A Method for Primary Frequency Regulation Parameter Planning in New Energy Power Plants Based on Frequency Response Model

Abstract

This invention relates to a method for planning primary frequency regulation parameters of a new energy power station based on a frequency response model. The method is characterized by: constructing a system frequency response model, obtaining system dynamic indicators and setting constraints, and solving the feasible region of virtual inertia / active power-frequency droop coefficient of the new energy power station through a two-layer loop.

Description

Technical Field

[0001] This invention belongs to the field of frequency stability control in new power systems, and relates to a method for planning primary frequency regulation parameters of new energy power plants based on a frequency response model. Background Technology

[0002] Against the backdrop of energy industry optimization, new energy power plants and energy storage systems are widely integrated into traditional power systems dominated by synchronous machines. However, as the installed capacity of new energy power plants and energy storage systems continues to increase, the total rotational inertia of the system will decrease, which is not conducive to the frequency stability of the system [1-3]. In response to this situation, frequency-supported control can be adopted for new energy power plants or energy storage systems, which can effectively improve the frequency stability of the system [4].

[0003] Existing work often uses virtual inertia and primary frequency regulation control for new energy power plants or energy storage systems [5]. However, in actual engineering, how to design the virtual inertia and active power-frequency droop coefficient of new energy or energy storage systems is an urgent problem to be solved. Reference [6] proposed the concept of inertia safety domain for new power systems, which describes the system inertia range that can guarantee system frequency stability and safety stability constraints, but did not solve the problem of how to reasonably configure the primary frequency regulation parameters of new energy so that the system meets the frequency stability requirements. Reference [7] proposed an adaptive parameter optimization design method for grid-connected virtual synchronous machines, but did not consider the frequency response characteristics of grid-side synchronous machines. Reference [8] used the minimum maximum system frequency deviation and the minimum expected damping ratio deviation of the dominant oscillation mode as the objective function to optimize the design of virtual inertia and virtual damping parameters of the wind farm in a two-region interconnected system containing a doubly fed wind farm, but did not consider the power and energy limitations of the wind farm during frequency regulation. Reference [9] proposed an analytical method for the feasible domain analysis and design of virtual inertia and damping coefficient of energy storage VSG for diesel-storage microgrids. However, the frequency dynamics of diesel generator sets considered by this method are relatively simple and cannot be applied to scenarios that take into account the complex frequency response characteristics of thermal power units or hydropower units.

[0004] To address the aforementioned problems, this invention proposes a primary frequency regulation parameter planning method for renewable energy power plants based on a frequency response model. According to the established system dynamic index constraints, the feasible region of the virtual inertia / active power-frequency droop coefficient of the renewable energy power plant is effectively solved, overcoming the difficulty in analytically obtaining the feasible region of parameters due to the complex frequency response characteristics of traditional synchronous generator units within the system. The proposed method is simple to implement and highly accurate.

[0005] References

[0006] [1]R.Yan,N.-Masood,T.Kumar Saha,F.Bai and H.Gu,"The Anatomy of the2016 South Australia Blackout:A Catastrophic Event in a High RenewableNetwork,"IEEE Trans.Power Syst.,vol.33,no.5,pp. 5374-5388,Sept.2018.

[0007] [2]D.Gautam,V.Vittal and T.Harbour,"Impact of Increased Penetrationof DFIG-Based Wind Turbine Generators on Transient and Small Signal Stabilityof Power Systems,"IEEE Trans.Power Syst.,vol.24,no.3, pp.1426-1434,Aug.2009.

[0008] [3]V.Gevorgian,Y.Zhang and E.Ela,"Investigating the Impacts of WindGeneration Participation in Interconnection Frequency Response,"IEEETrans.Sustain.Energy,vol.6,no.3,pp.1004-1012,July 2015.

[0009] [4]Jia Liu,Y.Miura and T.Ise,"Dynamic characteristics and stabilitycomparisons between virtual synchronous generator and droop control ininverter-based distributed generators,"2014 International Power ElectronicsConference(IPEC-Hiroshima 2014-ECCE ASIA),2014,pp.1536-1543.

[0010] [5] Zhang Xu, Chen Yunlong, Yue Shuai, Zha Xiaobing, Zhang Dongying, Xue Lei. A review and prospect of research on wind power participation in power system frequency regulation technology [J]. Power System Technology, 2018, 42(06): 1793-1803.

[0011] [6] Lin Xiaohuang, Wen Yunfeng, Yang Weifeng. Inertia safety domain: concept, characteristics and evaluation method [J]. Proceedings of the CSEE, 2021, 41(09):3065-3079.

