A frequency safety evaluation method and system for a high-proportion new energy power system

Abstract

This invention discloses a frequency security assessment method and system for a high-proportion renewable energy power system, comprising: calculating the system's rotational inertia margin and tolerable disturbance margin under a large disturbance fault scenario, using a frequency margin index as a constraint; calculating the in-regulation resource margin, ramping resource margin, and reserve resource margin under a power fluctuation scenario, using a frequency margin index as a constraint; determining the disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin; determining the frequency regulation capability based on the in-regulation resource margin, ramping resource margin, and reserve resource margin; and performing optimized control based on the disturbance rejection capability and frequency regulation capability to ensure that the high-proportion renewable energy power system is in a safe and stable state. This invention can realize online calculation of the system's disturbance rejection capability and frequency regulation capability, and quickly assess the current frequency security level of the power grid, achieving panoramic perception and early warning of frequency security.

Description

Technical Field

[0001] This invention relates to the field of power system operation and control technology, and more specifically, to a frequency security assessment method and system for a high-proportion renewable energy power system. Background Technology

[0002] As the proportion of renewable energy integration continues to increase, the operating characteristics of the power system are undergoing profound changes. On the one hand, the large-scale replacement of synchronous generators by renewable energy units has led to a decrease in the system's moment of inertia. When a major disturbance fault causes a large power loss, the risk of transient frequency instability in the power grid increases. On the other hand, renewable energy sources such as wind power and solar power are highly volatile. Even without faults, they face the risk of frequency exceeding limits due to the continuous decrease / increase in grid frequency caused by large fluctuations in renewable energy and load power.

[0003] Existing frequency early warning methods primarily rely on transient frequency simulation results under anticipated faults to determine whether transient frequency extremes and steady-state frequency values ​​are within allowable deviation ranges, thereby assessing whether the system frequency is in a safe state. The drawbacks are: 1) In traditional power systems, power fluctuations mainly originate from load changes. Compared to the power loss caused by large disturbances due to faults, load fluctuations are smaller. Therefore, when the frequency meets requirements after a large disturbance, the frequency also meets requirements under power fluctuation scenarios. However, as the proportion of renewable energy integration continues to increase and becomes the main power source, power fluctuations in the system originate from both renewable energy and load, significantly increasing the fluctuation range. If existing solutions are still used, focusing only on large disturbances without considering power fluctuations and other disturbance patterns after a high proportion of renewable energy integration, it is difficult to meet the frequency safety and stability requirements under the new circumstances. 2) Frequency response curve changes are a manifestation of power system power balance regulation. Judging only the transient frequency extremes and steady-state frequency values ​​under large disturbances cannot comprehensively reflect the causes of system frequency risks and is insufficient to help dispatchers accurately grasp the operating status of the new power system.

[0004] Therefore, a frequency security assessment method for high-proportion renewable energy power systems is needed. Summary of the Invention

[0005] This invention proposes a frequency security assessment method and system for high-proportion renewable energy power systems to address the problem of how to quantitatively assess the grid frequency security of high-proportion renewable energy power systems under scenarios of large disturbance faults and fault-free power fluctuations.

[0006] To address the aforementioned problems, according to one aspect of the present invention, a frequency security assessment method for a high-proportion renewable energy power system is provided, the method comprising:

[0007] Using the frequency margin index as a constraint, the system rotational inertia margin and tolerable disturbance margin are calculated under large disturbance fault scenarios.

[0008] Using frequency margin as a constraint, calculate the frequency modulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios;

[0009] Based on the system's rotational inertia margin and tolerable disturbance margin, the disturbance rejection capability is determined;

[0010] Based on the aforementioned frequency regulation resource margin, ramping resource margin, and reserve resource margin, the frequency regulation capability is determined;

[0011] Optimized control is implemented based on disturbance rejection and frequency regulation capabilities to ensure that the high-proportion renewable energy power system remains in a safe and stable state.

[0012] Preferably, the calculation of the system's rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios, constrained by the frequency margin index, includes:

[0013] Determine the online anticipated disturbance power under large disturbance fault scenarios;

[0014] For the online anticipated disturbance power, simulation calculations are performed based on the frequency response model of the large disturbance system. During the simulation, other parameters are kept constant, and the equivalent inertia of the model is gradually reduced. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the inertial constant at this time is determined as the target inertial constant. The system rotational inertia margin is determined based on the target inertial constant.

[0015] Based on the online anticipated disturbance power, simulation calculations are performed using a frequency response model of a large disturbance system. During the simulation, other parameters are kept constant, and the disturbance power is gradually increased. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the disturbance power at this time is determined as the maximum disturbance power that the system can withstand. The tolerable disturbance margin is determined based on the maximum disturbance power that the system can withstand.

[0016] Preferably, determining the system's rotational inertia margin based on the target inertia constant includes:

[0017] ,

[0018] Among them, M H H represents the system's rotational inertia margin. sys H is the equivalent inertial constant of the system under the current operating mode;cri Let be the target inertial constant.

[0019] Preferably, determining the tolerable disturbance margin based on the maximum disturbance power the system can withstand includes:

[0020] ,

[0021] Among them, M P Tolerable disturbance margin; ΔP cri The maximum disturbance power that the system can withstand; ΔP d This represents the system's online anticipated disturbance power under the current operating mode.

[0022] Preferably, the calculation of frequency regulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios, constrained by the frequency margin index, includes:

[0023] Determine the online expected power fluctuation in power fluctuation scenarios;

[0024] Simulation calculations are performed based on a power grid frequency calculation model for fluctuating scenarios, letting ΔP agc =0 and ΔP ct =0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limiting and unit output range, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the primary frequency regulation capacity; determine the frequency regulation resource margin based on the primary frequency regulation capacity;

[0025] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agc Let ΔP ct =0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limit and unit output range, consider the difference in ramp rate of different units in the secondary frequency regulation and the constraint of cross-sectional power limit, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any one of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the ramp capacity; determine the ramp resource margin based on the ramp capacity;

[0026] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agc According to the security control strategy table, ΔP is triggered based on the frequency deviation setpoint. ctThe online anticipated power fluctuation is gradually increased, taking into account the primary frequency regulation dead zone, amplitude limit, and unit output range; the differences in ramp rate of different units in the secondary frequency regulation and the constraints of the cross-sectional power limit; and the safety control action. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitoring output frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the reserve capacity is determined; the reserve resource margin is determined based on the ramp capacity.

[0027] Preferably, determining the frequency modulation resource margin based on the primary frequency modulation capacity includes:

[0028] ,

[0029] ,

[0030] Among them, M fre For frequency modulation resource margin; ΔP fre This represents the primary frequency modulation capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP g, i represents the primary frequency regulation capacity of unit i; ΔP new,i N represents the primary frequency regulation capacity of the new energy power station i; G N represents the total number of synchronous generator units under startup mode; S This represents the total number of new energy power stations under the start-up mode.

[0031] Preferably, determining the climbing resource margin based on the climbing capacity includes:

[0032] ,

[0033] ,

[0034] ,

[0035] Among them, M ramp For climbing resource margin; ΔP ramp For climbing capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc For the secondary frequency regulation capacity of the AGC unit; ΔP agc,i For unit i, the secondary frequency regulation capability; N agc This represents the total number of AGC units. This is the secondary frequency modulation allocation coefficient. This is the sum of the secondary frequency regulation allocation coefficients for each generating unit; This represents the change in tie line power. B is the frequency deviation; B is the regional frequency control coefficient. and These are the control parameters for the secondary frequency modulation mode; This is a correction amount under the constraints of climbing rate and adjustment range.

