System and method for estimating inertial energy of renewable energy generator based on grid-following inverter connected to synchronous condenser

Abstract

According to the present embodiments, a system for estimating inertial energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser is provided, the system comprising: a perturbation injection device connected to a specific bus so as to apply a perturbation injection signal, thereby generating a momentary power change in a power system; and an inverter and a synchronous condenser, which have a system response data measurement unit for measuring system response data in the specific bus of the power system after the application of the perturbation injection signal, and an inertial estimation calculation unit for calculating an estimated inertial constant and a prediction error rate on the basis of the system response data and determining the estimated inertial constant as an effective inertial constant if the prediction error rate is a preset reference value or less.

Description

System and method for estimating inertial energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser

[0001] The present disclosure relates to a technology for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser.

[0002] Generally, power system inertia acts as a key factor in maintaining frequency stability by mitigating system frequency fluctuations through the rotational mass of generators. However, with the recent increase in the proportion of renewable energy sources, the ratio of synchronous generators with mechanical rotational mass has decreased, and as power electronics-based inverter-linked facilities become more widespread, a problem is emerging in which the level of effective inertia across the entire system is declining.

[0003] In such an environment, system operators need to estimate the inertia constant (H) and damping constant (D) of the actual system in real time to evaluate frequency response characteristics and ensure system stability based on this. However, conventional inertia estimation techniques have limitations in that they fail to reflect the control response characteristics of power electronics-based inverters, as they primarily rely on data from the entire system or estimation methods based on the rotational mass of synchronous generators.

[0004] In particular, conventional technologies often failed to accurately reflect actual frequency attenuation behavior because they frequently derived only inertia constants using simplified parameters or failed to consider attenuation constants. Furthermore, the absence of a mechanism to quantify the contribution of inverter equipment—which is a digital control-based active power input / output device rather than a rotating mechanism—in terms of inertia constants made it difficult to accurately evaluate the inertia contribution effect of asynchronous equipment within the grid.

[0005] Therefore, unlike existing synchronous generator-based estimation methods, a new technology is required that quantitatively calculates the inertia constants of the actual system by reflecting the active power control response characteristics of the inverter, and enables more accurate and reliable estimation of inertia energy by correcting the dynamic characteristics of the inertia response, including damping constants, in real time.

[0006] These embodiments can provide a technology for estimating the inertia energy of a renewable energy generator based on a grid-following inverter linked to a synchronous condenser.

[0007] In one aspect, the present embodiments may provide an inertia energy estimation system for a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, comprising: a perturbation injection device connected to a specific bus to apply a perturbation injection signal to generate an instantaneous power change in the power system; a system response data measurement unit that measures system response data at a specific bus of the power system after applying the perturbation injection signal; and an inertia estimation calculation unit that calculates an estimated inertia constant and a prediction error rate based on the system response data and determines the estimated inertia constant as a valid inertia constant when the prediction error rate is less than or equal to a preset reference value, and an inverter and a synchronous condenser.

[0008] In another aspect, the present embodiments may provide a method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, comprising the steps of: generating an instantaneous power change in a power system by applying perturbation injection power from a perturbation injection device connected to a specific bus; measuring system response data at a specific bus of the power system after applying the perturbation injection power; calculating an estimated inertia constant and a prediction error rate based on the system response data; and determining the estimated inertia constant as a valid inertia constant when the prediction error rate is less than or equal to a preset reference value.

[0009] According to the embodiments of the present disclosure, by acquiring real-time system response data for perturbation injection power at a specific busbar of a power system, the inertia contribution of grid-following inverters and synchronous condensers that do not have rotational mass can be easily verified. Furthermore, the inertia characteristics and frequency stability of the actual system can be precisely diagnosed through the absolute calculation of inertia constants based on the frequency change characteristics of the system response, comparative evaluation of system inertia over time using periodic inertia estimates, or relative comparison based on equipment configuration, operating conditions, etc. Through this, reliable inertia evaluation results can be provided even in systems where inertia has decreased due to the increasing proportion of renewable energy.

[0010] FIG. 1 is a configuration diagram of an inertia estimation system in a power grid based on a grid-following inverter according to one embodiment.

[0011] FIG. 2 is a diagram illustrating an exemplary single facility configuration for verifying the validity of inertia constants estimated based on the system of FIG. 1.

[0012] FIG. 3 is a flowchart illustrating an inertia estimation procedure according to one embodiment.

