Grid frequency control method for low inertia power system

Abstract

The present application discloses a method for controlling the frequency of a power grid in a low-inertia power system. The method comprises: based on a frequency response model constructed by each frequency regulation resource in the low-inertia power system, minimizing the lowest point of the power grid frequency during fluctuation as a first control target, minimizing the total frequency regulation cost of the frequency regulation resources as a second control target, satisfying the safety constraint at the lowest point of the power grid frequency during fluctuation as a first constraint, requiring the power generated by each frequency regulation resource to satisfy the power limit as a second constraint, and requiring the total power generated by each frequency regulation resource to satisfy the total power demand of the low-inertia power system as a third constraint. The power generated by each frequency regulation resource is required to be output to eliminate the frequency deviation, and the frequency regulation resources include synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices. The method can achieve the coordinated optimization of multiple frequency regulation resources and cope with the needs of complex dynamic power systems.

Description

Technical Field

[0001] The present application relates to the technical field of power control, and in particular to a grid frequency control method for low-inertia power systems. Background Art

[0002] With the rapid growth of renewable energy generation capacity, power systems are facing a series of challenges, including declining inertia, increased frequency fluctuations, and insufficient frequency regulation resources. In particular, in low-inertia power systems with a high proportion of renewable energy, the random volatility of renewable energy and load forecasting errors significantly increase the difficulty of frequency control, seriously threatening the frequency stability and operational safety of the power system. Summary of the Invention

[0003] In view of this, the present application provides a grid frequency control method for low-inertia power systems, which can comprehensively consider the synergistic effect of grid-building and grid-following virtual inertia devices, as well as deal with the uncertainty effects brought by new energy volatility and load forecast errors, thereby improving frequency stability and frequency regulation efficiency, and ensuring the robustness and economy of the optimization scheme.

[0004] According to one aspect of the present application, a method for controlling grid frequency in a low-inertia power system is provided, the method comprising:

[0005] real-time monitoring of the grid frequency of the low-inertia power system and obtaining a frequency deviation of the monitored grid frequency relative to a preset standard grid frequency, wherein the grid frequency of the low-inertia power system fluctuates;

[0006] Based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, minimizing the lowest point of the fluctuating grid frequency is the first control target, minimizing the total frequency regulation cost of the frequency regulation resources is the second control target, satisfying the safety constraint is the first constraint condition, requiring the generated power output by each frequency regulation resource to satisfy the power limit is the second constraint condition, and requiring the total generated power output by each frequency regulation resource to satisfy the total power demand of the low-inertia power system is the third constraint condition. In order to eliminate the frequency deviation, the generated power output by each frequency regulation resource is solved, wherein the frequency regulation resources include synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices;

[0007] Each frequency regulation resource is regulated to output the solved power generation power, wherein when the power generation power of the frequency regulation resource is changed, the grid frequency of the low inertia power system will change.

[0008] By means of the above technical solution, the present application provides a grid frequency control method for low-inertia power systems, which aims to solve the key technical problems faced by frequency stability and frequency regulation optimization in low-inertia power systems with high penetration of renewable energy access. At the same time, the uncertainty of new energy volatility and load forecast error is taken into account. First, the frequency response characteristics of grid-forming and grid-following virtual inertia devices are introduced into the frequency regulation optimization model. Combined with the inertia characteristics of synchronous generators, a multi-control mode collaborative optimization mechanism is constructed to give full play to the dynamic response advantages of different types of frequency regulation resources. Secondly, a penalty term reflecting the dynamic uncertainty of the system is constructed, and the probability constraint of the frequency minimum point deviation and the power balance constraint are introduced into the frequency regulation optimization target to ensure that the optimization scheme has strong robustness in uncertain scenarios. In addition, a closed-loop feedback control mechanism based on frequency deviation is proposed. Combined with the real-time updated new energy output and load power forecast, the output power of the frequency regulation resources is dynamically adjusted to achieve a rapid response to frequency fluctuations.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0011] Figure 1 A schematic diagram of a flow chart of a method for controlling grid frequency in a low-inertia power system provided in an embodiment of the present application is shown;

[0012] Figure 2 A flow chart of a method for regulating power generation using frequency modulation resources provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0013] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0014] In this embodiment, a method for controlling the grid frequency of a low-inertia power system is provided. Figure 1 As shown, the method includes:

[0015] Step 101 : monitor the grid frequency of the low-inertia power system in real time, and obtain a frequency deviation of the monitored grid frequency relative to a preset standard grid frequency, wherein the grid frequency of the low-inertia power system fluctuates.

[0016] Virtual inertia control technology, as an important solution to addressing frequency stability issues in low-inertia systems, has garnered widespread attention in recent years. Virtual inertia devices, using energy storage devices and inverters, provide inertia support and damping, mimicking the inertia characteristics of synchronous generators and effectively mitigating system frequency fluctuations. In practical applications, virtual inertia devices can be categorized into two control methods: grid-forming and grid-following. Grid-forming devices actively support grid frequency and voltage, providing inertia responses similar to synchronous generators; grid-following devices, on the other hand, use inverters to follow grid frequency fluctuations, providing rapid frequency regulation. However, most current technologies employ only a single control method and fail to fully consider the synergistic effects of grid-forming and grid-following virtual inertia devices. This results in limited frequency regulation response capabilities in scenarios with high renewable energy penetration. Furthermore, the randomness of renewable energy output and load power forecasting errors further complicate frequency regulation optimization. Errors in renewable energy output forecasts can cause frequency scheduling to deviate from actual demand, potentially exceeding safe frequency limits, and seriously impacting grid operational safety. Load forecasting errors can lead to irrational allocation of frequency regulation resources and increase the risk of system fluctuations. However, existing frequency optimization technologies are typically based on deterministic modeling, ignoring the important role of renewable energy volatility and load uncertainty in frequency regulation. Furthermore, existing methods typically only target synchronous generators or a specific virtual inertia control method (such as grid-forming or grid-following), failing to achieve the coordinated optimization of multiple frequency regulation resources and struggling to meet the complex dynamic demands of power systems.

