CN115719975A - A wind farm equivalent virtual inertia constant online evaluation method, device and storage medium - Google Patents

A wind farm equivalent virtual inertia constant online evaluation method, device and storage medium Download PDF

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CN115719975A
CN115719975A CN202211488214.9A CN202211488214A CN115719975A CN 115719975 A CN115719975 A CN 115719975A CN 202211488214 A CN202211488214 A CN 202211488214A CN 115719975 A CN115719975 A CN 115719975A
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power plant
wind power
equivalent
inertia constant
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吕振华
李强
伏祥运
李群
宋家康
贾勇勇
汪成根
唐伟佳
韩华春
李光熹
岳付昌
朱立位
李红
王博
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State Grid Jiangsu Electric Power Co Ltd
Electric Power Research Institute of State Grid Jiangsu Electric Power Co Ltd
Lianyungang Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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State Grid Jiangsu Electric Power Co Ltd
Electric Power Research Institute of State Grid Jiangsu Electric Power Co Ltd
Lianyungang Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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Abstract

The invention discloses an on-line evaluation method, device and storage medium for equivalent virtual inertia constant of a wind power plant, belonging to the technical field of new energy power generation control, and the method comprises the following steps: preprocessing measured data of the wind power plant; establishing an equivalent oscillation equation of the wind power plant according to the oscillation equation of the synchronous unit; constructing a station-level inertia constant evaluation model according to the equivalent oscillation equation of the wind power plant by using a time-frequency transformation method; inputting the preprocessed wind power plant actual measurement data into the station-level inertia constant evaluation model to output an evaluation result; performing singular point removing operation on the evaluation result to obtain an equivalent virtual inertia constant of the wind power plant; the measured data of the wind power plant comprise a system frequency signal and an active power signal of the wind power plant. According to the method, the equivalent virtual inertia constant of the wind power plant is evaluated on line through a time-frequency transformation method, and the inertia contribution of the wind power plant to a power grid can be quantitatively expressed.

Description

一种风电场等效虚拟惯量常数在线评估方法、装置及存储 介质A wind farm equivalent virtual inertia constant online evaluation method, device and storage medium

技术领域technical field

本发明涉及一种风电场等效虚拟惯量常数在线评估方法、装置及存储介质,属于新能源发电控制技术领域。The invention relates to an online evaluation method, device and storage medium for an equivalent virtual inertia constant of a wind farm, and belongs to the technical field of new energy power generation control.

背景技术Background technique

近年来,因新能源过多并网导致系统惯量支撑能力不足,进而引发停电事故的现象时有发生。准确评估系统的惯量水平有助于电网调度人员掌握惯量的薄弱阶段,进而及时采取惯量补偿措施,预防电网的频率跌落事故。In recent years, due to the excessive grid connection of new energy sources, the system inertia support capacity is insufficient, and power outages have occurred from time to time. Accurately assessing the inertia level of the system will help grid dispatchers grasp the weak stage of inertia, and then take inertia compensation measures in time to prevent frequency drop accidents in the grid.

电力系统中同步发电机的惯量常数是固定值,而对于施加了虚拟惯量控制的风电场而言,由于风电机组出力具有间歇性和不确定性,因此其等效虚拟惯量常数是未知的,并且具有快速时变特征。目前多数的惯量评估方法是对已发生的频率事件进行的离线辨识,无法在线实时评估风电场的惯量、帮助电网调度人员及时制定惯量补偿策略。Q.Mengqi等人发表的文献["Inertial Response of Doubly-fed Induction Generator with thePhase-locked Loop,"2019IEEE Innovative Smart Grid Technologies-Asia(ISGTAsia),2019,pp.1435-1439],利用风电机组的控制策略,定义了等效虚拟惯量常数的表达式以实现惯量的实时评估,但该方法仅适应于并网型惯量控制的风机,因此它不具备通用性。J.Zhang等人发表的文献["Online Identification of Power System EquivalentInertia Constant,"in IEEE Transactions on Industrial Electronics,vol.64,no.10,pp.8098-8107,Oct.2017],提出了一种利用电力电子器件对闭环系统进行微扰动的在线评估方法,实现了时变非线性等效惯量常数的实时识别,但外加的微扰动信号可能会影响系统的频率响应,进而影响系统运行的安全性。The inertia constant of a synchronous generator in a power system is a fixed value, but for a wind farm with virtual inertia control applied, its equivalent virtual inertia constant is unknown due to the intermittent and uncertain output of wind turbines, and have fast time-varying characteristics. Most of the current inertia evaluation methods are offline identification of frequency events that have occurred, which cannot evaluate the inertia of wind farms online in real time and help grid dispatchers formulate inertia compensation strategies in a timely manner. The literature published by Q. Mengqi et al ["Inertial Response of Doubly-fed Induction Generator with the Phase-locked Loop," 2019IEEE Innovative Smart Grid Technologies-Asia (ISGTAsia), 2019, pp.1435-1439], using the control of wind turbines strategy, which defines the expression of the equivalent virtual inertia constant to realize the real-time evaluation of inertia, but this method is only suitable for wind turbines with grid-connected inertia control, so it is not universal. The document ["Online Identification of Power System EquivalentInertia Constant," in IEEE Transactions on Industrial Electronics, vol.64, no.10, pp.8098-8107, Oct.2017] published by J. Zhang et al. proposed a method using The online evaluation method of micro-disturbance by power electronic devices on the closed-loop system realizes the real-time identification of the time-varying nonlinear equivalent inertia constant, but the external micro-disturbance signal may affect the frequency response of the system, and then affect the safety of the system operation.