[0013] FIG. 4 is a diagram exemplarily showing the results of the inertia contribution evaluation of a grid-following inverter according to one embodiment.

[0014] FIG. 5 is a diagram exemplarily showing the model verification results of an inertia estimation system according to one embodiment.

[0015] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the exemplary drawings. In assigning reference numerals to the components of each drawing, the same components may have the same reference numeral as much as possible, even if they are shown in different drawings. Furthermore, in describing the embodiments, if it is determined that a detailed description of related known components or functions may obscure the essence of the technical concept, such detailed description may be omitted. Where terms such as "comprising," "having," or "consisting of" are used in this specification, other parts may be added unless "only" is used. Where a component is expressed in the singular, it may include a plural unless otherwise specified.

[0016] Additionally, terms such as first, second, A, B, (a), (b), etc., may be used to describe the components of the present disclosure. These terms are used merely to distinguish the components from other components, and the nature, order, sequence, or number of the components are not limited by such terms.

[0017] In describing the positional relationship of components, where it is stated that two or more components are "connected," "combined," or "joined," it should be understood that while the two or more components may be directly "connected," "combined," or "joined," they may also be "connected," "combined," or "joined" with other components "intervened." Here, the other components may be included in one or more of the two or more components that are "connected," "combined," or "joined" with one another.

[0018] In describing the temporal flow relationship regarding components, methods of operation, or methods of production, for example, when the temporal or sequential relationship is described using "after," "following," "next," or "before," it may include cases where the relationship is not continuous unless "immediately" or "directly" is used.

[0019] Meanwhile, where numerical values ​​or corresponding information regarding a component (e.g., levels, etc.) are mentioned, even without separate explicit notation, the numerical values ​​or corresponding information may be interpreted as including a range of error that may occur due to various factors (e.g., process factors, internal or external shocks, noise, etc.).

[0020] FIG. 1 is a diagram illustrating the configuration of an inertia estimation system in a power grid based on a grid-following inverter according to one embodiment.

[0021] As illustrated in FIG. 1, a system according to one embodiment may be composed of a power system (100), a perturbation injection device (200), an inverter and a synchronous condenser (300), and a specific bus (400). The inertia constant (H) of the system can be calculated by measuring the frequency change rate (df / dt) and the active power response at the specific bus (400), and verified through the test configuration illustrated in FIG. 2.

[0022] The power system (100) may be composed of a generator (110) and a ZIP load (Z: impedance type, I: current type, P: power type load) (120), and the active power (P) of the system G ) and load power (P load It can simulate ). This can serve as a reference system for estimating inertial energy and can experimentally reproduce the output response of a generator during frequency fluctuations.

[0023] The perturbation injection device (200) injects a fine power perturbation (ΔP) into a specific busbar (400). target The inertia response of the system can be induced by applying perturbation injection power. The perturbation injection device (200) generates a perturbation signal to induce minute power perturbation (ΔP) for a predetermined time. target , perturbation injection power) can be injected. This can induce a rate of change of frequency (RoCoF) in the system, and the magnitude and duration of the perturbation can be adjusted so as not to impair system stability.

[0024] The inverter and the synchronous condenser (300) can be connected in parallel to a specific bus (400) and can perform virtual inertia control and phase stabilization functions. At this time, the inverter can be operated in either a grid-forming or grid-following mode based on digital control, and in the grid-following mode, the active power (P) according to the grid frequency fluctuation inv It can automatically adjust the voltage and frequency, and in grid mode, perform virtual inertia control to stabilize the voltage and frequency.

[0025] Additionally, the inverter and synchronous condenser (300) may include a grid-type inverter (310) and a grid-following inverter (320), and through parallel operation of these, a composite response characteristic combining physical inertia and virtual inertia can be formed.

[0026] The inverter and synchronous condenser (300) receive grid response data measured at a specific bus (400) along with a virtual inertia control function according to grid frequency fluctuation, and the estimated inertia constant (H est It may include an inertia estimation unit that calculates the prediction error rate (PE(%)). The inertia estimation unit may be embedded in an inverter control module (such as a DSP or microcontroller).

[0027] A specific bus (400) may be a common node connected to a power system (100), a perturbation injection device (200), an inverter, and a synchronous condenser (300), serving as a reference measurement point for inertia estimation. This bus may include an impedance equivalent circuit simulating a power transmission path and a frequency measurement node, and may measure the rate of change of frequency (df / dt) in real time using a phase-locked loop (PLL) or a phasor measurement unit (PMU).