[0036] Preferably, determining the reserve resource margin based on the ramp capacity includes:

[0037] ,

[0038] ,

[0039] Among them, M res Reserve resource margin; ΔP res Reserve capacity; ΔP w For online anticipated fluctuation power; ΔP ct Active power provided to activate backup measures; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc This refers to the secondary frequency regulation capacity of the AGC unit.

[0040] Preferably, the determination of disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin includes:

[0041] ,

[0042] ,

[0043] ,

[0044] ,

[0045] ,

[0046] in, To enhance disturbance rejection capability; and These are the weighting coefficients for the system's rotational inertia margin and tolerable disturbance margin, respectively. and They are respectively and k-th power; and These represent the current system rotational inertia margin M, respectively. H and the tolerance margin M PQuantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MH, the series variables and functions correspond to the system's moment of inertia margin; when mag=MP, the series variables and functions correspond to the permissible disturbance margin.

[0047] Preferably, determining the frequency regulation capability based on the frequency modulation resource margin, ramping resource margin, and reserve resource margin includes:

[0048] ,

[0049] ,

[0050] ,

[0051] ,

[0052] ,

[0053] ,

[0054] in, For frequency adjustment capability; , and These are the weighting coefficients for system frequency regulation margin, ramp-up margin, and reserve margin, respectively. , and These represent the current frequency modulation resource margin M respectively. fre Slope resource margin M ramp and reserve resource margin M res Quantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; Where is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MFRE, the series variables and functions correspond to the frequency modulation margin; when mag=MRAMP, the series variables and functions correspond to the ramp-up margin; when mag=MRES, the series variables and functions correspond to the reserve margin.

[0055] Preferably, the optimized control based on disturbance rejection capability and frequency regulation capability to ensure that the high-proportion renewable energy power system is in a safe and stable state includes:

[0056] When the disturbance rejection capability is less than or equal to the preset disturbance rejection capability warning threshold, optimized control is performed by optimizing the unit combination start-up mode, calling inertia resources and limiting disturbance power, and / or when the frequency regulation capability is less than or equal to the preset frequency regulation capability threshold, optimized control is performed by supplementing frequency regulation resources, optimizing ramping resources, dynamically adjusting reserve resources and suppressing power fluctuations, so as to ensure that the high proportion of new energy power system is in a safe and stable state.

[0057] According to another aspect of the present invention, a frequency security assessment system for a high-proportion renewable energy power system is provided, the system comprising:

[0058] The first margin calculation unit is used to calculate the system rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios, with the frequency margin index as a constraint.

[0059] The second margin calculation unit is used to calculate the frequency regulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios, with the frequency margin index as a constraint.

[0060] The disturbance rejection capability determination unit is used to determine the disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin.

[0061] The frequency regulation capability determination unit is used to determine the frequency regulation capability based on the frequency modulation resource margin, ramping resource margin, and reserve resource margin.

[0062] The control unit is used to perform optimized control based on disturbance rejection capability and frequency regulation capability, so as to ensure that the high proportion of new energy power system is in a safe and stable state.

[0063] Based on another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the steps in a frequency security assessment method for a high-proportion renewable energy power system.

[0064] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0065] The aforementioned computer-readable storage medium; and

[0066] One or more processors for executing a program in the computer-readable storage medium.

[0067] This invention provides a frequency security assessment method and system for high-proportion renewable energy power systems, comprising: calculating the system rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios, using frequency margin indicators as constraints; calculating the in-regulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios, using frequency margin indicators as constraints; determining the disturbance rejection capability based on the system rotational inertia margin and tolerable disturbance margin; determining the frequency regulation capability based on the in-regulation resource margin, ramping resource margin, and reserve resource margin; and performing optimized control based on the disturbance rejection capability and frequency regulation capability to ensure that the high-proportion renewable energy power system is in a safe and stable state. This invention elevates frequency security analysis from a traditional single indicator to a multi-dimensional panoramic perception of the security situation, automatically completing rolling calculations and updates, and achieving accurate quantification of frequency security margins; it enables online calculation of the system's disturbance rejection capability and frequency regulation capability, and rapidly assesses the current frequency security level of the power grid, achieving panoramic perception and early warning of frequency security. Attached Figure Description

[0068] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0069] Figure 1 This is a flowchart of a frequency security assessment method 100 for a high-proportion renewable energy power system according to an embodiment of the present invention;

[0070] Figure 2 This is a schematic diagram of the frequency response adjustment process according to an embodiment of the present invention;

[0071] Figure 3 This is a schematic diagram of the frequency response model of a large disturbance system according to an embodiment of the present invention;

[0072] Figure 4 This is a schematic diagram of a power grid frequency calculation model for a fluctuating scenario according to an embodiment of the present invention;

[0073] Figure 5 This is a schematic diagram of the frequency security assessment system 500 for a high-proportion renewable energy power system according to an embodiment of the present invention. Detailed Implementation

[0074] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0075] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0076] To adapt to the changing characteristics brought about by the integration of high-proportion renewable energy sources, this paper proposes a multi-dimensional index system hierarchical construction method to comprehensively assess the frequency security risks faced by the system, addressing the frequency security and stability issues of high-proportion renewable energy power systems. Specifically, this includes: 1) Constructing a basic layer of indicators based on existing frequency security indicators to quantitatively characterize the frequency security constraints of the power grid; 2) Differentiating between large disturbance fault scenarios and power fluctuation scenarios based on the dynamic process of frequency regulation, constructing scenario-level indicators that satisfy the basic layer frequency constraints, and refining the characterization of the causes of frequency risks; 3) Building upon the scenario-level indicators, constructing two dimensions: system anti-disturbance capability and system frequency regulation capability, to achieve multi-dimensional frequency risk assessment and early warning.

[0077] Figure 1 This is a flowchart of a frequency security assessment method 100 for a high-proportion renewable energy power system according to an embodiment of the present invention. Figure 1 As shown, the frequency security assessment method for high-proportion renewable energy power systems provided by this invention elevates frequency security analysis from a traditional single indicator to a multi-dimensional panoramic perception of the security situation, automatically completing rolling calculations and updates, and achieving accurate quantification of frequency security margin. It enables online calculation of the system's disturbance resistance and frequency regulation capabilities, and rapidly assesses the current frequency security level of the power grid, achieving panoramic perception and early warning of frequency security. The frequency security assessment method 100 for high-proportion renewable energy power systems provided by this invention begins at step 101. In step 101, using the frequency margin index as a constraint, it calculates the system's rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios.

[0078] Preferably, the calculation of the system's rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios, constrained by the frequency margin index, includes:

[0079] Determine the online anticipated disturbance power under large disturbance fault scenarios;

[0080] For the online anticipated disturbance power, simulation calculations are performed based on the frequency response model of the large disturbance system. During the simulation, other parameters are kept constant, and the equivalent inertia of the model is gradually reduced. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the inertial constant at this time is determined as the target inertial constant. The system rotational inertia margin is determined based on the target inertial constant.

[0081] Based on the online anticipated disturbance power, simulation calculations are performed using a frequency response model of a large disturbance system. During the simulation, other parameters are kept constant, and the disturbance power is gradually increased. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the disturbance power at this time is determined as the maximum disturbance power that the system can withstand. The tolerable disturbance margin is determined based on the maximum disturbance power that the system can withstand.

[0082] Preferably, determining the system's rotational inertia margin based on the target inertia constant includes:

[0083] ,

[0084] Among them, M H H represents the system's rotational inertia margin. sys H is the equivalent inertial constant of the system under the current operating mode; cri Let be the target inertial constant.

[0085] Preferably, determining the tolerable disturbance margin based on the maximum disturbance power the system can withstand includes:

[0086] ,

[0087] Among them, M P Tolerable disturbance margin; ΔP cri The maximum disturbance power that the system can withstand; ΔP d This represents the system's online anticipated disturbance power under the current operating mode.

