An emergency frequency control method for the receiving-end power grid based on the optimal frequency trajectory

Abstract

The present application provides an emergency frequency control method for the receiving-end power grid based on the optimal frequency trajectory. First, the governor-prime mover model and parameters of the synchronous generator units are obtained, and the maximum frequency deviation under the optimal frequency trajectory is calculated through the optimal control algorithm. Based on this deviation, an equivalent transfer function for the wind farm to participate in frequency response is established. For the anticipated contingency, an evaluation model is constructed with the frequency safety limit as the constraint, and the additional requirements for system inertia and frequency regulation strength are solved. Combining the characteristics of various types of frequency regulation resources and the equivalent model of the wind farm, a frequency response model including virtual inertia and droop control is established. With the goal of minimizing the control cost, the emergency power control amounts of each resource and the corresponding virtual control parameters are optimized and solved in combination with the constraint conditions. Finally, according to the inertia and frequency regulation requirements, the virtual inertia coefficient of the grid-forming new energy power station is adjusted. A variety of flexible frequency regulation resources are comprehensively considered, and the solution process of the emergency frequency control optimization model is simplified.

Description

Technical Field

[0001] This application relates to the technical field of power systems, specifically to the field of power grid frequency control. Background Art

[0002] As multi-type new energy power generation devices gradually replace traditional thermal power plants, the power grids in most areas of a certain place gradually show the characteristics of low inertia and low frequency regulation ability while the new energy penetration rate is increasing. The resulting system frequency safety and stability problems cannot be ignored. Considering that frequency instability events in the receiving-end power grid are mainly frequency drops caused by large-scale active power deficit accidents, when the equivalent inertia and frequency regulation ability are gradually weakened, the frequency of the receiving-end power grid will be more likely to deviate severely or even become unstable when accidents such as DC blocking occur. To effectively respond to low-frequency events after active power deficit in the receiving-end power grid, it is necessary to fully exploit the frequency regulation potential of various types of flexible frequency regulation resources in the power grid and construct an emergency frequency control method in which multiple frequency regulation resources are coordinated with each other.

[0003] The active power output of wind turbines has high flexibility and freedom of adjustment. By adding an active power control link, the frequency active support ability of wind farms can be deeply exploited, effectively improving the frequency safety and stability of the receiving-end power grid. Traditional additional active power control for wind power is comprehensive inertia control, which includes virtual inertia control and virtual droop control links. It can adjust the wind power active output by tracking the system frequency change and provide power support for the power grid. However, under this control method, wind farms need to face the risks of tripping due to excessive release of rotor kinetic energy and frequency secondary drop caused by withdrawing from frequency regulation. Therefore, it is necessary to improve the additional active power control for wind power to ensure the rotor speed recovery of wind farms after participating in frequency response and the lossless withdrawal from frequency regulation.

[0004] After determining the frequency regulation control strategy of wind farms, to further reduce the maximum rate of change of frequency and the maximum deviation of frequency after active power accidents occur in the receiving-end power grid, it is also necessary to make full use of other various types of frequency regulation resources in the power grid for emergency power support. How to reasonably utilize the frequency regulation potential of various flexible frequency regulation resources such as high-voltage DC, new energy storage power stations, pumped-storage power stations, and adjustable loads, and coordinate multiple frequency regulation resources to jointly participate in the emergency power support of the receiving-end power grid is an urgent problem to be solved. Summary of the Invention

[0005] To overcome the above technical defects, this application provides an emergency frequency control method for a receiving-end power grid based on an optimal frequency trajectory. To achieve the above object, this application is implemented according to the following technical solutions:

[0006] In a first aspect, this application provides an emergency frequency control method for a receiving-end power grid based on an optimal frequency trajectory, including:

[0007] Obtain the specific model and parameter data of the synchronous unit governor - prime mover of the receiving - end power grid, as well as the control methods of various flexible frequency - regulation resources;

[0008] Based on the specific model and parameter data of the synchronous unit governor - prime mover, obtain the maximum frequency deviation value in the scenario where the wind farm participates in frequency response;

[0009] Based on the maximum frequency deviation value, determine the equivalent transfer function of each wind farm participating in frequency response;

[0010] Set a contingency, and construct a frequency - support strength demand assessment model with the frequency safety limit as the constraint condition;

[0011] Solve the frequency - support strength demand assessment model to obtain the additional demand for the inertia strength and frequency - regulation strength of the receiving - end power grid;

[0012] Combined with the control methods of various flexible frequency - regulation resources and the equivalent transfer function of each wind farm participating in frequency response, establish an optimal frequency - trajectory response model including multiple types of frequency - regulation resources;

[0013] Construct an emergency frequency - control optimization model with the minimum total control cost as the objective function;

[0014] According to the optimal frequency - trajectory response model, determine the constraint conditions of the emergency frequency - control optimization model;

[0015] Solve the emergency frequency - control optimization model to obtain the emergency power control amounts of various types of frequency - regulation resources;

[0016] Based on the emergency power control amounts of various types of frequency - regulation resources, determine the virtual inertia and virtual droop coefficients issued by various types of frequency - regulation resources;

[0017] Based on the inertia strength of the receiving - end power grid and the additional demand for frequency - regulation strength, adjust the virtual inertia coefficients of each grid - forming new - energy power stations in the receiving - end power grid.

