Battery energy storage embedded novel power system stabilizer

Abstract

The invention relates to a novel battery energy storage embedded power system stabilizer. The oscillation mode measuring and distinguishing module is used for obtaining an oscillation characteristic parameter set based on grid-connected point three-phase voltage data and current data of a target oscillation system; the adaptive parameter optimization module is used for establishing an impedance branch model according to the oscillation characteristic parameter set and obtaining an optimal damping control gain and a time constant by optimizing the impedance branch model; and the damping control module is used for obtaining a three-phase additional reference current based on the oscillation characteristic parameter set, the optimal damping control gain and the time constant, and inhibiting the risk oscillation mode of the target oscillation system based on the three-phase additional reference current. Therefore, through the novel battery energy storage embedded power system stabilizer, the problem that the prior art is limited by factors such as site, topology and investment cost and cannot be flexibly applied to all occasions is solved, the adaptability and flexibility of the stabilizer in various complex environments are improved, and meanwhile, the stability of a power system is improved.

Description

Technical Field

[0001] The present application relates to the technical field of power system operation and stability control, and in particular to a new type of power system stabilizer embedded with battery energy storage. Background Art

[0002] As power systems evolve toward the "dual highs" of a high proportion of renewable energy access and a high proportion of power electronics, inverter-based resource (IBR) or converter-interfaced generation (CIG) power supplies, AC / DC transmission systems that rely on power electronics for energy conversion, and new loads, typified by electric vehicles, are profoundly changing the stability mechanisms and dynamic characteristics of these new power systems from three different perspectives: the source, the grid, and the load. The high penetration of power electronics and its complex "electromechanical-magnetic-control" interactions with AC / DC hybrid grids can trigger broadband electromagnetic oscillations, posing new challenges to power system stability and security.

[0003] In related technologies, the New-type Power System Stabilizer (NPSS) is an effective adaptive oscillation suppression method that can be attached to various grid devices, such as wind / solar renewable energy generators, flexible DC converters, and energy storage converters. It can be combined with existing controllers through serial / parallel embedding to form an embedded NPSS. Alternatively, an external NPSS solution using a dedicated converter can be connected to the grid as a multi-frequency power converter, enabling energy exchange between non-industrial frequency, DC, and industrial frequency, actively dissipating the grid's oscillating power / energy, and achieving the goal of suppressing oscillations.

[0004] However, the external NPSS solution is limited by factors such as site, topology and investment cost, and cannot be flexibly applied in all situations, which urgently needs to be solved. Summary of the Invention

[0005] This application provides a new type of battery energy storage embedded power system stabilizer to solve the problem that the existing technology cannot be flexibly applied in all occasions due to factors such as site, topology and investment cost, improve its adaptability and flexibility in various complex environments, and at the same time improve the stability of the power system.

[0006] To achieve the above objectives, the first embodiment of the present application proposes a new type of power system stabilizer embedded with battery energy storage, which is characterized by comprising:

[0007] an oscillation mode detection module, the oscillation mode detection module being used to obtain three-phase voltage data and three-phase current data of a grid connection point of a target oscillation system, and to obtain an oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point;

[0008] An adaptive parameter optimization module, configured to establish an impedance branch model according to the oscillation characteristic parameter set, and optimize the impedance branch model based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant;

[0009] A damping control module is configured to obtain the oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid connection point, perform gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant, obtain a three-phase additional reference current, and suppress the risk oscillation mode of the target oscillation system based on the three-phase additional reference current.

[0010] Optionally, in some embodiments, the oscillation mode detection module includes:

[0011] A first acquisition unit is configured to acquire three-phase voltage data and three-phase current data of a grid connection point of the target oscillation system.

[0012] Optionally, in some embodiments, the oscillation mode detection module further includes:

[0013] An obtaining unit is used to obtain the oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point.

[0014] Optionally, in some embodiments, the obtaining unit includes:

[0015] an analog-to-digital conversion subunit, configured to perform analog-to-digital conversion on the three-phase voltage data and the three-phase current data of the grid connection point to obtain discrete signal data;

[0016] The first processing subunit is used to determine a signal containing an oscillation component based on the discrete signal data, perform discrete Fourier transform on the signal containing the oscillation component to obtain a discrete sequence of spectral lines, and determine a dominant oscillation mode frequency based on the discrete sequence of spectral lines.

[0017] Optionally, in some embodiments, the obtaining unit further includes:

[0018] A calculation subunit, the calculation subunit being used to calculate the dominant oscillation mode phase angle and the dominant oscillation mode amplitude using an interpolation algorithm and a compensation correction algorithm;

[0019] A modeling subunit, the modeling subunit is used to model the change of the amplitude of the dominant oscillation mode over time to obtain the divergence rate of the dominant oscillation mode;

[0020] An obtaining subunit is configured to obtain the oscillation characteristic parameter set based on the dominant oscillation mode phase angle, the dominant oscillation mode amplitude, the dominant oscillation mode frequency, and the divergence rate of the dominant oscillation mode.

