A power system inertia constant adaptive control method and system

Abstract

The present application belongs to the technical field of power system control, and particularly relates to a power system inertia constant adaptive control method and system, which comprises the following steps: processing the collected voltage and current signals by using phase synchronization and frequency tracking technology to obtain the grid measurement frequency, and obtaining the rated frequency and sampling period in advance; taking the difference between the grid measurement frequency and the rated frequency as the frequency deviation; obtaining the frequency change rate; obtaining the frequency phase plane energy index; calculating the inertia adjustment tendency index; obtaining the adaptive inertia control coefficient; substituting the adaptive inertia control coefficient into the virtual synchronous generator swing equation to construct the dynamic relationship of the inverter output frequency; and obtaining the output angular frequency and voltage phase angle by integrating the swing equation. The present application effectively solves the technical problems of insufficient inertia of power electronic equipment in the power system, inability of fixed parameter control to balance the anti-disturbance and recovery demand, and poor frequency stability.

Description

Technical Field

[0001] This invention relates to the field of power system control technology. More specifically, this invention relates to an adaptive control method and system for the inertia constant of a power system. Background Technology

[0002] With the escalating global energy crisis and the advancement of dual-carbon goals, the proportion of new energy power generation, represented by wind and solar power, is continuously increasing. The power system is undergoing a profound transformation from being dominated by traditional synchronous machines to being dominated by power electronics. Grid-connected inverters, as the core interface for new energy to access the grid, have largely replaced traditional rotating electric machines.

[0003] However, power electronic devices lack a physical rotor, and their low inertia and weak damping characteristics significantly reduce the frequency immunity of the power grid when facing load disturbances or faults. The frequency change rate is easily exceeded, seriously threatening the safe and stable operation of the power system. Virtual synchronous generator technology, by simulating the rotor motion equations and excitation characteristics of a synchronous generator in the control algorithm, endows inverter-like synchronous machines with inertia and damping support capabilities, becoming a key technology for solving the low inertia problem.

[0004] However, existing VSG control strategies typically employ fixed rotational inertia parameters. In the initial stages of system disturbance, a large inertia is needed to suppress rapid frequency changes; however, during the recovery phase from extreme values ​​back to the rated value, excessive inertia can generate a large inertial torque, hindering frequency return and leading to prolonged settling time or even system power oscillations. This contradiction between large inertia disturbance rejection and small inertia recovery is an inherent flaw of fixed-parameter control, making it difficult to balance dynamic response speed and steady-state regulation accuracy, thus limiting the further application of virtual synchronous generator technology in high-proportion renewable energy power systems. Summary of the Invention

[0005] To address the technical problems of insufficient inertia of power electronic equipment in the aforementioned power systems, the inability of fixed parameter control to simultaneously meet disturbance rejection and recovery requirements, and poor frequency stability, this invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides an adaptive control method for the inertia constant of a power system, comprising: The acquired voltage and current signals are processed using phase synchronization and frequency tracking technology to obtain the grid measurement frequency, and the rated frequency and sampling period are pre-acquired. The difference between the grid measurement frequency and the rated frequency is recorded as the frequency deviation. The deviation increment is calculated based on the frequency deviation at the current and previous sampling times, and discrete differential calculation is performed in conjunction with the sampling period to obtain the frequency change rate. The frequency deviation and the frequency change rate are weighted and summed to obtain the frequency phase plane energy index. Based on the correlation between the signs of the frequency change direction and its acceleration direction, and combined with the energy characteristic index, the inertial adjustment tendency index is calculated. The pre-acquired reference moment of inertia is dynamically corrected according to the inertial adjustment tendency index to obtain the adaptive inertial control coefficient. The adaptive inertial control coefficient is substituted into the virtual synchronous generator swing equation to construct the dynamic relationship of the inverter output frequency. The swing equation is integrally solved to obtain the output angular frequency and voltage phase angle, driving the grid-connected inverter to operate.