[0018] Optionally, the obtaining the maximum frequency deviation value in the scenario where the wind farm participates in frequency response based on the specific model and parameter data of the synchronous unit governor - prime mover includes:

[0019] Based on the specific model and parameter data of the synchronous unit governor - prime mover, establish a speed - regulation system model;

[0020] Use the least - squares method to reduce the order and aggregate the speed - regulation system model to obtain the equivalent transfer function of the entire synchronous unit speed - regulation system;

[0021] Obtain the synchronous unit rotational inertia and installed capacity data;

[0022] According to the rotational inertia data of the synchronous generator sets, the installed capacity data, and the equivalent transfer function of the speed control systems of all the synchronous generator sets, a first grid frequency response equation including the active power increment of the wind farm station is obtained;

[0023] Based on the first grid frequency response equation, with the active power increment of the wind farm station as the control variable, a frequency response state space equation is established;

[0024] Based on the frequency response state space equation, an optimal control model is established with the maximum frequency deviation value as the objective function;

[0025] The optimal control model is solved to obtain the maximum frequency deviation value in the scenario where the wind farm station participates in the frequency response.

[0026] Optionally, the determining the equivalent transfer function of each wind farm station participating in the frequency response based on the maximum frequency deviation value includes:

[0027] Based on the maximum frequency deviation value, a second grid frequency response equation is determined;

[0028] Based on the second grid frequency response equation, the total equivalent transfer function of all the wind farm stations is determined;

[0029] Based on the total equivalent transfer function of all the wind farm stations, the equivalent transfer function of each wind farm station participating in the frequency response is determined.

[0030] Optionally, the setting of the contingency, with the frequency safety limit as the constraint condition, to construct a frequency support strength demand assessment model includes:

[0031] According to the contingency screening set of the receiving-end grid, the active power deficit accidents with an impact on frequency safety and stability greater than the first threshold are screened out;

[0032] With the sum of the additional demands for the inertia strength and the frequency modulation strength of the receiving-end grid being minimized as the objective function, and the maximum frequency deviation value, the quasi-steady state frequency deviation value, the maximum frequency change rate, and the average frequency change rate being less than the upper limit value as the constraint conditions, a frequency support strength demand assessment model is established.

[0033] Optionally, the determining the constraint conditions of the emergency frequency control optimization model according to the optimal frequency trajectory response model includes:

[0034] According to the optimal frequency trajectory response model, the grid frequency constraint conditions of the emergency frequency control optimization model are determined.

[0035] Optionally, the adjusting the installed capacity ratio of the new energy power stations in each network-forming type of the receiving-end grid based on the inertia strength of the receiving-end grid and the additional demand for the frequency modulation strength includes:

[0036] Determine whether the relationship between the inertia strength of the receiving-end power grid and the additional demand for the frequency regulation strength satisfies a first preset condition;

[0037] If it is satisfied, determine the inertia strength deficit according to the inertia strength and the additional demand for the frequency regulation strength;

[0038] Based on the inertia strength deficit, adjust the virtual inertia coefficients of each grid-forming new energy power station in the receiving-end power grid.

[0039] Optionally, the constraint conditions of the emergency frequency control optimization model further include the adjustment resource power adjustment space constraint:

[0040] ,

[0041] In the formula, are the maximum active powers of four types of frequency regulation resources respectively, are the active powers of four types of frequency regulation resources at time respectively, respectively represent the th high-voltage DC converter station, the th energy storage power station, the th pumped-storage power station, and the rd adjustable load's active power increment, are the total numbers of four types of frequency regulation resources respectively.

[0042] Optionally, the constraint conditions of the emergency frequency control optimization model further include the energy storage power station's available energy constraint:

[0043] ,

[0044] In the formula, are the rated voltage, rated capacity, charge state, minimum and maximum charge states of the th energy storage power station and the transmission line power flow constraint.

[0045] Optionally, the constraint conditions of the emergency frequency control optimization model further include the transmission line power flow constraint:

[0046] ,

[0047] In the formula, are the maximum active power of line and the active power transmission value at time respectively, is the total number of transmission lines in the power grid, are the power flow transfer coefficients of four types of frequency regulation resources for line respectively.

[0048] The present application has the following beneficial effects:

[0049] The advantages of the method provided in the above embodiments of the present application are as follows: ① Ensure that the wind farms in the receiving-end power grid can achieve autonomous recovery of rotational speed during primary frequency regulation, reducing the frequency secondary drop accidents caused by excessive release of rotor kinetic energy by the wind turbines; ② Propose how to evaluate the inertial strength and frequency regulation strength requirements of the receiving-end power grid under the optimal frequency trajectory. Compared with the method for evaluating the frequency support strength requirements based on the traditional frequency response model, its principle is more simplified and the calculation efficiency is higher; ③ The proposed emergency frequency control method comprehensively considers various flexible frequency regulation resources, and by deriving the numerical relationship between the optimal frequency trajectory and the virtual inertia and virtual droop control of the new energy power station, it proves the interchangeability of the step-form active power increment with the virtual inertia and virtual droop control, simplifying the solution process of the emergency frequency control optimization model.