[0021] Optionally, in some embodiments, the adaptive parameter optimization module includes:

[0022] A modeling unit is used to establish the impedance branch model according to the oscillation characteristic parameter set.

[0023] Optionally, in some embodiments, the adaptive parameter optimization module further includes:

[0024] An optimization unit is used to optimize the impedance branch model based on the preset objective function and the preset constraint conditions to obtain the optimal damping control gain and the optimal damping control time constant.

[0025] Optionally, in some embodiments, the damping control module includes:

[0026] a second acquiring unit, configured to acquire an oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid connection point;

[0027] a processing unit, configured to obtain the three-phase additional reference current based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant;

[0028] A suppression unit is configured to suppress a risky oscillation mode of the target oscillation system based on the three-phase additional reference current.

[0029] Optionally, in some embodiments, the processing unit includes:

[0030] a second processing subunit, configured to perform the gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant, to obtain the oscillation component after the gain adjustment and phase compensation operations;

[0031] The third processing subunit is used to perform a limiting process on the oscillation component after gain adjustment and phase compensation operations based on a preset converter capacity range, and obtain the three-phase additional reference current based on the oscillation component after the limiting process.

[0032] According to the battery energy storage embedded new power system stabilizer proposed in the embodiment of the present application, an oscillation characteristic parameter set is obtained based on the three-phase voltage data and current data of the grid connection point of the target oscillation system through the oscillation mode detection module; an impedance branch model is established according to the oscillation characteristic parameter set through the adaptive parameter optimization module, and the optimal damping control gain and time constant are obtained by optimizing the impedance branch model; a three-phase additional reference current is obtained based on the oscillation characteristic parameter set, the optimal damping control gain and time constant through the damping control module, and the risk oscillation mode of the target oscillation system is suppressed based on the three-phase additional reference current. In this way, the problem that the existing technology cannot be flexibly applied in all occasions due to the limitations of factors such as site, topology and investment cost is solved, its adaptability and flexibility in various complex environments are improved, and the stability of the power system is improved at the same time.

[0033] To achieve the above objectives, a second embodiment of the present application provides a method for suppressing risky oscillation modes. The method adopts the battery energy storage embedded novel power system stabilizer of the first embodiment, wherein the method includes the following steps:

[0034] Obtaining three-phase voltage data and three-phase current data of a grid connection point of a target oscillation system, and obtaining an oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point;

[0035] Establishing an impedance branch model according to the oscillation characteristic parameter set, and optimizing the impedance branch model based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant;

[0036] Based on the three-phase voltage data and the three-phase current data of the grid connection point, the oscillation component of the dominant mode is obtained, and based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant, the oscillation component of the dominant mode is gain adjusted and phase compensated to obtain a three-phase additional reference current, and the risk oscillation mode of the target oscillation system is suppressed based on the three-phase additional reference current.

[0037] According to the method for suppressing risk oscillation modes proposed in the embodiment of the present application, a new power system stabilizer embedded with battery energy storage is used to solve the problem that the existing technology is limited by factors such as site, topology and investment cost and cannot be flexibly applied in all occasions. The method improves its adaptability and flexibility in various complex environments, while improving the stability of the power system.

[0038] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0040] Figure 1 A block diagram of a battery storage based embedded new-type power system stabilizer (BSE-NPSS) provided according to an embodiment of the present application;

[0041] Figure 2 A flowchart for designing and implementing a new power system stabilizer embedded with battery energy storage according to an embodiment of the present application;

[0042] Figure 3 A schematic diagram of multiple wind farms and energy storage systems connected for example verification according to an embodiment of the present application;

[0043] Figure 4 A schematic diagram of the suppression effect of a risky oscillation mode after the battery energy storage embedded novel power system stabilizer is put into operation according to one embodiment of the present application;

[0044] Figure 5 This is a schematic diagram of the suppression effect of another risk oscillation mode after the battery energy storage embedded novel power system stabilizer is put into use according to one embodiment of the present application;

[0045] Figure 6 The flowchart of the method for suppressing risk oscillation mode provided in accordance with an embodiment of the present application is shown. DETAILED DESCRIPTION

[0046] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0047] The following describes a novel power system stabilizer with embedded battery energy storage according to an embodiment of the present application with reference to the accompanying drawings.

[0048] Figure 1 It is a block diagram of a battery energy storage embedded novel power system stabilizer according to an embodiment of the present application.

[0049] For example, Figure 1 As shown, the battery energy storage embedded novel power system stabilizer 10 includes: an oscillation mode detection module 100, an adaptive parameter optimization module 200 and a damping control module 300.