[0007] This invention achieves dynamic adaptive adjustment of inertial parameters by accurately acquiring signals and calculating various state indicators. When the system's operating state deteriorates, it can promptly increase inertia to resist fluctuations; during the recovery phase, it can decrease inertia to accelerate the return to stability. This adjustment method avoids rapid frequency changes or slow recovery, reduces the risk of oscillations, and enhances the system's ability to cope with disturbances. Simultaneously, through a scientific calculation model and smooth parameter correction, it ensures the stability of the adjustment process, avoids secondary shocks, and allows the power system to maintain safe and stable operation even with the increasing proportion of renewable energy, thus compensating for the shortcomings of traditional fixed-parameter control.

[0008] Preferably, obtaining the power grid measurement frequency and pre-obtaining the rated frequency and sampling period includes: The three-phase voltage and current signals are acquired in real time through the high-precision voltage and current transformers at the inverter port. The three-phase voltage signals are input to the software phase-locked loop module for phase tracking and frequency calculation to obtain the grid measurement frequency. At the same time, the standard operating frequency of the system is obtained from the database and recorded as the rated frequency, as well as the discrete sampling time interval of the digital control system and recorded as the sampling period.

[0009] Preferably, the difference between the measured frequency and the rated frequency is recorded as the frequency deviation, including: Obtain the power grid measurement frequency and the rated frequency, and record the difference between the power grid measurement frequency and the rated frequency as the frequency deviation.

[0010] Preferably, obtaining the rate of change of frequency includes: Obtain the frequency deviation at the current sampling time and retrieve the frequency deviation at the previous sampling time; calculate the difference between the frequency deviation at the current sampling time and the frequency deviation at the previous sampling time to obtain the frequency deviation increment; obtain the sampling period; divide the frequency deviation increment by the sampling period to obtain the frequency change rate.

[0011] Preferably, the frequency phase plane energy index satisfies the following expression: ; In the formula, This indicates the frequency phase plane energy index; This is for frequency deviation; The rate of change of frequency; This is the normalized time constant, and its unit is square seconds.

[0012] This invention comprehensively considers the degree of frequency deviation and the rate of change to form an index that reflects the overall stability of the system. This index can reflect the degree of instability of the system; the larger the value, the higher the risk, providing a clear basis for whether further adjustments are needed.

[0013] Preferably, the inertial adjustment tendency index satisfies the following expression: ; In the formula, Indicators representing the tendency of inertial adjustment; This refers to the energy index of the phase plane at the frequency. This is for frequency deviation; The rate of change of frequency; It is a very small positive number, and the denominator is guaranteed to be non-zero.

[0014] This invention can clearly identify whether a system is in a deterioration or recovery phase, guiding whether the inertial parameter should be increased or decreased. It effectively solves the problem of blindness in traditional fixed adjustments, allowing inertial adjustments to better meet actual needs and achieve flexible adjustment that strengthens when necessary and weakens when appropriate.

[0015] Preferably, obtaining the adaptive inertial control coefficients includes: Obtain the inertia adjustment tendency index, read the reference moment of inertia and adjustment gain coefficient from the database; calculate the product of the adjustment gain coefficient and the inertia adjustment tendency index to obtain the inertia correction increment; calculate the sum of the inertia correction increment and the value 1 to obtain the inertia adjustment ratio; calculate the product of the reference moment of inertia and the inertia adjustment ratio to obtain the adaptive inertia control coefficient.

[0016] This invention dynamically corrects a preset benchmark value based on an adjustment tendency index to obtain inertial parameters adapted to the current state. This correction method allows for smooth changes in inertial parameters, avoiding secondary shocks caused by sudden changes, while flexibly adapting to different operating scenarios. It makes inertial adjustment more precise, ensuring the ability to cope with disturbances without affecting the system's recovery speed.

[0017] Preferably, the swing equation satisfies the following expression: ; In the formula, This represents the reference value for active power. This indicates the output active power measurement value; Represents the adaptive inertial control coefficients; This indicates the inverter's output angular frequency; This represents the time derivative of the inverter's output angular frequency; Indicates the damping coefficient; Indicates the rated angular frequency.

[0018] This invention integrates various parameters to construct a dynamic relationship model, clarifying the correlation between energy balance and frequency change. This model can simulate the stability characteristics of traditional equipment, enabling power electronic devices to have similar adjustment capabilities and avoid rapid frequency drift.