[0012] [7] Yan Xiangwu, Zhang Weichao, Cui Sen, Huang Hanyan, Li Tiecheng. Time-domain characteristics of frequency response and adaptive parameter design of voltage source inverter based on virtual synchronous machine [J]. Journal of Electrical Engineering, 2021, 36(S1):241-254.

[0013] [8] Yang Tao, Liao Yong. Coordinated control method of virtual inertia and virtual damping for interconnected power systems with doubly fed wind farms [J]. Electric Power Automation Equipment, 2020, 40(11):92-100.

[0014] [9] Zhao Zihan, Guo Li, Li Xialin, Xing Jianchun, Yang Qiliang, Liu Rui, Wang Hongda, Wang Chengshan. Feasible domain analysis method for virtual inertia and damping coefficient of diesel-storage microgrid [J / OL]. Proceedings of the CSEE, 2020, 1-16. Summary of the Invention

[0015] This invention discloses a method for planning primary frequency regulation parameters of renewable energy power plants based on a frequency response model, which has the advantages of simple implementation and high accuracy. The technical solution is as follows:

[0016] A method for primary frequency regulation parameter planning of renewable energy power plants based on a frequency response model is characterized by the following steps: constructing a system frequency response model, obtaining system dynamic indicators and setting constraints, and solving the feasible region of virtual inertia / active power-frequency droop coefficient of the renewable energy power plant using a double-layer loop.

[0017] The first step is to construct a system frequency response model.

[0018] For power systems where renewable energy power plants participate in primary frequency regulation, construct the system's equivalent frequency response model:

[0019] Δω=-G(s)ΔP L (1)

[0020] In equation (1), the transfer function G(s) is expressed as:

[0021]

[0022] ΔP LThe active load power disturbance is represented by Δω, the system frequency change is represented by R, and the regional equivalent unit dispatch rate is represented by T. G F is the time delay constant of the regional equivalent unit speed governor; HP T RH T CH Parameters reflecting the turbine characteristics of the regional equivalent unit: T CH T is the time constant of the equivalent gas chamber. RH F is the equivalent reheater time constant. HP H is the equivalent high-pressure turbine coefficient; sg D represents the inertia of the equivalent unit in the region. sg It is the load damping coefficient; H RES K represents the virtual inertia of the new energy power station. RES The active power-frequency droop coefficient for new energy power plants;

[0023] The second step is to establish system dynamic indicators and constraints.

[0024] Equation (1) yields two frequency indices after the system is disturbed: the rate of frequency change RoCoF at the moment of disturbance and the maximum frequency deviation f after the disturbance. nadir The rate of change of the system's frequency at the instant of disturbance is expressed as:

[0025] RoCoF| t＝0 =L -1 [-sG(s)ΔP L ]| t＝0 (3)

[0026] The maximum frequency deviation of the system after being disturbed is expressed as:

[0027] f nadir =max(|L -1 [-G(s)ΔP L ]|) (4)

[0028] symbol L -1 Indicates the inverse Laplace transform;

[0029] The frequency regulation time of the new energy power station participating in the system is set to 15 seconds, and the maximum output P of the new energy power station is obtained. RES,max Energy E of primary frequency regulation system with new energy power stations RES,15s , where P RES,max Represented as:

[0030] P RES，max =max(|L -1 [-(H RES s+K RES )G(s)ΔP L ]|) (5)

[0031] E RES,15s Expressed as:

[0032]

[0033] The following constraints are set: 1) The rate of change of the system's frequency RoCoF at the moment of disturbance must not exceed the limit RoCoF. limit ;2) The maximum frequency deviation f after the system is disturbed nadir It must not exceed Δf limit ;3) Maximum output P of new energy power stations RES,max Not exceeding P RES,limit ;4) Energy E of new energy power stations participating in the primary frequency regulation system RES,15s Not exceeding E RES,max ;

[0034] Step 3: Solve the feasible region of virtual inertia / active power-frequency droop coefficient of renewable energy power plants using a double-layer loop.

[0035] (1) Preset all H RES The possible values ​​are H RES1 ~H RESm Preset all K RES The possible values ​​are K RES1 ~K RESn Define two counting variables i and j, and set i = 1;

[0036] (2) Determine if i is less than or equal to m. If yes, set j = 1 and execute step (3); otherwise, the algorithm ends.

[0037] (3) Determine if j is less than or equal to n. If yes, proceed to step (4); otherwise, increment i by 1 and proceed to step (2) and the following steps.