[0050] In addition to the purposes, features, and advantages described above, the present application has other purposes, features, and advantages. The following will refer to the accompanying drawings to further elaborate on the present application in detail. Description of the Drawings

[0051] The accompanying drawings constituting a part of the present application are used to provide a further understanding of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0052] Figure 1 is a schematic flow chart of an emergency frequency control method for a receiving-end power grid based on an optimal frequency trajectory provided by an embodiment of the present application;

[0053] Figure 2 is a schematic structural diagram of the IEEE 39-node system as a test system in the experimental verification stage of an embodiment of the present application;

[0054] Figure 3 is a schematic diagram of an optimal frequency trajectory response model constructed based on the improved IEEE 39 system in the experimental verification stage of an embodiment of the present application;

[0055] Figure 4 is a control block diagram of a new energy power station under the optimal frequency trajectory in the experimental verification stage of an embodiment of the present application;

[0056] Figure 5 is a schematic diagram comparing the time-domain simulation and the simulation results of the optimal frequency trajectory response model in the experimental verification stage of an embodiment of the present application, Figure 5 (a) is a schematic diagram comparing the frequency simulation results of the time-domain simulation and the optimal frequency trajectory response model, Figure 5 (b) is a schematic diagram comparing the additional power generation simulation results of the time-domain simulation and the optimal frequency trajectory response model;

[0057] Figure 6 It is a schematic diagram showing the frequency, wind farm power, and rotational speed curves under the optimal frequency trajectory during the experimental verification stage of the embodiments of this application. Figure 6 (a) is a schematic diagram of the frequency change under the optimal frequency trajectory; Figure 6 (b) is a schematic diagram of the wind farm changing with the rotational speed; Figure 6 (c) is a schematic diagram of the wind farm changing with time; Figure 6 (d) is a schematic diagram showing the rotational speed curve;

[0058] Figure 7 It is a schematic diagram of the change in the grid frequency curve after each frequency regulation resource participates in emergency frequency control under an 8% load sudden increase accident during the verification stage of the embodiments of this application;

[0059] Figure 8 It is a schematic diagram of the operating curves of each frequency regulation resource under an 8% load sudden increase accident during the verification stage of the embodiments of this application; Figure 8 (a) is a schematic diagram of the wind power operating curve; Figure 8 (b) is a schematic diagram of the wind turbine rotational speed operating curve; Figure 8 (c) is a schematic diagram of the energy storage power operating curve; Figure 8 (d) is a schematic diagram of the pumped storage power operating curve. Detailed implementation manners

[0060] The embodiments of this application will be described in detail below with reference to the accompanying drawings, but this application can be implemented in many different ways defined and covered by the claims.

[0061] To solve the technical problems raised in the above background art, as Figure 1 shown, this application proposes an emergency frequency control method for the receiving-end power grid based on the optimal frequency trajectory, including:

[0062] Step S101: Obtain the specific models and parameter data of the synchronous generator governor-prime mover in the receiving-end power grid, as well as the control methods of various flexible frequency regulation resources;

[0063] The specific models and parameter data of the synchronous generator governor-prime mover generally include the prime mover models and parameters and the governor models and parameters. The prime mover models and parameters include the steam turbine model and the water turbine model. The governor models and parameters include the steam turbine governor and the water turbine governor. The governor-prime mover parameters directly affect the frequency stability and dynamic response of the receiving-end power grid. The steam turbine parameters focus on the steam volume effect, the water turbine parameters emphasize the water hammer effect, and the governor parameters need to balance the adjustment speed and stability. In practical applications, it is necessary to optimize the parameters in combination with on-site tests, multi-machine coordinated control, and the characteristics of new energy to improve the system robustness.

[0064] Control methods for various flexible frequency regulation resources generally include control methods for various flexible frequency regulation resources such as high-voltage direct current, energy storage power stations, pumped-storage power stations, and adjustable loads in the receiving-end power grid. The control methods corresponding to each frequency regulation resource are different. For example, the grid-connected energy storage power station generally adopts virtual inertia plus virtual droop control.

[0065] Step S102: Based on the specific model and parameter data of the synchronous generator governor-prime mover, obtain the maximum frequency deviation value in the scenario where the wind farm participates in frequency response.

[0066] After obtaining the above specific model and parameter data of the synchronous generator debugger-prime mover, a speed control system model is constructed according to the specific model and parameter data of the synchronous generator debugger-prime mover. The speed control system model is a mathematical model used in the power system to describe the dynamic characteristics of the synchronous generator governor and prime mover. Its core is to simulate the response process of the unit to frequency changes through parameterization, and its parameters directly affect the power grid frequency stability. The steam turbine model focuses on steam volume delay compensation, the water turbine model pays attention to suppressing water hammer effect, and modern electro-hydraulic governors improve the regulation accuracy through intelligent algorithms. In the context of the increasing proportion of new energy, the model needs to further integrate virtual synchronous control technology to meet the requirements of the new power system.