[0019] Preferably, the output angular frequency and voltage phase angle are obtained by integrating the swing equation, including: Based on the swing equation, the inverter output angular frequency at the current moment is calculated by discrete integration in the digital controller; the voltage phase angle is obtained by time integration of the inverter output angular frequency at the current moment; and the calculated voltage phase angle is converted into six PWM drive pulses using pulse width modulation control technology to control the on and off of the power switching transistors inside the inverter, thereby outputting three-phase AC power.

[0020] Secondly, the present invention provides an adaptive control system for the inertial constant of a power system, comprising a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned adaptive control method for the inertial constant of a power system is implemented.

[0021] By adopting the above technical solution, a computer program for the adaptive control method of inertial constant of a power system is generated and stored in a memory so that it can be loaded and executed by a processor. Terminal equipment can then be made based on the memory and the processor for convenient use.

[0022] The beneficial effects of this invention are as follows: by optimizing the regulation methods of power equipment, it improves the operational stability and flexibility of the entire power system, reducing operational risks caused by fluctuations. It requires no large-scale modification of existing equipment; performance improvements can be achieved through algorithm optimization, demonstrating good practicality and economy. The application of this technology helps promote the utilization of clean energy sources such as wind and solar power, contributing to the achievement of dual-carbon goals, while ensuring a reliable and stable power supply, providing solid power security for industrial production and daily life, and driving the power system towards a more efficient, stable, and environmentally friendly direction. Attached Figure Description

[0023] Figure 1 The flowchart of an adaptive control method for the inertia constant of a power system according to the present invention is shown schematically. Figure 2 The diagram illustrates the energy characteristics and inertial regulation tendency indices in this invention. Figure 3 The diagram illustrates the effect of adaptive inertial control in this invention. Detailed Implementation

[0024] This invention discloses an adaptive control method for the inertia constant of a power system, referring to... Figure 1 This includes steps S1-S4: S1: The acquired voltage and current signals are processed using phase synchronization and frequency tracking technology to obtain the power grid measurement frequency, and the rated frequency and sampling period are obtained in advance.

[0025] It should be noted that in power electronic grid-connected systems, the grid environment is complex and variable, and voltage signals often contain harmonic interference and transient noise. If simple methods such as zero-crossing detection are used to obtain the frequency directly, the measured value is easily affected by signal distortion, leading to jumps and subsequent controller malfunctions. The phase synchronization and frequency tracking technology in this invention is a phase-locked loop (PLL) technology. Through an internal closed-loop regulation mechanism, it can accurately extract the phase and frequency information of the fundamental voltage while suppressing noise interference, providing a highly reliable input reference for subsequent inertial control. Furthermore, digital control systems are essentially discrete systems, and the sampling period directly determines the system's sensitivity to dynamic capture of the grid frequency and the update frequency of control commands. An excessively large sampling period will introduce significant delays, weakening the timeliness of the inertial response. A reasonable sampling period setting is a prerequisite for ensuring that the discrete model approximates the characteristics of a continuous physical system, guaranteeing the numerical stability of subsequent differential and integral control operations.

[0026] Specifically, the acquired voltage and current signals are processed using phase synchronization and frequency tracking techniques to obtain the power grid measurement frequency, and the rated frequency and sampling period are pre-acquired, including: The three-phase voltage and current signals are acquired in real time through the high-precision voltage and current transformers at the inverter port. The three-phase voltage signals are input to the software phase-locked loop module for phase tracking and frequency calculation to obtain the grid measurement frequency. At the same time, the standard operating frequency of the system is obtained from the database and recorded as the rated frequency, as well as the discrete sampling time interval of the digital control system and recorded as the sampling period.

[0027] Thus, the power grid measurement frequency, rated frequency, and sampling period were obtained.

[0028] S2: The difference between the measured frequency of the power grid and the rated frequency is recorded as the frequency deviation; the deviation increment is calculated based on the frequency deviation at the current and previous sampling times, and discrete differential calculation is performed in combination with the sampling period to obtain the frequency change rate; the frequency deviation and the frequency change rate are weighted and squared to obtain the frequency phase plane energy index.