[0088] In this invention, the computational data foundation mainly involves the state estimation E-format data of the dispatch automation basic platform standard, the .QS data file format generated by the online dispatch automation system, the .LF data file format of the PSASP software, and related strategy configuration data files. Specifically, the QS data from the online dispatch automation system mainly involves real-time operating data of various devices, including the grid structure under the current grid operating mode, power plant start-up status and generating power, transmission line operating status and power, and power system load data. The LF file data mainly involves the model parameters of various components and equipment, including unit type, governor parameters, maximum and minimum unit output, and equipment control parameters. The related strategy configuration data files mainly include the fault-corresponding security control strategy table and frequency defense action plan, including security control adjustment equipment, adjustment amount, action strategy, frequency defense action dead zone, action setpoint, adjustment equipment, and adjustment amount.

[0089] In this invention, based on the analysis of frequency dynamic response and adjustment process, a multi-dimensional frequency security index system is constructed, including the basic layer: power grid frequency security constraint index; the scenario layer: indexes related to frequency dynamic response under different scenarios; and the capability dimension layer: core system capability indexes.

[0090] (1) Basic layer: Power grid frequency security constraints

[0091] Based on the concepts of initial frequency, rate of change of frequency, maximum frequency change, minimum frequency change, and steady-state frequency in the frequency response curve, indicators such as transient frequency margin, steady-state frequency margin, and rate of change of frequency margin are constructed to convert the frequency concept into a safety margin constraint, as shown in Table 1.

[0092] Table 1 Basic Layer Indicators

[0093] index meaning Transient frequency margin During a transient process where the frequency increases or decreases, the safe distance between the transient frequency and the threshold for the action of safety control measures is defined as the safety margin of the transient frequency. steady-state frequency margin After a transient process of frequency increase or decrease, when the frequency reaches a new steady-state frequency, the distance between the frequency and the maximum frequency deviation allowed for system operation is defined as the safety margin of the steady-state frequency. Frequency change margin The distance between the maximum rate of frequency change and the limit of the rate of frequency change allowed for system operation during frequency change is defined as the rate of frequency change margin.

[0094] 1) Transient frequency margin index

[0095] For situations where a fault causes a rise in system frequency, such as the sending-end power grid after an inter-regional DC fault, the transient frequency margin index under the frequency rise scenario is defined as follows:

[0096] ,

[0097] In the formula, f0 represents the rated frequency. This indicates the setpoint for the high-frequency defense line action. This represents the maximum value of the transient frequency during the frequency response process.

[0098] For situations where a fault causes a decrease in system frequency, such as the receiving-end power grid after an inter-regional DC fault, the transient frequency margin index under the frequency decrease scenario is defined as follows:

[0099] ,

[0100] In the formula, f0 represents the rated frequency. This indicates the setpoint for low-frequency defense line action. This represents the lowest value of the transient frequency during the frequency response process.

[0101] 2) Steady-state frequency margin index

[0102] For situations where a fault causes a rise in system frequency, the steady-state frequency margin index under the frequency rise condition is defined as follows:

[0103] ,

[0104] In the formula, This represents the maximum upward frequency offset setpoint during system operation. This represents the steady-state frequency.

[0105] For situations where a fault causes a decrease in system frequency, the steady-state frequency margin index under the frequency decrease scenario is defined as follows:

[0106] ,

[0107] In the formula, This represents the maximum downward frequency offset setpoint for system operation. This represents the steady-state frequency.

[0108] 3) Frequency change rate margin index

[0109] For situations where a fault causes the system frequency to increase or decrease, the frequency change rate margin index is defined as follows:

[0110] ,

[0111] In the formula, This represents the maximum rate of change of frequency during the frequency response process, which generally occurs at the instant after a fault occurs. This indicates the limit on the rate of frequency change allowed by the system.

[0112] (2) Scene layer: includes indicators related to frequency dynamic response under different scenes.

[0113] Taking frequency reduction as an example, the system frequency response adjustment process is as follows: Figure 2As shown, for large disturbance scenarios such as DC blocking faults and unplanned generator outages, the system inertia response and primary frequency regulation response play a major supporting role in the frequency response process. For disturbance scenarios such as new energy sources and load power fluctuations, the primary and secondary frequency regulation stages play a major regulatory role in the system frequency regulation process. Taking the frequency reduction caused by a large disturbance as an example, the lower the rotational inertia level, the faster the frequency change rate, the smaller the transient minimum frequency value, and the weaker the system's disturbance resistance. The steady-state frequency is not affected by the magnitude of the rotational inertia; the stronger the primary frequency regulation capability, the smaller the steady-state frequency deviation after a large disturbance. For minute-level power fluctuations, the larger the ramp capacity, the faster the system regulation rate; the larger the reserve capacity, the larger the disturbance power that can be balanced, and the stronger the system regulation capability.

[0114] Based on the above analysis, indices related to frequency dynamic response under different scenarios are constructed. Specifically, as shown in Table 2, for large disturbance fault scenarios, the indices of anticipated disturbance power, system rotational inertia margin, and tolerable disturbance margin are used to quantitatively assess transient frequency risk and system anti-disturbance capability; for power fluctuation scenarios, the indices of anticipated fluctuation power, frequency regulation capacity margin, ramp-up capacity margin, and reserve capacity margin are constructed to quantitatively assess system frequency regulation capability.

[0115] Table 2 Scene Layer Indicators

[0116]

[0117] 1) Indicators for large disturbance fault scenarios

[0118] The system frequency response model is a classic method in the field of frequency analysis. To adapt it to frequency analysis under large disturbance fault scenarios in high-proportion renewable energy power systems, this scheme improves upon it. The frequency response model of the large disturbance system is as follows: Figure 3 As shown. The margin indicators involved in the large disturbance fault scenario are based on the boundary condition that the indicators of the basic layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) are greater than zero.

[0119] ① Online predicted disturbance power index

[0120] Defined as the active power loss caused by the anticipated disturbance, denoted as ΔP d The term ΔP refers to the active power imbalance that causes changes in system frequency. In practical engineering applications, anticipated disturbances mainly include DC blocking, DC commutation failure, power plant faults, low-voltage ride-through of new energy units, and AC transmission equipment faults. The active power loss after a fault is denoted as ΔP. d .

[0121] ② System rotational inertia margin index

[0122] The rotational inertia of a high-proportion renewable energy power system mainly includes the inertia of synchronous generators and the virtual synchronous inertia of renewable energy equipment, which can be expressed as follows:

[0123] ,

[0124] Among them, J SG J is the moment of inertia of the synchronous generator; VS This is virtual inertia.

[0125] The moment of inertia of the synchronous generator system, J SG The expression is as follows:

[0126] ,

[0127] In the formula, J SGi N is the moment of inertia of unit i. G ω0 is the number of synchronous generators in the system; S is the rated electrical angular velocity; Σ H represents the system's power generation capacity. sys S is the equivalent inertial constant of the system synchronizer; Ni H is the rated capacity of unit i; i τ is the inertial constant of unit i; i This indicates the operating status of unit i. When unit i is put into operation, τ represents the operating status of the unit. i =1, τ during shutdown i =0.

[0128] Virtual synchronization technology simulates the changes in electromagnetic power released or absorbed by a synchronous machine due to changes in rotor kinetic energy during system frequency variations. VS The expression is

[0129] ,

[0130] Where Ns is the number of virtual synchronous generators in the system, P Ni The rated power of the virtual synchronizer; H i It is the inertial constant.

[0131] In engineering applications, the equivalent inertial constant of a system is often used to characterize the system's moment of inertia. The expression for the equivalent inertial constant of the system under the current operating mode is:

[0132] ,

[0133] Based on this, regarding the anticipated disturbance ΔP dKeeping other conditions of the frequency response model of the large disturbance system unchanged, gradually decrease the equivalent inertia parameter of the model, and calculate the changes of the basic layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) indices of the monitored frequency response curve. When the margin of any one of the basic layer indices is 0 (while the other margins are still greater than or equal to zero), record the inertia constant at this time as H. cri .

