Power system frequency response prediction method and system

Abstract

The invention discloses a power system frequency response prediction method and system, and relates to the technical field of power system frequency response prediction, and the method comprises the steps: carrying out the statistics of the output proportion and key parameters of each type of unit, and constructing a power system frequency response model; analyzing the load frequency response supporting capability of the power system; the load frequency supporting capacity is refined, and the power system frequency response model is optimized. The method improves the understanding of the dynamic behavior of the power system, lays a foundation for the subsequent analysis and optimization of the load frequency response supporting capability, promotes the stability and safety of the power system, enables the power system to recover the stable state more quickly when the frequency fluctuation occurs, reduces the power failure risk, and improves the reliability of the power system. The reliability and flexibility of the whole system are improved, unnecessary loss caused by frequency fluctuation is effectively reduced, it is ensured that the electric power system can operate more efficiently, the requirement for continuous increasing of renewable energy sources is met, and sustainable development is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power system frequency response prediction, and in particular to a power system frequency response prediction method and system. Background Art

[0002] In recent years, the global power system has undergone changes with the large-scale access of renewable energy and the continuous deepening of the power market. The frequency response capability of the power system, as an important indicator of power system stability, has received widespread attention from academia and industry. With the gradual increase in the proportion of unstable power generation sources such as wind power and solar energy, the power system is facing the challenge of intensified frequency fluctuations. How to effectively predict and manage frequency response has become a key issue. Traditional frequency response models are often based on static analysis methods and fail to fully consider the impact of dynamic load changes and various unit output mechanisms on frequency response. Therefore, constructing a frequency response model that can integrate the output ratios and key parameters of various units and can reflect the system load characteristics in real time is of great significance to maintaining the stability of the power system.

[0003] However, the existing power system frequency response prediction technology has some shortcomings. Most traditional methods use static models and cannot effectively capture the frequency response characteristics under rapid load changes and renewable energy fluctuations. When dealing with the output ratios of different types of units, the existing technology often fails to achieve highly refined dynamic analysis, resulting in insufficient accuracy and timeliness of model predictions. The existing technology also lacks in-depth analysis of the power system load frequency response support capacity, and fails to fully consider the impact of various load types on frequency and its changing trends, resulting in these technologies being unable to adapt to the complex operating environment of modern power systems, limiting the actual application effect of frequency response models. In contrast, the present invention constructs a dynamic frequency response model through refined data analysis, which can effectively optimize the power system frequency response based on considering multiple unit characteristics and load changes, so that the power system can maintain higher stability and reliability when facing dynamic loads and renewable energy challenges, thereby achieving high-quality and economical power supply. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: the existing power system frequency response prediction technology has a static model that cannot cope with dynamic changes, lacks the ability to carefully handle the unit output, fails to comprehensively analyze the load frequency response support capability, and how to achieve accurate prediction of frequency response in complex power systems.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a method for predicting the frequency response of a power system, comprising statistically analyzing the output ratios and key parameters of various types of units to construct a power system frequency response model; analyzing the load frequency response support capacity of the power system; refining the load frequency support capacity and optimizing the power system frequency response model.

[0007] As a preferred solution of the power system frequency response prediction method described in the present invention, the statistics of the output proportion and key parameters of each type of unit include statistics of the output proportion and unit parameters of steam turbines, water turbines and new energy units controlled by the grid.

[0008] The primary frequency regulation response characteristics of thermal power units are analyzed and expressed as:

[0009]

[0010] Among them, ΔP R (s) is the output power change of the non-reheat steam turbine, F H is the high pressure turbine coefficient, T R is the reheater time constant, T G1 is the time constant of the reheat turbine governor, R 1 is the regulation coefficient of the reheat turbine governor, Δω(s) is the Laplace transform representation of the system frequency change, and s is the complex frequency domain variable in the Laplace transform.

[0011] The primary frequency regulation response characteristics of the turbine unit are analyzed and expressed as:

[0012]

[0013] Among them, ΔP H (s) is the change in turbine output power, T RT is the reset time constant of the turbine, R P is the permanent decline rate, R T is the temporary drop rate, T w is the time constant of water hammer effect, T G2 is the time constant of the turbine governor, K H is the regulation coefficient of the turbine governor.