根据评估层级不同,惯量评估可分为针对单机、多个节点及整个系统的辨识。W.He等人发表的文献["Inertia Provision and Estimation of PLL-Based DFIG WindTurbines,"in IEEE Transactions on Power Systems,vol.32,no.1,pp.510-521,Jan.2017],研究了定量解析表征时变的风电机组等效虚拟惯量常数的方法,但该方法需要获得较多的风电机组控制参数及状态参数,不适应于系统级的惯量评估,不能直接应用于实际风电场的惯量评估。对于系统级的惯量辨识,多数学者借助系统参数辨识模型(如输入/输出模型或状态空间模型)表征频率和功率间的传递函数,然后根据辨识结果提取惯量常数。K.Tuttelberg等人发表的文献["Estimation of Power System Inertia FromAmbient Wide Area Measurements,"in IEEE Transactions on Power Systems,vol.33,no.6,pp.7249-7257,Nov.2018],利用受控自回归模型代替风电场的摆动方程,从场站层面利用高阶模型替换法实现了对惯量的评估,但是高阶模型的最优阶数不易确认,并且评估结果的精度与辨识模型的类型相关。According to different evaluation levels, inertia evaluation can be divided into identification for single machine, multiple nodes and the whole system. The literature published by W.He et al ["Inertia Provision and Estimation of PLL-Based DFIG WindTurbines," in IEEE Transactions on Power Systems, vol.32, no.1, pp.510-521, Jan.2017], studied Quantitative analytical method to characterize the time-varying wind turbine equivalent virtual inertia constant, but this method needs to obtain more wind turbine control parameters and state parameters, which is not suitable for system-level inertia evaluation and cannot be directly applied to the actual wind farm inertia Evaluate. For system-level inertia identification, most scholars use system parameter identification models (such as input/output models or state-space models) to characterize the transfer function between frequency and power, and then extract inertia constants based on the identification results. The literature published by K.Tuttelberg et al ["Estimation of Power System Inertia From Ambient Wide Area Measurements," in IEEE Transactions on Power Systems, vol.33, no.6, pp.7249-7257, Nov.2018], using controlled The autoregressive model replaces the swing equation of the wind farm, and the high-order model replacement method is used to evaluate the inertia from the station level. However, the optimal order of the high-order model is not easy to confirm, and the accuracy of the evaluation results is related to the type of identification model. .

对于风电场等效虚拟惯量常数而言,当前缺乏一种系统级、数据易于获取且评估精度较高的在线评估方法。For the equivalent virtual inertia constant of wind farms, there is currently a lack of an online evaluation method at the system level, with easy access to data and high evaluation accuracy.

发明内容Contents of the invention

本发明的目的在于提供一种风电场等效虚拟惯量常数在线评估方法、装置及存储介质,通过时频变换法,对风电场等效虚拟惯量常数进行在线评估,能够定量表达风电场对电网的惯量贡献。The purpose of the present invention is to provide an online evaluation method, device and storage medium for the equivalent virtual inertia constant of a wind farm. Through the time-frequency transformation method, the online evaluation of the equivalent virtual inertia constant of the wind farm can be quantitatively expressed. inertia contribution.

为达到上述目的,本发明提供如下技术方案:To achieve the above object, the present invention provides the following technical solutions:

第一方面,本发明提供一种风电场等效虚拟惯量常数在线评估方法,包括:In a first aspect, the present invention provides an online evaluation method for an equivalent virtual inertia constant of a wind farm, comprising:

对风电场实测数据进行预处理;Preprocessing the measured data of the wind farm;

根据同步机组的摆动方程,建立风电场等效摆动方程;According to the swing equation of the synchronous unit, the equivalent swing equation of the wind farm is established;

利用时频变换法,根据所述风电场等效摆动方程,构建场站级惯量常数评估模型;Using the time-frequency transformation method, according to the equivalent swing equation of the wind farm, a station-level inertia constant evaluation model is constructed;

将经过预处理的风电场实测数据输入至所述场站级惯量常数评估模型,以输出评估结果;Inputting the preprocessed wind farm measured data into the station-level inertia constant evaluation model to output evaluation results;

对所述评估结果进行去奇异点操作,以获取风电场等效虚拟惯量常数;Performing a singular point removal operation on the evaluation result to obtain the equivalent virtual inertia constant of the wind farm;

其中,所述风电场实测数据包括系统频率信号和风电场有功功率信号。Wherein, the measured data of the wind farm includes a system frequency signal and an active power signal of the wind farm.

结合第一方面,进一步的,所述预处理包括:标幺化、去趋势和预滤波。With reference to the first aspect, further, the preprocessing includes: per unitization, detrending and pre-filtering.

结合第一方面,进一步的,所述风电场等效摆动方程的表达式如公式(1)所示:In combination with the first aspect, further, the expression of the equivalent swing equation of the wind farm is shown in formula (1):

Figure BDA0003963636740000031
Figure BDA0003963636740000031

公式(1)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,Pm为机械功率,Pe为电磁功率,ωs为系统频率,ωs0为系统额定频率。In formula (1), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, P m is the mechanical power, Pe is the electromagnetic power, ω s is the system frequency, and ω s0 is the system rated frequency.

结合第一方面,进一步的,利用时频变换法,根据所述风电场等效摆动方程,构建场站级惯量常数评估模型包括:In combination with the first aspect, further, using the time-frequency transformation method, according to the equivalent swing equation of the wind farm, constructing a station-level inertia constant evaluation model includes:

根据拉普拉斯变换和拉普拉斯逆变换,将所述风电场等效摆动方程由微分形式转换为积分形式,以获取风电场等效摆动积分方程;According to the Laplace transform and the inverse Laplace transform, the equivalent swing equation of the wind farm is converted from a differential form to an integral form to obtain an equivalent swing integral equation of the wind farm;

根据数值积分的梯度法,将所述风电场等效摆动积分方程由连续域转换为离散域,以获取场站级惯量常数评估模型。According to the gradient method of numerical integration, the equivalent swing integral equation of the wind farm is converted from the continuous domain to the discrete domain to obtain the station-level inertia constant evaluation model.

结合第一方面,进一步的,根据拉普拉斯变换和拉普拉斯逆变换,将所述风电场等效摆动方程由微分形式转换为积分形式,以获取风电场等效摆动积分方程包括:In combination with the first aspect, further, according to the Laplace transform and the inverse Laplace transform, converting the equivalent swing equation of the wind farm from a differential form to an integral form to obtain the equivalent swing integral equation of the wind farm includes:

对所述风电场等效摆动方程做拉普拉斯变换,用输出变量代替系统频率变化量,用输入变量代替风电场有功功率变化量,并忽略风电场机械功率变化量,以获取风电场等效摆动代数方程;Laplace transform is performed on the equivalent swing equation of the wind farm, the output variable is used to replace the system frequency variation, the input variable is used to replace the wind farm active power variation, and the wind farm mechanical power variation is ignored to obtain the wind farm, etc. effective swing algebraic equation;

根据所述风电场等效摆动代数方程,对运算算子求导,在求导后的等式两侧同时乘以s-2,并做拉普拉斯逆变换,以获取风电场等效摆动积分方程;According to the equivalent swing algebraic equation of the wind farm, derivate the operator, multiply both sides of the derived equation by s -2 , and perform Laplace inverse transformation to obtain the equivalent swing of the wind farm Integral equation;