[0050] Among them, the oscillation mode detection module 100 is used to obtain the three-phase voltage data and the three-phase current data of the grid-connected point of the target oscillation system, and obtain the oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid-connected point; the adaptive parameter optimization module 200 is used to establish an impedance branch model according to the oscillation characteristic parameter set, and optimize the impedance branch model based on a preset objective function and preset constraints to obtain the optimal damping control gain and the optimal damping control time constant; the damping control module 300 is used to obtain the oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid-connected point, and perform gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant to obtain the three-phase additional reference current, and suppress the risk oscillation mode of the target oscillation system based on the three-phase additional reference current.

[0051] That is to say, in the face of a new power system with "double high" characteristics (i.e., a high proportion of renewable energy access and a high proportion of power electronic equipment use), the embodiment of the present application proposes a battery energy storage embedded new power system stabilizer (BSE-NPSS) 10, which is mainly composed of an oscillation mode detection module 100, an adaptive parameter optimization module 200 and a damping control module 300. Among them, the oscillation mode detection module 100 takes the three-phase voltage data and the three-phase current data of the grid connection point as input, and outputs an oscillation characteristic parameter set, including the dominant oscillation mode frequency, the dominant oscillation mode phase angle, the dominant oscillation mode amplitude and the divergence rate of the dominant oscillation mode. The adaptive parameter optimization module 200 takes the oscillation characteristic parameter set as input, and outputs the optimal damping control gain and the optimal damping control time constant. The damping control module 300 takes the three-phase voltage data, the three-phase current data, the damping control parameter combination (dominant oscillation mode frequency, optimal damping control gain and optimal damping control time constant) and the control mode instruction as input, and outputs a three-phase additional reference current. The three-phase additional reference current can track the dominant oscillation mode of the system, respond to the time-varying characteristics of the oscillation frequency in real time, provide a sufficient damping level, and thus suppress the risky oscillation mode.

[0052] For ease of understanding, the oscillation mode identification module 100 , the adaptive parameter optimization module 200 and the damping control module 300 are respectively described in detail below.

[0053] Optionally, in some embodiments, the oscillation mode detection module 100 includes: a first acquisition unit and an acquisition unit, wherein the first acquisition unit is used to obtain the three-phase voltage data and the three-phase current data of the grid connection point of the target oscillation system; the acquisition unit is used to obtain the oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point.

[0054] It can be understood that the target oscillation system refers to a power system with a dominant oscillation mode, whose stability is affected by broadband electromagnetic oscillations. The grid connection point refers to the specific location where a system connects to the external power grid or other subsystems. In a power system, the grid connection point is often a key node for energy exchange, and its voltage and current data can reflect the system's operating status. Oscillation characteristic parameters are used to describe the specific parameters of oscillation behavior.

[0055] Specifically, the acquisition of three-phase voltage and current data at the grid connection point can be achieved by directly retrieving sampled data from the existing converter control system. Alternatively, high-precision, high-response, wide-bandwidth voltage and current sensors can be deployed at the grid connection point for real-time measurement. Furthermore, data from these sensors can be collected via industrial communication protocols. Furthermore, by analyzing the three-phase voltage and current data at the grid connection point, a set of oscillation characteristic parameters can be extracted.

[0056] For ease of understanding, the following describes in detail how to obtain an oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point.

[0057] Optionally, in some embodiments, the acquisition unit includes: an analog-to-digital conversion subunit, a first processing subunit, a calculation subunit, a modeling subunit and an acquisition subunit, wherein the analog-to-digital conversion subunit is used to perform analog-to-digital conversion operations on the three-phase voltage data and the three-phase current data of the grid-connected point to obtain discrete signal data; the first processing subunit is used to determine the signal containing the oscillation component based on the discrete signal data, perform discrete Fourier transform on the signal containing the oscillation component to obtain a discrete sequence of spectral lines, and determine the dominant oscillation mode frequency based on the discrete sequence of spectral lines; the calculation subunit is used to calculate the dominant oscillation mode phase angle and the dominant oscillation mode amplitude using an interpolation algorithm and a compensation correction algorithm; the modeling subunit is used to model the change of the dominant oscillation mode amplitude over time to obtain the divergence rate of the dominant oscillation mode; the acquisition subunit is used to obtain an oscillation characteristic parameter set based on the dominant oscillation mode phase angle, the dominant oscillation mode amplitude, the dominant oscillation mode frequency and the divergence rate of the dominant oscillation mode.

[0058] Signals containing oscillatory components refer to signals containing oscillatory components in the three-phase voltage and current data at the grid connection point in the power system. These signals may oscillate in the power system due to various reasons (such as faults, load changes, fluctuations in power generation equipment, etc.).