[0014] Analyze the frequency support capability of the new energy generator network, including simulated inertia and primary frequency regulation capability, expressed as:

[0015]

[0016] Among them, ΔP N is the output power change of the new energy unit, H N To simulate the inertia time constant, R N and TN They respectively represent the governor droop coefficient and governor time constant of the grid-connected new energy unit, and Δω is the system frequency change.

[0017] As a preferred solution of the power system frequency response prediction method described in the present invention, the power system frequency response model is constructed by characterizing the overall frequency response of the system based on the inertia of the inertia center, and the inertia time constant and damping coefficient of the inertia center are calculated by the weighted average method, which is expressed as:

[0018]

[0019] Among them, S i is the rated capacity of the i-th unit, H i is the inertia time constant of the i-th unit, D i is the damping coefficient of the i-th unit, and n is the total number of units participating in frequency regulation.

[0020] Calculate the adjustment coefficient, expressed as:

[0021]

[0022] Among them, R i is the regulation coefficient of the i-th unit.

[0023] A power system frequency response model is established based on the output and proportion of various types of units in the power system.

[0024] As a preferred solution of the power system frequency response prediction method described in the present invention, wherein: the analysis of the power system load frequency response support capacity includes calculating the frequency regulation effect coefficient K of the load based on the static frequency characteristics of the load PF , expressed as:

[0025]

[0026] Among them, P L is the system load active power, and f is the system frequency.

[0027] The static load model of the power system is established and expressed as:

[0028]

[0029] Among them, P s0 , Q s0 、V 0 are the rated active power, reactive power and voltage respectively, Δf is the frequency deviation, f 0 is the nominal frequency, A p , B p , C pare the active power ratios of constant impedance load, constant current load and constant power load in the power system, A q , B q , C q are the reactive power ratios of constant impedance load, constant current load and constant power load, respectively, K PF and K QF are the frequency dependence factors of load active and reactive power, respectively.

[0030] Active power P consumed by node i load Li , expressed as:

[0031]

[0032] Among them, n p is the load type indicator, when the load is constant power, n p =0, constant current load n p =1, constant impedance load n p =2.

[0033] Calculate the adjustment efficiency coefficient ΔP of the node load Li , expressed as:

[0034]

[0035] Among them, λ i is the proportion of each load type, K npi It represents the coefficient related to the load type, and n represents the number of load nodes.

[0036] Calculating λ i It is expressed as:

[0037]

[0038] Calculate K npi , expressed as:

[0039]

[0040] Calculate the total resistance to system frequency change ΔP based on the type and proportion of all static loads in the system L , expressed as:

[0041]

[0042] Among them, λ is the proportionality coefficient of the load.

[0043] As a preferred solution of the power system frequency response prediction method of the present invention, the analysis of the power system load frequency response support capability also includes calculating the frequency response capability of the asynchronous motor, which is expressed as:

[0044]

[0045] Among them, H asy is the inertia time constant of the asynchronous motor.

[0046] K a , K b , K c Respectively expressed as:

[0047]

[0048] Among them, ω r0 is the initial value of the asynchronous motor rotor speed, ω 0 is the initial value of the system speed, f cs 、f ms 、f mw They are the initial working point, the partial derivative of the slip change with respect to the electromagnetic power, the partial derivative of the slip change with respect to the mechanical power, and the partial derivative of the speed change with respect to the mechanical power.

[0049] By actively cutting off part of the load when the frequency drops, the system power shortage is offset to maintain the stability of the system frequency. The delayed load shedding control is set. k is the proportion of the interruptible load. The load change ΔP is calculated. LC , expressed as:

[0050] ΔP LC = k·(tt 0 )

[0051] Where t is the current time, t 0 is the initial time.

[0052] As a preferred solution of the power system frequency response prediction method described in the present invention, wherein: the optimization of the power system frequency response model includes calculating the inertia time constant, which is expressed as:

[0053]

[0054] Among them, H sys Represents the total inertia time constant of the power system, H R It represents the inertia time constant of the steam turbine unit, H H It represents the inertia time constant of the steam turbine unit, H asy Indicates the inertia time constant of the asynchronous motor, H N represents the inertia time constant of the new energy unit with network control capability, M is the number of steam turbine units, and represents the total number of steam turbine units in the system analysis, S i is the rated capacity of the i-th steam turbine unit, W is the number of water turbine units, S jis the rated capacity of the jth turbine unit, N is the number of asynchronous motors, S n is the rated capacity of the nth asynchronous motor, X is the number of new energy units with grid-connecting capability, S k is the rated capacity of the kth renewable energy unit.