其中,所述风电场等效摆动代数方程的表达式如公式(2)所示:Wherein, the expression of the equivalent swing algebraic equation of the wind farm is shown in formula (2):

Figure BDA0003963636740000041
Figure BDA0003963636740000041

公式(2)中,s为运算算子,Y为输出变量,U为输入变量,DWF为风电场阻尼系数,HWF为风电场等效虚拟惯量常数;In formula (2), s is the operation operator, Y is the output variable, U is the input variable, D WF is the damping coefficient of the wind farm, and H WF is the equivalent virtual inertia constant of the wind farm;

所述风电场等效摆动积分方程的表达式如公式(3)所示:The expression of the equivalent swing integral equation of the wind farm is shown in formula (3):

Figure BDA0003963636740000042
Figure BDA0003963636740000042

公式(3)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,TF=nFT,TF为时间间隔,nF为时间窗长度,T为采样周期,δ为积分变量,y(δ)为输出变量Y的时域表达式,u(δ)为输入变量U的时域表达式。In formula (3), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, T F = n F T, T F is the time interval, n F is the time window length, T is the sampling period, δ is the integral variable, y(δ) is the time-domain expression of the output variable Y, and u(δ) is the time-domain expression of the input variable U.

结合第一方面,进一步的,所述场站级惯量常数评估模型的表达式如公式(4)所示:In combination with the first aspect, further, the expression of the station-level inertia constant evaluation model is shown in formula (4):

Figure BDA0003963636740000043
Figure BDA0003963636740000043

公式(4)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,T为采样周期,i为第i个采样点,nF为时间窗长度,k为当前时刻采样点,y(i)为第i个采样时刻的输出量,y(i-1)为第i-1个采样时刻的输出量,y(i)=Δψ(k-(nF-i)),Δω为系统频率变化量,u(i)为第i个采样时刻的输入量,u(i)=ΔPe(k-(nF-i)),ΔPe为风电场有功功率变化量。In formula (4), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, T is the sampling period, i is the i-th sampling point, n F is the length of the time window, and k is the current sampling time point, y(i) is the output at the i-th sampling moment, y(i-1) is the output at the i-1th sampling moment, y(i)=Δψ(k-(n F -i)) , Δω is the system frequency variation, u(i) is the input quantity at the i-th sampling moment, u(i)=ΔP e (k-(n F -i)), ΔP e is the wind farm active power variation.

结合第一方面,进一步的,所述去奇异点操作所使用的公式如公式(5)所示:In combination with the first aspect, further, the formula used in the singular point removal operation is shown in formula (5):

Figure BDA0003963636740000051
Figure BDA0003963636740000051

公式(5)中,HWF(k)为当前采样时刻风电场等效虚拟惯量常数,HWF(k-1)为前一采样时刻风电场等效虚拟惯量常数,k为当前时刻采样点,

Figure BDA0003963636740000052
Figure BDA0003963636740000053
T为采样周期,i为第i个采样点,nF为时间窗长度,DWF为风电场阻尼系数,y(i)为第i个采样时刻的输出量,u(i)为第i个采样时刻的输入量,
Figure BDA0003963636740000054
y(i-1)为第i-1个采样时刻的输出量,ε为防止出现数值误差的阈值,β为防止出现数值误差的比例系数,β<<1。In formula (5), H WF (k) is the equivalent virtual inertia constant of the wind farm at the current sampling moment, H WF (k-1) is the equivalent virtual inertia constant of the wind farm at the previous sampling moment, k is the sampling point at the current moment,
Figure BDA0003963636740000052
Figure BDA0003963636740000053
T is the sampling period, i is the ith sampling point, n F is the length of the time window, D WF is the damping coefficient of the wind farm, y(i) is the output at the i-th sampling time, u(i) is the i-th The input quantity at the sampling moment,
Figure BDA0003963636740000054
y(i-1) is the output at the i-1th sampling time, ε is the threshold to prevent numerical errors, β is the proportional coefficient to prevent numerical errors, β<<1.

第二方面,本发明提供一种风电场等效虚拟惯量常数在线评估装置,包括:In a second aspect, the present invention provides an online evaluation device for an equivalent virtual inertia constant of a wind farm, comprising:

预处理模块:用于对风电场实测数据进行预处理;Preprocessing module: used to preprocess the measured data of the wind farm;

方程构建模块:用于根据同步机组的摆动方程,建立风电场等效摆动方程;Equation building module: used to establish the equivalent swing equation of the wind farm according to the swing equation of the synchronous unit;

模型构建模块:用于利用时频变换法,根据所述风电场等效摆动方程,构建场站级惯量常数评估模型;Model building module: used to construct a site-level inertia constant evaluation model according to the equivalent swing equation of the wind farm by using the time-frequency transformation method;

评估模块:用于将经过预处理的风电场实测数据输入至所述场站级惯量常数评估模型,以输出评估结果;Evaluation module: used to input the preprocessed wind farm measured data into the station-level inertia constant evaluation model to output evaluation results;

去奇异点模块:用于对所述评估结果进行去奇异点操作,以获取风电场等效虚拟惯量常数;Singular point removal module: used to perform singular point removal operation on the evaluation result to obtain the equivalent virtual inertia constant of the wind farm;

其中,所述风电场实测数据包括系统频率信号和风电场有功功率信号。Wherein, the measured data of the wind farm includes a system frequency signal and an active power signal of the wind farm.

第三方面,本发明提供一种风电场等效虚拟惯量常数在线评估装置,包括处理器及存储介质;In a third aspect, the present invention provides an online evaluation device for an equivalent virtual inertia constant of a wind farm, including a processor and a storage medium;

所述存储介质用于存储指令;The storage medium is used to store instructions;

所述处理器用于根据所述指令进行操作以执行根据第一方面任一项所述方法的步骤。The processor is configured to operate according to the instructions to perform the steps of any one of the methods according to the first aspect.