[0067] After constructing the speed control system model, the least squares method is used to reduce the order and aggregate the speed control system model, so as to obtain the equivalent transfer function (third-order form) of the speed control system of all synchronous generators as:

[0068] (1)

[0069] In the formula, is the third-order equivalent transfer function, are all the coefficients of the numerator and denominator of the transfer function. For the convenience of subsequent analysis and calculation, is decomposed into three first-order inertia links, is the equivalent gain of the first-order inertia link, is the time constant of the first-order inertia link;

[0070] At this time, the synchronous generator moment of inertia and installed capacity data are obtained again. After obtaining the synchronous generator moment of inertia and installed capacity data, combined with the equivalent transfer function of the speed control system of all synchronous generators in formula (1), the first frequency response equation including the active power increment of the wind farm is established as follows:

[0071] (2)

[0072] In the formula, is the equivalent inertia coefficient of the power grid, is the th synchronous generator moment of inertia, is the installed capacity of the th synchronous generator unit, is the total number of synchronous generator units in the power grid, is the equivalent damping coefficient, is the th damping coefficient of the synchronous generator unit, is the installed capacity of the th wind farm, is the total capacity, is the frequency deviation, is the active power increment of the wind farm, is the active power imbalance in the power grid.

[0073] After the active power imbalance appears in the power grid, if the wind farm has not participated in the frequency response, the frequency drops from the rated value until it recovers to the quasi-steady state frequency :

[0074] (3)

[0075] After obtaining the first frequency response equation containing the active power increment of the wind farm, taking the active power increment of the wind farm as the control variable, the frequency response state space equation is established as follows:

[0076] (4)

[0077] In the formula, are the three components of the active power increment of the synchronous generator unit respectively, is derivative of, Similarly, is the energy released during the frequency regulation of the wind farm, and are the starting moment and the end moment of the primary frequency regulation respectively.

[0078] Taking as the control variable and the frequency deviation as the objective function to establish the optimal control model, the endpoint constraints of each state variable are as follows:

[0079] (5)

[0080] Solving the optimal control model to obtain the maximum frequency deviation . Under the optimal frequency trajectory, the maximum frequency deviation will be greater than or equal to the quasi-steady state frequency when the wind farm does not participate in the response, that is:

[0081] (6)

[0082] In the formula, is the optimal tracking coefficient of the wind farm. When and is equal to , the total energy released by the wind farm during the end of primary frequency regulation can be made equal to 0, thereby realizing the autonomous recovery of the rotational speed during frequency regulation.

[0083] Step S103: Based on the maximum frequency deviation value, determine the equivalent transfer functions of each wind farm participating in frequency response;

[0084] By solving the optimal control model to obtain and , the second frequency response equation of the power grid can be obtained as follows:

[0085] (7)

[0086] In the formula, and are the optimal frequency response coefficients, is the frequency regulation intensity coefficient of the power grid.

[0087] According to the above second frequency response equation of the power grid, the total equivalent transfer function of all wind farms can be determined:

[0088] (8)

[0089] After obtaining the total equivalent transfer function of all the above wind farms, comprehensively considering the real-time wind speed, rotor kinetic energy size and power adjustment space of different wind farms, determine the weight of each wind farm participating in frequency response. According to this weight, is allocated to each wind farm, and the equivalent transfer function of each wind farm participating in frequency response can be obtained. At this time, the optimal frequency trajectory response model of the power grid can be expressed as:

[0090] (9)

[0091] In the formula, are respectively the weight of the th wind farm participating in frequency response and its active power increment, is the real-time or predicted value of the active power output of the th wind farm, is the total number of wind farms in the power grid.

[0092] When the active power increment of the wind farm intersects with its maximum power point tracking (MPPT) curve, it will automatically exit frequency regulation, and at this time the frequency will recover to the quasi-steady state value . The The small-signal model of the MPPT link of a wind farm station can be expressed as:

[0093] (10)

[0094] In the formula, is the additional active power signal of MPPT, is the MPPT coefficient, are the initial value of the wind turbine speed and the change in speed respectively. At the moment of exiting frequency regulation , when , the wind farm station will exit frequency regulation.

[0095] Step S104: Set a contingency, and construct a frequency support strength demand assessment model with the frequency safety limit as the constraint condition;

[0096] Set a contingency, that is, according to the contingency set of the receiving-end power grid, select the active power deficit accident that has a greater impact on frequency safety and stability than the first threshold. The first threshold can be set by oneself. Exceeding this threshold can be understood as that the predetermined accident has a greater impact on frequency safety and stability. With the frequency safety limit as the constraint, that is, the maximum frequency deviation value, the quasi-steady state frequency deviation value, the maximum frequency change rate, and the average frequency change rate are less than the upper limit value as the constraint conditions, and a frequency support strength demand assessment model is established. The specific process is as follows:

[0097] Determine the active power imbalance caused by a contingency (such as a large-scale active power deficit accident such as DC bipolar blocking) and set the limit of the maximum frequency change rate at the moment of the accident , the limit of the average frequency change rate within seconds after the accident , the maximum frequency deviation limit , and the frequency quasi-steady state deviation limit ;

[0098] Let and represent the additional demands for the inertia strength and frequency regulation strength of the receiving-end power grid respectively. Then the time-domain expression of the power grid frequency deviation at this time and the corresponding frequency safety limits (including the maximum frequency change rate , the average frequency change rate , the maximum frequency deviation , and the frequency quasi-steady state deviation of the four) are:

[0099] (11)

[0100] In the formula, is the average time.