[0017] In other words, current frequency regulation optimization technologies have two major shortcomings: First, they rely on a single control approach. Existing methods typically rely solely on the inertia response model of synchronous generators, or employ a single virtual inertia control approach (such as a grid-forming or grid-following approach). These methods fail to achieve the coordinated optimization of multiple control approaches and fail to fully leverage the advantages of different frequency regulation resources. Second, they ignore the impact of uncertainty.

[0018] In the above-mentioned embodiment of the present application, the grid frequency of the low-inertia power system is monitored in real time, and the frequency deviation of the monitored grid frequency relative to the preset standard grid frequency is obtained. The grid frequency of the low-inertia power system fluctuates. In particular, the preset standard grid frequency in my country is generally 50Hz, which means that the direction of the alternating current changes 50 times per second, from positive to negative, and then from negative to positive. The setting of this standard frequency is crucial to the stable operation of the power system. It is the basis for the stable operation of the power grid and can ensure that the electrical parameters such as voltage and current of the power grid remain stable, thereby ensuring the safe and reliable operation of the power system. In addition, the standard frequency of 50Hz is also widely used in various fields, including industry, agriculture, commerce, residential life, etc.

[0019] Step 102, based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, minimizing the lowest point of the fluctuating grid frequency is a first control objective, minimizing the total frequency regulation cost of the frequency regulation resources is a second control objective, satisfying the safety constraint is a first constraint, requiring the generated power output by each frequency regulation resource to satisfy the power limit is a second constraint, and requiring the total generated power output by each frequency regulation resource to satisfy the total power demand of the low-inertia power system is a third constraint. The generated power required to be output by each frequency regulation resource to eliminate the frequency deviation is solved, wherein the frequency regulation resources include synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices.

[0020] Next, the frequency response models of multiple frequency regulation resources, the first regulation target, the second regulation target, the first constraint, the second constraint and the third constraint are used to calculate the power generation power required to be output by each frequency regulation resource in order to eliminate the frequency deviation.

[0021] Step 103 : regulating each frequency regulation resource to output the solved generated power. When the generated power of the frequency regulation resource is changed, the grid frequency of the low inertia power system will change.

[0022] Ultimately, each frequency regulation resource is regulated to output the calculated power. Specifically, changing the power of a frequency regulation resource will cause the grid frequency of the low-inertia power system to change. The regulation process involves adjusting power generation based on frequency fluctuations. By monitoring frequency deviations in real time, the output power of the generator sets is adjusted. The degree of frequency fluctuation directly determines the magnitude of the regulated power. Regarding power frequency regulation, power frequency regulation refers to controlling the grid frequency and maintaining its stability by adjusting the power generation of power plants. Grid frequency stability is crucial to the safety and reliability of the power system. Primary frequency regulation relies on the turbine speed control system to autonomously respond to generator load changes based on grid frequency fluctuations. Secondary frequency regulation relies more on human intervention or more advanced technical means to effectively control grid frequency, such as by changing the minimum and maximum power generation of frequency regulation resources (such as thermal power units, hydropower units, and energy storage systems). In secondary frequency regulation, the dispatch center can directly issue commands to individual power plants to adjust their production power, varying their minimum and maximum power generation within a certain range to accommodate changes in grid frequency. In addition, relying on advanced automatic control systems (such as automatic power generation control system AGC), each generator set can automatically adjust its output power according to its own situation and participate in the secondary frequency regulation process.

[0023] Optionally, in step 102, the step of “solving the generated power required to be output by each frequency regulation resource in order to eliminate the frequency deviation based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system” specifically includes:

[0024] Step 1021: Construct a frequency response model for the synchronous generator set based on the frequency deviation, as well as the inertia coefficient, damping coefficient, input mechanical power deviation, output power generation power deviation, rotor inertia time constant, unit capacity, and rated frequency of the synchronous generator set, wherein the input mechanical power deviation is a known parameter and the output power generation power deviation is a solution parameter.

[0025] Step 1022: Based on the frequency response model, the output power deviation of the synchronous generator set is calculated to eliminate the frequency deviation. The frequency response model for the synchronous generator set is:

[0026]

[0027] Δf is the frequency deviation, M SG 、D SG , ΔP m , ΔP e ,H,S B and f n, respectively, are the inertia coefficient, damping coefficient, input mechanical power deviation, output power deviation, rotor inertia time constant, unit capacity and rated frequency of the synchronous generator set, and t is the time variable.

[0028] Accordingly, refer to Figure 2 As shown, step 103 regulates each frequency modulation resource to output the solved generated power, specifically including:

[0029] Step 1031 : Based on the rated output power of the synchronous generator set and the calculated output power deviation, the synchronous generator set is regulated to output a power that can eliminate the frequency deviation.

[0030] In the above-described embodiments of this application, input power deviation is typically provided by an external mechanical drive and is not directly regulated. Input power deviation itself is determined by the externally supplied mechanical power and is not directly regulated. Input power deviation is typically a natural reflection of the system's operating state, while synchronous generators primarily adjust their output power based on frequency deviation.

[0031] ΔP m It is the difference between the input power of a synchronous generator (such as the power of a steam or hydraulic drive) and the power required by the grid load (the power required by a low-inertia power system). This deviation originates from the external mechanical drive and directly determines the mechanical power received by the generator. The input power deviation reflects the difference between the mechanical input power of the synchronous generator and the power required by the grid (the power required by a low-inertia power system); it affects the power output of the synchronous generator but is not directly regulated by the control system. Instead, the control system adjusts the generator's output power to adapt to load changes. In particular, the input power of a synchronous generator primarily refers to the mechanical power provided to the generator by the prime mover. The magnitude of this power directly determines the electrical power the generator can output. In actual operation, not all of the generator's input power is converted into electrical power output; instead, a portion is lost as heat within the generator.