[0134] The system rotational inertia margin is defined as the relative distance between the equivalent inertial constant of the system under the current operating mode and the inertial constant when the margin in the basic layer index is zero, as shown in the following formula:

[0135] .

[0136] ③ Tolerable disturbance margin index

[0137] The actual expected disturbance ΔP in the current mode d Based on this, the disturbance power is gradually increased while keeping the frequency response model parameters of the large disturbance system constant. The changes in the basic layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) indicators of the monitored frequency response curve are calculated. When the margin of any one of the basic layer indicators is 0 (while the other margins are still greater than or equal to zero), the disturbance power at this time is recorded as the maximum disturbance power that the system can withstand, denoted as ΔP. cri .

[0138] The tolerable disturbance margin is defined as the relative distance between the anticipated disturbance under the current operating mode and the maximum disturbance power that the system can withstand when the margin in the basic layer indicators is zero. The formula is as follows:

[0139] .

[0140] In step 102, using the frequency margin index as a constraint, the frequency modulation resource margin, ramping resource margin, and reserve resource margin are calculated under the power fluctuation scenario.

[0141] Preferably, the calculation of frequency regulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios, constrained by the frequency margin index, includes:

[0142] Determine the online expected power fluctuation in power fluctuation scenarios;

[0143] Simulation calculations are performed based on a power grid frequency calculation model for fluctuating scenarios, letting ΔP agc =0 and ΔP ct=0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limiting and unit output range, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the primary frequency regulation capacity; determine the frequency regulation resource margin based on the primary frequency regulation capacity;

[0144] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agc Let ΔP ct =0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limit and unit output range, consider the difference in ramp rate of different units in the secondary frequency regulation and the constraint of cross-sectional power limit, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any one of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the ramp capacity; determine the ramp resource margin based on the ramp capacity;

[0145] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agc According to the security control strategy table, ΔP is triggered based on the frequency deviation setpoint. ct The online anticipated power fluctuation is gradually increased, taking into account the primary frequency regulation dead zone, amplitude limit, and unit output range; the differences in ramp rate of different units in the secondary frequency regulation and the constraints of the cross-sectional power limit; and the safety control action. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitoring output frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the reserve capacity is determined; the reserve resource margin is determined based on the ramp capacity.

[0146] Preferably, determining the frequency modulation resource margin based on the primary frequency modulation capacity includes:

[0147] ,

[0148] ,

[0149] Among them, M fre For frequency modulation resource margin; ΔP fre This represents the primary frequency modulation capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP g, i represents the primary frequency regulation capacity of unit i; ΔPnew,i N represents the primary frequency regulation capacity of the new energy power station i; G N represents the total number of synchronous generator units under startup mode; S This represents the total number of new energy power stations under the start-up mode.

[0150] Preferably, determining the climbing resource margin based on the climbing capacity includes:

[0151] ,

[0152] ,

[0153] ,

[0154] Among them, M ramp For climbing resource margin; ΔP ramp For climbing capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc For the secondary frequency regulation capacity of the AGC unit; ΔP agc,i For unit i, the secondary frequency regulation capability; N agc This represents the total number of AGC units. This is the secondary frequency modulation allocation coefficient. This is the sum of the secondary frequency regulation allocation coefficients for each generating unit; This represents the change in tie line power. B is the frequency deviation; B is the regional frequency control coefficient. and These are the control parameters for the secondary frequency modulation mode; This is a correction amount under the constraints of climbing rate and adjustment range.

[0155] Preferably, determining the reserve resource margin based on the ramp capacity includes:

[0156] ,

[0157] ,

[0158] Among them, M res Reserve resource margin; ΔP res Reserve capacity; ΔP w For online anticipated fluctuation power; ΔP ct Active power provided to activate backup measures; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc This refers to the secondary frequency regulation capacity of the AGC unit.

[0159] 2) Power fluctuation scenario indicators

[0160] To adapt to frequency analysis under power fluctuation scenarios, a power grid frequency calculation model for fluctuation scenarios is proposed, such as... Figure 4 As shown. In power fluctuation scenarios, the margin indicators are defined with the basic layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) indicators being greater than zero as a boundary condition.

[0161] ① Online predicted fluctuation power index

[0162] By fusing time-stamped historical power system operation data and meteorological data, feature extraction and selection are performed on fluctuating power. Clustering results are obtained based on the K-Means++ method. The group to which the sample belongs at the current moment is determined by the distance between the real-time data sample and each cluster. The net load power fluctuation range under multiple confidence levels is determined based on the joint probability distribution, and the online expected fluctuating power ΔP is determined. w Its fluctuation pattern is defined as the slope disturbance power that varies on a minute-level time scale.

[0163] ② Frequency modulation resource margin

[0164] First, calculate the primary frequency modulation capacity under the current power-on mode, based on... Figure 4 The power grid frequency calculation model shown in the fluctuation scenario is given by ΔP. agc =0 and ΔP ct =0, gradually increase the fluctuation power ΔP w Considering the primary frequency regulation dead zone, amplitude limiting, and unit output range, the monitoring output frequency response curve is calculated using the formula f=(1-Δω)×f0. The changes in the basic layer indicators (transient frequency margin, steady-state frequency margin, and frequency change rate margin) are monitored. When the margin of any one of the basic layer indicators is 0 (while the other margins are still greater than or equal to zero), the primary frequency regulation capacity is calculated using the following formula.

[0165] ,

[0166] Based on this, the online anticipated fluctuation power ΔP w The primary frequency regulation capacity margin index is:

[0167] .

[0168] ③ Slope resource sufficiency

[0169] First, calculate the ramp-up capacity under the current boot mode, based on... Figure 4 The power grid frequency calculation model shown in the fluctuation scenario, ΔP agc Based on the real-time frequency deviation and the secondary frequency modulation strategy, let ΔP ct=0, gradually increase the fluctuation power ΔP w Considering the dead zone, amplitude limit, and unit output range of primary frequency regulation, and taking into account the differences in ramp rates of different units in secondary frequency regulation and the constraints of cross-sectional power limits, the monitoring output frequency response curve is calculated using the formula f=(1-Δω)×f0. The changes in the base layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) indicators are monitored. When the margin of any one of the base layer indicators is 0 (while the other margins are still greater than or equal to zero), the ramp capacity is calculated using the following formula:

[0170] ,

[0171] Where, ΔP agc The calculation formula is based on the real-time frequency deviation and the secondary frequency modulation strategy.

[0172] ,

[0173] Based on this, the online anticipated fluctuation power ΔP w The ramp capacity margin index is:

[0174] .

[0175] ④ Reserve resource margin

[0176] First, calculate the standby capacity under the current power-on mode, based on... Figure 4 The power grid frequency calculation model shown in the fluctuation scenario, ΔP agc Based on the real-time frequency deviation and the secondary frequency modulation strategy, ΔP is calculated. ct According to the security control strategy table, the fluctuation power ΔP is gradually increased based on the frequency deviation setpoint. w Considering the dead zone, amplitude limit, and unit output range of primary frequency regulation, the differences in ramp rate of different units in secondary frequency regulation, and the constraints of cross-sectional power limits, as well as the safety control actions, the monitoring output frequency response curve is calculated using the formula f=(1-Δω)×f0. The changes in the basic layer (transient frequency margin, steady-state frequency margin, and frequency change rate margin) indicators are monitored. When the margin of any one of the basic layer indicators is 0 (while the other margins are still greater than or equal to zero), the reserve capacity is calculated using the following formula:

[0177] ,

[0178] Based on this, the online anticipated fluctuation power ΔP w The reserve capacity margin index is:

[0179] .