[0055] Analyze the dynamic response characteristics of the system frequency when the maximum power generation feed-in loss occurs, and calculate the current maximum power imbalance ΔP of the system d , taking into account the node voltage characteristics of the system static load, corrected to ΔP d- ΔPL-ΔPLc.

[0056] As a preferred solution of the power system frequency response prediction method described in the present invention, the optimization of the power system frequency response model also includes calculating each frequency response link of the aggregated power system frequency response model, which is expressed as:

[0057]

[0058] Among them, ΔP d It represents the disturbance power received by the system.

[0059] Another object of the present invention is to provide a power system frequency response prediction system, which can optimize the power system frequency response model by refining the load frequency support capability, thereby solving the problem of insufficient model adaptability in current power system frequency response prediction technology.

[0060] As a preferred solution of the power system frequency response prediction system described in the present invention, it includes: a model building module, a capability analysis module, and a model optimization module.

[0061] The model building module is used to count the output ratios and key parameters of various types of units and build a power system frequency response model; the capacity analysis module is used to analyze the load frequency response supporting capacity of the power system; and the model optimization module is used to refine the load frequency supporting capacity and optimize the power system frequency response model.

[0062] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a method for predicting frequency response of a power system.

[0063] A computer-readable storage medium stores a computer program, which implements the steps of a method for predicting frequency response of a power system when executed by a processor.

[0064] Beneficial effects of the present invention: The power system frequency response prediction method provided by the present invention counts the output ratios and key parameters of various types of units, constructs a power system frequency response model, improves the understanding of the dynamic behavior of the power system, lays a foundation for subsequent load frequency response support capability analysis and optimization, promotes the stability and safety of the power system, analyzes the power system load frequency response support capability, and enables the power system to more quickly restore a stable state when frequency fluctuations occur, reduces the risk of power outages, improves the reliability and flexibility of the overall system, refines the load frequency support capability, optimizes the power system frequency response model, effectively reduces unnecessary losses caused by frequency fluctuations, ensures that the power system can operate more efficiently, meets the growing demand for renewable energy, and promotes the realization of sustainable development. The present invention achieves better results in terms of technical versatility, economy, and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0066] Figure 1 An overall flow chart of a method for predicting frequency response of a power system provided in the first embodiment of the present invention.

[0067] Figure 2 A power system load model diagram of a power system frequency response prediction method provided by the first embodiment of the present invention.

[0068] Figure 3 A diagram of a power system frequency response prediction model of a power system frequency response prediction method provided in a first embodiment of the present invention.

[0069] Figure 4 An overall flow chart of a power system frequency response prediction system provided for the third embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0071] Example 1, reference Figure 1-Figure 3, as an embodiment of the present invention, provides a method for predicting frequency response of a power system, comprising:

[0072] S1: Count the output ratio and key parameters of each type of unit and build a power system frequency response model.

[0073] Furthermore, the output proportion and key parameters of each type of unit are counted, including the output proportion and unit parameters of steam turbines, water turbines and grid-controlled new energy units.

[0074] The primary frequency regulation response characteristics of thermal power units are analyzed and expressed as:

[0075]

[0076] Among them, ΔP R (s) is the output power change of the non-reheat steam turbine, F H is the high pressure turbine coefficient, T R is the reheater time constant, T G1 is the time constant of the reheat turbine governor, R 1 is the regulation coefficient of the reheat turbine governor, Δω(s) is the Laplace transform representation of the system frequency change, and s is the complex frequency domain variable in the Laplace transform.

[0077] The primary frequency regulation response characteristics of the turbine unit are analyzed and expressed as:

[0078]

[0079] Among them, ΔP H (s) is the change in turbine output power, T RT is the reset time constant of the turbine, R P is the permanent decline rate, R T is the temporary drop rate, T w is the time constant of water hammer effect, T G2 is the time constant of the turbine governor, K H is the regulation coefficient of the turbine governor.

