the main parameters of the tested renewable energy power system. Two operating conditions were set, using different fault disturbances to evaluate the inertia and primary frequency regulation control parameters of the renewable energy station. Operating Condition 1: Synchronous generators participate in frequency regulation, while DC generators do not, with fault disturbances of 600 MW and 700 MW; Operating Condition 2: Synchronous generators participate in frequency regulation, while DC generators participate in frequency regulation, with fault disturbances of 800 MW and 900 MW. Secondly, to determine whether the system frequency is safe after the fault, the following frequency safety boundary conditions for low-frequency faults were set: the maximum frequency deviation of the system after the fault does not exceed -0.5 Hz, and the maximum frequency change rate does not exceed -1 Hz / s.

[0206] The comparison results of frequency curves before and after adding new energy station control under different working conditions and different disturbances are as follows: Figure 8 and Figure 9 As shown. Figure 8 and Figure 9 It can be seen intuitively that the system's frequency support capability was significantly insufficient before the addition of renewable energy station control. However, the addition of renewable energy station control significantly improved the system's frequency interference resistance, demonstrating the necessity of integrating grid-connected converters in systems with a high proportion of power electronics.

[0207] Table 3 Comparison of frequency change rate and maximum frequency deviation before and after the addition of new energy stations

[0208] ;

[0209] Further analysis of the configuration under different working conditions and Parameters, it can be seen that: when the load disturbance is large (such as 700MW and 900MW), the system requires a higher equivalent inertia ( ) and enhanced FM capability ( ) to meet the frequency stability requirements. For example, in the working condition of 1-700MW, Reaching 7.56 s, It is 8.85 MW / Hz, and the suppression effect on RoCoF and △fmax is better than the setting in the low disturbance scenario.

[0210] In summary, the method proposed in this application takes the system frequency safety constraint as the core, comprehensively considers key indicators such as the maximum frequency change rate and the minimum frequency, and effectively reversely infers the minimum virtual inertia and primary frequency regulation capabilities required by the new energy station under different disturbance conditions, thereby ensuring frequency stability from the source and improving safety adaptability. Based on the multi-machine system frequency response model, the coupling effect of inertia response and primary frequency regulation is fully considered. The method has good dynamics and universality and is applicable to a variety of power system structures and operating scenarios. The evaluation results can provide engineering guidance for the configuration of control parameters of new energy stations, support the optimization of controllers and the implementation of active support strategies, and improve frequency response under various working conditions to enhance the safety and stability of the system.

[0211] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for dynamic evaluation of control parameters of new energy stations, characterized in that: include: Step S101: According to the frequency dynamic response process of the system after being disturbed, retain the nonlinear links and corresponding parameters that affect the frequency response of each unit of the multi-heterogeneous frequency modulation resources and build a system multi-machine frequency response model; Step S102: determining the frequency change rate of the system at the moment of disturbance based on the system multi-machine frequency response model; Step S103: determining a virtual inertia control parameter of the new energy station based on the frequency change rate; Step S104: determining the maximum frequency deviation of the system after being disturbed based on the virtual inertia control parameter and the system multi-machine frequency response model; Step S105: determining a primary frequency regulation control parameter of the new energy station based on the maximum frequency deviation and the virtual inertia control parameter; The step of determining the frequency change rate of the system at the moment of disturbance based on the system multi-machine frequency response model includes: Step S401: setting the fault magnitude, setting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables to zero, and then substituting the initial values ​​of the virtual inertia control parameters of the new energy station, the initial values ​​of the primary frequency modulation control parameters, and the flag variables into the system multi-machine frequency response model; Step S402: simulating the system multi-machine frequency response model to obtain the frequency change rate during the frequency response process; The determining of the virtual inertia control parameter of the new energy station based on the frequency change rate includes: Step S403: Determine whether the flag variable is 1; If not, proceed to step S404; If so, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, the simulation ends, and step S104 is executed; Step S404: determining whether the frequency change rate is at a critical position of the constraint condition; If so, the current virtual inertia control parameter value corresponding to the frequency change rate is used as the virtual inertia control parameter, and the flag variable is updated to 0, the simulation ends, and step S104 is executed; If not, the virtual inertia control parameter is corrected using the Brent iteration algorithm, and then step S402 is executed.

2. The method according to claim 1, characterized in that The multi-heterogeneous frequency regulation resources include hydropower units, thermal power units, gas turbines, direct current transmission, and new energy stations.

3. The method according to claim 2, characterized in that According to the frequency dynamic response process after the system is disturbed, the nonlinear links and corresponding parameters affecting the frequency response of each unit of the multi-heterogeneous frequency modulation resources are retained and a system multi-machine frequency response model is constructed, including: The frequency dynamic response process of the system after being disturbed can be expressed as: ； Where, is the equivalent inertia constant of the system, is the maximum frequency deviation, is the sum of the primary frequency regulation powers of all synchronous generator sets; The power released by DC participating in FLC control; Provide fast frequency modulation power for new energy stations; is the equivalent damping coefficient of the system, is the fault disturbance amount; Aggregate the inertia constant of the new energy station with the inertia constant of the synchronous unit to determine the equivalent inertia constant of the system: ； Where, represents the inertia constant of the thermal power unit, represents the inertia constant of the hydropower unit, represents the gas turbine inertia constant, is the virtual inertia control constant of the new energy station; Based on the equivalent inertia constant of the system and the frequency dynamic response process of the system after being disturbed, the nonlinear links and corresponding parameters affecting the frequency in each unit of the multi-heterogeneous frequency regulation resources are retained and a system multi-machine frequency response model is constructed.