[0180] In step 103, the disturbance rejection capability is determined based on the system's rotational inertia margin and tolerable disturbance margin.

[0181] Preferably, the determination of disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin includes:

[0182] ,

[0183] ,

[0184] ,

[0185] ,

[0186] ,

[0187] in, To enhance disturbance rejection capability; and These are the weighting coefficients for the system's rotational inertia margin and tolerable disturbance margin, respectively. and They are respectively and k-th power; and These represent the current system rotational inertia margin M, respectively. H and the tolerance margin M P Quantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MH, the series variables and functions correspond to the system's moment of inertia margin; when mag=MP, the series variables and functions correspond to the permissible disturbance margin.

[0188] In step 104, the frequency regulation capability is determined based on the frequency regulation resource margin, ramping resource margin, and reserve resource margin.

[0189] Preferably, determining the frequency regulation capability based on the frequency modulation resource margin, ramping resource margin, and reserve resource margin includes:

[0190] ,

[0191] ,

[0192] ,

[0193] ,

[0194] ,

[0195] ,

[0196] in, For frequency adjustment capability; , and These are the weighting coefficients for system frequency regulation margin, ramp-up margin, and reserve margin, respectively. , and These represent the current frequency modulation resource margin M respectively. fre Slope resource margin M ramp and reserve resource margin M res Quantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; Where is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MFRE, the series variables and functions correspond to the frequency modulation margin; when mag=MRAMP, the series variables and functions correspond to the ramp-up margin; when mag=MRES, the series variables and functions correspond to the reserve margin.

[0197] In this invention, for the capability layer, considering the transient response process after a large disturbance in the power system and the minute-level adjustment process under power fluctuations, the system frequency security can be summarized into two dimensions: disturbance resistance capability and frequency regulation capability, as shown in Table 3 below.

[0198] Table 3 Capability Level Indicators

[0199]

[0200] Based on this, disturbance rejection capability indicators and frequency regulation capability indicators are constructed. The core requirement of the indicators is that they should not only reflect the influence of the physical quantities related to the indicators, but also be able to characterize the dynamic changes in disturbance rejection capability and frequency regulation capability caused by changes in the power grid operation mode.

[0201] In this invention, the process of determining disturbance rejection capability includes:

[0202] 1) Historical data preparation

[0203] Calculate scenario-level margin indicators based on collected historical operational data (such as the past month, quarter, year, etc.) to form a dataset.

[0204] ①Scenarios with large disturbances:

[0205] Historical inertia margin: ;

[0206] Historical disturbance margin: .

[0207] ② Minute-level scenarios:

[0208] Historical FM resource margin ;

[0209] Historical climbing resource sufficiency ;

[0210] Historical reserve resource margin .

[0211] 2) Calculate the cumulative distribution function (CDF) using kernel density estimation.

[0212] Fit probability density functions (PDFs) to MH, MP, MFRE, MRAMP, and MRES respectively:

[0213] ,

[0214] Where K(⋅) is the Gaussian kernel function; h mag For bandwidth, optimization was verified using the Silverman criterion. .

[0215] The CDF is obtained by fitting the probability density function (PDF) and integrating the cumulative distribution function:

[0216] .

[0217] 3) Construction of Disturbance Resistance Indicators

[0218] For scenarios with large disturbances, the rotational inertia margin and the tolerable disturbance margin are indicators that measure the rate of change and the degree of deviation during the transient frequency change process. Their specific characteristics are shown in Table 4.

[0219] Table 4 Characteristics of Indicators in Large Disturbance Scenarios

[0220]

[0221] Rotational inertia margin and tolerable disturbance margin are two sides of the same coin in the process of frequency transient changes under large disturbance scenarios. In order to accurately reflect the nonlinear coupling relationship between inertia margin and disturbance margin, and to avoid the situation where a high value of one index is close to zero while the other index masks the system risk, the disturbance resistance index is defined as follows:

[0222] ,

[0223] in, and The weighting coefficients representing inertia margin and tolerable disturbance margin can be set according to the actual emphasis of different power grids. For power grids with a high proportion of renewable energy, the weighting coefficients can be increased. ,like =0.6 and =0.4. k is an introduced nonlinear correction factor. When k=2 (Euclidean distance form), lower index values ​​have a greater impact on the results. When k→∞, it becomes the "weakest link" method; when k=1, it degenerates into a linear weighted method. The value of k can be adjusted according to the actual operation, depending on the penetration rate of new energy sources. and The size is dynamically adjusted. and These represent the quantile values ​​for mapping the current moment of inertia margin and tolerable disturbance margin to the historical cumulative distribution function, respectively.

[0224] ,

[0225] The disturbance rejection capability is suggested to be divided into three states: good, average, and warning. The recommended execution thresholds are shown in Table 5.

[0226] Table 5 Classification of Disturbance Immunity

[0227]

[0228] In terms of constructing frequency regulation capability indicators, for power fluctuation scenarios, the indicators of frequency regulation resource margin, ramping resource margin, and reserve resource margin are all essentially indicators describing the strength of the power system's ability to achieve power balance and are highly correlated. However, they differ in the time scale and core role of maintaining power system frequency stability, as shown in Table 6.

[0229] Table 6 Characteristics of Minute-Level Indicators

[0230]

[0231] Therefore, considering the synergistic effect among indicators, a comprehensive index is constructed using a geometric weighted average, and the calculation formula for the frequency regulation capability index is defined as follows:

[0232] ,

[0233] Where a1, a2, and a3 represent the weighting coefficients of frequency regulation resource margin, ramping resource margin, and reserve resource margin, respectively. The weighting of the contribution of each power grid indicator to frequency regulation capability can be determined based on expert experience or historical data statistics (e.g., a1=0.4, a2=0.3, a3=0.3). , and Each represents the current M fre M ramp M res Quantile values ​​mapped to the historical cumulative distribution function:

[0234] ,

[0235] The advantage of the frequency adjustment capability index is that when any scene layer index is close to zero, A adj A significant decrease can reflect the bottleneck effect; on the other hand, the proportion of new energy access in different power grids is not the same, and the weighting coefficient can be dynamically adjusted to adapt the indicator to different power grids. For example, power grids with a high proportion of new energy use a larger value of a2, which has greater adaptability.

[0236] Frequency regulation capability is recommended to be divided into three states: good, average, and warning. The recommended execution thresholds are shown in Table 7.

[0237] Table 7 Frequency Adjustment Capability Classification

[0238]

[0239] In step 105, optimized control is performed based on disturbance rejection capability and frequency regulation capability to ensure that the high proportion of new energy power system is in a safe and stable state.

[0240] Preferably, the optimized control based on disturbance rejection capability and frequency regulation capability to ensure that the high-proportion renewable energy power system is in a safe and stable state includes:

[0241] When the disturbance rejection capability is less than or equal to the preset disturbance rejection capability warning threshold, optimized control is performed by optimizing the unit combination start-up mode, calling inertia resources and limiting disturbance power, and / or when the frequency regulation capability is less than or equal to the preset frequency regulation capability threshold, optimized control is performed by supplementing frequency regulation resources, optimizing ramping resources, dynamically adjusting reserve resources and suppressing power fluctuations, so as to ensure that the high proportion of new energy power system is in a safe and stable state.

[0242] In this invention, the optimized control strategy for operation mode during indicator early warning includes:

[0243] 1) Early warning of disturbance resistance

[0244] When the system's disturbance rejection capability index A anti When the system is in a warning state, it indicates that its ability to withstand disturbances under large disturbance scenarios is lower than its historical operating level. The following adjustment measures can be taken based on the scenario-level indicator results:

[0245] ①Optimize the unit combination start-up method: give priority to keeping the high-inertia synchronous generator set in operation, while improving the system's primary frequency regulation capability;

[0246] ② Inertia resource allocation: Start the virtual synchronous machine control to switch the new energy power station from maximum power point tracking mode to virtual inertia mode;

[0247] ③ Disturbance power limitation: Implement power limitation on key transmission sections to avoid excessive power deficit caused by a single fault.