第四方面,本发明提供一种计算机可读存储介质,其上存储有计算机程序,该程序被处理器执行时实现第一方面任一项所述方法的步骤。In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

与现有技术相比,本发明的有益效果是:Compared with prior art, the beneficial effect of the present invention is:

本发明利用时频变换法将风电场等效摆动方程由微分形式转换为积分形式,实现了间接处理频率导数项,避免了导数尖峰问题;本发明所利用的时频变换法无需迭代过程,提高了评估速度;本发明实现了场站级别等效惯量常数的在线评估,具有一定的实际应用性;本发明的评估方法能够运用于其他新能源场群或其他虚拟惯量控制方式。The present invention uses the time-frequency transformation method to convert the equivalent swing equation of the wind farm from the differential form to the integral form, realizes the indirect processing of the frequency derivative term, and avoids the derivative peak problem; the time-frequency transformation method used in the present invention does not need an iterative process, and improves The evaluation speed is improved; the present invention realizes the online evaluation of the equivalent inertia constant at the station level, and has certain practical applicability; the evaluation method of the present invention can be applied to other new energy field groups or other virtual inertia control methods.

附图说明Description of drawings

图1是本发明实施例提供的一种风电场等效虚拟惯量常数在线评估方法流程图;Fig. 1 is a flow chart of an online evaluation method for an equivalent virtual inertia constant of a wind farm provided by an embodiment of the present invention;

图2是本发明实施例提供的sinmulink平台的风电场拓扑图;Fig. 2 is the topological diagram of the wind farm of the sinmulink platform provided by the embodiment of the present invention;

图3是本发明实施例提供的sinmulink平台风电场在负荷突增时频率扰动波形图;Fig. 3 is the sinmulink platform wind farm provided by the embodiment of the present invention frequency disturbance waveform diagram when the load suddenly increases;

图4是本发明实施例提供的sinmulink平台风电场在负荷突增时增发的有功功率波形图;Fig. 4 is a waveform diagram of active power generated by the wind farm of the sinmulink platform provided by the embodiment of the present invention when the load suddenly increases;

图5是本发明实施例提供的sinmulink平台10m/s风速下风电场等效虚拟惯量常数评估结果;Fig. 5 is the evaluation result of the equivalent virtual inertia constant of the wind farm under the sinmulink platform 10m/s wind speed provided by the embodiment of the present invention;

图6是本发明实施例提供的sinmulink平台8m/s风速下风电场等效虚拟惯量常数评估结果;Fig. 6 is the evaluation result of the equivalent virtual inertia constant of the wind farm under the sinmulink platform 8m/s wind speed provided by the embodiment of the present invention;

图7是本发明实施例提供的sinmulink平台12m/s风速下风电场等效虚拟惯量常数评估结果;Fig. 7 is the evaluation result of the equivalent virtual inertia constant of the wind farm under the sinmulink platform 12m/s wind speed provided by the embodiment of the present invention;

图8是本发明实施例提供的频率下扰时大丰风电场等效虚拟惯量常数评估结果;Fig. 8 is the evaluation result of the equivalent virtual inertia constant of Dafeng wind farm when the frequency is disturbed by the embodiment of the present invention;

图9是本发明实施例提供的频率上扰时大丰风电场等效虚拟惯量常数评估结果。Fig. 9 is the evaluation result of the equivalent virtual inertia constant of the Dafeng wind farm when the frequency is disturbed by the embodiment of the present invention.

具体实施方式Detailed ways

下面结合具体实施方式对本专利的技术方案作进一步详细地说明。The technical solution of this patent will be further described in detail below in conjunction with specific embodiments.

下面详细描述本专利的实施例,所述实施例的示例在附图中示出,其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的,仅用于解释本专利,而不能理解为对本专利的限制。在不冲突的情况下,本申请实施例以及实施例中的技术特征可以相互组合。Embodiments of the present patent are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are only used for explaining the patent, and should not be construed as limiting the patent. In the case of no conflict, the embodiments of the present application and the technical features in the embodiments may be combined with each other.

实施例一:Embodiment one:

图1是本发明实施例一提供的一种风电场等效虚拟惯量常数在线评估方法流程图,本流程图仅仅示出了本实施例方法的逻辑顺序,在互不冲突的前提下,在本发明其它可能的实施例中,可以以不同于图1所示的顺序完成所示出或描述的步骤。Figure 1 is a flowchart of an online evaluation method for an equivalent virtual inertia constant of a wind farm provided by Embodiment 1 of the present invention. This flowchart only shows the logical sequence of the method in this embodiment. On the premise of not conflicting with each other, in this In other possible embodiments of the invention, the steps shown or described may be performed in an order different from that shown in FIG. 1 .

本实施例提供的风电场等效虚拟惯量常数在线评估方法可应用于终端,可以由风电场等效虚拟惯量常数在线评估装置来执行,该装置可以由软件和/或硬件的方式实现,该装置可以集成在终端中,例如:任一具备通信功能的平板电脑或计算机设备。参见图1,本实施例的方法具体包括如下步骤:The wind farm equivalent virtual inertia constant online evaluation method provided in this embodiment can be applied to a terminal, and can be executed by a wind farm equivalent virtual inertia constant online evaluation device, which can be implemented by software and/or hardware. It can be integrated in a terminal, such as any tablet or computer device with communication functions. Referring to Fig. 1, the method of the present embodiment specifically includes the following steps:

步骤一:对风电场实测数据进行预处理;Step 1: Preprocessing the measured data of the wind farm;

风电场实测数据包括系统频率信号和风电场有功功率信号;对风电场实测数据进行预处理包括如下步骤:The measured data of the wind farm includes the system frequency signal and the active power signal of the wind farm; the preprocessing of the measured data of the wind farm includes the following steps:

步骤A:对风电场实测数据进行标幺化处理;Step A: Carry out per-unit processing on the measured data of the wind farm;

对风电场实测数据进行标幺化处理包括:将系统频率信号和风电场有功功率信号分别除以其各自的额定值。The per-unit processing of the measured data of the wind farm includes: dividing the system frequency signal and the active power signal of the wind farm by their respective rated values.

步骤B:对经过标幺化处理的风电场实测数据进行去趋势处理;Step B: detrending the measured data of the wind farm after per-unit processing;

对经过标幺化处理的风电场实测数据进行去趋势处理包括:将经过标幺化处理后的系统频率信号、风电场有功功率信号分别减去其各自采用平均值法拟合所得的最优趋势直线数据,以去除系统频率信号、风电场有功功率信号中的直流分量。The detrending process of the measured data of the wind farm after the per-unit processing includes: respectively subtracting the optimal trend obtained by fitting the average value method from the system frequency signal and the active power signal of the wind farm after the per-unit processing. Straight line data to remove the DC component in the system frequency signal and the active power signal of the wind farm.