[0101] Combined with , , and , construct a frequency support strength requirement evaluation model:

[0102] (12)

[0103] Step S105: Solve the frequency support strength requirement evaluation model to obtain the additional requirements for the inertia strength and frequency regulation strength of the receiving-end power grid;

[0104] Solve the above formula (10), that is, solve the frequency support strength requirement evaluation model, and the current inertia strength of the receiving-end power grid can be determined and the additional requirements for the frequency regulation strength .

[0105] Step S106: Combine the control methods of various flexible frequency regulation resources and the equivalent transfer functions of each wind farm participating in frequency response to establish an optimal frequency trajectory response model including multiple types of frequency regulation resources;

[0106] Combine the control methods of various flexible frequency regulation resources such as voltage direct current, energy storage water stations, pumped storage power stations, and adjustable loads in the receiving-end power grid and the equivalent transfer functions of each wind farm participating in frequency response to establish an optimal frequency trajectory response model including multiple types of frequency regulation resources under the optimal frequency trajectory, specifically:

[0107] (13)

[0108] In the formula, respectively represent the active power increments of the th high-voltage direct current converter station, the th energy storage power station, the th pumped storage power station, and the th adjustable load, are the total numbers of the four types of frequency regulation resources respectively;

[0109] Under the optimal frequency trajectory, assume that the virtual inertia coefficient and virtual droop coefficient of a certain new energy power station (such as a high-voltage direct current, energy storage power station) are and respectively, then the active power increment of the power station at this time can be expressed as:

[0110] (14)

[0111] Observing the above formula, when , the output by the power station is and The value can make the active power increment of the new energy power station become a step signal form during the frequency response process to offset the active power imbalance of the receiving-end power grid. Moreover, it will not damage the power absorption and speed recovery effects of the wind farm under the optimal frequency trajectory.

[0112] Furthermore, observing Equations (11) and (14), it can be seen that under the optimal frequency trajectory, the of the receiving-end power grid mainly affects and but will not affect and Therefore, in the emergency frequency control optimization model, only the and constraints can be considered first to preliminarily evaluate the emergency power control amounts of various types of frequency modulation resources. Then, according to the and numerical relationship, it is judged whether the grid-connected new energy power stations in the receiving-end power grid need to provide additional virtual inertia. As for how to make the judgment, it will be described in detail later.

[0113] Step S107: Construct an emergency frequency control optimization model with the minimum total control cost as the objective function.

[0114] According to the foregoing conditions, corresponding derivations can be carried out to construct an emergency frequency control optimization model with the minimum total control cost as the objective function, where the active power increments of various types of frequency modulation resources are decision variables, and the minimum total control cost is the objective:

[0115] (15)

[0116] In the formula, are the proportion coefficients of the four types of frequency modulation resources respectively, and are the control costs per kW of the active power of the four types of frequency modulation resources (unit: p.u. / kW);

[0117] Step S108: Determine the constraint conditions of the emergency frequency control optimization model according to the optimal frequency trajectory response model.

[0118] After constructing the emergency frequency control optimization model with the minimum total control cost as the objective, it is necessary to determine the constraint conditions. The constraint conditions of this model include power grid frequency constraints, power adjustment space constraints of frequency modulation resources, energy release constraints of energy storage power stations, and power flow constraints of transmission lines.

[0119] 1) Power grid frequency constraints: According to Equation (13), it can be directly derived, that is, according to the optimal frequency trajectory response model, determine the power grid frequency constraint conditions of the emergency frequency control optimization model:

[0120] (16)

[0121] 2) FM resource power adjustment space constraint:

[0122] (17)

[0123] In the formula, are the maximum active powers of four types of FM resources respectively, are the active powers of four types of FM resources at moment;

[0124] 3) Energy storage power station available energy constraint:

[0125] (18)

[0126] In the formula, are the rated voltage, rated capacity, charge state, minimum and maximum charge states of the th energy storage power station respectively;

[0127] 4) Transmission line power flow constraint:

[0128] (19)

[0129] In the formula, are the maximum active power of line and the active power transmission value at moment, is the total number of transmission lines in the power grid, are the power flow transfer coefficients of four types of FM resources for line respectively.

[0130] Step S109: Solve the emergency frequency control optimization model to obtain the emergency power control amounts of various types of FM resources;

[0131] Solve the above emergency frequency control model. According to the solution results and the foregoing derivations, the emergency power control amounts of various types of resources can be determined. The active power increment signal is sent to each pumped storage power station and adjustable load operating in the electric mode, so that they can slow down the frequency drop through pump cut-off or load shedding operations after a pre-conceived accident occurs; the virtual inertia and virtual droop parameters are sent to each high-voltage DC converter station, energy storage power station, and pumped storage power station operating in the power generation mode, so that they can change their power reference values according to the frequency change amount after a pre-conceived accident occurs, thereby realizing power increase.