[0248] 2) Frequency regulation capability early warning

[0249] When the system frequency regulation capability index A adj When the system is in an early warning state, it indicates that the system's frequency adjustment capability under minute-level fluctuation scenarios is lower than the historical operating level. The following adjustment measures can be taken in conjunction with scenario-level indicators:

[0250] ① FM resource supplementation

[0251] Optimize the unit combination start-up method to improve frequency regulation response capability;

[0252] Activate the rapid frequency regulation function of new energy power plants and energy storage systems to supplement primary frequency regulation capacity;

[0253] ②Optimization of climbing resources

[0254] Optimize the composition of the AGC control unit to improve the adjustment rate;

[0255] Coordinate cross-regional AGC resources to form regional mutual assistance and increase the capacity of climbing resources;

[0256] ③ Dynamic adjustment of reserve resources

[0257] Conduct sensitivity analysis of regulation resources, optimize the geographical distribution of backup resources, and reduce the impact of transmission constraints;

[0258] Increase the hot standby ratio of fast-start units;

[0259] ④ Power fluctuation suppression

[0260] Implement maximum ramp rate limits for new energy power to smooth out power fluctuations;

[0261] Activate load-side response resources to balance power deficits.

[0262] The method of this invention can be applied to national, regional, and provincial control centers. For power grids with a high proportion of renewable energy, this method can realize online calculation of the system's disturbance rejection capability and frequency regulation capability, and quickly assess the current frequency security level of the power grid, achieving panoramic perception and early warning of frequency security. It can be installed and deployed as long as standard state estimation E-format data and the basic platform environment of a smart grid dispatch and control system are available.

[0263] Figure 5 This is a schematic diagram of the frequency security assessment system 500 for a high-proportion renewable energy power system according to an embodiment of the present invention. Figure 5As shown, the frequency security assessment system 500 for a high proportion of new energy power system provided in this embodiment of the invention includes: a first margin calculation unit 501, a second margin calculation unit 502, an anti-disturbance capability determination unit 503, a frequency regulation capability determination unit 504, and a control unit 505.

[0264] Preferably, the first margin calculation unit 501 is used to calculate the system rotational inertia margin and the tolerable disturbance margin under a large disturbance fault scenario, with the frequency margin index as a constraint.

[0265] Preferably, the first margin calculation unit 501, constrained by the frequency margin index, calculates the system rotational inertia margin and tolerable disturbance margin under large disturbance fault scenarios, including:

[0266] Determine the online anticipated disturbance power under large disturbance fault scenarios;

[0267] For the online anticipated disturbance power, simulation calculations are performed based on the frequency response model of the large disturbance system. During the simulation, other parameters are kept constant, and the equivalent inertia of the model is gradually reduced. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the inertial constant at this time is determined as the target inertial constant. The system rotational inertia margin is determined based on the target inertial constant.

[0268] Based on the online anticipated disturbance power, simulation calculations are performed using a frequency response model of a large disturbance system. During the simulation, other parameters are kept constant, and the disturbance power is gradually increased. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the disturbance power at this time is determined as the maximum disturbance power that the system can withstand. The tolerable disturbance margin is determined based on the maximum disturbance power that the system can withstand.

[0269] Preferably, the first margin calculation unit 501 determines the system rotational inertia margin based on the target inertia constant, including:

[0270] ,

[0271] Among them, M H H represents the system's rotational inertia margin. sys H is the equivalent inertial constant of the system under the current operating mode; cri Let be the target inertial constant.

[0272] Preferably, the first margin calculation unit 501 determines the tolerable disturbance margin based on the maximum disturbance power that the system can withstand, including:

[0273] ,

[0274] Among them, M P Tolerable disturbance margin; ΔP cri The maximum disturbance power that the system can withstand; ΔP d This represents the system's online anticipated disturbance power under the current operating mode.

[0275] Preferably, the second margin calculation unit 502 is used to calculate the frequency modulation resource margin, ramping resource margin and reserve resource margin under the power fluctuation scenario, with the frequency margin index as a constraint.

[0276] Preferably, the second margin calculation unit 502, constrained by the frequency margin index, calculates the frequency modulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios, including:

[0277] Determine the online expected power fluctuation in power fluctuation scenarios;

[0278] Simulation calculations are performed based on a power grid frequency calculation model for fluctuating scenarios, letting ΔP agc =0 and ΔP ct =0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limiting and unit output range, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the primary frequency regulation capacity; determine the frequency regulation resource margin based on the primary frequency regulation capacity;

[0279] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agc Let ΔP ct =0, gradually increase the online expected fluctuation power, consider the primary frequency regulation dead zone, amplitude limit and unit output range, consider the difference in ramp rate of different units in the secondary frequency regulation and the constraint of cross-sectional power limit, calculate the changes in transient frequency margin, steady-state frequency margin and frequency change rate margin of the monitoring output frequency response curve, when any one of the transient frequency margin, steady-state frequency margin and frequency change rate margin is less than or equal to 0, determine the ramp capacity; determine the ramp resource margin based on the ramp capacity;

[0280] Simulation calculations are performed based on a power grid frequency calculation model under fluctuating scenarios, and ΔP is calculated according to the real-time frequency deviation and the secondary frequency regulation strategy. agcAccording to the security control strategy table, ΔP is triggered based on the frequency deviation setpoint. ct The online anticipated power fluctuation is gradually increased, taking into account the primary frequency regulation dead zone, amplitude limit, and unit output range; the differences in ramp rate of different units in the secondary frequency regulation and the constraints of the cross-sectional power limit; and the safety control action. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitoring output frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the reserve capacity is determined; the reserve resource margin is determined based on the ramp capacity.

[0281] Preferably, the second margin calculation unit 502 determines the frequency modulation resource margin based on the primary frequency modulation capacity, including:

[0282] ,

[0283] ,

[0284] Among them, M fre For frequency modulation resource margin; ΔP fre This represents the primary frequency modulation capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP g, i represents the primary frequency regulation capacity of unit i; ΔP new,i N represents the primary frequency regulation capacity of the new energy power station i; G N represents the total number of synchronous generator units under startup mode; S This represents the total number of new energy power stations under the start-up mode.

[0285] Preferably, the second margin calculation unit 502 determines the climbing resource margin based on the climbing capacity, including:

[0286] ,

[0287] ,

[0288] ,

[0289] Among them, M ramp For climbing resource margin; ΔP ramp For climbing capacity; ΔP w For online anticipated fluctuation power; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc For the secondary frequency regulation capacity of the AGC unit; ΔP agc,iFor unit i, the secondary frequency regulation capability; N agc This represents the total number of AGC units. This is the secondary frequency modulation allocation coefficient. This is the sum of the secondary frequency regulation allocation coefficients for each generating unit; This represents the change in tie line power. B is the frequency deviation; B is the regional frequency control coefficient. and These are the control parameters for the secondary frequency modulation mode; This is a correction amount under the constraints of climbing rate and adjustment range.

[0290] Preferably, the second margin calculation unit 502 determines the reserve resource margin based on the ramp capacity, including:

[0291] ,

[0292] ,

[0293] Among them, M res Reserve resource margin; ΔP res Reserve capacity; ΔP w For online anticipated fluctuation power; ΔP ct Active power provided to activate backup measures; ΔP g ΔP is the primary frequency modulation capacity of the synchronous machine. new For the primary frequency regulation capacity of new energy power plants; ΔP agc This refers to the secondary frequency regulation capacity of the AGC unit.