[0080] Analyze the frequency support capability of the new energy generator network, including simulated inertia and primary frequency regulation capability, expressed as:

[0081]

[0082] Among them, ΔP N is the output power change of the new energy unit, H N To simulate the inertia time constant, R N and T NThey respectively represent the governor droop coefficient and governor time constant of the grid-connected new energy unit, and Δω is the system frequency change.

[0083] It should be noted that the construction of the power system frequency response model includes characterizing the overall frequency response of the system based on the inertia of the inertia center, and using the weighted average method to calculate the inertia time constant and damping coefficient of the inertia center, which is expressed as:

[0084]

[0085] Among them, S i is the rated capacity of the i-th unit, H i is the inertia time constant of the i-th unit, D i is the damping coefficient of the i-th unit, and n is the total number of units participating in frequency regulation.

[0086] Calculate the adjustment coefficient, expressed as:

[0087]

[0088] Among them, R i is the regulation coefficient of the i-th unit.

[0089] A power system frequency response model is established based on the output and proportion of various types of units in the power system.

[0090] It should also be noted that by statistically analyzing the output ratios and key parameters of various types of units and constructing a power system frequency response model, a comprehensive evaluation of the output characteristics of different power types (such as steam turbines, hydro turbines and new energy units) is achieved, laying a solid foundation for the subsequent establishment of a frequency response model. Through a detailed analysis of the frequency regulation response characteristics of thermal power units and hydro turbines, the role of each unit in dynamic frequency regulation can be accurately identified, and then these key parameters are used for reasonable mathematical modeling when constructing the frequency response model. This not only reflects the current operating status of the power system, but also can dynamically capture frequency fluctuations caused by load changes, external disturbances and other factors. By introducing mathematical tools such as Laplace transform, the frequency response characteristics of the unit can be analyzed in the complex frequency domain, thereby achieving quantitative prediction of system frequency changes. The constructed frequency response model improves the adaptability of the power system to frequency disturbances and provides a scientific basis for subsequent frequency management and stability control.

[0091] S2: Analyze the power system load frequency response support capability.

[0092] Furthermore, the analysis of the load frequency response support capacity of the power system includes the calculation of the load frequency regulation effect coefficient K based on the static frequency characteristics of the load. PF , expressed as:

[0093]

[0094] Among them, P L is the system load active power, and f is the system frequency.

[0095] The static load model of the power system is established and expressed as:

[0096]

[0097] Among them, P s0 , Q s0 、V 0 are the rated active power, reactive power and voltage respectively, Δf is the frequency deviation, f 0 is the nominal frequency, A p , B p , C p are the active power ratios of constant impedance load, constant current load and constant power load in the power system, A q , B q , C q are the reactive power ratios of constant impedance load, constant current load and constant power load, respectively, K PF and K QF are the frequency dependence factors of load active and reactive power, respectively.

[0098] Active power P consumed by node i load Li , expressed as:

[0099]

[0100] Among them, n p is the load type indicator, when the load is constant power, n p =0, constant current load n p =1, constant impedance load n p =2.

[0101] Calculate the adjustment efficiency coefficient ΔP of the node load Li , expressed as:

[0102]

[0103] Among them, λ i is the proportion of each load type, K npi It represents the coefficient related to the load type, and n represents the number of load nodes.

[0104] Calculating λ i It is expressed as:

[0105]

[0106] Calculate K npi , expressed as:

[0107]

[0108] Calculate the total resistance to system frequency change ΔP based on the type and proportion of all static loads in the system L , expressed as:

[0109]

[0110] Among them, λ is the proportionality coefficient of the load.

[0111] It should be noted that the analysis of the load frequency response support capability of the power system also includes the calculation of the frequency response capability of the asynchronous motor, which is expressed as:

[0112]

[0113] Among them, H asy is the inertia time constant of the asynchronous motor.

[0114] K a , K b , K c Respectively expressed as:

[0115]

[0116] Among them, ω r0 is the initial value of the asynchronous motor rotor speed, ω 0 is the initial value of the system speed, f cs 、f ms 、f mw They are the initial working point, the partial derivative of the slip change with respect to the electromagnetic power, the partial derivative of the slip change with respect to the mechanical power, and the partial derivative of the speed change with respect to the mechanical power.