[0059] Specifically, after using voltage and current sensors to obtain the three-phase voltage data and three-phase current data of the target oscillation system at the grid connection point, the analog signal obtained can be converted into a digital signal (i.e., discrete signal data) through an analog-to-digital conversion operation, providing a data basis for subsequent oscillation modal analysis and identification. Subsequently, based on a sliding window waveform acquisition strategy (a technology for analyzing voltage or current signals), a time sliding window can be set for the collected voltage and current data, and the signal data can be segmented and stored. The change trend of the signal data within the time window is observed (whether the amplitude is continuous and does not decay), so as to preliminarily determine whether the power system has a divergent oscillation risk. If the oscillation amplitude of the signal does not decay within a continuous time window, or even gradually increases, it can indicate that the system has a divergent oscillation risk.

[0060] Furthermore, a signal containing an oscillatory component may be determined based on the discrete signal data. In some embodiments, the signal containing an oscillatory component is:

[0061]

[0062] Where s(n) is a general notation for signals containing both power frequency and oscillation components (including voltage and current), n is the sampling point number, a is the amplitude of the mode component, and f is the frequency of the mode component. is the phase of the mode component, the subscripts 0 and i represent the power frequency and the i-th oscillation component, N is the number of oscillation frequencies of interest, T s is the sampling interval.

[0063] Performing a discrete Fourier transform on a signal containing an oscillating component yields a discrete sequence of spectral lines containing the oscillation frequency:

[0064]

[0065] Among them, l w is the time window length, and the input sampling signal range is [1,l w ]; m is the spectral line number, the corresponding frequency is related to the sampling rate, which is mf s / l w ; W(n) is the window function.

[0066] Furthermore, by using an interpolation algorithm (cubic spline interpolation) to interpolate the discrete sequence of spectral lines, the dominant oscillation mode phase angle and the dominant oscillation mode amplitude can be calculated. Since the amplitude of the signal will change over time during the oscillation process, for unstable oscillation modes, the amplitude may increase (diverge) over time; for stable oscillation modes, the amplitude will decay over time. Through the regression analysis strategy, the change of the dominant oscillation mode amplitude over time can be modeled to obtain the trend parameter of the amplitude change, that is, the divergence rate of the dominant oscillation mode. Since the actual oscillation frequency is not an integer multiple of the power frequency fundamental wave, the dominant oscillation mode phase angle and the dominant oscillation mode amplitude can also be compensated and corrected to ensure the accuracy of the results, thereby providing more reliable data support for subsequent oscillation analysis and control. Finally, the oscillation characteristic parameter set can be obtained based on the dominant oscillation mode phase angle, dominant oscillation mode amplitude, dominant oscillation mode frequency and divergence rate of the dominant oscillation mode obtained after the above operation.

[0067] Optionally, in some embodiments, the adaptive parameter optimization module 200 includes: a modeling unit and an optimization unit, wherein the modeling unit is used to establish an impedance branch model based on the oscillation characteristic parameter set; the optimization unit is used to optimize the impedance branch model based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant.

[0068] Specifically, after obtaining the oscillation characteristic parameter set, an equivalent circuit model at the dominant oscillation frequency can be established based on the oscillation characteristic parameter set, and the oscillation mode that satisfies the oscillation characteristic parameter set can be characterized by a second-order resistance-inductance-capacitance (RLC) model, and then the BSE-NPSS is equivalent to a controllable impedance branch in the circuit (i.e., an impedance branch model). The impedance amplitude and phase angle of the impedance branch model correspond to the gain and time constant of the damping control branch, respectively. These parameters can be calculated by designing a constrained optimization problem. Among them, the preset objective function is to maximize the target oscillation mode damping (the real part of the eigenvalue is farthest from the imaginary axis); the preset constraints may include that all eigenvalues ​​are on the left side of the imaginary axis, the mode frequency of the third-order circuit cannot deviate from the original oscillation frequency, and the impedance amplitude of the controllable impedance branch is affected by the controller's own output limiting. Based on the preset objective function and preset constraints, by selecting a suitable constrained optimization solution technology (such as the feasible direction method, gradient projection method, penalty function method, commercial solver, etc., which are not specifically limited here), the impedance amplitude and phase angle of the impedance branch model (corresponding to the gain and time constant of the damping control branch) can be optimized and solved, thereby obtaining the optimal damping control gain and optimal damping control time constant that meet the preset objective function and preset constraints.

[0069] Then, the third-order circuit model of the integrated BSE-NPSS is expressed in the form of a state space matrix, and its eigenvalue (λ c1,2 =α c ±j2πf c ) to analyze the dynamic behavior of the system. The distance between the real part of the eigenvalue and the imaginary axis is used to quantify the stability of the system after the loop is closed: the closer the real part of the eigenvalue is to the imaginary axis, the closer the system is to an unstable state.