[0132] Step S110: Based on the emergency power control amounts of various types of FM resources, determine the virtual inertia and virtual droop coefficients sent by various types of FM resources;

[0133] After obtaining the emergency power control amounts of various types of frequency regulation resources, it is necessary to determine the virtual inertia and virtual droop coefficients issued by various types of frequency regulation resources. The specific process of issuance is as follows:

[0134] The th pumped-storage power station (in motor mode) and the th adjustable load's active power increment and are issued, respectively reducing the grid active power imbalance by means of cutting off the water pumps of the pumped-storage power station and cutting off the adjustable load. The th HVDC converter station, the th energy storage power station, and the th pumped-storage power station (in generation mode)'s active power increment and are issued in the form of virtual inertia and virtual droop coefficients:

[0135] (20)

[0136] In the formula, are respectively the virtual inertia coefficient, virtual droop coefficient of the th HVDC converter station, the virtual inertia coefficient, virtual droop coefficient of the th energy storage power station, and the virtual inertia coefficient, virtual droop coefficient of the th pumped-storage power station;

[0137] Step S111: Based on the additional demand of the grid inertia strength and the frequency regulation strength, adjust the virtual inertia coefficients of each grid-forming new energy power station in the receiving-end grid.

[0138] According to Equation (14) and the corresponding derivation, combined with Equation (20), it can be known that the equivalent inertia strength provided by all frequency regulation resources (except wind power stations) in the grid is , and this value is not exactly equal to the additional demand of the inertia strength . Therefore, after issuing the active power increments of the frequency regulation resources according to the foregoing steps, it is necessary to judge the numerical relationship between the inertia strength of the receiving-end grid and the additional demand of the frequency regulation strength and . When , that is, when the first preset condition is satisfied, then according to the inertia strength and the additional demand of the frequency regulation strength, determine the remaining inertia strength shortage of the receiving-end grid:

[0139] (21)

[0140] To meet the inertial strength requirements of the receiving-end power grid, it is necessary to adjust the virtual inertia coefficients of each grid-forming new energy power station in the receiving-end power grid, that is: the deficit still needs to be Perform a secondary allocation of the virtual inertia coefficient according to the power adjustment space of each grid-forming (GFM) new energy power station in the receiving-end power grid, as follows:

[0141] (22)

[0142] In the formula, are respectively the secondary allocation results of the virtual inertia coefficients of the th grid-forming new energy power station and its installed capacity, is the total number of grid-forming new energy power stations, is the th grid-forming new energy power station's power adjustment space. After sending the secondary allocation results to each grid-forming power station, the frequency response of the receiving-end power grid will meet the constraints of the frequency safety limit.

[0143] Experimental verification

[0144] To verify the feasibility and accuracy of the above-mentioned receiving-end power grid emergency frequency control method based on the optimal frequency trajectory provided by the embodiments of the present invention, an IEEE 39-node system is built on the DIgSILENT / PowerFactory 2022 software platform and a specific implementation example is analyzed. Among them, the calculation programs are all compiled using MATLAB on a computer.

[0145] Application example: Taking the IEEE 39-node system as the test system, as Figure 2 shown. The conventional synchronous units include 9 thermal power units and 1 hydroelectric unit. The thermal power units adopt the IEEE-G1 type governor-prime mover model, and the hydroelectric unit adopts the IEEE-G3 governor-prime mover model. In terms of new energy, 30 doubly-fed wind turbines with a rated output of 6 MW are connected to nodes 3, 12, 15, 16, 23, and 29 respectively to form 6 wind farm stations. Among them, W1-W4 are grid-following stations, and W5 and W6 are grid-forming stations, and the power factor is constantly 0.9; 4 energy storage power stations with a rated power of 60 MW are connected to nodes 2, 8, 19, and 24 respectively. Among them, B1 and B4 are grid-following stations, and B2 and B3 are grid-forming stations; 3 pumped-storage power stations with a capacity of 45 MW are connected to nodes 4, 23, and 29 respectively; a high-voltage DC line with a rated power of 400 MW is connected to node 26; the loads at nodes 8, 18, and 21 are adjustable loads. The total installed capacity of the system synchronous units is 6500 MVA, the inertial time constant is 4.153 s, the total system load demand is 7500 MW, and the load damping coefficient is 1.

[0146] Based on the improved IEEE 39 system above, an optimal frequency trajectory response model is constructed in MATLAB / Simulink, as Figure 3 shown. The control block diagram of the new energy power station under the optimal frequency trajectory is shown in Figure 4 Figure. The pre-contingency is set as an 8% sudden increase in the power consumption load of the power grid. The time-domain simulation results of PowerFactory are compared with the constructed optimal frequency trajectory response model (ωop = 1.0724). The results are shown in Figure 5 Figure, where Figure 5 (a) compares the frequency curves before and after the wind power participates in the frequency response. It can be seen that the frequency deviation is effectively reduced after the wind power station participates in the frequency response through the equivalent transfer function; Figure 5 (b) shows the increased power of all synchronous units, all wind turbines in the power grid, and the sum of the two. It can be seen that the increased power of the wind power station shows a characteristic of increasing first and then decreasing. In the first half, the increased power is greater than 0, and it is in the stage of releasing rotor kinetic energy. In the second half, the increased power is less than 0, which makes it enter the speed recovery stage and return to the initial speed at the end of the primary frequency regulation (the primary frequency regulation duration is set to 20 s in this embodiment). The comparison between the time-domain simulation and the calculation results of the optimal frequency trajectory response model under this pre-contingency is shown in Table 1, including the average rate of change of frequency RoCoFav within 200 ms and the maximum frequency deviation ∆fmax. It can be seen from the comparison that the proposed optimal frequency trajectory response model has high accuracy.