[0029] It is important to note that the steady-state operation of a power system depends on the balance between active power supply and demand. Macroscopically, this means the frequency remains at its rated value, such as 50Hz or 60Hz. Once disturbances such as a sudden increase in load or the disconnection of generating units occur, the balance is disrupted, and the frequency drifts. Frequency deviation is not merely a numerical difference; it physically reflects the degree of power deficit or surplus in the system. In adaptive control strategies, frequency deviation is the most fundamental error signal, equivalent to the proportional term input in the control loop. Only by quantifying this deviation accurately and in real time can the control system determine whether the power grid is in a power deficit or power surplus state, thereby deciding the direction and intensity of subsequent power support. Without calculating this deviation, the system will lose its target benchmark for regulation and will be unable to achieve regression control towards the steady-state operating point.

[0030] Specifically, the difference between the measured frequency and the rated frequency is recorded as the frequency deviation, which includes: Obtain the power grid measurement frequency and the rated frequency, and record the difference between the power grid measurement frequency and the rated frequency as the frequency deviation.

[0031] Thus, the frequency deviation was obtained.

[0032] It should be noted that frequency deviation alone cannot fully describe the dynamic behavior of the power grid. At the initial moment of a disturbance, the frequency deviation may be small, but its rate of decrease or increase, i.e., the rate of frequency change, may already be extremely large, indicating a huge power surge. From the physical mechanism of inertial response, the output of inertial power is proportional to the rate of frequency change, not the frequency deviation. Therefore, obtaining the rate of frequency change is a key step in simulating the rotor inertial characteristics of a synchronous generator. Since continuous differentiation is not possible in practical digital systems, a discrete difference method is required for approximate solution. This invention extracts the speed information of frequency fluctuations by comparing the deviation changes at adjacent sampling times and combining them with a time base. This allows the control system not only to sense how much deviation has occurred but also to predict how fast the deviation will occur, thereby reducing losses before the anomaly becomes severe.

[0033] Preferably, the frequency change rate is obtained by calculating the frequency increment based on the frequency deviation at the current and previous sampling times, and performing discrete differential calculations in conjunction with the sampling period, including: Obtain the frequency deviation at the current sampling time and retrieve the frequency deviation at the previous sampling time; calculate the difference between the frequency deviation at the current sampling time and the frequency deviation at the previous sampling time to obtain the frequency deviation increment; obtain the sampling period; divide the frequency deviation increment by the sampling period to obtain the frequency change rate.

[0034] Thus, the rate of change of frequency was obtained.

[0035] It should be noted that a single-dimensional rate of frequency change is insufficient to comprehensively reflect the system's safety status. For example, a small deviation coupled with a large rate of frequency change, or a large deviation coupled with a small rate of frequency change, may correspond to different risk levels. The phase plane analysis method is introduced to map the system state onto a two-dimensional space composed of displacement and velocity. From this perspective, the system's frequency fluctuations are considered an energy oscillation process. The constructed energy characteristic index is similar to a Lyapunov function, where the deviation term represents the system's potential energy deviation, and the rate of change term represents the system's kinetic energy trend. Through this comprehensive energy index, the complex dynamic process can be compressed into a scalar. The larger the scalar value, the stronger the current frequency fluctuation energy of the system, and the higher the risk of deviating from steady state. This provides a physically meaningful calculation basis for subsequent judgments on whether strong inertial intervention is necessary. This expression directly analogous to the basic model in classical physics: total energy = potential energy + kinetic energy, and is a universally standardized method in the field of power system frequency stability analysis.

[0036] Preferably, a weighted sum of squares is calculated on the frequency deviation and the rate of frequency change to obtain the frequency phase plane energy index, including: The frequency phase plane energy index satisfies the following expression: ; In the formula, This indicates the frequency phase plane energy index; This is for frequency deviation; The rate of change of frequency; This is the normalized time constant, with units of square seconds, used to balance the dimensional differences between the frequency deviation term and the frequency change rate term and adjust their weights.