[0070] For example, when the impedance angle θ of the controllable impedance branch is c ∈(0,π / 2], the controllable impedance branch can be equivalent to the resistor R c and inductor L c , based on the commonly used principles for selecting state variables, the state space matrix A1 can be expressed as:

[0071]

[0072] Among them, R s is the equivalent resistance on the source side, L s is the equivalent inductance on the source side, R g is the grid-side equivalent resistance, C g is the grid-side equivalent capacitance, R c is the equivalent resistance of the controllable impedance branch, L c is the equivalent inductance of the controllable impedance branch.

[0073] When the impedance angle θ of the controllable impedance branch c ∈[-π / 2,0) and θ c = 0, the state space matrices are:

[0074]

[0075] Optionally, in some embodiments, the damping control module 300 includes: a second acquisition unit, a processing unit and a suppression unit, wherein the second acquisition unit is used to obtain the oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid-connected point; the processing unit is used to obtain the three-phase additional reference current based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant; and the suppression unit is used to suppress the risk oscillation mode of the target oscillation system based on the three-phase additional reference current.

[0076] Specifically, by performing power frequency band-stop filtering on the three-phase voltage data and the three-phase current data at the grid connection point, the power frequency portion can be removed; then, coupling frequency band-stop filtering is performed to further remove the coupling frequency component; and finally, target frequency band-pass filtering is performed to extract the oscillation component of the dominant mode. Among them, the filter can adopt a finite impulse response filter or an infinite impulse response filter. Next, through the proportional phase shift link, the dominant oscillation mode frequency, the optimal damping control gain and the optimal damping control time constant in the oscillation characteristic parameter set are used to obtain the three-phase additional reference current. This current reflects the current value that the converter needs to adjust under the current operating conditions. It will guide the converter to make corresponding current output adjustments, thereby effectively suppressing the oscillation mode that may cause risks in the target oscillation system.

[0077] It should be noted that the damping control parameter combination can also be directly input from the outside without going through the adaptive parameter optimization module 200. Therefore, the switching of different control modes can be completed through the control mode instruction MODE as needed, which is convenient for early debugging and adaptation to various types of application scenarios.

[0078] The following describes in detail how to obtain the three-phase additional reference current.

[0079] In some embodiments, the processing unit includes: a second processing subunit and a third processing subunit, wherein the second processing subunit is used to perform gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant to obtain the oscillation component after the gain adjustment and phase compensation operations; the third processing subunit is used to perform limiting processing on the oscillation component after the gain adjustment and phase compensation operations based on a preset converter capacity range, and obtain the three-phase additional reference current based on the oscillation component after the limiting processing.

[0080] Specifically, a damping control parameter combination can be obtained based on the dominant oscillation mode frequency, optimal damping control gain and optimal damping control time constant in the oscillation characteristic parameter set. By using this damping control parameter combination to perform gain adjustment and phase compensation operations on the oscillation component of the dominant mode, it can play a role in enhancing the damping level of the converter grid-connected system.

[0081] It is understandable that converter equipment typically only has a certain capacity percentage available for non-power frequency stability control requirements such as wideband oscillations. Therefore, after performing gain adjustment and phase compensation on the oscillation component of the dominant mode, the oscillation component after gain adjustment and phase compensation can also be limited based on the preset converter capacity range to control the amplitude of the oscillation component within a certain range, thereby preventing excessive oscillations during converter operation. Through the limiting process, the three-phase voltage and three-phase current data at the grid connection point are ultimately converted into the three-phase reference current of the target oscillation mode, namely the three-phase additional reference current, which provides additional reference instructions for the converter.

[0082] It should be noted that to implement the above steps in actual converter hardware, the mode filtering and proportional phase shifting steps require discretization. This process involves converting the frequency-domain transfer function commonly used in theoretical analysis into a time-domain difference equation. To accomplish this conversion, various discretization methods can be used (such as forward differencing, backward differencing, and bilinear transformation). The choice of these methods can be determined based on actual needs and is not specifically limited here.

[0083] In order to facilitate those skilled in the art to further understand the battery energy storage embedded new power system stabilizer proposed in the embodiment of the present application, the following is combined with Figures 2 to 5 For further explanation.

[0084] like Figure 2 As shown, the BSE-NPSS proposed in the embodiment of the present application is based on the principle of "immediate measurement-immediate identification-immediate control", and is mainly composed of an oscillation mode measurement and identification module, an adaptive parameter optimization module and a damping control module. According to the input, output and expected functions of the oscillation mode measurement and identification module, the adaptive parameter optimization module and the damping control module, appropriate computer programs can be written in the software and hardware environment to be deployed to complete the construction. In addition, under some specific requirements, some modules can be customized based on the characteristics of the actual power system to which the existing converter is intended to be connected, which contains the risk of wide-band oscillations. For example, for some new energy stations or thermal power plants with relatively fixed oscillation modes, the identification results are usually supported by a large amount of operating record data. At this time, the functions of the BSE-NPSS can be concentrated in the damping control module; for some systems with oscillation modes concentrated within a specific frequency band, the performance of pattern detection and feature identification can be further refined to achieve more accurate results and faster response times.