[0028] In addition, a system response data measurement unit (e.g., PMU, Phasor Measurement Unit, etc.) may be installed within a specific busbar (400) to collect data such as the system's active power (P), reactive power (Q), and frequency change rate (df / dt) in real time. The system response data measurement unit monitors response characteristics in real time according to the instantaneous inertia change of the system and estimates the inertia constant (H est It can provide basic data necessary for the calculation.

[0029] The system uses measured data (generator active power (P G ), load power (P load) , inverter power change (ΔP inv) Estimated inertia constant (H) based on the rate of change of frequency (df / dt) est ) can be calculated. The estimated inertia constant can be defined as in Equation 1 below.

[0030] [Mathematical Formula 1]

[0031]

[0032] P G : Generator active power

[0033] P load : Load active power

[0034] ΔP target : A change in power applied by the perturbation injection device (200) (perturbation injection power)

[0035] ΔP G : Change in generator power

[0036] ΔP inv : Inverter power change amount,

[0037] (df / dt) dt=0∼1 : Rate of change of frequency (RoCoF) during the time interval (dt=0~1)

[0038] Calculated estimated inertia constant (H est ) is the actual inertia constant (H true It is compared with ) to calculate the prediction error rate (PE, Prediction Error), and can be defined as Equation 2 below.

[0039] [Mathematical Formula 2]

[0040]

[0041] If the error rate is less than ±20%, the estimated inertia constant (H est ) can be determined as a valid value.

[0042] Figure 2 shows the inertia constant (H) estimated based on the system of Figure 1. est This is a drawing that exemplarily shows a single facility configuration for verifying the validity of ).

[0043] FIG. 2(a) illustrates an exemplary test system comprising a generator (110), an impedance circuit (410), and a grid-type inverter (310). This configuration is based on the rotational inertia (H) of the generator GEN ) and the virtual inertia of the inverter (H GFMIt is intended to verify the relationship between ), and the inverter's virtual inertia (H GFM ) is the droop coefficient (K droop It can have an approximate relationship with ) (H GFM K droop ).

[0044] FIG. 2(b) is a test system in which a grid-type inverter (310) and a grid-following inverter (320) are connected through an impedance (410), and the difference in active power between the two inverters can be proportional to the rate of change of frequency (df / dt) as shown in Equation 3 below.

[0045] [Mathematical Formula 3]

[0046]

[0047] H: Inertia constant

[0048] f: System frequency

[0049] df / dt: rate of change of frequency

[0050] P GFM : Grid-type inverter output power

[0051] P GFL Grid-following inverter output power

[0052] Through this, the estimated inertia constant (H) calculated in Fig. 1 est It can verify the accuracy of ) and quantitatively distinguish between load inertia and equipment inertia within the system.

[0053] Consequently, the modeling-estimation-verification procedure of an inertia estimation system can be completed by injecting perturbations into the system to calculate inertia constants and verifying the results in a test system of the same structure.

[0054] FIG. 3 is a flowchart illustrating an inertia estimation procedure according to one embodiment.

[0055] As illustrated in FIG. 3, first, a perturbation injection device (200) can apply a perturbation signal to a specific busbar (400) (S310). At this time, the perturbation injection device (200) applies a minute power perturbation (ΔP target The rate of change of grid frequency (RoCoF) can be induced by controlling the magnitude and duration of the perturbation injection power.

[0056] Next, the active power (P) of the generator (110) and inverter (310, 320) at a specific busbar (400) G,0 , P G,dt , P inv,0 , P inv,dt System response data including the frequency change rate (RoCoF) and the signal can be measured through a phase-locked loop (PLL) or a phase measurement unit (PMU) (S320). At this time, the measurement data can be collected at intervals of Δt (100 ms to 1 s), and noise can be removed by applying a finite impulse response filter (FIR) or a Kalman filter as needed.

[0057] Next, based on the measured data, the system estimates the inertia constant (H est ) and the prediction error rate (PE(%)) can be calculated (S330). At this time, the estimated inertia constant (H est ) can be calculated using the aforementioned Equation 1, and the prediction error rate (PE(%)) is calculated using the actual inertia constant (H true It can be calculated by comparing with ).

[0058] Next, if the calculated prediction error rate (PE(%)) is ±20% or less, the estimated inertia constant (H est ) is determined to be a valid inertia constant, and the procedure can be terminated (S340).