[0037] In the formula, The potential energy deviation of the system was simulated, characterizing the displacement energy of the system deviating from the equilibrium point. Its physical essence corresponds to the cumulative effect of active power supply and demand imbalance in the power system. The larger the absolute value, the further the system frequency deviates from the rated value, the more significant the static potential energy of power imbalance, and the stronger the adjustment force is needed to counteract this deviation. The kinetic energy trend of the system was simulated, characterizing the dynamic energy of frequency changes. It directly reflects the speed of frequency fluctuations. The larger the value, the higher the instantaneous intensity of the power surge and the greater the risk of dynamic disturbances faced by the system. As the sum of the two energies, it comprehensively reflects the total energy level at the current state point. or When the absolute value increases, It increases significantly on a quadratic scale. The nonlinear characteristics of the amplified system are a risk signal that deviates significantly from the steady state, providing a basis for judging the risk level for subsequent inertial adjustment. That is, the higher the energy, the more unstable the system is, and the more necessary it is to adjust the inertial parameters to suppress disturbances or accelerate recovery.

[0038] For example, setting ,like , ,but .

[0039] Thus, the frequency phase plane energy index was obtained.

[0040] S3: Based on the correlation between the signs of the frequency change direction and the acceleration direction, and combined with the energy characteristic index, calculate the inertial adjustment tendency index; dynamically correct the pre-acquired reference moment of inertia according to the inertial adjustment tendency index to obtain the adaptive inertial control coefficient; substitute the adaptive inertial control coefficient into the virtual synchronous generator swing equation to construct the dynamic relationship of the inverter output frequency.

[0041] It should be noted that blindly increasing inertia during frequency regulation is not always reasonable. When the frequency is accelerating away from the rated value, a large amount of inertia is needed to suppress this trend. However, when the frequency has already passed the extreme point and is recovering to the rated value, excessive inertia will hinder the frequency's return and slow down the system's recovery speed. Therefore, it is necessary to identify the current dynamic stage of the system and accurately determine the direction of frequency movement by analyzing the sign relationship between frequency deviation and the rate of frequency change. This invention combines this directional logic with the frequency phase plane energy index to construct an inertial regulation tendency index. This inertial regulation tendency index has intelligent decision-making capabilities, that is, it outputs a high value when disturbance rejection is needed and a low value or even a negative value when recovery is needed. This mechanism can effectively solve the contradiction between speed and overshoot in traditional fixed inertial control.

[0042] It should be noted that the inertial regulation tendency index expression in this invention is constructed based on the physical laws of power system frequency stability control. First, all addition and subtraction operations in the inertial regulation tendency index expression ensure complete dimensional uniformity, with the final output dimension being seconds, perfectly matching the standard dimension of the power system's inertial time constant, providing a compliant physical quantity input for subsequent inertial parameter correction. Second, by correlating the signs of frequency deviation and frequency change rate, the inertial regulation tendency index expression accurately identifies whether the system is in a frequency deterioration or recovery phase, realizing an adaptive adjustment logic of increasing inertial disturbance rejection during deterioration and decreasing inertial acceleration during recovery, conforming to the objective physical laws of synchronous generator rotor motion. Finally, the inertial regulation tendency index expression only includes core state variables strongly correlated with inertial regulation, achieving precise quantification of the direction and intensity of inertial regulation through the simplest four arithmetic operations, consistent with engineering practice principles.

[0043] Specifically, based on the correlation between the signs of frequency change direction and acceleration direction, and combined with energy characteristic indicators, inertial adjustment tendency indicators are calculated, including: The inertial accommodation tendency index satisfies the following expression: ; In the formula, Indicators representing the tendency of inertial adjustment; This refers to the energy index of the phase plane at the frequency. This is for frequency deviation; The rate of change of frequency; It is a very small positive number, and the denominator is guaranteed to be non-zero.

[0044] In the formula, This constitutes a soft symbolic function, when and When the same sign appears, it indicates that the frequency is rapidly deviating from the rated value, and the system is in a deteriorating phase. When it is a positive value; and When the sign is different, it indicates that the frequency is decelerating or returning to its rated value, and the system is in the recovery phase. It is a negative value.

[0045] For example, , and The same sign makes the product term positive, and the product term is calculated. If the value is positive, round it to one decimal place; there is another case, and The opposite signs make the product term negative, and the calculation is as follows: It is a negative value.