[0117] By actively cutting off part of the load when the frequency drops, the system power shortage is offset to maintain the stability of the system frequency. The delayed load shedding control is set. k is the proportion of the interruptible load. The load change ΔP is calculated. LC , expressed as:

[0118] ΔP LC = k·(tt 0 )

[0119] Where t is the current time, t 0 is the initial time.

[0120] It should also be noted that by analyzing the load frequency response support capacity of the power system and calculating the static frequency characteristics of the load, it is possible to quantitatively evaluate the role of the load in frequency regulation. The static load model is used to provide theoretical support for further understanding of the dynamic characteristics and frequency dependence of various load types. By calculating the frequency regulation effect coefficient and node load consumption, the load types that play a key role in system frequency stability can be effectively identified, thereby improving the system's resistance to frequency changes. The power system can restore stability more quickly when frequency fluctuations occur, reducing the risk of power outages and improving the reliability and flexibility of the overall system.

[0121] S3: Refine the load frequency support capability and optimize the power system frequency response model.

[0122] Furthermore, the optimization of the power system frequency response model includes the calculation of the inertia time constant, which is expressed as:

[0123]

[0124] Among them, H sys Represents the total inertia time constant of the power system, H R It represents the inertia time constant of the steam turbine unit, H H It represents the inertia time constant of the steam turbine unit, H asy Indicates the inertia time constant of the asynchronous motor, H N represents the inertia time constant of the new energy unit with network control capability, M is the number of steam turbine units, and represents the total number of steam turbine units in the system analysis, S i is the rated capacity of the i-th steam turbine unit, W is the number of water turbine units, S j is the rated capacity of the jth turbine unit, N is the number of asynchronous motors, S n is the rated capacity of the nth asynchronous motor, X is the number of new energy units with grid-connecting capability, S k is the rated capacity of the kth renewable energy unit.

[0125] Analyze the dynamic response characteristics of the system frequency when the maximum power generation feed-in loss occurs, and calculate the current maximum power imbalance ΔP of the system d , taking into account the node voltage characteristics of the system static load, corrected to ΔP d -ΔPL-ΔPLc.

[0126] It should be noted that the optimization of the power system frequency response model also includes calculating the frequency response links of the aggregated power system frequency response model, which can be expressed as:

[0127]

[0128] Among them, ΔPd It represents the disturbance power received by the system.

[0129] It should also be noted that through the analysis and calculation of the refined load frequency support capacity, the power system frequency response model has been further optimized, involving the optimization calculation of the inertia time constant and other parameters, combining the theoretical research of load frequency support with practical application, ensuring that the model can be effectively adjusted to different operating conditions. By adjusting the refined parameter settings, real-time response to the power system is achieved, and it can quickly adapt to actual changes. Through the management of emergency controllable loads, the function of actively cutting off part of the load when the frequency drops is realized, so that the power system can quickly adjust the load to offset the power gap when facing sudden disturbances, thereby maintaining frequency stability. This not only improves the power system's ability to respond to emergencies, but also effectively reduces the impact of system frequency fluctuations on the balance of power supply and demand.