[0059] Conversely, if the calculated prediction error rate (PE(%)) exceeds the threshold, the system returns to step S310 and the minute power perturbation (ΔP targetRemeasurements can be performed by adjusting the magnitude of the perturbation injection power or the measurement period. Through this iterative loop, the error can be gradually reduced, and finally, a stable estimated inertia constant (H est It can be corrected to converge to the value.

[0060] In addition, this procedure can be configured in the form of a real-time feedback loop, and a minute power perturbation (ΔP) at every sampling period target By updating the values ​​of perturbation injection power and the rate of change of frequency (RoCoF), the instantaneous inertia change of the system can be tracked in real time.

[0061] Furthermore, unlike conventional inertia estimation techniques based on rotational mass-based synchronous generators, the inertia energy estimation method according to the present embodiment is characterized by its ability to directly reflect complex response characteristics occurring in a grid environment where synchronous condensers and grid-following inverters are mixed. In particular, by simultaneously considering the digital control-based active power input / output characteristics unique to inverter equipment and the physical inertia component contributed by the synchronous condenser, it is possible to integrally estimate the contributions of virtual and physical inertia, which were difficult to separate and quantify using existing methods. Accordingly, the present embodiment can provide a highly accurate inertia estimation technology that can be utilized to quantitatively evaluate inertia degradation issues in actual power systems and to establish strategies for securing inertia required in inverter-driven power systems.

[0062] FIG. 4 is a diagram exemplarily showing the results of an inertia contribution evaluation of a grid-following (GFL) inverter according to one embodiment.

[0063] As shown in Fig. 4, in this evaluation, a grid-following inverter connected in parallel with a synchronous generator (60MW) in a single busbar system was used, as shown in Table 1.

[0064] Bus No. Generator Capacity / Inertia (H) Voltage Magnitude / Phase GFL Inverter @ No. 5 Single Bus 120 MVA / 3.117s 1.0 pu / 0.0 deg S=35 MVA 1(slack) 300 MVA / 4.117s 1.0 pu / 0.0 deg Vdc=28.0 kV 2200 MVA / 4.117s 1.0 pu / 16.8 deg τ=20 ms 3200 MVA / 6.117s 1.0 pu / 17.78 deg R=20 mΩ, L=2.7 mH

[0065] The test conditions were based on the IEEE 9 bus model, the generator capacity was set to a range of 120 MVA to 200 MVA, and the inverter was operated under conditions of a rated capacity of 35 MVA, a DC voltage (Vdc) of 28.0 kV, and a time constant (τ) of 20 ms. An inverter and a synchronous condenser (300) connected to a specific bus (400) according to one embodiment are configured together with the power system (100) and perturbation injection device (200) shown in FIG. 1, and a fine power perturbation (ΔP target When ) is injected, the inverter output power (P inv By measuring ) and the rate of change of frequency (df / dt) in real time, the inertia constant (H est ) can be calculated. In addition, the inverter can be implemented in a parallel operation structure of a grid-type inverter (310) and a grid-following inverter (320) as shown in FIG. 2(b), and active power (P) can be calculated according to grid frequency fluctuations. inv ) can be automatically adjusted.

[0066] The graph in FIG. 4 shows the results of comparing the active power and angular frequency responses with and without the grid-following inverter (320) under this configuration.

[0067] When an inverter is included, it can be seen that the initial peak of active power is reduced from approximately 0.83 pu to 0.63 pu, and the fluctuation range of frequency (angular velocity) is also reduced by approximately 2.15 rad / s.

[0068] In other words, when inverters are operated in parallel, the active power response of the grid becomes smoother and frequency stability is improved, which is the effect of the estimated inertia constant (H) calculated according to the procedure (S310~S340) of Fig. 3. est It demonstrates that ) is substantially improved by the virtual inertia control of the inverter.

[0069] FIG. 5 is a diagram exemplarily showing the model verification results of an inertia estimation system according to one embodiment.

[0070] In this embodiment, power perturbation (ΔP) through the phase and load of a specific bus (400) is performed using an IEEE 9-Bus benchmark model. target After applying ), the active power (P) and reactive power (Q) responses of the actual system were measured and compared with the model estimates calculated using the inertia estimation algorithm proposed in one embodiment.

[0071] Figure 5(a) shows the verification results for active power, and Figure 5(b) shows the verification results for reactive power.

[0072] In the graph, red represents the actual measured phasor measurement unit (PMU) data, and yellow represents the model prediction value calculated by the inertia estimation algorithm. The two response curves show almost identical trends, and it can be seen that they converge to a steady state after about 0.2 seconds in the initial perturbation period.