[0046] It should be noted that, Figure 2 This is a graph showing the energy characteristics and inertial regulation tendency indicators. The graph includes an energy index curve representing the total energy of the system's frequency fluctuations and a tendency index curve reflecting the direction and intensity of inertial regulation decisions. In the initial stage of the disturbance, the frequency deviation and the rate of frequency change have the same sign, and both the energy index curve and the inertial regulation tendency index curve show an upward trend, reflecting the accumulation of system fluctuation energy.

[0047] Thus, the inertial adjustment tendency index was obtained.

[0048] It should be noted that the reference moment of inertia of a virtual synchronous generator is usually a fixed value pre-designed based on the inverter's capacity and allowable frequency variation range. It represents the system's disturbance rejection capability under nominal conditions. However, to cope with complex and ever-changing grid disturbances, a fixed reference value alone is insufficient. The core of this invention lies in establishing a mapping channel from situational awareness to parameter execution. By utilizing an inertial adjustment tendency index, the reference moment of inertia is multiplicatively modulated in real time. This modulation method ensures a smooth transition of control parameters and avoids secondary shocks caused by parameter abrupt changes.

[0049] Preferably, the pre-acquired reference moment of inertia is dynamically corrected according to the inertia adjustment tendency index to obtain adaptive inertia control coefficients, including: Obtain the inertia adjustment tendency index, read the reference moment of inertia and adjustment gain coefficient from the database; calculate the product of the adjustment gain coefficient and the inertia adjustment tendency index to obtain the inertia correction increment; calculate the sum of the inertia correction increment and the value 1 to obtain the inertia adjustment ratio; calculate the product of the reference moment of inertia and the inertia adjustment ratio to obtain the adaptive inertia control coefficient.

[0050] It should be noted that the reference moment of inertia is a fixed value or equivalent inertial time constant preset before the controller leaves the factory or during the commissioning stage, based on core parameters such as the rated capacity of the grid-connected inverter, the allowable frequency fluctuation range of the power grid, and the power response characteristics of the new energy power generation unit. In this invention, it is set to 4s. The adjustment gain coefficient is a proportional coefficient preset to adapt to different power grid disturbance scenarios and flexibly adjust the change amplitude of the inertial parameters. It is stored in the controller's control algorithm parameter library, and its value needs to be set in combination with the system stability requirements: if the gain coefficient is too large, it may cause a sudden change in the inertial parameters, causing system power oscillations; if it is too small, it will weaken the sensitivity of adaptive adjustment and fail to respond to severe disturbances in time. In practical applications, it can be dynamically fine-tuned according to scenarios such as the penetration rate of new energy in the power grid and load fluctuation characteristics, but it remains fixed within a single control cycle and is used to multiply with the inertial adjustment tendency index to quantify the magnitude of inertial correction. In this invention, it is set to 0.3.

[0051] Thus, the adaptive inertial control coefficients were obtained.

[0052] It should be noted that the swing equation is the mathematical description of the rotor kinematics of a synchronous generator and the core of the virtual synchronous generator control strategy. It establishes the physical relationship between unbalanced power and rotor angular acceleration. In traditional VSGs, the inertia coefficient in the equation is constant, resulting in a single dynamic response. This invention incorporates an adaptive inertia coefficient into the swing equation, giving the inverter a virtual rotor with variable mass. That is, when the grid is impacted, this virtual rotor can instantly become heavier to resist frequency changes; when the impact disappears and recovery is needed, it can instantly become lighter to quickly stabilize.

[0053] It should be noted that the swing equation in this invention is the standard mathematical description of the rotor motion of a synchronous generator, which has been used in the power industry for decades and is known as Newton's second law of motion for power systems, perfectly conforming to the classical physical laws of rigid body rotation. This invention replaces the fixed inertia coefficient in the traditional scheme with an adaptive inertia control coefficient, enabling the swing equation to respond in real time to dynamic changes in the grid frequency, giving the inverter the adaptive adjustment capability of increasing inertia during disturbances and decreasing inertia during recovery. The dimensions on both sides of the swing equation are completely unified; the dimension of the unbalanced power on the left is watt, and the dimensions of both terms on the right are watts, conforming to the objective physical laws of power balance.