[0032] ΔP e Indicates the difference between the actual output power of the synchronous generator and the grid load (the power required by the low-inertia power system). Changes in the output power deviation will directly affect changes in the grid frequency, and therefore is the key to frequency regulation. The output power deviation reflects the power matching between the generator and the grid. By adjusting the output power of the synchronous generator, the power gap ΔP can be eliminated. e , thus affecting the recovery of the frequency deviation Δf.

[0033] In particular, when the output power deviation is positive, the generated power = the rated output generated power of the synchronous generator set + the output generated power deviation; when the output power deviation is negative, the generated power = the rated output generated power of the synchronous generator set - |output generated power deviation|.

[0034] Before constructing the frequency response model for the synchronous generator set, the synchronous generator rotor can also be modeled according to the swing equation to establish the following synchronous generator rotation equation:

[0035]

[0036] Where J is the rotor inertia, ω m is the rotor angular velocity, T m is the rotor input torque, T e Output torque to the rotor.

[0037] In order to transform the mechanical dynamics description into the analysis of electrical frequency deviation, the synchronous generator rotation equation can be used to establish the aforementioned frequency response model for the synchronous generator set, and finally transformed into an inertia dynamics model of frequency deviation.

[0038] Optionally, in step 102, the step of “the grid-type virtual inertia device includes a virtual synchronous generator, and based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, solving the generated power required to be output by each frequency regulation resource in order to eliminate the frequency deviation” specifically includes:

[0039] Step 1023: Construct a dynamic response equation of the virtual synchronous generator based on the frequency deviation and the virtual inertia coefficient, virtual damping coefficient, and dynamic power change of the virtual synchronous generator in the meshed virtual inertia device. Perform a Laplace transform on the dynamic response equation of the virtual synchronous generator to obtain a frequency response model for the meshed virtual inertia device.

[0040] Step 1024: Based on the dynamic response equation of the virtual synchronous generator, a dynamic power change amount that needs to be output by the networked virtual inertia device to eliminate the frequency deviation is solved. Based on the frequency response model for the networked virtual inertia device and the dynamic power change amount, a frequency response change amount of the networked virtual inertia device is determined. The dynamic response equation of the virtual synchronous generator is:

[0041]

[0042] The frequency response model for the networked virtual inertia device is:

[0043]

[0044] Δf is the frequency deviation, M VSM 、D VSM , ΔP VSM , Δf(s) and P VSM (s), are the virtual inertia coefficient, virtual damping coefficient, dynamic power variation, frequency response variation and Laplace transform of the virtual synchronous generator in the networked virtual inertia device, t is the time variable, G LT,VSM (s) is the frequency response model for the networked virtual inertia device, and s is a complex frequency variable.

[0045] Accordingly, refer to Figure 2 As shown, step 103 regulates each frequency modulation resource to output the solved generated power, specifically including:

[0046] Step 1032: Based on the frequency response variation, the gridded virtual inertia device is regulated to output a power generation power that can eliminate the frequency deviation.

[0047] In the above-described embodiments of the present application, the output power of the grid-type virtual inertia device is regulated by solving the frequency response variation Δf(s). When the grid frequency changes, the device uses the inertia and damping characteristics in the dynamic response equation of the virtual synchronous generator to determine the power required to restore the frequency. Furthermore, by using a frequency response model for the grid-type virtual inertia device, the virtual inertia device adjusts its output power based on the frequency variation Δf(s), allowing the low-inertia power system frequency to return to a normal range.

[0048] In particular, s usually represents a complex frequency variable, which is a core element in the Laplace transform. In the Laplace transform, the function f(t) is converted into a function F(s) in the complex domain, where t is the time variable and s is the complex frequency variable, defined as s = σ + jω, where σ is the real part, representing the attenuation coefficient; j is the imaginary unit (satisfying j 2 =-1); ω is the imaginary part, representing the angular frequency. In power systems, the Laplace transform can be used to convert the dynamic equations in the time domain into models in the frequency domain, making it easier to analyze the frequency response characteristics of the system. s appears as a complex frequency variable in the frequency response model G GF (s) plays a key role in helping describe the system's response to input signals of varying frequencies.

[0049] Optionally, in step 102, the following steps include: “the grid-following virtual inertia device includes an inverter, and based on the frequency response models constructed by the frequency regulation resources in the low-inertia power system, solving the generated power required to be output by each frequency regulation resource in order to eliminate the frequency deviation”, specifically including:

[0050] Step 1024: Construct an inverter dynamic response equation based on the frequency deviation, the virtual inertia coefficient, the virtual damping coefficient, and the dynamic power change of the inverter in the grid-following virtual inertia device. Perform a Laplace transform on the inverter dynamic response equation to obtain a frequency response model for the grid-following virtual inertia device.

[0051] Step 1025: Based on the inverter dynamic response equation, a dynamic power change required to be output by the grid-following virtual inertia device to eliminate the frequency deviation is solved. Based on the frequency response model for the grid-following virtual inertia device and the dynamic power change, a frequency response change of the grid-following virtual inertia device is determined. The inverter dynamic response equation is:

[0052]

[0053] The frequency response model for the network-following virtual inertia device is:

[0054]

[0055] Accordingly, refer to Figure 2 As shown, step 103 regulates each frequency modulation resource to output the solved generated power, specifically including:

[0056] Step 1033: Based on a fast power compensation model and the frequency response variation, the dynamic power variation of the grid-following virtual inertia device is regulated so that the grid-following virtual inertia device outputs a generated power capable of eliminating the frequency deviation based on the dynamic power variation. The fast power compensation model is:

[0057]

[0058] Δf is the frequency deviation, M VSG 、D VSG , ΔP VSG 、R VSG , Δf(s) and P VSG (s), are the virtual inertia coefficient, virtual damping coefficient, dynamic power variation, frequency regulation margin, frequency response variation and Laplace transform of the inverter in the grid-following virtual inertia device, t is the time variable, T VSG is the time constant, G LT,VSG (s) is the frequency response model for the grid-following virtual inertia device, and s is a complex frequency variable.