[0038] (4) H RESi and K RESj Substitute into formulas (3)(4)(5)(6) to calculate RoCoF| t＝0 f nadir P RES,max E RES,15s If the four established constraints are met, then step (5) is executed; otherwise, j is incremented by 1, and step (3) and subsequent steps are executed.

[0039] (5) H RES With K as the horizontal axis RES Using H as the vertical axis, record (H) RESi ,K RESj Find the coordinates, increment j by 1, and execute step (3) and the subsequent steps.

[0040] The beneficial effects of this invention are:

[0041] 1) It can obtain the feasible region of virtual inertia / active power-frequency droop coefficient of new energy power plants through data analysis based solely on the system frequency response model, avoiding the tedious and complex difficulties of solving using analytical methods.

[0042] 2) The method proposed in this invention is simple and effective, and easy to implement in practical engineering. It has been fully verified in the IEEE 10-machine 39-bus system containing wind farms. Attached Figure Description

[0043] Figure 1 Single-area power system

[0044] Figure 2 Equivalent system frequency response model

[0045] Figure 3 Virtual Inertia / Active Power-Frequency Droop Coefficient Planning Algorithm for New Energy Power Stations

[0046] Figure 4 IEEE 10-machine 39-node system

[0047] Figure 5 Feasible region of virtual inertia / active power-frequency droop coefficient for wind farm

[0048] Figure 6 Simulation Verification of Feasible Region for Virtual Inertia / Active Power-Frequency Droop Coefficient of Wind Farm Detailed Implementation

[0049] The technical solution of this invention, in the integration of new energy sources into a traditional power system, firstly, constructs an equivalent frequency response model for the inertia and primary frequency regulation of the power system involving new energy sources. Secondly, based on the equivalent frequency response model, four dynamic indicators of the system after being subjected to power disturbances are obtained: the rate of frequency change at the instant of disturbance, the maximum frequency deviation after disturbance, the maximum output of the new energy power station, and the 15s frequency regulation energy of the new energy power station. Finally, the constraint range of the above four indicators after the system is disturbed is set, and the feasible region of the virtual inertia / active power-frequency droop coefficient of the new energy power station is obtained using a double-layer cyclic traversal solution method. This feasible region of the virtual inertia / active power-frequency droop coefficient of the new energy power station can be used for upper-level dispatching of the power system as the basic basis for issuing primary frequency regulation parameters of the new energy power station. The technical solution is as follows:

[0050] The first step is to construct a system frequency response model.

[0051] For power systems where renewable energy power plants participate in primary frequency regulation, construct the system's equivalent frequency response model:

[0052] Δω=-G(s)ΔP L (1)

[0053] In equation (1), the transfer function G(s) is expressed as:

[0054]

[0055] ΔP L The active load power disturbance is represented by Δω, the system frequency change is represented by R, and the regional equivalent unit dispatch rate is represented by T. G F is the time delay constant of the regional equivalent unit speed governor. HP T RH T CH Parameters reflecting the turbine characteristics of the regional equivalent unit: T CH T is the time constant of the equivalent gas chamber. RH F is the equivalent reheater time constant. HP H represents the equivalent high-pressure turbine coefficient. sg D represents the inertia of the equivalent unit in the region. sg This is the load damping coefficient (which can generally be ignored). H RES K represents the virtual inertia of the new energy power station. RES The active power-frequency droop factor (Pf droop factor) is used for new energy power plants.

[0056] The second step involves defining system dynamic indicators and constraints.

[0057] Equation (1) yields two frequency indices after the system is disturbed: the rate of change of the system frequency at the instant of disturbance (RoCoF) and the maximum frequency deviation of the system (f). nadir ), where the rate of change of the system's frequency at the instant of disturbance is expressed as:

[0058] RoCoF| t＝0 =L -1 [-sG(s)ΔP L ]| t＝0 (3)

[0059] The maximum frequency deviation of the system is expressed as:

[0060] f nadir =max(|L -1 [-G(s)ΔP L ]|) (4)

[0061] The symbol L in equations (3) and (4) -1 This represents the inverse Laplace transform.