步骤C:对经过去趋势处理的风电场实测数据进行预滤波处理;Step C: pre-filtering the measured wind farm data after detrending processing;

对经过去趋势处理的风电场实测数据进行预滤波处理包括:采用截止频率为0.5Hz的低通巴特沃斯滤波器,对经过去趋势处理的系统频率信号、风电场有功功率信号进行预滤波,以消除系统频率信号、风电场有功功率信号中的高频噪声,提高评估模型的鲁棒性。The pre-filtering of the detrended measured wind farm data includes: using a low-pass Butterworth filter with a cutoff frequency of 0.5 Hz to pre-filter the detrended system frequency signal and wind farm active power signal. In order to eliminate the high-frequency noise in the system frequency signal and the active power signal of the wind farm, the robustness of the evaluation model is improved.

步骤二:根据同步机组的摆动方程,建立风电场等效摆动方程;Step 2: According to the swing equation of the synchronous unit, establish the equivalent swing equation of the wind farm;

风电场等效摆动方程的表达式如公式(1)所示:The expression of the equivalent swing equation of the wind farm is shown in formula (1):

Figure BDA0003963636740000081
Figure BDA0003963636740000081

公式(1)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,Pm为机械功率,Pe为电磁功率,ωs为系统频率,ωs0为系统额定频率。In formula (1), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, P m is the mechanical power, Pe is the electromagnetic power, ω s is the system frequency, and ω s0 is the system rated frequency.

根据虚拟惯量作用机理,能够建立风电场等效虚拟惯量常数的计算表达式;采用虚拟惯量控制的风电机组是通过释放转子动能向电网提供惯量支撑功率的,因此风机转子转速与系统频率相耦合,风机释放的转子动能变化量也能够用系统频率与等效虚拟转动惯量来表示:According to the mechanism of virtual inertia, the calculation expression of the equivalent virtual inertia constant of the wind farm can be established; the wind turbine with virtual inertia control provides inertia support power to the grid by releasing the kinetic energy of the rotor, so the rotor speed of the fan is coupled with the system frequency, The change in kinetic energy of the rotor released by the fan can also be expressed by the system frequency and the equivalent virtual moment of inertia:

Figure BDA0003963636740000091
Figure BDA0003963636740000091

Figure BDA0003963636740000092
Figure BDA0003963636740000092

其中,Jequ为风电机组等效虚拟转动惯量,Jinherent为风电机组固有转动惯量,Ek为单台风机额定转速时的发电机转子储存动能,n为风电机组极对数,SN为风机额定容量,ωr为风机转子转速,ωr0为风机初始转子转速,Δωr为风机转子转速变化量,Δωs为系统频率变化量。Among them, J equ is the equivalent virtual moment of inertia of the wind turbine, J inherent is the inherent moment of inertia of the wind turbine, E k is the stored kinetic energy of the generator rotor at the rated speed of a single wind turbine, n is the number of pole pairs of the wind turbine, and S N is the wind turbine Rated capacity, ω r is the rotor speed of the fan, ω r0 is the initial rotor speed of the fan, Δω r is the variation of the fan rotor speed, and Δω s is the variation of the system frequency.

由此,能够获得风电机组和风电场等效虚拟惯量常数计算表达式:Thus, the calculation expressions of equivalent virtual inertia constants of wind turbines and wind farms can be obtained:

Figure BDA0003963636740000093
Figure BDA0003963636740000093

Figure BDA0003963636740000094
Figure BDA0003963636740000094

其中,Hinherent为风电机组固有惯量常数,HWF为风电场等效虚拟惯量常数,m为风场内风电机组的个数。Among them, H inherent is the inherent inertia constant of the wind turbine, H WF is the equivalent virtual inertia constant of the wind farm, and m is the number of wind turbines in the wind farm.

通过此方法计算风电场的等效虚拟惯量常数需要每个风机的固有惯量常数Hinherent,但在实际应用中,厂家通常不会给出固有惯量常数Hinherent,这给评估风电场的惯量水平带来挑战,本发明所提供的方法能够有效解决这一问题。Calculating the equivalent virtual inertia constant of the wind farm by this method requires the inherent inertia constant H inherent of each wind turbine, but in practical applications, the manufacturer usually does not give the inherent inertia constant H inherent , which makes it difficult to evaluate the inertia level of the wind farm. To challenge, the method provided by the present invention can effectively solve this problem.

步骤三:利用时频变换法,根据风电场等效摆动方程,构建场站级惯量常数评估模型;Step 3: Use the time-frequency transformation method to construct a station-level inertia constant evaluation model according to the equivalent swing equation of the wind farm;

利用时频变换法,根据风电场等效摆动方程,构建场站级惯量常数评估模型包括如下步骤:Using the time-frequency transformation method and according to the equivalent swing equation of the wind farm, the construction of a station-level inertia constant evaluation model includes the following steps:

步骤Ⅰ:根据拉普拉斯变换和拉普拉斯逆变换,将风电场等效摆动方程由微分形式转换为积分形式,以获取风电场等效摆动积分方程;Step Ⅰ: According to the Laplace transform and Laplace inverse transform, the equivalent swing equation of the wind farm is converted from the differential form to the integral form to obtain the equivalent swing integral equation of the wind farm;

根据拉普拉斯变换和拉普拉斯逆变换,将风电场等效摆动方程由微分形式转换为积分形式,以获取风电场等效摆动积分方程包括如下步骤:According to the Laplace transform and the inverse Laplace transform, the equivalent swing equation of the wind farm is converted from the differential form to the integral form to obtain the equivalent swing integral equation of the wind farm, which includes the following steps:

步骤①:对风电场等效摆动方程做拉普拉斯变换,用输出变量代替系统频率变化量,用输入变量代替风电场有功功率变化量,并忽略风电场机械功率变化量,以获取风电场等效摆动代数方程;Step ①: Laplace transform the equivalent swing equation of the wind farm, replace the system frequency variation with the output variable, replace the active power variation of the wind farm with the input variable, and ignore the mechanical power variation of the wind farm to obtain the wind farm Equivalent swing algebraic equation;

步骤②:根据风电场等效摆动代数方程,对运算算子求导,在求导后的等式两侧同时乘以s-2,以减弱噪声,并做拉普拉斯逆变换,以获取风电场等效摆动积分方程;Step ②: According to the equivalent swing algebraic equation of the wind farm, derive the derivative of the operator, multiply both sides of the derived equation by s -2 at the same time to reduce the noise, and perform Laplace inverse transform to obtain Equivalent swing integral equation of wind farm;