[0085] Based on the above-mentioned BSE-NPSS module structure and logical connection, its overall function can be summarized as follows: Based on the waveform information detected at the new energy grid connection point, a three-phase additional reference current at the oscillation frequency is generated through the damping control loop. The identification results and control parameters can all be realized within the BSE-NPSS. Therefore, the input of the BSE-NPSS is the three-phase voltage data U of the grid connection point. abc , three-phase current data of grid connection point I abc , the output is the three-phase additional reference current I osci_ref , the interface between BSE-NPSS and converter can be set through these three groups of quantities.

[0086] In the power system, the voltage U abc and the current I at the grid connection point abc These two key parameters are typically already sampled and measured within the existing converter control structure and can therefore be directly used as inputs for the BSE-NPSS. Furthermore, if direct access to the converter's internal sampling and measurement data is unavailable for some reason, a separate sampling device can be configured for the BSE-NPSS at the grid connection point. This device can collect the necessary voltage and current data and accurately transmit it back to the BSE-NPSS via appropriate communication methods, ensuring the proper operation of the grid stability control system and real-time data updates.

[0087] In the power system, the three-phase additional reference current I osci_ref It is mainly used to improve the damping characteristics of a specific oscillation mode. The three-phase additional reference current is designed specifically for the frequency component of the target oscillation mode to ensure that it only affects the specific frequency. To achieve this goal, I osci_ref It needs to be superimposed with the current reference value generated by the original control loop of the converter. The superimposed comprehensive current reference value will be used in subsequent processing processes such as pulse width modulation to generate the actual three-phase current output.

[0088] Taking a typical converter control strategy of “power outer loop + current inner loop” as an example, I osci_ref After the abc / dq (a coordinate transformation method used to simplify the analysis and control of three-phase AC systems, which converts the three-phase stationary coordinate system (abc) into a two-phase rotating coordinate system (dq)) transformation, it is added to the original current reference value i dref and i qref In this way, it can participate in the current loop control process and pulse width modulation process, while the inner and outer loop control strategies of the entire converter maintain their original stability and continuity. It can be specifically expressed as follows:

[0089]

[0090] Among them, i dosci 、i qosci is the BSE-NPSS output current instruction in dq coordinates, i dref 、i qref The current reference value generated by the converter power outer loop through proportional-integral regulation or given power calculation, is the quadrature axis current reference value after BSE-NPSS correction, is the direct-axis current reference value after BSE-NPSS correction.

[0091] Different BSE-NPSS interface solutions are designed based on the availability of control programs for grid-connected converters in operation. For converter grid-connected control systems in real-world projects, if the control algorithms and programs are directly accessible (i.e., a "white box" system), the various BSE-NPSS modules can be directly called within the existing control program as encapsulated functions. If the control algorithms and programs are not accessible or only partially accessible (i.e., a "black / gray box" system), the converter control program can be used to provide the required interface data, such as the grid connection point voltage, grid connection point current, and power outer loop output reference value, to the BSE-NPSS. The BSE-NPSS then performs calculations based on this data and feeds the results back to the converter.

[0092] After completing the configuration of the BSE-NPSS modules and the interface between the BSE-NPSS and the existing converter, the BSE-NPSS control program is integrated with the converter. Following the sequential steps of "discrete testing, open-loop testing, and closed-loop testing," the functionality of each BSE-NPSS component is verified. During the discrete testing phase, test signals are used to verify the functionality of each module. During the open-loop verification phase, waveform data from existing oscillation cases is input into the BSE-NPSS to generate an additional current reference value. This allows the converter to test its ability to suppress oscillations under the given additional reference current and assess the corresponding damping level. During the closed-loop verification phase, the BSE-NPSS is encapsulated as a function module and called in real time by the converter control program. Appropriate power system electromagnetic oscillation scenarios are selected to verify the closed-loop operation of the broadband oscillation adaptive suppression function through the converter output.

[0093] After functional testing is complete, the BSE-NPSS can operate in various converter operating scenarios. If it detects unstable electromagnetic oscillation modes in the connected system, it generates a suppression current at the corresponding frequency, thereby enhancing the damping of that mode. Furthermore, the BSE-NPSS output can be monitored and recorded during operation.