[0062] The frequency regulation time for the renewable energy power station to participate in the system is set to 15 seconds. The maximum output P of the renewable energy power station can then be obtained. RES,max With 15s frequency modulation energy E RES,15s Among them, P RES,max Expressed as:

[0063] P RES，max =max(|L -1 [-(H RES s+K RES )G(s)ΔP L ]|) (5)

[0064] E RES,15s Expressed as:

[0065]

[0066] The following constraints are set: 1) The rate of change of the system frequency at the time of disturbance must not exceed the limit RoCoF. limit 2) The maximum frequency deviation of the system after being disturbed must not exceed Δf. limit ;3) The maximum output of new energy power plants shall not exceed P RES,limit ;4) The primary frequency regulation energy of the renewable energy power station participating in the system shall not exceed E RES,max The above constraints can be expressed as:

[0067]

[0068] 1. Solving the feasible region of virtual inertia / active power-frequency droop coefficient for renewable energy power plants using a double-layer loop traversal method.

[0069] (1) Preset all H RES The possible values ​​are H RES1 ~H RESm Preset all K RES The possible values ​​are K RES1 ~K RESn Define two counting variables i and j, and set i = 1;

[0070] (2) Determine if i is less than or equal to m. If yes, set j = 1 and execute step (3); otherwise, the algorithm ends.

[0071] (3) Determine if j is less than or equal to n. If yes, proceed to step (4); otherwise, increment i by 1 and proceed to step (2) and the following steps.

[0072] (4) H RESi and K RESj Substitute (3)(4)(5)(6) to calculate RoCoF| t＝0 f nadir P RES,max E RES,15s If equation (7) is satisfied, then proceed to step (5); otherwise, increment j by 1 and proceed to step (3) and the subsequent steps.

[0073] (5) HRES With K as the horizontal axis, RES Using H as the vertical axis, record (H) RESi ,K RESj Find the coordinates, increment j by 1, and execute step (3) and the subsequent steps.

[0074] The following detailed description is provided in conjunction with the accompanying drawings and embodiments.

[0075] 1. Frequency response model of power system considering frequency regulation of new energy sources

[0076] This invention can be applied to Figure 1 The illustrated single-region power system includes multiple synchronous generating units and renewable energy power plants, with the renewable energy participating in grid inertia and primary frequency regulation control. Figure 1 All synchronous generators in the system shown are replaced by an equivalent synchronous generator, and considering the aggregation frequency regulation effect of new energy generators, a system can be constructed as follows: Figure 2 The equivalent system frequency response model is shown. Where ΔP L The active load power disturbance is represented by Δω, the system frequency change is represented by R, and the regional equivalent unit dispatch rate is represented by T. G F is the time delay constant of the regional equivalent unit speed governor. HP T RH T CH Parameters reflecting the turbine characteristics of the regional equivalent unit: T CH T is the time constant of the equivalent gas chamber. RH F is the equivalent reheater time constant. HP H represents the equivalent high-pressure turbine coefficient. sg D represents the inertia of the equivalent unit in the region. sg This is the load damping coefficient (which can generally be ignored). H RES K represents the virtual inertia of the new energy power station. RES The active power-frequency droop factor (Pf droop factor) is used for new energy power plants.

[0077] 2. Feasible region planning for virtual inertia / Pf droop coefficient of new energy power stations

[0078] against Figure 2 The system frequency response model shown takes into account the frequency regulation of new energy sources, where the parameters (H) related to the regional equivalent synchronous generator units are... sg R, T G F HP T RH T CH All of these parameters can be obtained through parameter aggregation methods or estimated using data-driven methods, and can be considered as known parameters. This invention is based on... Figure 2Based on the model shown, after the system is subjected to power disturbance, frequency dynamic correlation constraints and power / energy constraints of new energy power stations are set to characterize the feasible region of virtual inertia / Pf droop coefficient of new energy power stations, that is, to obtain H. RES With K RES The two-dimensional parameter feasible region is formed. The specific planning steps are as follows:

[0079] Firstly, according to Figure 2 In the model shown, when the system is subjected to a power disturbance, the expression for the system frequency with respect to the load power is:

[0080] Δω=-G(s)ΔP L (1)

[0081] In equation (1), the transfer function G(s) is expressed as:

[0082]

[0083] Equation (1) yields two frequency indices after the system is disturbed: the rate of change of the system frequency at the instant of disturbance (RoCoF) and the maximum frequency deviation of the system (f). nadir ), where the rate of change of the system's frequency at the instant of disturbance is expressed as:

[0084] RoCoF| t＝0 =L -1 [-sG(s)ΔP L ]| t＝0 (3)

[0085] The maximum frequency deviation of the system is expressed as:

[0086] f nadir =max(|L -1 [-G(s)ΔP L ]|) (4)

[0087] The symbol L in equations (3) and (4) -1 This represents the inverse Laplace transform.