[0130] Embodiment 2 is an embodiment of the present invention, which provides a method for predicting frequency response of a power system. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0131] Firstly, the experiment simulated the output ratio and key parameters of the generator sets, analyzed the frequency response characteristics of various types of units, optimized the frequency response model and compared the shortcomings of the existing technology; the experiment adopted a simulated power system, which included steam turbine units (hydropower and thermal power), new energy grid units (such as wind power, photovoltaic), asynchronous motor load and static load module; the experimental hardware was a real-time digital simulation platform (RTDS) and load test platform, and the software environment included MATLABSimulink and PSCAD; the initial value of the system frequency was set to 50Hz, and the experimental time range was 0-60 seconds; the thermal generator The parameters of the group (such as high-pressure turbine coefficient, reheater time constant, etc.) are set. It is assumed that the high-pressure turbine coefficient is 0.8 and the reheater time constant is 5 seconds; the time constant of the turbine governor is set to 1 second, and the water hammer effect time constant is set to 3 seconds; the inertia time constant of the new energy unit is set to 0.5 seconds, and the governor time constant is 2 seconds; the unit output ratio and key parameters are counted: the output ratio of thermal power units, hydropower units and new energy units are counted respectively, the output ratio of thermal power units is 40%, the output ratio of hydropower units is 30%, and the output ratio of new energy units is 30%; extract the key parameters of each unit ( The frequency response model of the power system is constructed by taking the above statistical data and the weighted average method into consideration to calculate the total inertia time constant of the power system, and the result is 2.7 seconds. At the same time, the system frequency response model is established through Laplace transform to simulate the influence of disturbance power on the frequency change of the system. The load frequency response supporting capacity is analyzed by establishing the load frequency response model and calculating the frequency regulation effect coefficient of the static load and the regulation utility coefficient of the node load. The experiment compares the response characteristics of the static load and the asynchronous motor load respectively, and finds that the frequency support capacity of the asynchronous motor is better than that of the asynchronous motor. Static load; when considering emergency controllable load, set the load shedding ratio to 10%; optimize the frequency response model: optimize the load frequency supporting capacity based on the original model, and by adjusting the inertia time constant of the asynchronous motor and the simulated inertia of the new energy unit, the total inertia time constant of the system is increased to 3.2 seconds after optimization, and the dynamic response of the system frequency is improved; from the experimental results, it can be obtained that the present invention effectively improves the dynamic response performance of the system frequency and shortens the response time by improving the simulated inertia and speed regulator performance of the new energy unit. The introduction of emergency controllable load further improves the anti-disturbance capability of the system, which is practical and forward-looking.

[0132] Example 3, reference Figure 4 , as an embodiment of the present invention, provides a power system frequency response prediction system, including a model building module, a capability analysis module, and a model optimization module.

[0133] The model construction module is used to count the output ratios and key parameters of various types of units and construct a power system frequency response model; the capacity analysis module is used to analyze the load frequency response support capacity of the power system; and the model optimization module is used to refine the load frequency support capacity and optimize the power system frequency response model.

[0134] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0135] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0136] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0137] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0138] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for predicting frequency response of a power system, characterized in that: include: Count the output ratios and key parameters of each type of unit and build a frequency response model for the power system; Analyze the load frequency response support capability of the power system; Refine the load frequency support capability and optimize the power system frequency response model.

2. The method for predicting the frequency response of a power system according to claim 1, wherein: The statistics of the output proportion and key parameters of each type of unit include statistics of the output proportion and unit parameters of steam turbines, water turbines and new energy units controlled by the grid; The primary frequency regulation response characteristics of thermal power units are analyzed and expressed as: Where ΔP R (s) is the output power change of the non-reheat steam turbine, F H is the high pressure turbine coefficient, T R is the reheater time constant, T G1 is the time constant of the reheat turbine governor, R1 is the differential coefficient of the reheat turbine governor, Δω(s) is the Laplace transform representation of the system frequency change, and s is the complex frequency domain variable in the Laplace transform; The primary frequency regulation response characteristics of the turbine unit are analyzed and expressed as: Where ΔP H (s) is the change in turbine output power, T RT is the reset time constant of the turbine, R P is the permanent decline rate, R T is the temporary drop rate, T w is the time constant of water hammer effect, T G2 is the time constant of the turbine governor, K H is the regulation coefficient of the turbine governor; Analyze the frequency support capability of the new energy generator network, including simulated inertia and primary frequency regulation capability, expressed as: Where ΔP N is the output power change of the new energy unit, H N To simulate the inertia time constant, R N and T N They respectively represent the governor droop coefficient and governor time constant of the grid-connected new energy unit, and Δω is the system frequency change.

3. The method for predicting the frequency response of a power system according to claim 2, characterized in that: The construction of the power system frequency response model includes characterizing the overall frequency response of the system based on the inertia of the inertia center, and calculating the inertia time constant and damping coefficient of the inertia center by the weighted average method, which is expressed as: Among them, S i is the rated capacity of the i-th unit, H i is the inertia time constant of the i-th unit, D i is the damping coefficient of the i-th unit, n is the total number of units participating in frequency regulation; Calculate the adjustment coefficient, expressed as: Among them, R i is the adjustment coefficient of the i-th unit; A power system frequency response model is established based on the output and proportion of various types of units in the power system.