[0094] For example, in Figure 3 In the F-structure of the direct-drive wind power grid-connected system shown, coupled subsynchronous oscillations with a frequency of 21 / 79 Hz can be observed in the system under a specific operating scenario when the number of grid-connected converters increases to 50%. Under the same basic operating scenario, if the wind speed in the area increases rapidly from 7.5 m / s to 9.6 m / s, the active power output of the wind farm will increase accordingly. This rapid change in wind speed leads to the emergence of a new oscillation mode within the power system with a frequency of 25 / 75 Hz.

[0095] In order to solve this broadband oscillation instability problem, an energy storage converter can be connected to the 35kV busbar outlet of the wind farm. By boosting the voltage from 0.69kV to 35kV, the grid-connected operation of the converter is achieved. Simulation tests conducted using PSCAD (Power Systems Computer Aided Design) / EMTDC (Electro-Magnetic Transients including DC) electromagnetic transient simulation software show that when BSE-NPSS is automatically put into operation, the oscillation phenomenon can be effectively controlled and suppressed. In addition, BSE-NPSS can operate independently based on the results of system identification, and can issue accurate additional current instructions to the energy storage converter to further stabilize the system. In the simulation results, it can be seen that the suppression effect of the 21 / 79Hz risk mode can be as follows Figure 4 As shown, Figure 4 (a) is a schematic diagram of the controller output current, Figure 4 (b) is a schematic diagram of the output power. The suppression effect of the 25 / 75Hz risk mode can be shown as follows: Figure 5 As shown, Figure 5 (a) is a schematic diagram of the controller output current, Figure 5 (b) is a schematic diagram of the output power.

[0096] In summary, the battery energy storage embedded new power system stabilizer (BSE-NPSS) proposed in the embodiments of the present application has the following advantages:

[0097] (1) By adopting the principle of "immediate measurement, immediate identification, and immediate control," the BSE-NPSS in this application is able to track the dominant oscillation mode of the system in real time, respond to the time-varying characteristics of the oscillation frequency, and suppress risky oscillation modes by providing sufficient damping. This solution is fully online and highly adaptable, providing a systematic solution for relevant scenarios and needs.

[0098] (2) The embodiments of the present application can be organically combined with existing grid-connected control strategies to reduce the demand for stable control equipment, and are highly economical.

[0099] (3) The control strategy implementation method of the embodiment of the present application can be independent of conventional grid-connected control, has good portability and reusability, and has good expansion space in the control of converters with similar structures such as new energy storage, reactive power compensation devices, and DC converters.

[0100] According to the battery energy storage embedded new power system stabilizer proposed in the embodiment of the present application, an oscillation characteristic parameter set is obtained based on the three-phase voltage data and current data of the grid connection point of the target oscillation system through the oscillation mode detection module; an impedance branch model is established according to the oscillation characteristic parameter set through the adaptive parameter optimization module, and the optimal damping control gain and time constant are obtained by optimizing the impedance branch model; a three-phase additional reference current is obtained based on the oscillation characteristic parameter set, the optimal damping control gain and time constant through the damping control module, and the risk oscillation mode of the target oscillation system is suppressed based on the three-phase additional reference current. In this way, the problem that the existing technology cannot be flexibly applied in all occasions due to the limitations of factors such as site, topology and investment cost is solved, its adaptability and flexibility in various complex environments are improved, and the stability of the power system is improved at the same time.

[0101] Next, a method for suppressing risk oscillation modes according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0102] Figure 6 This is a flow chart of a method for suppressing risk oscillation modes according to an embodiment of the present application.

[0103] like Figure 6 As shown, the method for suppressing the risk oscillation mode adopts Figure 1 The battery energy storage embedded novel power system stabilizer of the embodiment, wherein the method comprises the following steps:

[0104] In step S601, the three-phase voltage data and the three-phase current data of the grid connection point of the target oscillation system are obtained, and based on the three-phase voltage data and the three-phase current data of the grid connection point, an oscillation characteristic parameter set is obtained.

[0105] In step S602, an impedance branch model is established according to the oscillation characteristic parameter set, and the impedance branch model is optimized based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant.

[0106] In step S603, based on the three-phase voltage data and the three-phase current data of the grid connection point, the oscillation component of the dominant mode is obtained, and based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant, the oscillation component of the dominant mode is gain adjusted and phase compensated to obtain a three-phase additional reference current, and the risk oscillation mode of the target oscillation system is suppressed based on the three-phase additional reference current.

[0107] It should be noted that the aforementioned explanation of the embodiment of the battery energy storage embedded novel power system stabilizer is also applicable to the method for suppressing the risk oscillation mode of this embodiment, and will not be repeated here.

[0108] According to the method for suppressing risk oscillation modes proposed in the embodiment of the present application, a new power system stabilizer embedded with battery energy storage is used to solve the problem that the existing technology is limited by factors such as site, topology and investment cost and cannot be flexibly applied in all occasions. The method improves its adaptability and flexibility in various complex environments, while improving the stability of the power system.