[0147] Table 1 Comparison of frequency response indexes between the time-domain simulation and the optimal frequency trajectory response model in the embodiment of the present invention

[0148] .

[0149] After the wind power station enters the speed recovery stage, when its active power increment is equal to the MPPT increment, it will switch to the MPPT operation model and return to the initial operating point. Figure 6 (a) shows the frequency change during the process of the wind power station participating in and exiting the frequency regulation. It can be seen that the lowest frequency point has been significantly improved. Figure 6 (b) shows the relationship between the speed and power of the wind power station during the frequency regulation process. It can be seen that under the optimal frequency trajectory, the wind power station goes through three stages and finally returns to the initial operating point, effectively avoiding the off-grid accident of the wind power station caused by excessive release of rotor kinetic energy. Figure 6 (c), Figure 6 (d) respectively show the changes in the active power increment and the speed change of four wind power stations during the primary frequency regulation. It can be seen that during the primary frequency regulation, the active power of the wind power station shows a characteristic of increasing first, then decreasing, and returning to the initial value, and all have completed the autonomous recovery of speed.

[0150] For three contingency events, namely an 8% sudden increase in electricity load, the tripping of synchronous generator unit G4, and the tripping of G7 + a 5% sudden increase in load, the grid frequency safety constraint limits are set as shown in Table 2. By constructing a frequency support strength demand assessment model and evaluating the additional requirements for inertia strength and frequency regulation strength, Hex and Rex, under the three contingency events, the results are shown in Table 2. Figure 7 It shows the partial node frequency curves before and after each frequency regulation resource participates in emergency frequency control under the contingency event of an 8% sudden increase in load. It can be seen that after the emergency frequency control, the grid frequency drop situation has been significantly improved. Figure 8 It shows the active power output curves of each frequency regulation resource under the contingency event of an 8% sudden increase in load. It can be seen that under the optimal frequency trajectory, by setting the virtual inertia and virtual droop coefficients of energy storage, DC, and pumped-storage power stations according to Equation (20), their output power can be approximated in a step form, verifying the feasibility and effectiveness of taking the active power increment of each frequency regulation resource as a decision variable in the emergency frequency control optimization model.

[0151] Table 2 Frequency safety constraint limits in the embodiments of the present invention

[0152] 。

[0153] Table 3 lists the active power increments of each type of frequency regulation resource under the three contingency events. Among them, for the composite contingency event of the tripping of G7 + a 5% sudden increase in load, since the active power deficit is the largest, the sum of the emergency control powers is the largest. Since the control cost of adjustable load is often higher than other frequency regulation costs, the adjustable load is 0 under the three contingency events.

[0154] Table 3 Emergency control powers of each type of frequency regulation resource under different contingency events in the embodiments of the present invention

[0155] 。

[0156] Table 4 lists the grid frequency response indicators after emergency frequency control under the three contingency events. Comparing with the frequency safety constraint limits given in Table 2, it can be seen that the emergency frequency control method proposed in the present invention effectively improves the frequency stability of the grid under large-scale active power contingency events, making each frequency response indicator within the safety constraint range.

[0157] Table 4 Frequency response indicators under different contingency events in the embodiments of the present invention (after emergency frequency control)

[0158] 。

[0159] In summary, the advantages of the method proposed in the above embodiments of the present application are as follows: ① Ensure that the wind farms in the receiving-end power grid can achieve autonomous restoration of rotational speed during primary frequency regulation, reducing the frequency secondary drop accident caused by excessive release of rotor kinetic energy by the wind turbines; ② Propose how to evaluate the inertial strength and frequency regulation strength requirements of the receiving-end power grid under the optimal frequency trajectory. Compared with the method for evaluating the frequency support strength requirements based on the traditional frequency response model, its principle is simpler and the calculation efficiency is higher; ③ The proposed emergency frequency control method comprehensively considers various flexible frequency regulation resources, and by deriving the numerical relationship between the optimal frequency trajectory and the virtual inertia and virtual droop control of the new energy power station, it proves the interoperability between the step-form active power increment and the virtual inertia and virtual droop control, simplifying the solution process of the emergency frequency control optimization model.