[0059] In the aforementioned embodiments of this application, in a grid-following virtual inertia device, the frequency deviation is used to calculate the required power regulation using the device's inertia coefficient and damping coefficient. The fast power compensation model demonstrates that the device's output power is dynamically adjusted as the frequency deviation and frequency change rate change, ensuring that the grid frequency remains stable within a predetermined range.

[0060] Optionally, in step 102, regarding “taking minimizing the lowest point of the fluctuating grid frequency as the first control target”, specifically includes:

[0061] Step 1026: Construct a first objective function with minimizing the lowest point of the fluctuating grid frequency as a first control objective. When solving the generated power output of each frequency regulation resource required to eliminate the frequency deviation, the lowest point of the fluctuating grid frequency is always minimized based on the first objective function. The first objective function is:

[0062]

[0063] minΔf lim Indicates the lowest point of the fluctuating grid frequency Δf lim Minimize the first objective function of the first control target, ΔP tot 、D tot and R tot , which are the total power shortage, total damping coefficient and total frequency regulation margin of the low inertia power system respectively.

[0064] In the above embodiment of the present application, the lowest frequency point Δf lim It is an important indicator for measuring power system frequency stability and can improve frequency stability. By minimizing the lowest point in the grid frequency, the amplitude of frequency fluctuations can be reduced, thereby improving grid frequency stability. This helps protect power equipment and ensure the reliability of power supply. By solving the required output power of each frequency regulation resource based on this objective function, frequency regulation resources can be more rationally allocated, ensuring efficient utilization of each resource during the frequency regulation process. When the grid is disturbed, minimizing the lowest point in the frequency can more quickly restore the grid frequency to normal levels, thereby enhancing the system's ability to cope with disturbances.

[0065] Specifically, first, the form of the objective function needs to be clarified, that is, with the goal of minimizing the lowest point of the grid frequency, and constructing the corresponding mathematical expression (the first objective function). In order to solve the objective function, it is necessary to collect relevant data, including the total power shortage, total damping coefficient and total frequency regulation margin of the low-inertia power system. This data will be used to construct a mathematical model and solve it. Solving the objective function will obtain the required output power of each frequency regulation resource. Based on the solution results, the output of each frequency regulation resource is adjusted to achieve stable control of the grid frequency. This may require coordination with the power dispatching center to ensure the effective implementation of the frequency regulation strategy.

[0066] In summary, constructing a primary objective function that minimizes the lowest point of fluctuating grid frequency as the primary control goal has significant benefits for improving grid frequency stability, optimizing frequency regulation resource allocation, and enhancing the system's ability to cope with disturbances. The specific operation requires defining the objective function, collecting data, solving the objective function, implementing the frequency regulation strategy, and conducting monitoring and evaluation.

[0067] Optionally, in step 102, the method of “minimizing the total frequency regulation cost of the frequency regulation resources as the second regulation objective and requiring the output power of each frequency regulation resource to meet a power limit as the second constraint condition” specifically includes:

[0068] Step 1027: Construct a second objective function with the minimum total frequency regulation cost of the frequency regulation resources as a second control objective. When solving the generated power output of each frequency regulation resource required to eliminate the frequency deviation, the total frequency regulation cost of the frequency regulation resources is always kept at a minimum based on the second objective function. The second objective function is:

[0069]

[0070] C i is the unit frequency regulation cost of the ith frequency regulation resource, P i is the power generation power required to be output by the i-th frequency regulation resource, and S is the total number of frequency regulation resources.

[0071] Step 1028: for any frequency modulation resource, limiting the generated power output by the frequency modulation resource to always meet a power limitation condition, wherein the power limitation condition is:

[0072] P i,min ≤P i ≤P i,max ,i=1,2,...S,

[0073] P i is the power generation of the ith frequency regulation resource, P i The value range is the preset minimum power generation power P i,min and preset maximum power generation power Pi,max between.

[0074] In the above embodiments of the present application, in the scheduling of frequency regulation resources, the goal is to minimize the total frequency regulation cost of all frequency regulation equipment, and the output power of each frequency regulation resource needs to meet its technical limitations. Regarding the preset minimum power generation power and the preset maximum power generation power, it can be determined according to the actual situation of the low inertia power system. Regarding the determination process, for example: the preset minimum power generation power of the system needs to meet the basic load requirements of the power grid and ensure the stable operation of the power grid. This set value is usually determined based on factors such as the load forecast of the power grid, the backup capacity requirements and the minimum technical output of the power generation equipment. The preset maximum power generation power is limited by factors such as the maximum capacity of the power generation equipment, the transmission capacity of the power grid, the load demand and the stability of the system. When setting, these factors need to be considered comprehensively to ensure that the power system can still maintain stable operation at the maximum power generation power.

[0075] Specifically, for low-inertia power systems, frequency stability may face greater challenges due to their smaller inertia. Therefore, when setting the preset minimum and maximum power generation capacities, the system stability requirements need to be considered more carefully.

[0076] The second objective function minimizes the total frequency regulation cost of frequency regulation resources, thereby improving the economic operation of the power system. Limiting the output power of frequency regulation resources to within power constraints prevents equipment overload and ensures safe and stable operation of the power system. While meeting both economic and power constraints, optimizing the output power of frequency regulation resources can still effectively eliminate frequency deviations and ensure frequency stability in the power system.

[0077] Specifically, the various resources involved in frequency regulation are clearly identified, such as synchronous generator sets, grid-forming virtual inertia devices and grid-following virtual inertia devices, and a second objective function is established to reflect the relationship between frequency regulation cost and frequency regulation power. The second objective function includes the frequency regulation costs of all frequency regulation resources and takes into account the weighted sum of their frequency regulation power (generated power).