4. The method for predicting the frequency response of a power system according to claim 3, characterized in that: The analysis of the load frequency response support capability of the power system includes calculating the frequency regulation effect coefficient K of the load based on the static frequency characteristics of the load. PF , expressed as: Among them, P L is the system load active power, f is the system frequency; The static load model of the power system is established and expressed as: Among them, P s0 , Q s0 , V0 are the rated active power, reactive power and voltage respectively, Δf is the frequency deviation, f0 is the nominal frequency, A p , B p , C p are the active power ratios of constant impedance load, constant current load and constant power load in the power system, A q , B q , C q are the reactive power ratios of constant impedance load, constant current load and constant power load, respectively, K PF and K QF are the frequency dependence factors of load active and reactive power, respectively; Active power P consumed by node i load Li , expressed as: Among them, n p is the load type indicator, when the load is constant power, n p =0, constant current load n p =1, constant impedance load n p =2; Calculate the adjustment efficiency coefficient ΔP of the node load Li , expressed as: Among them, λ i is the proportion of each load type, K npi represents the coefficient related to the load type, and n represents the number of load nodes; Calculating λ i It is expressed as: Calculate K npi , expressed as: Calculate the total resistance to system frequency change ΔP based on the type and proportion of all static loads in the system L , expressed as: Among them, λ is the proportionality coefficient of the load.

5. The method for predicting the frequency response of a power system according to claim 4, characterized in that: The analysis of the power system load frequency response support capability also includes calculating the frequency response capability of the asynchronous motor, which is expressed as: Among them, H asy is the inertia time constant of the asynchronous motor; K a , K b , K c Respectively expressed as: Among them, ω r0 is the initial value of the asynchronous motor rotor speed, ω0 is the initial value of the system speed, f cs 、f ms 、f mw They are the initial working point, the partial derivative of the slip change with respect to the electromagnetic power, the partial derivative of the slip change with respect to the mechanical power, and the partial derivative of the speed change with respect to the mechanical power; By actively cutting off part of the load when the frequency drops, the system power shortage is offset to maintain the stability of the system frequency. The delayed load shedding control is set. k is the proportion of the interruptible load. The load change ΔP is calculated. LC , expressed as: ΔP LC =k·(t-t0) Among them, t is the current time and t0 is the initial time.

6. The method for predicting the frequency response of a power system according to claim 5, characterized in that: The optimized power system frequency response model includes calculating the inertia time constant, which is expressed as: Among them, H sys Represents the total inertia time constant of the power system, H R It represents the inertia time constant of the steam turbine unit, H H It represents the inertia time constant of the steam turbine unit, H asy Indicates the inertia time constant of the asynchronous motor, H N represents the inertia time constant of the new energy unit with network control capability, M is the number of steam turbine units, and represents the total number of steam turbine units in the system analysis, S i is the rated capacity of the i-th steam turbine unit, W is the number of water turbine units, S j is the rated capacity of the jth turbine unit, N is the number of asynchronous motors, S n is the rated capacity of the nth asynchronous motor, X is the number of new energy units with grid-connecting capability, S k is the rated capacity of the kth renewable energy unit; Analyze the dynamic response characteristics of the system frequency when the maximum power generation feed-in loss occurs, and calculate the current maximum power imbalance ΔP of the system d , taking into account the node voltage characteristics of the system static load, corrected to ΔP d- ΔPL-ΔPLc.

7. The method for predicting the frequency response of a power system according to claim 6, characterized in that: The optimized power system frequency response model also includes calculating each frequency response link of the aggregated power system frequency response model, which is expressed as: Where ΔP d It represents the disturbance power received by the system.

8. A system using the method for predicting the frequency response of a power system according to any one of claims 1 to 7, characterized in that: Including model building module, capability analysis module, and model optimization module; The model building module is used to count the output ratios and key parameters of various types of units and build a power system frequency response model; The capability analysis module is used to analyze the load frequency response support capability of the power system; The model optimization module is used to refine the load frequency support capability and optimize the power system frequency response model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for predicting the frequency response of a power system according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for predicting frequency response of a power system according to any one of claims 1 to 7 are implemented.

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