[0054] Preferably, the adaptive inertial control coefficients are substituted into the virtual synchronous generator swing equation to construct the dynamic relationship of the inverter output frequency, including: The active power reference value and damping coefficient are obtained from the database. The output active power measurement value is obtained by multiplying the actual collected voltage and current signals. The product of the rated frequency and 2π is recorded as the rated angular frequency. The inverter output angular frequency of the previous control cycle is obtained.

[0055] The swing equation satisfies the following expression: ; In the formula, This represents the reference value for active power. This indicates the output active power measurement value; Represents the adaptive inertial control coefficients; This indicates the inverter's output angular frequency; This represents the time derivative of the inverter's output angular frequency; Indicates the damping coefficient; Indicates the rated angular frequency.

[0056] In the formula, This represents the difference between the active power reference value and the active power measurement value, indicating the unbalanced power. If the former is greater than the latter, it indicates excess energy, driving the rotor to accelerate. If the former is less than the latter, it indicates insufficient energy, causing the rotor to decelerate and release kinetic energy. Simulating the rotor inertia effect of a synchronous generator is the core component for inverters to achieve large inertia disturbance rejection and small inertia recovery, which is equivalent to a buffer to suppress frequency mutations. The damping torque effect of a synchronous generator is simulated to suppress frequency oscillations and accelerate the return of the frequency to a steady state. This indicates that the unbalanced power driving force on the left and the anti-interference feedback force on the right are always dynamically balanced. The inverter output angular frequency is calculated using the virtual synchronous generator swing equation to avoid directly letting the inverter follow the grid frequency output. Once the grid is disturbed, the frequency will drift rapidly and may even cause a chain of faults.

[0057] For example, when When increased, for the same power difference According to the rocking equation, The frequency will decrease accordingly, thereby slowing down the frequency change and suppressing the disturbance.

[0058] Thus, the swing equation was obtained.

[0059] S4: Integrate the swing equation to obtain the output angular frequency and voltage phase angle, and drive the grid-connected inverter to operate.

[0060] It's important to note that the swing equation only provides the differential relationship of frequency change. However, the control signals from the inverter's underlying hardware require specific voltage amplitude and phase information. Therefore, the differential equation needs to be solved using numerical integration. First, integration yields the angular frequency, which determines the periodicity of the output voltage. Second, integration yields the voltage phase angle, which determines the instantaneous position of the output voltage waveform. This process completes the final conversion from a mechanical model to an electrical signal. Finally, space vector pulse width modulation (SVPWM) technology is used to convert the calculated continuous phase angle signal into discrete power switch on / off commands. SVPWM technology efficiently utilizes the DC bus voltage, reduces output harmonics, and ensures that the AC power actually generated by the inverter faithfully reproduces the dynamic trajectory planned by the swing equation, thereby achieving active support for the grid frequency.

[0061] Specifically, the output angular frequency and voltage phase angle are obtained by integrating the swing equation, which drives the grid-connected inverter to operate, including: Based on the swing equation, the inverter output angular frequency at the current moment is calculated by discrete integration in the digital controller; the voltage phase angle is obtained by time integration of the inverter output angular frequency at the current moment; and the calculated voltage phase angle is converted into six PWM drive pulses using pulse width modulation control technology to control the on and off of the power switching transistors inside the inverter, thereby outputting three-phase AC power.

[0062] It should be noted that, Figure 3 This is a diagram illustrating the effect of adaptive inertial control. The diagram includes the power grid frequency deviation curve and the dynamic curve of the adaptive inertial control coefficient. In the initial stage of power grid disturbance, the frequency deviation curve, i.e., the system frequency, drops rapidly, while the adaptive inertial control coefficient, i.e., the adaptive moment of inertia, rises rapidly to its peak value. By increasing inertia, the rate of frequency drop is significantly slowed down, thus preventing the frequency change rate from exceeding the limit.

[0063] Thus, an adaptive control method for the inertia constant of a power system has been completed.

[0064] This invention also discloses an adaptive control system for the inertial constant of a power system, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement an adaptive control method for the inertial constant of a power system according to the present invention.

[0065] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0066] While this specification has shown and described numerous embodiments of the invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will occur to those skilled in the art without departing from the spirit and essence of the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in the practice of this invention.