[0078] For each frequency regulation resource, corresponding power limit conditions are set according to its technical characteristics and safety requirements. These conditions can be expressed as the upper and lower limits of the frequency regulation power to ensure that the frequency regulation resources do not exceed their allowable range when outputting power generation power. Under the premise of meeting the power limit conditions, the second objective function is solved by an optimization algorithm (such as quadratic programming, genetic algorithm, etc.) to obtain the optimal frequency regulation power of each frequency regulation resource. During the optimization process, the output power of each frequency regulation resource should be iteratively adjusted until the optimal solution with the lowest total frequency regulation cost and meeting the power limit conditions is reached. Finally, according to the optimal frequency regulation power obtained by the optimization solution, the frequency regulation of each frequency regulation resource is controlled in real time. During the frequency regulation process, the frequency deviation of the power system and the output power of the frequency regulation resources can also be continuously monitored to ensure the dual realization of frequency regulation effect and economy.

[0079] In summary, constructing a second objective function with the minimum total frequency regulation cost of frequency regulation resources as the second control target, and limiting the output power of frequency regulation resources to meet the power limit conditions during the solution process can achieve the dual optimization effects of economy and safety.

[0080] Specifically, in step 102, regarding "taking the lowest point of the fluctuating power grid frequency as the first constraint condition to satisfy the safety constraint", the steps specifically include:

[0081] Step 1029: Construct a first constraint function with the lowest point of the fluctuating grid frequency satisfying a safety constraint as a first constraint condition. When solving the generated power output by each frequency regulation resource to eliminate the frequency deviation, the first constraint function is used to ensure that the lowest point of the fluctuating grid frequency always satisfies the safety constraint. The first constraint function is:

[0082] P(Δf≥-f lim )≥1-α,

[0083] P(Δf≥-f lim ) is the frequency deviation Δf greater than or equal to the opposite of the lowest grid frequency allowed by the low inertia power system -f lim The probability of Δf is the frequency deviation, -f lim is the opposite of the lowest point of the grid frequency, 1-α is the probability that the frequency deviation meets the safety constraint, which is at least 1-α, α is the probability that the frequency deviation allowed by the low inertia power system exceeds the safety range, f lim It is the minimum grid frequency allowed for low inertia power systems.

[0084] In the above embodiment of the present application, ensure that the lowest frequency f limSatisfy safety constraints. By setting safety constraints for the lowest point of the grid frequency, we can ensure that the grid frequency does not fall into an unsafe range during the frequency regulation process, thereby ensuring the stable operation of the power system. While meeting safety constraints, the output power of each frequency regulation resource can be adjusted more flexibly, eliminating frequency deviations in a more economical and efficient manner. In the face of uncertainties and disturbances in the grid, frequency regulation strategies that meet safety constraints can improve the system's robustness and response capabilities, ensuring that the grid frequency is stable under various operating conditions.

[0085] Specifically, a safety threshold for the lowest grid frequency should be set based on power system operating specifications and experience. This threshold should take into account the system's steady-state and transient frequency characteristics, as well as the response speed and capacity of the frequency regulation resources. The safety constraints should be converted into mathematical expressions to construct a first constraint function. This function should reflect the relationship between the lowest grid frequency and the output power of the frequency regulation resources, ensuring that the lowest frequency never falls below the safety threshold during the frequency regulation process.

[0086] The first constraint function is embedded in the frequency modulation model (the frequency response model of each frequency modulation resource) to ensure that the safety constraints are always met when solving the frequency modulation strategy. An optimization algorithm (such as linear programming, nonlinear programming, or heuristic algorithms) is used to solve the frequency modulation model and determine the optimal output power of each frequency modulation resource.

[0087] During the solution process, the output power of the frequency modulation resource should be adjusted iteratively and the lowest frequency point should be verified to meet the safety constraints. If not, the optimization algorithm or constraints should be adjusted until the optimal solution that meets the safety constraints is found.

[0088] Based on the optimal frequency regulation strategy obtained, each frequency regulation resource is controlled in real time. During the frequency regulation process, the changes in the grid frequency should be continuously monitored, and the frequency regulation strategy should be adjusted as needed to cope with new disturbances or uncertainties.

[0089] The implemented frequency regulation strategy can also be evaluated to analyze its effectiveness in eliminating frequency deviations, ensuring grid frequency security, and achieving economic efficiency. Based on the evaluation results, the frequency regulation strategy can be optimized and improved to enhance its adaptability and robustness.

[0090] In summary, constructing a first constraint function, where the minimum point of the fluctuating grid frequency satisfies the safety constraint, is crucial for ensuring the frequency stability and safety of the power system. By implementing these specific steps, a frequency regulation strategy that satisfies safety constraints can be developed and continuously optimized and improved to meet the actual needs of the power system.

[0091] Optionally, in step 102, “the third constraint condition of requiring the total power output of each frequency regulation resource to meet the total power demand of the low-inertia power system” specifically includes:

[0092] 10210. Construct a third constraint function with the third constraint condition that the total power generated by each frequency regulation resource must meet the total power demand of the low-inertia power system. When solving the power generated by each frequency regulation resource required to eliminate the frequency deviation, the third constraint function is used to ensure that the total power generated by each frequency regulation resource always meets the total power demand of the low-inertia power system. The third constraint function is:

[0093]

[0094] D tot is the total damping coefficient, and are the damping coefficient and inertia coefficient of the pth synchronous generator set, both of which are fixed constants. and are the damping coefficient and inertia coefficient of the qth meshed virtual inertial device, and are the damping coefficient and inertia coefficient of the jth meshed virtual inertial device, M tot is the sum of the inertia coefficients of each frequency regulation resource, l, m, and n are the total number of synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices in the low-inertia power system, respectively.