其中,风电场等效摆动代数方程的表达式如公式(2)所示:Among them, the expression of the equivalent swing algebraic equation of the wind farm is shown in formula (2):

Figure BDA0003963636740000101
Figure BDA0003963636740000101

公式(2)中,s为运算算子,Y为输出变量,U为输入变量,DWF为风电场阻尼系数,HWF为风电场等效虚拟惯量常数;In formula (2), s is the operation operator, Y is the output variable, U is the input variable, D WF is the damping coefficient of the wind farm, and H WF is the equivalent virtual inertia constant of the wind farm;

风电场等效摆动积分方程的表达式如公式(3)所示:The expression of the wind farm equivalent swing integral equation is shown in formula (3):

Figure BDA0003963636740000102
Figure BDA0003963636740000102

公式(3)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,TF=nFT,TF为时间间隔,nF为时间窗长度,T为采样周期,δ为积分变量,y(δ)为输出变量Y的时域表达式,u(δ)为输入变量U的时域表达式。In formula (3), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, T F = n F T, T F is the time interval, n F is the time window length, T is the sampling period, δ is the integral variable, y(δ) is the time-domain expression of the output variable Y, and u(δ) is the time-domain expression of the input variable U.

步骤Ⅱ:根据数值积分的梯度法,将风电场等效摆动积分方程由连续域转换为离散域,以获取场站级惯量常数评估模型;Step Ⅱ: According to the gradient method of numerical integration, the equivalent swing integral equation of the wind farm is converted from the continuous domain to the discrete domain to obtain the station-level inertia constant evaluation model;

场站级惯量常数评估模型的表达式如公式(4)所示:The expression of the station-level inertia constant evaluation model is shown in formula (4):

Figure BDA0003963636740000111
Figure BDA0003963636740000111

公式(4)中,HWF为风电场等效虚拟惯量常数,DWF为风电场阻尼系数,T为采样周期,i为第i个采样点,nF为时间窗长度,k为当前时刻采样点,y(i)为第i个采样时刻的输出量,y(i-1)为第i-1个采样时刻的输出量,y(i)=Δω(k-(nF-i)),Δω为系统频率变化量,u(i)为第i个采样时刻的输入量,u(i)=ΔPe(k-(nF-i)),ΔPe为风电场有功功率变化量。In formula (4), H WF is the equivalent virtual inertia constant of the wind farm, D WF is the damping coefficient of the wind farm, T is the sampling period, i is the i-th sampling point, n F is the length of the time window, and k is the current sampling time point, y(i) is the output at the i-th sampling moment, y(i-1) is the output at the i-1th sampling moment, y(i)=Δω(k-(n F -i)) , Δω is the system frequency variation, u(i) is the input quantity at the i-th sampling moment, u(i)=ΔP e (k-(n F -i)), ΔP e is the wind farm active power variation.

步骤四:将经过预处理的风电场实测数据输入至场站级惯量常数评估模型,以输出评估结果;Step 4: Input the preprocessed wind farm measured data into the station-level inertia constant evaluation model to output the evaluation results;

经过预处理后的系统频率信号和风电场有功功率信号作为场站级惯量常数评估模型的输入信号,经过场站级惯量常数评估模型输出评估结果。The preprocessed system frequency signal and wind farm active power signal are used as the input signals of the station-level inertia constant evaluation model, and the evaluation results are output through the station-level inertia constant evaluation model.

步骤五:对评估结果进行去奇异点操作,以获取风电场等效虚拟惯量常数;Step 5: Perform singular point removal operation on the evaluation results to obtain the equivalent virtual inertia constant of the wind farm;

去奇异点操作所使用的公式如公式(5)所示:The formula used for the singular point removal operation is shown in formula (5):

Figure BDA0003963636740000112
Figure BDA0003963636740000112

公式(5)中,HWF(k)为当前采样时刻风电场等效虚拟惯量常数,HWF(k-1)为前一采样时刻风电场等效虚拟惯量常数,k为当前时刻采样点,

Figure BDA0003963636740000113
Figure BDA0003963636740000114
T为采样周期,i为第i个采样点,nF为时间窗长度,DWF为风电场阻尼系数,y(i)为第i个采样时刻的输出量,u(i)为第i个采样时刻的输入量,
Figure BDA0003963636740000115
y(i-1)为第i-1个采样时刻的输出量,ε为防止出现数值误差的阈值,β为防止出现数值误差的比例系数,β<<1。In formula (5), H WF (k) is the equivalent virtual inertia constant of the wind farm at the current sampling moment, H WF (k-1) is the equivalent virtual inertia constant of the wind farm at the previous sampling moment, k is the sampling point at the current moment,
Figure BDA0003963636740000113
Figure BDA0003963636740000114
T is the sampling period, i is the ith sampling point, n F is the length of the time window, D WF is the damping coefficient of the wind farm, y(i) is the output at the i-th sampling time, u(i) is the i-th The input quantity at the sampling moment,
Figure BDA0003963636740000115
y(i-1) is the output at the i-1th sampling time, ε is the threshold to prevent numerical errors, β is the proportional coefficient to prevent numerical errors, β<<1.

为验证本发明所提供的评估方法的准确性,利用Matlab/Sinmulink仿真软件建立风电场仿真系统。如图2所示,系统模型包含1个容量为60MW的风电场和1个容量为100MW的同步发电机,其中60MW的风电场(采用单机等值模型)由30台容量为2MW的直驱风电机组组成。同步机和风机的参数分别见表1和表2。为方便分析,仿真采用标幺值模型。In order to verify the accuracy of the evaluation method provided by the present invention, a wind farm simulation system is established using Matlab/Sinmulink simulation software. As shown in Figure 2, the system model includes a wind farm with a capacity of 60MW and a synchronous generator with a capacity of 100MW, in which the wind farm with a capacity of 60MW (using the equivalent model of a single machine) is composed of 30 direct-drive wind power generators with a capacity of 2MW Crew composition. The parameters of the synchronous machine and fan are shown in Table 1 and Table 2, respectively. For the convenience of analysis, the simulation adopts the per unit value model.