4. The method according to claim 1, wherein The adopting of the Brent iteration algorithm to correct the virtual inertia control parameter includes: Step S501: determining whether the difference between the frequency change rate and a set frequency change rate target value is less than zero; If so, the following formula is used to update the current first evaluation interval range: ； Where, is the virtual inertia control parameter, is the minimum value of the current first evaluation range, The maximum value of the current first evaluation range; If not, the following formula is used to update the current first evaluation interval range: ； Step S502: determining whether the length of the updated current first evaluation interval is greater than a first preset value, and whether the difference between the frequency change rate and the set frequency change rate target value is also greater than a first accuracy value; If yes, update the dynamic switching condition parameter to 0 and execute step S503; If not, update the dynamic switching condition parameter to 1 and execute step S503; Step S503: Determine whether the dynamic switching condition parameter is 1; If not, proceed to step S504; If yes, execute step S505; Step S504: using a dichotomy method to correct the virtual inertia control parameter; ； Step S505: Correct the virtual inertia control parameters using the secant method: ； Where, The updated maximum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed, The updated minimum value of the current first evaluation interval The corresponding frequency change rate of the system after being disturbed, is the set frequency change rate target value; Step S506: determining whether the virtual inertia control parameter corrected by the secant method is within the updated current first evaluation interval; If not, proceed to step S504; If so, execute step S402.

5. The method according to claim 4, characterized in that After the step of correcting the virtual inertia control parameter by using the dichotomy method, the following steps are further included: Determining whether the updated length of the current first evaluation interval is less than the second precision value; If yes, update the flag variable to 1 and execute step S402; If not, update the flag variable to 0 and execute step S402.

6. The method according to claim 1, characterized in that The determining, based on the virtual inertia control parameter and the system multi-machine frequency response model, of the maximum frequency deviation after the system is disturbed includes: Step S701: Substituting the initial values ​​of the virtual inertia control parameter and the primary frequency modulation control parameter, and the flag variable into the system multi-machine frequency response model; Step S702: simulating the system multi-machine frequency response model to obtain the maximum frequency deviation after the system is disturbed; The determining of the primary frequency regulation control parameter of the new energy station based on the maximum frequency deviation and the virtual inertia control parameter includes: Step S703: Determine whether the flag variable is 1; If not, proceed to step S704; If yes, the current primary frequency modulation control parameter value corresponding to the frequency change rate is used as the primary frequency modulation control parameter, and the simulation and evaluation are terminated; Step S704: determining whether the maximum frequency deviation is at a critical position of the constraint condition; If yes, the current primary frequency modulation control parameter value corresponding to the frequency change rate is used as the primary frequency modulation control parameter, and the simulation and evaluation are terminated; If not, the primary frequency modulation control parameter is corrected using the Brent iteration algorithm, and then step S702 is executed.

7. The method according to claim 6, characterized in that The adopting of the Brent iterative algorithm to correct the primary frequency modulation control parameter includes: Step S801: determining whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is less than zero; If so, the following formula is used to update the current second evaluation interval range: ； Where, is the primary frequency modulation control parameter, is the minimum value of the current second evaluation range, The maximum value of the current second evaluation range; If not, update the current second evaluation interval range in the following manner: ； Step S802: determining whether the updated length of the current second evaluation interval is greater than the first preset value, and whether the difference between the maximum frequency deviation and the set maximum frequency deviation target value is also greater than the first accuracy value; If yes, update the dynamic switching condition parameter to 0 and execute step S803; If not, update the dynamic switching condition parameter to 1 and execute step S803; Step S803: Determine whether the dynamic switching condition parameter is 1; If not, proceed to step S804; If yes, execute step S805; Step S804: using a binary method to modify the primary frequency modulation control parameters; ； Step S805: the secant method is used to correct the primary frequency modulation control parameters: ； Where, The updated maximum value of the current second evaluation interval The corresponding maximum frequency deviation of the system after being disturbed, The updated minimum value of the current second evaluation interval The corresponding maximum frequency deviation of the system after being disturbed, is the set maximum frequency deviation target value; Step S806: determining whether the primary frequency modulation control parameter corrected by the secant method is within the updated current second evaluation interval; If not, proceed to step S804; If so, execute step S702.

8. The method according to claim 7, characterized in that After the step of correcting the primary frequency modulation control parameter by using the dichotomy method, the following steps are further included: Determining whether the updated length of the current second evaluation interval is less than the second precision value; If yes, update the flag variable to 1 and execute step S702; If not, update the flag variable to 0, and then execute step S702.

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