[0294] Preferably, the disturbance rejection capability determination unit 503 is used to determine the disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin.

[0295] Preferably, the disturbance rejection capability determination unit 503 determines the disturbance rejection capability based on the system's rotational inertia margin and tolerable disturbance margin, including:

[0296] ,

[0297] ,

[0298] ,

[0299] ,

[0300] ,

[0301] in, To enhance disturbance rejection capability; and These are the weighting coefficients for the system's rotational inertia margin and tolerable disturbance margin, respectively. and They are respectively and k-th power; and These represent the current system rotational inertia margin M, respectively. H and the tolerance margin M P Quantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MH, the series variables and functions correspond to the system's moment of inertia margin; when mag=MP, the series variables and functions correspond to the permissible disturbance margin.

[0302] Preferably, the frequency regulation capability determination unit 504 is used to determine the frequency regulation capability based on the frequency regulation resource margin, ramping resource margin, and reserve resource margin.

[0303] Preferably, the frequency regulation capability determination unit 504 determines the frequency regulation capability based on the frequency modulation resource margin, ramping resource margin, and reserve resource margin, including:

[0304] ,

[0305] ,

[0306] ,

[0307] ,

[0308] ,

[0309] ,

[0310] in, For frequency adjustment capability; , and These are the weighting coefficients for system frequency regulation margin, ramp-up margin, and reserve margin, respectively. , and These represent the current frequency modulation resource margin M respectively. fre Slope resource margin M ramp and reserve resource margin M res Quantile values ​​mapped to the historical cumulative distribution function; It is the cumulative distribution function; It is the probability density function; Where is the bandwidth; n is the sample size; K() is the Gaussian kernel function; when mag=MFRE, the series variables and functions correspond to the frequency modulation margin; when mag=MRAMP, the series variables and functions correspond to the ramp-up margin; when mag=MRES, the series variables and functions correspond to the reserve margin.

[0311] Preferably, the control unit 505 is used to perform optimized control based on anti-disturbance capability and frequency regulation capability, so as to ensure that the high proportion of new energy power system is in a safe and stable state.

[0312] Preferably, the control unit 505 performs optimized control based on disturbance rejection capability and frequency regulation capability to ensure that the high-proportion renewable energy power system is in a safe and stable state, including:

[0313] When the disturbance rejection capability is less than or equal to the preset disturbance rejection capability warning threshold, optimized control is performed by optimizing the unit combination start-up mode, calling inertia resources and limiting disturbance power, and / or when the frequency regulation capability is less than or equal to the preset frequency regulation capability threshold, optimized control is performed by supplementing frequency regulation resources, optimizing ramping resources, dynamically adjusting reserve resources and suppressing power fluctuations, so as to ensure that the high proportion of new energy power system is in a safe and stable state.

[0314] The safety assessment system 500 for a proportional new energy power system in an embodiment of the present invention corresponds to the safety assessment method 100 for a proportional new energy power system in another embodiment of the present invention, and will not be described again here.

[0315] Based on another aspect of the present invention, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the steps in a method for safety assessment of a proportional new energy power system.

[0316] According to another aspect of the present invention, the present invention provides an electronic device, comprising:

[0317] The aforementioned computer-readable storage medium; and

[0318] One or more processors for executing a program in the computer-readable storage medium.

[0319] The present invention has been described with reference to a few embodiments. However, it will be apparent to those skilled in the art that other embodiments besides those disclosed above fall equivalently within the scope of the present invention.

[0320] Generally, all terms used in this invention are interpreted according to their ordinary meaning in the art, unless otherwise expressly defined herein. All references to “a / the / the [device, component, etc.]” ​​are openly interpreted as at least one instance of said device, component, etc., unless otherwise expressly stated. The steps of any method disclosed herein need not be performed in the exact order disclosed unless explicitly stated otherwise.

[0321] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0322] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0323] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0324] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0325] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. A frequency security assessment method for a high-proportion new energy power system, characterized in that, The method includes: Using the frequency margin index as a constraint, the system rotational inertia margin and tolerable disturbance margin are calculated under large disturbance fault scenarios. Using frequency margin as a constraint, calculate the frequency modulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios; Based on the system's rotational inertia margin and tolerable disturbance margin, the disturbance rejection capability is determined; Based on the aforementioned frequency regulation resource margin, ramping resource margin, and reserve resource margin, the frequency regulation capability is determined; Optimized control is implemented based on disturbance rejection capability and frequency regulation capability to ensure that the high proportion of new energy power system is in a safe and stable state. The disturbance rejection capability is determined based on the system's rotational inertia margin and tolerable disturbance margin, including: ， ， ， ， ， wherein, is the disturbance rejection capability; and are the weight coefficients of the system moment of inertia margin and the disturbance tolerance margin, respectively; and are the and are the k power; and respectively represent mapping the current system moment of inertia margin M H and the disturbance tolerance margin M P to quantile values of the historical cumulative distribution function; is the cumulative distribution function; is the probability density function; is the bandwidth; n is the sample size; K () is the Gaussian kernel function; mag= MH is the time series variable corresponding to the function of the system moment of inertia margin, mag= MP is the time series variable corresponding to the function of the disturbance tolerance margin; Among them, the system's rotational inertia margin and tolerable disturbance margin are calculated under large disturbance fault scenarios, using the frequency margin index as a constraint, including: Determine the online expected disturbance power under large disturbance fault scenarios; For the online anticipated disturbance power, simulation calculations are performed based on the frequency response model of the large disturbance system. During the simulation, other parameters are kept constant, and the equivalent inertia of the model is gradually reduced. The changes in transient frequency margin, steady-state frequency margin, and frequency change rate margin of the monitored frequency response curve are calculated. When any one of the transient frequency margin, steady-state frequency margin, and frequency change rate margin is less than or equal to 0, the inertial constant at this time is determined as the target inertial constant. The system rotational inertia margin is determined based on the target inertial constant. Based on the online anticipated disturbance power, simulation calculations are performed using a frequency response model of a large disturbance system. During the simulation, other parameters remain constant, and the disturbance power is gradually increased. The changes in transient frequency margin, steady-state frequency margin, and rate of change margin of the monitored frequency response curve are calculated. When any one of these margins is less than or equal to 0, the disturbance power at that moment is determined as the maximum disturbance power the system can withstand. Based on this maximum disturbance power, the tolerable disturbance margin is determined. The determination of the system's rotational inertia margin based on the target inertial constant includes: ， wherein, M H is the system rotational inertia margin; H sys is the equivalent inertia constant of the system under the current operating mode; H cri is the target inertia constant; The determination of the tolerable disturbance margin based on the maximum disturbance power that the system can withstand includes: ， wherein, M P is the disturbance margin that the system can withstand; Δ P cri is the maximum disturbance power that the system can withstand; Δ P d is the online predicted disturbance power of the system under the current operating mode.