[0109] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0110] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0111] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A new type of battery energy storage embedded power system stabilizer, characterized in that: include: an oscillation mode detection module, the oscillation mode detection module being used to obtain three-phase voltage data and three-phase current data of a grid connection point of a target oscillation system, and to obtain an oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point; An adaptive parameter optimization module, configured to establish an impedance branch model according to the oscillation characteristic parameter set, and optimize the impedance branch model based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant; A damping control module is configured to obtain the oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid connection point, perform gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant, obtain a three-phase additional reference current, and suppress the risk oscillation mode of the target oscillation system based on the three-phase additional reference current.

2. The battery energy storage embedded new power system stabilizer according to claim 1 is characterized in that: The oscillation mode detection module includes: A first acquisition unit is configured to acquire three-phase voltage data and three-phase current data of a grid connection point of the target oscillation system.

3. The battery energy storage embedded new power system stabilizer according to claim 2 is characterized in that: The oscillation mode detection module further includes: An obtaining unit is used to obtain the oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point.

4. The battery energy storage embedded new power system stabilizer according to claim 3 is characterized in that: The obtaining unit includes: an analog-to-digital conversion subunit, configured to perform analog-to-digital conversion on the three-phase voltage data and the three-phase current data of the grid connection point to obtain discrete signal data; The first processing subunit is used to determine a signal containing an oscillation component based on the discrete signal data, perform discrete Fourier transform on the signal containing the oscillation component to obtain a discrete sequence of spectral lines, and determine a dominant oscillation mode frequency based on the discrete sequence of spectral lines.

5. The battery energy storage embedded new power system stabilizer according to claim 4 is characterized in that: The obtaining unit further includes: A calculation subunit, the calculation subunit being used to calculate the dominant oscillation mode phase angle and the dominant oscillation mode amplitude using an interpolation algorithm and a compensation correction algorithm; A modeling subunit, the modeling subunit is used to model the change of the amplitude of the dominant oscillation mode over time to obtain the divergence rate of the dominant oscillation mode; An obtaining subunit is configured to obtain the oscillation characteristic parameter set based on the dominant oscillation mode phase angle, the dominant oscillation mode amplitude, the dominant oscillation mode frequency, and the divergence rate of the dominant oscillation mode.

6. The battery energy storage embedded new power system stabilizer according to claim 1 is characterized in that: The adaptive parameter optimization module includes: A modeling unit is used to establish the impedance branch model according to the oscillation characteristic parameter set.

7. The battery energy storage embedded new power system stabilizer according to claim 6 is characterized in that: The adaptive parameter optimization module further includes: An optimization unit is used to optimize the impedance branch model based on the preset objective function and the preset constraint conditions to obtain the optimal damping control gain and the optimal damping control time constant.

8. The battery energy storage embedded new power system stabilizer according to claim 1 is characterized in that: The damping control module includes: a second acquiring unit, configured to acquire an oscillation component of the dominant mode based on the three-phase voltage data and the three-phase current data of the grid connection point; a processing unit, configured to obtain the three-phase additional reference current based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant; A suppression unit is configured to suppress a risky oscillation mode of the target oscillation system based on the three-phase additional reference current.

9. The battery energy storage embedded new power system stabilizer according to claim 8, characterized in that: The processing unit includes: a second processing subunit, configured to perform the gain adjustment and phase compensation operations on the oscillation component of the dominant mode based on the oscillation characteristic parameter set, the optimal damping control gain, and the optimal damping control time constant, to obtain the oscillation component after the gain adjustment and phase compensation operations; The third processing subunit is used to perform a limiting process on the oscillation component after gain adjustment and phase compensation operations based on a preset converter capacity range, and obtain the three-phase additional reference current based on the oscillation component after the limiting process.

10. A method for suppressing risk oscillation mode, characterized in that: The battery energy storage embedded novel power system stabilizer according to any one of claims 1 to 9 is used, wherein the method comprises the following steps: Obtaining three-phase voltage data and three-phase current data of a grid connection point of a target oscillation system, and obtaining an oscillation characteristic parameter set based on the three-phase voltage data and the three-phase current data of the grid connection point; Establishing an impedance branch model according to the oscillation characteristic parameter set, and optimizing the impedance branch model based on a preset objective function and preset constraints to obtain an optimal damping control gain and an optimal damping control time constant; Based on the three-phase voltage data and the three-phase current data of the grid connection point, the oscillation component of the dominant mode is obtained, and based on the oscillation characteristic parameter set, the optimal damping control gain and the optimal damping control time constant, the oscillation component of the dominant mode is gain adjusted and phase compensated to obtain a three-phase additional reference current, and the risk oscillation mode of the target oscillation system is suppressed based on the three-phase additional reference current.

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