Claims

1. An adaptive control method for the inertia constant of a power system, characterized in that, include: The acquired voltage and current signals are processed using phase synchronization and frequency tracking technology to obtain the power grid measurement frequency, and the rated frequency and sampling period are obtained in advance. The difference between the measured frequency and the rated frequency is recorded as the frequency deviation; the deviation increment is calculated based on the frequency deviation at the current and previous sampling times, and discrete differential calculation is performed in conjunction with the sampling period to obtain the frequency change rate; The frequency phase plane energy index is obtained by calculating the weighted sum of squares of the frequency deviation and the frequency change rate. Based on the correlation between the signs of frequency change direction and acceleration direction, and combined with energy characteristic indicators, the inertial adjustment tendency index is calculated; the pre-acquired reference moment of inertia is dynamically corrected according to the inertial adjustment tendency index to obtain the adaptive inertial control coefficient; the adaptive inertial control coefficient is substituted into the virtual synchronous generator swing equation to construct the dynamic relationship of the inverter output frequency. The output angular frequency and voltage phase angle are obtained by integrating the swing equation, which drives the grid-connected inverter to operate.

2. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The process of obtaining the power grid measurement frequency and pre-acquiring the rated frequency and sampling period includes: The three-phase voltage and current signals are acquired in real time through the high-precision voltage and current transformers at the inverter port. The three-phase voltage signals are input to the software phase-locked loop module for phase tracking and frequency calculation to obtain the grid measurement frequency. At the same time, the standard operating frequency of the system is obtained from the database and recorded as the rated frequency, as well as the discrete sampling time interval of the digital control system and recorded as the sampling period.

3. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The term "frequency deviation" refers to the difference between the measured frequency and the rated frequency of the power grid. Obtain the power grid measurement frequency and the rated frequency, and record the difference between the power grid measurement frequency and the rated frequency as the frequency deviation.

4. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The acquisition of the frequency change rate includes: Obtain the frequency deviation at the current sampling time and retrieve the frequency deviation at the previous sampling time; calculate the difference between the frequency deviation at the current sampling time and the frequency deviation at the previous sampling time to obtain the frequency deviation increment; obtain the sampling period; divide the frequency deviation increment by the sampling period to obtain the frequency change rate.

5. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The frequency phase plane energy index satisfies the following expression: ； In the formula, This indicates the frequency phase plane energy index; This is for frequency deviation; The rate of change of frequency; This is the normalized time constant, and its unit is square seconds.

6. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The inertial adjustment tendency index satisfies the following expression: ； In the formula, Indicators representing the tendency of inertial adjustment; This refers to the energy index of the phase plane at the frequency. This is for frequency deviation; The rate of change of frequency; It is a very small positive number, and the denominator is guaranteed to be non-zero.

7. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The process of obtaining the adaptive inertial control coefficients includes: Obtain the inertia adjustment tendency index, read the reference moment of inertia and adjustment gain coefficient from the database; calculate the product of the adjustment gain coefficient and the inertia adjustment tendency index to obtain the inertia correction increment; calculate the sum of the inertia correction increment and the value 1 to obtain the inertia adjustment ratio; calculate the product of the reference moment of inertia and the inertia adjustment ratio to obtain the adaptive inertia control coefficient.

8. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The swing equation satisfies the following expression: ； In the formula, This represents the reference value for active power. This indicates the output active power measurement value; Represents the adaptive inertial control coefficients; This indicates the inverter's output angular frequency; This represents the time derivative of the inverter's output angular frequency; Indicates the damping coefficient; Indicates the rated angular frequency.

9. The adaptive control method for the inertia constant of a power system according to claim 1, characterized in that, The integral solution of the swing equation to obtain the output angular frequency and voltage phase angle includes: Based on the swing equation, the inverter output angular frequency at the current moment is calculated by discrete integration in the digital controller; the voltage phase angle is obtained by time integration of the inverter output angular frequency at the current moment; and the calculated voltage phase angle is converted into six PWM drive pulses using pulse width modulation control technology to control the on and off of the power switching transistors inside the inverter, thereby outputting three-phase AC power.

10. An adaptive control system for the inertial constant of a power system, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement an adaptive control method for the inertial constant of a power system according to any one of claims 1-9.

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