[0095] In the above embodiment of the present application, the power output of all frequency regulation resources must meet the total power balance of the load and the new energy power. By ensuring that the total power output of each frequency regulation resource meets the total power demand of the low-inertia power system, the power balance of the power system can be effectively maintained, and frequency instability caused by power shortage or surplus can be prevented. In a low-inertia power system, due to the reduction of system inertia, the response speed to power changes is required to be higher. Through the third constraint function, the output power of each frequency regulation resource can be controlled more accurately, thereby improving the stability and response speed of the system. On the premise of meeting the total power demand, the third constraint function can also guide each frequency regulation resource to allocate output power according to its own frequency regulation capability and economy, thereby achieving optimal resource allocation. In the face of uncertainties and disturbances in the power grid, the robustness of the system can be enhanced by a frequency regulation strategy that meets the total power demand, ensuring that the stable operation of the power system can be maintained under various working conditions.

[0096] Specifically, the total power demand of the low-inertia power system is determined based on factors such as the power system's load forecast, network structure, and power generation plan. Appropriate margin adjustments are made to the total power demand, taking into account the system's dynamic characteristics and uncertainties. The total system power demand is converted into a mathematical expression, and a third constraint function is constructed. This function should reflect the relationship between the total output power of each frequency regulation resource and the total system power demand, ensuring that the total output power consistently meets the system demand during the frequency regulation process.

[0097] Combining the third constraint function with the frequency response model of each frequency regulation resource (which should simulate the grid frequency response process and account for various uncertainties and disturbances), an optimization algorithm is used to solve the frequency regulation model and determine the optimal output power for each frequency regulation resource. During the solution process, the third constraint function must be satisfied, ensuring that the total output power of each frequency regulation resource equals the total system power demand. If the solution does not meet the constraint, the optimization algorithm or constraints are adjusted until an optimal solution that does meet the requirements is found. Based on the optimal frequency regulation strategy obtained, real-time frequency regulation control is implemented for each frequency regulation resource. During the frequency regulation process, grid frequency and power changes should be continuously monitored, and the frequency regulation strategy should be adjusted as needed to address new disturbances or uncertainties. The implemented frequency regulation strategy is evaluated to analyze its effectiveness in meeting the total system power demand, eliminating frequency deviations, and achieving economic efficiency. Based on the evaluation results, the frequency regulation strategy is optimized and improved to enhance its adaptability and robustness.

[0098] In summary, by constructing the third constraint function and following certain operating steps, it is possible to ensure that the output power of each frequency regulation resource is allocated and controlled while meeting the total power demand of the low-inertia power system, thereby ensuring the stable operation and frequency security of the power system.

[0099] Optionally, refer to Figure 2 As shown, step 103 regulates each frequency modulation resource to output the solved generated power, specifically including:

[0100] Step 1034: monitor the difference between the actual load and the predicted load in the low-inertia system in real time, and introduce the difference as error change information into the frequency response model constructed by each frequency regulation resource, so that the frequency response model controls the output of each frequency regulation resource based on the error change information.

[0101] Step 1035: Construct a power generation control equation including a control gain coefficient. Based on the power generation control equation, control each frequency modulation resource to output the solved power generation. The power generation control equation is:

[0102] P i (t+1)=P i(t)-K i Δf(t),

[0103] P i (t) and P i (t+1) is the power generation of the ith frequency regulation resource at the current moment t and the next moment, K i is the preset control gain coefficient of the i-th frequency modulation resource, and Δf(t) is the frequency deviation at the current time t.

[0104] In the above embodiment of the present application, the uncertainty of new energy is mainly reflected in the random fluctuation of its output, which can be predicted by power and random error ε RES To determine, as follows:

[0105]

[0106] in, For the predicted power of new energy, ε RES (t) is the random error, ε RES (t)~Ν(0,σ RES 2 ) indicates that the error follows a normal distribution, σ RES 2 The variance of renewable energy output indicates the degree of fluctuation. The load forecast error modeling has the same meaning as above. The load forecast error modeling is as follows:

[0107]

[0108] Based on the predicted power of renewable energy and load and their random error distribution, N scenarios are generated through the Monte Carlo sampling method. Each scenario contains the values ​​of renewable energy power and load power:

[0109]

[0110] in, Indicates the renewable energy power and load power in the i-th scenario; N is the number of scenarios. Specifically, when the gap is introduced as error change information into the frequency response model constructed by each frequency modulation resource, the following steps can be performed:

[0111] 1. Error modeling and real-time measurement: During the actual scheduling process, these errors are measured in real time (for example, monitoring the gap between actual load and predicted load), and then this error information is introduced into the frequency regulation control model.

[0112] 2. Power Regulation and Error Adjustment: When the system detects an error, the power output of the frequency modulation resource will be adjusted accordingly. Specifically, if the error is large, the power output may need to be increased to quickly restore the frequency. Conversely, if the error is large, the power output may be reduced to avoid over-regulation.

[0113] 3. Feedback mechanism: The control strategy uses feedback control to update the system status in real time. As the error changes, the control parameters (such as the inertia coefficient of the synchronous generator or the response gain of the virtual inertia device) are adjusted to ensure that the system can adapt to fluctuations in the prediction error.

[0114] 4. Probabilistic constraint: While combining the error, probabilistic constraint (probabilistic safety constraint in the first constraint function) can be added to ensure that the grid frequency can remain stable within a certain error tolerance range.

[0115] Next, in the power generation control equation, the output power is solved for, and the regulation coefficient, acting as the regulation gain, is a factor used to control how the frequency regulation resources adjust the output power. Generally, the regulation coefficient is given by system design and is not directly solved from the model. Instead, it is set during actual scheduling based on system needs and regulation objectives.

[0116] P i The calculation of P(t+1) is based on the power of the previous moment, plus the adjustment of Δf(t). In the three types of models (the frequency response models of synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices), each model calculates P at each moment. i (t), therefore, there is a prescribed reference power at the beginning of the calculation, and the subsequent P at each moment is deduced based on the three models (the frequency response model of each frequency modulation resource) i (t), the three types of resources are added together to obtain the total P i (t).