表1同步机参数Table 1 Synchronous Machine Parameters

参数parameter 符号symbol 数值value 网侧相电压额定幅值Grid side phase voltage rated amplitude U<sub>base</sub>U<sub>base</sub> 20kV20kV 有功功率额定值Active power rating P<sub>nom</sub>P<sub>nom</sub> 45.7MW45.7MW 额定容量Rated Capacity S<sub>N</sub>S<sub>N</sub> 100MW100MW 转动惯量Moment of inertia JJ 27000kg·m<sup>2</sup>27000kg·m<sup>2</sup> 阻尼因子damping factor K<sub>d</sub>K<sub>d</sub> 55 极对数Number of pole pairs nno 22 网侧角频率Grid side angular frequency ω<sub>g</sub>ω<sub>g</sub> 100πrad/s100πrad/s 转子机械角频率Rotor mechanical angular frequency ω<sub>r</sub>ω<sub>r</sub> 50πrad/s50πrad/s

表2直驱风电机参数Table 2 Direct Drive Wind Motor Parameters

参数parameter 符号symbol 数值value 网侧相电压额定幅值Grid side phase voltage rated amplitude U<sub>base</sub>U<sub>base</sub> 563V563V 有功功率额定值Active power rating P<sub>nom</sub>P<sub>nom</sub> 1.49MW1.49MW 额定容量Rated Capacity S<sub>N</sub>S<sub>N</sub> 2MW2MW 转动惯量Moment of inertia J<sub>inherent</sub>J<sub>inherent</sub> 7·10<sup>6</sup>kg·m<sup>2</sup>7·10<sup>6</sup>kg·m<sup>2</sup> 阻尼因子damping factor DD. 55 极对数Number of pole pairs nno 3030 网侧角频率Grid side angular frequency ω<sub>g</sub>ω<sub>g</sub> 100πrad/s100πrad/s 转子机械角频率Rotor mechanical angular frequency ω<sub>r</sub>ω<sub>r</sub> 60rad/s60rad/s

仿真过程中假设风速恒定为额定风速10m/s,在12s时,20kV母线处负荷突增2.5MW,造成电网频率下降。当系统频率偏差大于0.01Hz时,风电机组启动虚拟惯量控制策略,仿真结果如图3、图4所示。图3、图4分别为风电场对负荷突增的频率响应及功率响应。During the simulation process, it is assumed that the wind speed is constant at the rated wind speed of 10m/s. At 12s, the load at the 20kV bus increases suddenly by 2.5MW, causing the power grid frequency to drop. When the system frequency deviation is greater than 0.01Hz, the wind turbine starts the virtual inertia control strategy, and the simulation results are shown in Figure 3 and Figure 4. Figure 3 and Figure 4 respectively show the frequency response and power response of the wind farm to the sudden increase of load.

将图3、图4的数据作为所提评估模型的输入,得到风电场等效惯量常数的辨识值HWF;将提取的转子转速变化量Δωr、系统频率变化量Δωs,与固有惯量常数Hinherent和风机个数m结合,综合计算得到风电场等效虚拟惯量常数的计算值HWF。风电场等效虚拟惯量常数的辨识值和计算值共同表示在图5中。Using the data in Figure 3 and Figure 4 as the input of the proposed evaluation model, the identification value H WF of the equivalent inertia constant of the wind farm is obtained; the extracted rotor speed change Δω r , system frequency change Δω s , and the intrinsic inertia constant H inherent is combined with the number of wind turbines m, and the calculated value H WF of the equivalent virtual inertia constant of the wind farm is obtained through comprehensive calculation. The identification value and calculated value of the equivalent virtual inertia constant of the wind farm are shown in Fig. 5 together.

由图5中HWF的比较曲线来看,风电场等效虚拟惯量常数计算值与辨识值吻合度较高,证明了本发明所提评估模型的有效性和准确性。图5中,HWF从一个较大的初始值持续减小,初始值在8s附近。在惯量响应初始时刻,系统频率变化率较大,导致风电场产生最强的频率抑制作用,因此风电场等效虚拟惯量常数最大。风电场的惯性响应作用是通过释放机组转子动能向电网提供动态有功功率支撑,因此虚拟惯量启动时,机组转子转速持续下降。由于风机采用最大功率点跟踪(MPPT),因此转子转速的下降程度会影响风电场输出的有功功率。有功功率变化量不仅与虚拟惯量控制作用的附加功率有关,而且与MPPT模式下输出的功率给定值有关,因此通过有功功率变化量和系统频率变化量辨识得到的HWF不是固定值,而是时变值。从图5可以看出,大约在12.5s处,风电场发出的有功功率开始受转子转速的影响,HWF开始持续减小。大约在17.7s以后,部分时间段会出现HWF<0的数值,这主要是因为机组转子转速变化与系统频率变化不同步。但是因为惯量响应是存在于系统频率跌落初期,因此HWF的评估只需要关注系统频率跌落后几秒时间内的频率和有功功率数据。From the comparison curve of HWF in Fig. 5, the calculated value of the equivalent virtual inertia constant of the wind farm is in good agreement with the identified value, which proves the validity and accuracy of the evaluation model proposed by the present invention. In Figure 5, H WF continues to decrease from a large initial value around 8s. At the initial moment of inertia response, the frequency change rate of the system is relatively large, resulting in the strongest frequency suppression effect of the wind farm, so the equivalent virtual inertia constant of the wind farm is the largest. The inertia response function of the wind farm is to provide dynamic active power support to the grid by releasing the kinetic energy of the rotor of the generator set. Therefore, when the virtual inertia starts, the rotor speed of the generator set continues to decrease. Since the wind turbine adopts maximum power point tracking (MPPT), the decrease degree of the rotor speed will affect the active power output by the wind farm. The variation of active power is not only related to the additional power of virtual inertia control, but also to the given value of output power in MPPT mode. Therefore, the HWF obtained by identifying the variation of active power and the variation of system frequency is not a fixed value, but time-varying value. It can be seen from Fig. 5 that at about 12.5s, the active power generated by the wind farm begins to be affected by the rotor speed, and HWF begins to decrease continuously. After about 17.7s, the value of H WF <0 will appear in some time periods, which is mainly because the change of the rotor speed of the unit is not synchronized with the change of the system frequency. However, because the inertia response exists at the initial stage of the system frequency drop, the evaluation of HWF only needs to focus on the frequency and active power data within a few seconds after the system frequency drops.