[0088] The frequency regulation time for new energy power plants participating in the system is set to 15 seconds. According to... Figure 2 The model shown can be used to obtain the maximum output P of the new energy power station. RES,max With 15s frequency modulation energy E RES,15s Among them, P RES,max Expressed as:

[0089] P RES，max =max(|L -1 [-(H RES s+K RES )G(s)ΔP L ]|) (5)

[0090] E RES,15s Represented as:

[0091]

[0092] Further constraints are set as follows: 1) The rate of change of the system frequency at the time of disturbance must not exceed the limit RoCoF. limit 2) The maximum frequency deviation of the system after being disturbed must not exceed Δf. limit ;3) The maximum output of new energy power plants shall not exceed P RES,limit ;4) The primary frequency regulation energy of the renewable energy power station participating in the system shall not exceed E RES,max The above constraints can be expressed as:

[0093]

[0094] The virtual inertia (H) of the new energy power station can be constructed according to equation (7). RES Active power-frequency droop factor (K) RES Feasible region, specific algorithm as follows Figure 3 As shown. The feasible region construction method of this patent adopts a two-layer loop traversal solution method: (1) Preset all H RES The possible values ​​are H RES1 ~H RESm Preset all K RES The possible values ​​are K RES1 ~K RESn Define two counting variables i and j, and set i = 1; (2) Determine if i is less than or equal to m. If yes, set j = 1 and execute step (3); if no, the algorithm ends; (3) Determine if j is less than or equal to n. If yes, execute step (4); if no, increment i by 1 and execute step (2) and the following steps; (4) Set H RESi and K RESj Substitute (3)(4)(5)(6) to calculate RoCoF| t＝0 f nadir P RES,max 、E RES,15s If equation (7) is satisfied, then proceed to step (5); otherwise, increment j by 1 and proceed to step (3) and the subsequent steps; (5) with H RES With K as the horizontal axis, RES Using H as the vertical axis, record (H) RESi ,K RESj Find the coordinates, increment j by 1, and execute step (3) and the subsequent steps.

[0095] Based on the above algorithm steps, it can eventually be achieved in H RES K is the horizontal axis. RES The virtual inertia (H) of the new energy power station is recorded on a two-dimensional plane with the vertical axis.RES Active power-frequency droop factor (K) RES All feasible solutions to ) are combined to form the region of virtual inertia (H) of the new energy power station. RES Active power-frequency droop factor (K) RES Feasible region.

[0096] 3. Simulation Results

[0097] To verify the accuracy of the above-mentioned method for primary frequency regulation parameter planning of new energy power plants based on the frequency response model, this study focuses on... Figure 4 The 400MW wind farm shown is connected to the standard IEEE 10-machine 39-bus system, and the virtual inertia / active power-frequency droop factor of the wind farm has been planned. The system rated frequency is 50Hz, and the power base value is set at 4000MW. Figure 4 The parameters of the 10 generators in the system are shown in Table 1.

[0098] Table 1 Parameters of IEEE 10-machine 39-node Synchronizer

[0099]

[0100] Based on the above synchronous machine parameters, the regional equivalent synchronous machine parameters can be obtained through parameter aggregation methods or data-driven estimation methods, as shown in Table 2.

[0101] Table 2 Parameters of Regional Equivalent Synchronous Generating Units

[0102]

[0103] Substitute the parameters shown in Table 2 into Figure 2 In the system frequency response model shown, to proceed with the subsequent H... RES -K RES Feasible region solution. The new energy power station under consideration is a 400MW permanent magnet direct-drive wind farm, and the basic parameters of a single 2MW wind turbine are shown in Table 3.

[0104] Table 3 Parameters of Permanent Magnet Direct Drive Fan

[0105]

[0106] The system operating scenario is as follows: the wind farm operates normally in Maximum Power Point Tracking (MPPT) mode, with a wind speed of 6.5 m / s, an initial turbine speed of 0.7094 pu, an output power of 1 MW, and a lower limit of turbine speed of 0.3 pu. The maximum transient disturbance considered is a sudden increase in system load of 200 MW. The maximum output constraint and the energy constraint for a 400 MW wind farm under a 15-second frequency regulation cycle can be calculated as follows:

[0107]

[0108] In addition, the dynamic index constraints for the system frequency response are set as follows:

[0109]

[0110] Under a power base of 4000MW, the above constraints can be rewritten as:

[0111]

[0112] Using the constraints shown in Equation (10), a feasible region planning of the virtual inertia / active power-frequency droop coefficient for a 400MW permanent magnet direct-drive wind farm is performed. Following the double-layer cyclic traversal solution method proposed in this invention, H is obtained. RESi -K RESj Two-dimensional feasible region such as Figure 5 As shown.