[0117] In particular, the frequency gain reflects the resource's ability to respond to frequency deviations. Since renewable energy output and load power are random, their power changes dynamically over time, for example, as follows:

[0118]

[0119] By applying the technical solution of this embodiment, the frequency regulation optimization model is improved to address the deficiencies in the frequency regulation of low-inertia power systems. By introducing the collaborative optimization of multiple control methods and modeling of uncertainties, the robustness and reliability of the system frequency regulation are improved. Specifically, the dynamic response characteristics of the grid-forming and grid-following virtual inertia devices are incorporated into the optimization model, achieving the collaborative optimization of multiple virtual inertia control methods and giving full play to the advantages of different types of frequency regulation resources. The covariance matrix of the new energy output forecast error and the load forecast error is used to construct an uncertainty penalty term, and the uncertainty factor is used as a key part of the optimization target, thereby enhancing the adaptability and robustness of the frequency regulation optimization scheme. Through the real-time dynamic feedback control mechanism, combined with the closed-loop adjustment of the frequency deviation and the real-time update of the forecast data, it is possible to quickly respond to frequency fluctuations and achieve a more efficient and flexible frequency regulation effect.

[0120] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or by hardware based on a low-inertia power system, wherein each frequency regulation resource constructs a frequency response model, with minimizing the lowest point of the fluctuating grid frequency as the first control target, minimizing the total frequency regulation cost of the frequency regulation resources as the second control target, satisfying the safety constraint at the lowest point of the fluctuating grid frequency as the first constraint, requiring the power generation output by each frequency regulation resource to satisfy the power limit as the second constraint, and requiring the total power generation output by each frequency regulation resource to satisfy the total power demand of the low-inertia power system as the third constraint. To solve the problem of eliminating frequency deviation, each frequency regulation resource needs to output its own power generation power, and the frequency regulation resources include synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices. The coordinated optimization of multiple frequency regulation resources is achieved, and the complex dynamic power system requirements can be met.

[0121] Those skilled in the art will understand that the accompanying drawings are only schematic diagrams of a preferred implementation scenario, and the processes in the accompanying drawings are not necessarily required to implement the present application.

[0122] The serial numbers of the above application are for descriptive purposes only and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosures are only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any changes that can be made by those skilled in the art should fall within the scope of protection of the present application.

Claims

1. A method for controlling the frequency of a power grid in a low-inertia power system, characterized in that: The method comprises: real-time monitoring of the grid frequency of the low-inertia power system and obtaining a frequency deviation of the monitored grid frequency relative to a preset standard grid frequency, wherein the grid frequency of the low-inertia power system fluctuates; Based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, minimizing the lowest point of the fluctuating grid frequency is used as the first control target, minimizing the total frequency regulation cost of the frequency regulation resources is used as the second control target, satisfying the safety constraint of the lowest point of the fluctuating grid frequency is used as the first constraint condition, requiring the generated power output by each frequency regulation resource to satisfy the power limit as the second constraint condition, and requiring the total generated power output by each frequency regulation resource to satisfy the total power demand of the low-inertia power system as the third constraint condition. In order to eliminate the frequency deviation, the generated power output by each frequency regulation resource is required, wherein the frequency regulation resources include synchronous generator sets, grid-forming virtual inertia devices, and grid-following virtual inertia devices. Minimizing the lowest point of the fluctuating grid frequency as the first control target includes: A first objective function is constructed with minimizing the lowest point of the fluctuating grid frequency as a first control objective. When solving the generated power output of each frequency regulation resource required to eliminate the frequency deviation, the lowest point of the fluctuating grid frequency is always minimized based on the first objective function. The first objective function is: ， Indicates the lowest point of the fluctuating grid frequency Minimize the first objective function of the first control objective, 、 and , are the total power shortage, total damping coefficient and total frequency regulation margin of the low inertia power system respectively; The second control objective of minimizing the total frequency regulation cost of frequency regulation resources includes: A second objective function is constructed with the minimum total frequency regulation cost of the frequency regulation resources as the second control objective. When solving the generated power required to be output by each frequency regulation resource to eliminate the frequency deviation, the total frequency regulation cost of the frequency regulation resources is always kept at the minimum based on the second objective function. The second objective function is: ， For the The unit frequency modulation cost of each frequency modulation resource, For the need The power output of each frequency regulation resource, is the total number of FM resources; Accordingly, the second constraint condition requiring the output power of each frequency modulation resource to meet the power limit includes: For any frequency modulation resource, the generated power output by the frequency modulation resource is limited to always meet a power limitation condition, wherein the power limitation condition is: ， For the The power generation of frequency regulation resources, The value range is the preset minimum power generation and preset maximum power generation between; Each frequency regulation resource is regulated to output the solved power generation power, wherein when the power generation power of the frequency regulation resource is changed, the grid frequency of the low inertia power system will change.

2. The method according to claim 1, characterized in that Based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, the generated power required to be output by each frequency regulation resource to eliminate the frequency deviation is solved, including: A frequency response model for the synchronous generator set is constructed based on the frequency deviation, as well as the inertia coefficient, damping coefficient, input mechanical power deviation, output power deviation, rotor inertia time constant, unit capacity, and rated frequency of the synchronous generator set, wherein the input mechanical power deviation is a known parameter and the output power deviation is a solution parameter; Based on the frequency response model, the output power deviation of the synchronous generator set is calculated to eliminate the frequency deviation. The frequency response model for the synchronous generator set is: ， ， is the frequency deviation, 、 、 、 、 、 and , respectively, are the inertia coefficient, damping coefficient, input mechanical power deviation, output power deviation, rotor inertia time constant, unit capacity and rated frequency of the synchronous generator set, is the time variable; Accordingly, regulating each frequency modulation resource to output the solved generated power includes: Based on the rated output power of the synchronous generator set and the solved output power deviation, the synchronous generator set is regulated to output power that can eliminate the frequency deviation.