[0160] The foregoing is only a preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A receiving-end power grid emergency frequency control method based on optimal frequency trajectory, characterized in that: include: Obtain the specific model and parameter data of the synchronous unit speed governor-prime mover of the receiving power grid and the control methods of various flexible frequency regulation resources; Based on the specific model and parameter data of the synchronous unit speed governor-prime mover, the maximum frequency deviation value in the frequency response scenario of the wind farm station is obtained; Based on the maximum frequency deviation value, determining the equivalent transfer function of each wind farm station participating in the frequency response; Set the anticipated accidents, take the frequency safety limit as the constraint condition, and build the frequency support strength demand assessment model; Solving the frequency support strength demand assessment model to obtain additional demand for the receiving-end power grid inertia strength and frequency regulation strength; Combining the control methods of the various flexible frequency regulation resources and the equivalent transfer functions of each wind farm station participating in the frequency response, an optimal frequency trajectory response model including multiple types of frequency regulation resources is established; Construct an emergency frequency control optimization model with the minimization of total control cost as the objective function; Determining the constraint conditions of the emergency frequency control optimization model according to the optimal frequency trajectory response model; Solving the emergency frequency control optimization model to obtain emergency power control amounts for various types of frequency modulation resources; Determining virtual inertia and virtual droop coefficients sent by each type of frequency modulation resource based on the emergency power control amount of each type of frequency modulation resource; Based on the inertia strength of the receiving-end power grid and the additional demand for the frequency regulation strength, the virtual inertia coefficients of each networking-type new energy station in the receiving-end power grid are adjusted.

2. The method according to claim 1, characterized in that The step of obtaining the maximum frequency deviation value in the frequency response scenario of the wind farm station based on the specific model and parameter data of the synchronous unit speed governor-prime mover comprises: Based on the specific model of the synchronous unit speed governor-prime mover, a speed control system model is established; The speed control system model is reduced and aggregated by using the least square method to obtain the equivalent transfer function of the speed control system of all synchronous units; Obtain the synchronous unit rotation inertia and installed capacity data; According to the synchronous unit rotation inertia data, the installed capacity data and the equivalent transfer function of the speed control system of all synchronous units, a first frequency response equation of the power grid including the active power increment of the wind farm is obtained; Based on the first frequency response equation of the power grid, a frequency response state space equation is established with the active power increment of the wind farm as the control variable; Based on the frequency response state space equation, an optimal control model is established with the maximum frequency deviation value as the objective function; The optimal control model is solved to obtain the maximum frequency deviation value in the frequency response scenario in which the wind farm participates.

3. The method according to claim 2, characterized in that The step of determining the equivalent transfer function of each wind farm station participating in the frequency response based on the maximum frequency deviation value comprises: Based on the maximum frequency deviation value, determining a second frequency response equation of the power grid; Based on the second frequency response equation of the power grid, determining the total equivalent transfer function of all wind farms; Based on the total equivalent transfer function of all wind farms, the equivalent transfer function of each wind farm participating in the frequency response is determined.

4. The method according to claim 1, characterized in that: The aforementioned setting of anticipated accidents and taking the frequency safety limit as a constraint condition to construct a frequency support intensity demand assessment model includes: According to the expected accident screening set of the receiving-end power grid, active power shortage accidents whose impact on frequency safety and stability is greater than a first threshold are screened out; A frequency support strength demand assessment model is established with the minimum sum of the inertia strength of the receiving power grid and the additional demand for frequency regulation strength as the objective function, and the maximum frequency deviation value, quasi-steady-state frequency deviation value, maximum frequency change rate, and average frequency change rate being less than the upper limit value as constraints.

5. The method according to claim 1, characterized in that Determining the constraint conditions of the emergency frequency control optimization model according to the optimal frequency trajectory response model includes: According to the optimal frequency trajectory response model, the power grid frequency constraint conditions of the emergency frequency control optimization model are determined.

6. The method according to claim 1, characterized in that The additional demand for the inertia strength of the receiving-end power grid and the frequency modulation strength is used to adjust the installed capacity ratio of the new energy stations in each grid type of the receiving-end power grid; including: Determining whether the relationship between the inertia strength of the receiving-end power grid and the additional demand for the frequency modulation strength meets a first preset condition; If it is satisfied, the inertia strength shortfall is determined according to the additional demand for the inertia strength and the frequency modulation strength; Based on the inertia strength shortfall, the virtual inertia coefficients of each networking-type new energy station of the receiving-end power grid are adjusted.

7. The method according to claim 5, characterized in that The constraint conditions of the emergency frequency control optimization model also include adjustment resource power adjustment space constraints: ， In the formula, are the maximum active powers of the four frequency modulation resources, There are four types of FM resources. Active power at the moment, Respectively represent High-voltage DC converter station, Energy storage power station, Pumped storage power station and The active power increment of an adjustable load, They are the total number of four frequency modulation resources respectively.

8. The method according to claim 7, characterized in that The constraint conditions of the emergency frequency control optimization model also include the energy release constraint of the energy storage power station: ， In the formula, Respectively The rated voltage, rated capacity, charging state, minimum and maximum charging state and transmission line flow constraints of each energy storage power station.

9. The method according to claim 7, characterized in that: The constraints of the emergency frequency control optimization model also include transmission line power flow constraints: ， In the formula, Line The maximum active power and The active power delivery value at the moment, is the total number of transmission lines in the power grid, There are four types of FM resources for lines. The power transfer coefficient.

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