[0113] The following section verifies the feasible parameters for primary frequency regulation of new energy power plants within the obtained feasible domain. Figure 5 It can be known that (H) RES ,K RES Since (3,3) falls within the feasible region, a 200MW power disturbance is applied to the IEEE 10-machine 39-bus system using frequency regulation parameters of virtual inertia of 3 and active power-frequency droop coefficient of 3 for a 400MW wind farm. The simulation results after the disturbance are as follows. Figure 6 As shown. By Figure 6 It is evident that by using this set of frequency regulation parameters, the wind farm can ensure that all dynamic indicators of the system remain within the constraints after being disturbed, thus verifying the effectiveness of the method proposed in this invention.

Claims

1. A method for planning primary frequency regulation parameters of a new energy power station based on a frequency response model, characterized in that: The steps include constructing a system frequency response model, obtaining system dynamic indicators and setting constraints, and using a double-loop traversal to obtain the feasible region of the virtual inertia / active power-frequency droop coefficient of the new energy power station. The first step is to construct a system frequency response model. For power systems where renewable energy power plants participate in primary frequency regulation, construct the system's equivalent frequency response model: Δω=-G(s)ΔP L (1) In equation (1), the transfer function G(s) is expressed as: ΔP L The active load power disturbance is represented by Δω, the system frequency change is represented by R, and the regional equivalent unit dispatch rate is represented by T. G F is the time delay constant of the regional equivalent unit speed governor; HP T RH T CH The parameter reflecting the turbine characteristics of the regional equivalent unit: T CH T is the time constant of the equivalent gas chamber. RH F is the equivalent reheater time constant. HP H is the equivalent high-pressure turbine coefficient; sg D represents the inertia of the equivalent unit in the region. sg It is the load damping coefficient; H RES K represents the virtual inertia of the new energy power station. RES The active power-frequency droop coefficient for new energy power plants; The second step is to establish system dynamic indicators and constraints. Equation (1) yields two frequency indices after the system is disturbed: the rate of frequency change RoCoF at the moment of disturbance and the maximum frequency deviation f after the disturbance. nadir The rate of change of the system's frequency at the instant of disturbance is expressed as: RoCoF| t＝0 =L -1 [-sG(s)ΔP L ]| t＝0 (3) The maximum frequency deviation of the system after being disturbed is expressed as: f nadir =max(|L -1 [-G(s)ΔP L ]|) (4) symbol L -1 Indicates the inverse Laplace transform; The frequency regulation time of the new energy power station participating in the system is set to 15 seconds, and the maximum output P of the new energy power station is obtained. RES,max Energy E of primary frequency regulation system with new energy power stations RES,15s , where P RES,max Expressed as: P RES，max =max(|L -1 [-(H RES s+K RES )G(s)ΔP L ]|) (5) E RES,15s Represented as: The following constraints are set: 1) The rate of change of the system's frequency RoCoF at the moment of disturbance must not exceed the limit RoCoF. limit ;2) The maximum frequency deviation f after the system is disturbed nadir It must not exceed Δf limit ;3) Maximum output P of new energy power stations RES,max Not exceeding P RES,limit ;4) Energy E of new energy power stations participating in the primary frequency regulation system RES,15s Not exceeding E RES,max ; Step 3: Solve the feasible region of virtual inertia / active power-frequency droop coefficient of renewable energy power plants using a double-layer loop. (1) Preset all H RES The possible values ​​are H RES1 ~H RESm Preset all K RES The possible values ​​are K RES1 ~K RESn Define two counting variables i and j, and set i = 1; (2) Determine if i is less than or equal to m. If yes, set j = 1 and execute step (3); otherwise, the algorithm ends. (3) Determine if j is less than or equal to n. If yes, proceed to step (4); otherwise, increment i by 1 and proceed to step (2) and the following steps. (4) H RESi and K RESj Substitute into formulas (3)(4)(5)(6) to calculate RoCoF| t＝0 f nadir P RES,max E RES,15s If the four established constraints are met, then step (5) is executed; otherwise, j is incremented by 1, and step (3) and subsequent steps are executed. (5) H RES With K as the horizontal axis, RES Using H as the vertical axis, record (H) RESi ,K RESj Find the coordinates, increment j by 1, and execute step (3) and the subsequent steps.

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