3. The method according to claim 1, characterized in that The grid-type virtual inertia device includes a virtual synchronous generator. Based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, the generated power required to be output by each frequency regulation resource in order to eliminate the frequency deviation is solved, including: Constructing a dynamic response equation of the virtual synchronous generator based on the frequency deviation and the virtual inertia coefficient, virtual damping coefficient, and dynamic power change of the virtual synchronous generator in the networked virtual inertia device, and performing a Laplace transform on the dynamic response equation of the virtual synchronous generator to obtain a frequency response model for the networked virtual inertia device; Based on the dynamic response equation of the virtual synchronous generator, a dynamic power change amount output by the networked virtual inertia device is solved to eliminate the frequency deviation. Based on the frequency response model for the networked virtual inertia device and the dynamic power change amount, a frequency response change amount of the networked virtual inertia device is determined, wherein the dynamic response equation of the virtual synchronous generator is: ， The frequency response model for the networked virtual inertia device is: ， is the frequency deviation, 、 、 、 and , are the virtual inertia coefficient, virtual damping coefficient, dynamic power variation, frequency response variation and Laplace transform of the virtual synchronous generator in the networked virtual inertia device, is the time variable, For the frequency response model of the networked virtual inertia device, is a complex frequency variable; Accordingly, regulating each frequency modulation resource to output the solved generated power includes: Based on the frequency response variation, the networked virtual inertia device is regulated to output a power generation capable of eliminating the frequency deviation.

4. The method according to claim 1, wherein The grid-following virtual inertia device includes an inverter. Based on the frequency response model constructed by each frequency regulation resource in the low-inertia power system, the generated power required to be output by each frequency regulation resource in order to eliminate the frequency deviation is solved, including: Constructing an inverter dynamic response equation based on the frequency deviation, as well as a virtual inertia coefficient, a virtual damping coefficient, and a dynamic power change of the inverter in the grid-following virtual inertia device, and performing a Laplace transform on the inverter dynamic response equation to obtain a frequency response model for the grid-following virtual inertia device; Based on the inverter dynamic response equation, a dynamic power change amount output by the grid-following virtual inertia device is solved to eliminate the frequency deviation. Based on the frequency response model for the grid-following virtual inertia device and the dynamic power change amount, a frequency response change amount of the grid-following virtual inertia device is determined, wherein the inverter dynamic response equation is: ， The frequency response model for the network-following virtual inertia device is: ， Accordingly, regulating each frequency modulation resource to output the solved generated power includes: Based on a fast power compensation model and the frequency response variation, the dynamic power variation of the grid-following virtual inertia device is regulated so that the grid-following virtual inertia device outputs a generated power capable of eliminating the frequency deviation based on the dynamic power variation, wherein the fast power compensation model is: ， is the frequency deviation, 、 、 、 、 and , are the virtual inertia coefficient, virtual damping coefficient, dynamic power variation, frequency regulation margin, frequency response variation and Laplace transform of dynamic power variation of the inverter in the grid-following virtual inertia device, is the time variable, is the time constant, It is the frequency response model for the network-following virtual inertia device. is a complex frequency variable.

5. The method according to claim 1, wherein The first constraint condition is that the lowest point of the fluctuating power grid frequency satisfies the safety constraint, including: A first constraint function is constructed with the lowest point of the fluctuating grid frequency satisfying a safety constraint as a first constraint condition. When solving the generated power output of each frequency regulation resource required to eliminate the frequency deviation, the lowest point of the fluctuating grid frequency is ensured to always satisfy the safety constraint based on the first constraint function. The first constraint function is: ， is the frequency deviation Greater than or equal to the opposite of the lowest grid frequency allowed for low inertia power systems The probability of is the frequency deviation, is the opposite number of the lowest point of the grid frequency, The probability that the frequency deviation satisfies the safety constraint is at least , is the probability that the frequency deviation allowed by the low inertia power system exceeds the safety range, It is the minimum grid frequency allowed for low inertia power systems.

6. The method according to claim 1, characterized in that The third constraint condition is that the total power generated by each frequency regulation resource must meet the total power demand of the low-inertia power system, including: A third constraint function is constructed, with the third constraint condition that the total power generated by each frequency regulation resource must meet the total power demand of the low-inertia power system. When solving the power generated by each frequency regulation resource required to eliminate the frequency deviation, the third constraint function is used to ensure that the total power generated by each frequency regulation resource always meets the total power demand of the low-inertia power system. The third constraint function is: ， is the total damping coefficient, and Respectively The damping coefficient and inertia coefficient of each synchronous generator set are fixed constants. and Respectively The damping coefficient and inertia coefficient of a networked virtual inertial device, and Respectively The damping coefficient and inertia coefficient of a networked virtual inertial device, is the sum of the inertia coefficients of each frequency modulation resource, 、 and They are the total number of synchronous generator sets, grid-forming virtual inertia devices and grid-following virtual inertia devices in the low-inertia power system.

7. The method according to any one of claims 1 to 6, characterized in that Before regulating each frequency modulation resource to output the solved generated power, the method further includes: The gap between the actual load and the predicted load in the low-inertia system is monitored in real time, and the gap is introduced as error change information into the frequency response model constructed by each frequency regulation resource, so that the frequency response model controls the output of each frequency regulation resource to obtain the solved power generation power based on the error change information.

8. The method according to claim 7, characterized in that The regulating each frequency modulation resource to output the solved generated power includes: Construct a power generation control equation including a control gain coefficient. Based on the power generation control equation, control each frequency modulation resource to output the solved power generation. The power generation control equation is: ， and Respectively FM resources are currently The power generation at this moment and the next moment, For the The preset control gain coefficient of each FM resource, For the current Frequency deviation at a given moment.

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