[0073] In addition, the accuracy of the model estimation was evaluated using the Mean Square Error (MSE), and the error rate was calculated to be about 3% or less, confirming that the accuracy of the model in reflecting dynamic characteristics is high.

[0074] From these results, the inertia estimation algorithm proposed in one embodiment accurately simulates the power response of an actual power system, and the inertia constant (H) estimated in real time est It can be seen that the reliability of ) can be verified.

[0075] The foregoing description is merely an illustrative explanation of the technical concept of the present disclosure, and those skilled in the art to which the present disclosure pertains may make various modifications and variations within the scope of the essential characteristics of the technical concept. Furthermore, since these embodiments are intended to explain, not limit, the scope of the technical concept is not limited by these embodiments. The scope of protection of the present disclosure shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of the present disclosure.

[0076]

[0077] CROSS-REFERENCE TO RELATED APPLICATION

[0078] This patent application claims priority pursuant to Section 119(a) of the U.S. Patent Act (35 USC §119(a)) to Korean Patent Application No. 10-2024-0186142 filed on December 13, 2024 and Korean Patent Application No. 10-2025-0164328 filed on November 4, 2025, all of which are incorporated by reference into this patent application. Additionally, this patent application claims priority in countries other than the United States for the same reasons as above, all of which are incorporated by reference into this patent application.

Claims

1. As an inertia energy estimation system for a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, A perturbation injection device connected to a specific busbar that applies a perturbation injection signal to generate an instantaneous power change in the power system; A system response data measuring unit that measures system response data at a specific busbar of the power system after applying the above perturbation injection signal; and An inertia energy estimation system for a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, comprising an inverter and a synchronous condenser having an inertia estimation operation unit that calculates an estimated inertia constant and a prediction error rate based on the above-mentioned grid response data, and determines the estimated inertia constant as a valid inertia constant when the prediction error rate is less than or equal to a preset reference value.

2. In Paragraph 1, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned grid response data includes at least one of the generator active power, load power, inverter power change amount, and frequency change rate.

3. In Paragraph 2, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned estimated inertia constant is calculated based on the time response characteristics between the change amount of the generator active power, load power, and inverter power and the frequency change rate of the above-mentioned grid response data.

4. In Paragraph 1, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned prediction error rate is calculated as the percentage of the difference between the actual inertia constant and the estimated inertia constant divided by the actual inertia constant.

5. In Paragraph 1, In the above judgment step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, further comprising the step of performing a re-measurement by adjusting the magnitude of the perturbation injection power applied to the perturbation injection device or the measurement period when the above prediction error rate exceeds the above reference value.

6. In Paragraph 1, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the calculation of the above-mentioned estimated inertia constant and prediction error rate is performed in the form of a real-time feedback loop, and the perturbation injection power and frequency change rate are updated at every sampling period to track the instantaneous inertia change of the grid in real time.

7. A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, A step of generating an instantaneous power change in the power system by applying perturbation injection power from a perturbation injection device connected to a specific busbar; A step of measuring system response data at a specific busbar of the power system after applying the above-mentioned perturbation injection power; A step of calculating estimated inertia constants and a prediction error rate based on the above system response data; and A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, comprising the step of determining the estimated inertia constant as a valid inertia constant when the above prediction error rate is less than or equal to a preset reference value.

8. In Paragraph 7, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned grid response data includes at least one of the generator active power, load power, inverter power change amount, and frequency change rate.

9. In Paragraph 8, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned estimated inertia constant is calculated based on the time response characteristics between the change amount of the generator active power, load power, and inverter power and the frequency change rate of the above-mentioned grid response data.

10. In Paragraph 7, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the above-mentioned prediction error rate is calculated as the percentage of the difference between the actual inertia constant and the estimated inertia constant divided by the actual inertia constant.

11. In Paragraph 7, In the above judgment step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, further comprising the step of performing a re-measurement by adjusting the magnitude of the perturbation injection power applied to the perturbation injection device or the measurement period when the above prediction error rate exceeds the above reference value.

12. In Paragraph 7, In the above calculation step, A method for estimating the inertia energy of a renewable energy generator based on a grid-following inverter connected to a synchronous condenser, wherein the calculation of the above-mentioned estimated inertia constant and prediction error rate is performed in the form of a real-time feedback loop, and the perturbation injection power and frequency change rate are updated at every sampling period to track the instantaneous inertia change of the grid in real time.

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