2. The method of claim 1, wherein, Using frequency margin as a constraint, the following calculations are performed on frequency regulation resource margin, ramping resource margin, and reserve resource margin under power fluctuation scenarios: Determine the online expected power fluctuation in power fluctuation scenarios; Simulation calculation is performed based on a fluctuation scenario power grid frequency calculation model, Δ P agc =0 and Δ P ct =0, gradually increase the online expected fluctuation power, consider the primary frequency modulation dead zone, amplitude limiting and unit output range, calculate the change of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin of the monitoring output frequency response curve, and when any one of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin is less than or equal to 0, determine the primary frequency modulation capacity; determine the frequency modulation resource margin based on the primary frequency modulation capacity; Based on the simulation calculation of the fluctuation scenario power grid frequency calculation model, Δ P agc is calculated according to the real-time frequency deviation and the secondary frequency modulation strategy P ct =0, the online expected fluctuation power is gradually increased, the primary frequency modulation dead zone, the amplitude limiting and the unit output range are considered, the difference in the ramp rate of different units in the secondary frequency modulation and the constraint of the section power limit are considered, the change of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin of the monitoring output frequency response curve is calculated, when any one of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin is less than or equal to 0, the ramping capacity is determined; and the ramping resource margin is determined based on the ramping capacity. Based on the fluctuation scenario power grid frequency calculation model for simulation calculation, according to real-time frequency deviation and secondary frequency modulation strategy calculation Δ P agc , according to the frequency deviation of the control strategy table according to the frequency deviation of the trigger Δ P ct , gradually increase the online expected fluctuation power, consider the primary frequency modulation dead zone, amplitude limiting and unit output range, consider the difference of the climbing rate of different units of the secondary frequency modulation and the constraint of the section power limit, consider the security control action, calculate the change of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin of the monitoring output frequency response curve, when any one of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin is less than or equal to 0, determine the standby capacity; determine the standby resource margin based on the climbing capacity.

3. The method of claim 2, wherein, Determining the frequency modulation resource margin based on the primary frequency modulation capacity includes: ， ， in, M fre For frequency modulation resource margin; Δ P fre This is the primary frequency modulation capacity; Δ P w For online anticipated fluctuation power; Δ P g The primary frequency regulation capacity of the synchronous machine; Δ P new For the primary frequency regulation capacity of new energy power plants; Δ P g, i For the unit i The primary frequency modulation capacity; Δ P new,i For new energy power stations i The primary frequency modulation capacity; N G This represents the total number of synchronous generator units under the start-up mode. N S This represents the total number of new energy power stations under the start-up mode.

4. The method of claim 2, wherein, Determining the ramp resource margin based on the ramp capacity includes: ， ， ， wherein, M ramp is the ramping resource margin; Δ P ramp is the ramping capacity; Δ P w is the online expected fluctuation power; Δ P g is the primary frequency modulation capacity of the synchronous machine; Δ P new is the primary frequency modulation capacity of the new energy station; Δ P agc is the secondary frequency modulation capacity of the AGC unit; Δ P agc,i is the secondary frequency modulation capacity of the unit i ; N agc is the total number of AGC units; is the secondary frequency modulation distribution coefficient, is the sum of the secondary frequency modulation distribution coefficients of each unit; is the power change amount of the tie line; is the frequency deviation; B is the regional frequency control coefficient; is the frequency deviation; is the secondary frequency modulation mode control parameter; is the correction amount under the ramping rate and adjustment range constraint.

5. The method of claim 2, wherein, Determining the reserve resource margin based on the ramp capacity includes: ， ， wherein, M res is the reserve resource margin; Δ P res is the reserve capacity; Δ P w is the online expected fluctuation power; Δ P ct is the active power provided for enabling the reserve measure; Δ P g is the primary frequency modulation capacity of the synchronous machine; Δ P new is the primary frequency modulation capacity of the new energy station; Δ P agc is the secondary frequency modulation capacity of the AGC unit.

6. The method of claim 1, wherein, Based on the aforementioned frequency regulation resource margin, ramping resource margin, and reserve resource margin, the frequency regulation capability is determined, including: ， ， ， ， ， ， wherein, is the frequency regulation capability; , and are the weight coefficients of the system frequency regulation margin, ramping margin and reserve margin, respectively; , and represent the quantile values of the current frequency regulation resource margin M fre , ramping resource margin M ramp and reserve resource margin M res mapped to the historical cumulative distribution function, respectively; is the cumulative distribution function; is the probability density function; is the bandwidth; n is the sample size; K () is the Gaussian kernel function; mag= MFRE is the time series variable corresponding to the frequency regulation margin of the function, mag= MRAMP is the time series variable corresponding to the ramping margin of the function, and mag= MRES is the time series variable corresponding to the reserve margin of the function.

7. The method of claim 1, wherein, The optimized control based on disturbance rejection capability and frequency regulation capability, to ensure that the high-proportion renewable energy power system is in a safe and stable state, includes: When the anti-disturbance capability is less than or equal to a preset anti-disturbance capability early warning threshold, optimization control is performed in a manner of optimizing unit commitment start mode, calling inertia resources and performing disturbance power limitation, and / or when the frequency regulation capability is less than or equal to a preset frequency regulation capability threshold, optimization control is performed in a manner of frequency regulation resource supplement, climbing resource optimization, standby resource dynamic adjustment and power fluctuation suppression, so that the high-proportion new energy power system is in a safe and stable state. 8.A frequency security assessment system for a high-proportion new energy power system, characterized in that, The system comprises: A first margin calculation unit configured to calculate system inertia margin and bearable disturbance margin under a large disturbance failure scenario with a frequency margin index as a constraint; A second margin calculation unit configured to calculate frequency regulation resource margin, climbing resource margin and standby resource margin under a power fluctuation scenario with the frequency margin index as a constraint; An anti-disturbance capability determination unit configured to determine the anti-disturbance capability based on the system inertia margin and the bearable disturbance margin; A frequency regulation capability determination unit configured to determine the frequency regulation capability based on the frequency regulation resource margin, the climbing resource margin and the standby resource margin; A control unit configured to perform optimization control based on the anti-disturbance capability and the frequency regulation capability, so that the high-proportion new energy power system is in a safe and stable state; The anti-disturbance capability determination unit determines the anti-disturbance capability based on the system inertia margin and the bearable disturbance margin, and comprises: ， ， ， ， ， wherein, is the disturbance rejection capability; and are the weight coefficients of the system moment of inertia margin and the disturbance rejection margin, respectively; and are the and are the k power of and respectively represent the mapping of the current system moment of inertia margin M H and the disturbance rejection margin M P to the quantile values of the historical cumulative distribution function; is the cumulative distribution function; is the probability density function; is the bandwidth; n is the sample size; K is the Gaussian kernel function; mag= MH is the time series variable corresponding to the function of the system moment of inertia margin, mag= MP is the time series variable corresponding to the function of the disturbance rejection margin; The first margin calculation unit calculates the system inertia margin and the bearable disturbance margin under the large disturbance failure scenario with the frequency margin index as a constraint, and comprises: Determining online expected disturbance power under the large disturbance failure scenario; Based on the online expected disturbance power, simulation calculation is performed based on a large disturbance system frequency response model, other parameters are kept unchanged in the simulation process, the equivalent inertia of the model is gradually reduced, and the change of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin of the monitored frequency response curve is calculated. When any one of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin is less than or equal to 0, the inertia constant at this time is determined as the target inertia constant; the system inertia margin is determined based on the target inertia constant; Based on the online expected disturbance power, simulation calculation is performed based on a large disturbance system frequency response model, other parameters are kept unchanged in the simulation process, the equivalent inertia of the model is gradually reduced, and the change of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin of the monitored frequency response curve is calculated. When any one of the transient frequency margin, the steady-state frequency margin and the frequency change rate margin is less than or equal to 0, the inertia constant at this time is determined as the target inertia constant; the system inertia margin is determined based on the target inertia constant; The first margin calculation unit determines the system inertia margin based on the target inertia constant, and comprises: ， wherein, M H is the system rotational inertia margin; H sys is the equivalent inertia constant of the system under the current operating mode; H cri is the target inertia constant; The first margin calculation unit determines the bearable disturbance margin based on the system bearable maximum disturbance power, and comprises: ， wherein, M P is the disturbance margin that the system can withstand; Δ P cri is the maximum disturbance power that the system can withstand; Δ P d is the online predicted disturbance power of the system under the current operating mode.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps of the method of any one of claims 1-7. The program is executed by the processor to realize the steps of the method of any one of claims 1-7.

10. An electronic device, comprising: comprising: the computer readable storage medium recited in claim 9; and one or more processors for executing a program in the computer readable storage medium.

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