为全方面验证本发明所提评估模型的准确性,本发明在不同风速条件下进行了仿真。图6、图7分别为风速8m/s和12m/s情况下所提算法的评估结果。从图6、图7可以看出,不同风速下所提算法的辨识值与计算值趋势基本一致。在惯量响应初期,评估结果存在一定的误差,但不影响整体的惯量评估结果。In order to fully verify the accuracy of the evaluation model proposed by the present invention, the present invention has carried out simulations under different wind speed conditions. Figure 6 and Figure 7 are the evaluation results of the proposed algorithm under the conditions of wind speed 8m/s and 12m/s respectively. It can be seen from Fig. 6 and Fig. 7 that the identification value of the proposed algorithm under different wind speeds is basically consistent with the trend of the calculated value. In the initial stage of inertia response, there are certain errors in the evaluation results, but this does not affect the overall inertia evaluation results.

本发明在天润大丰风电场进行现场测试,测试分为频率上扰和频率下扰两种类型。将所获取的润龙二线风电数据——系统频率、有功功率输入评估模型,评估结果如图8、图9所示。由于天润大丰风电场在惯量响应是令风电机组的MPPT模式闭锁,因此评估所得的等效虚拟惯量常数应为常值。图8、图9所示的评估结果HWF在设定值5s左右浮动,证明了本发明所提评估算法的有效性和准确性。The present invention is tested on-site at Tianrun Dafeng Wind Farm, and the test is divided into two types of frequency disturbance and frequency disturbance. The obtained Runlong second line wind power data - system frequency and active power are input into the evaluation model, and the evaluation results are shown in Figure 8 and Figure 9. Since the inertia response of Tianrun Dafeng Wind Farm is to block the MPPT mode of the wind turbine, the equivalent virtual inertia constant obtained from the evaluation should be a constant value. The evaluation results H WF shown in Fig. 8 and Fig. 9 fluctuate around the set value of 5s, which proves the validity and accuracy of the evaluation algorithm proposed in the present invention.

本实施例中,将风电场等效摆动方程由时域内的微分方程形式转换为频域内的代数方程形式,进行代数运算,然后利用拉普拉斯逆变换将频域内的代数方程转换为时域内可辨识的积分方程,最后利用数值积分的梯度法求解等效惯量常数的表达式,以构建场站级惯量常数评估模型。该方法将风电场等效摆动方程由微分方程形式转换为积分方程形式,实现了间接处理惯量评估模型方程中的频率导数项,避免了导数尖峰问题;并且该方法充分利用频率偏差和功率偏差的历史数据,避免了单个不良数据点造成的辨识误差;对评估结果进行去奇异点操作,能够在防止评估结果HWF突然增大的同时,保持HWF的变化趋势,选择合适的β能够有效消除数值误差,提高评估结果的准确度,令评估模型对噪声的敏感度降低。In this embodiment, the equivalent swing equation of the wind farm is converted from a differential equation in the time domain to an algebraic equation in the frequency domain, algebraic operations are performed, and then the algebraic equation in the frequency domain is converted into a time domain by inverse Laplace transform. The identifiable integral equation is finally used to solve the expression of the equivalent inertia constant by using the gradient method of numerical integration to construct a station-level inertia constant evaluation model. This method converts the equivalent swing equation of the wind farm from a differential equation form to an integral equation form, realizes the indirect processing of the frequency derivative term in the inertia evaluation model equation, and avoids the derivative peak problem; and this method makes full use of the frequency deviation and power deviation. Historical data avoids the identification error caused by a single bad data point; the singular point removal operation on the evaluation results can prevent the sudden increase of H WF in the evaluation results while maintaining the change trend of H WF , and choosing an appropriate β can effectively eliminate Numerical errors improve the accuracy of the evaluation results and reduce the sensitivity of the evaluation model to noise.

实施例二:Embodiment two:

本实施例提供一种风电场等效虚拟惯量常数在线评估装置,包括:This embodiment provides an online evaluation device for an equivalent virtual inertia constant of a wind farm, including:

预处理模块:用于对风电场实测数据进行预处理;Preprocessing module: used to preprocess the measured data of the wind farm;

方程构建模块:用于根据同步机组的摆动方程,建立风电场等效摆动方程;Equation building module: used to establish the equivalent swing equation of the wind farm according to the swing equation of the synchronous unit;

模型构建模块:用于利用时频变换法,根据风电场等效摆动方程,构建场站级惯量常数评估模型;Model building module: used to construct a site-level inertia constant evaluation model based on the equivalent swing equation of the wind farm using the time-frequency transformation method;

评估模块:用于将经过预处理的风电场实测数据输入至场站级惯量常数评估模型,以输出评估结果;Evaluation module: used to input the preprocessed wind farm measured data into the station-level inertia constant evaluation model to output the evaluation results;

去奇异点模块:用于对评估结果进行去奇异点操作,以获取风电场等效虚拟惯量常数;Singularity removal module: used to remove the singularity of the evaluation results to obtain the equivalent virtual inertia constant of the wind farm;

其中,风电场实测数据包括系统频率信号和风电场有功功率信号。Among them, the measured data of the wind farm includes the system frequency signal and the active power signal of the wind farm.

本发明实施例所提供的风电场等效虚拟惯量常数在线评估装置可执行本发明任意实施例所提供的风电场等效虚拟惯量常数在线评估方法,具备执行方法相应的功能模块和有益效果。The wind farm equivalent virtual inertia constant online evaluation device provided by the embodiments of the present invention can execute the wind farm equivalent virtual inertia constant online evaluation method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

实施例三:Embodiment three:

本实施例提供一种风电场等效虚拟惯量常数在线评估装置,包括处理器及存储介质;This embodiment provides an online evaluation device for an equivalent virtual inertia constant of a wind farm, including a processor and a storage medium;

存储介质用于存储指令;The storage medium is used to store instructions;

处理器用于根据指令进行操作以执行实施例一中方法的步骤。The processor is configured to operate according to the instructions to execute the steps of the method in the first embodiment.

实施例四:Embodiment four:

本实施例提供一种计算机可读存储介质,其上存储有计算机程序,该程序被处理器执行时实现实施例一中方法的步骤。This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the method in Embodiment 1 are implemented.

本领域内的技术人员应明白,本申请的实施例可提供为方法、系统、或计算机程序产品。因此,本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present application is described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

以上所述仅是本发明的优选实施方式,应当指出,对于本技术领域的普通技术人员来说,在不脱离本发明技术原理的前提下,还可以做出若干改进和变形,这些改进和变形也应视为本发明的保护范围。The above is only a preferred embodiment of the present invention, and it should be pointed out that for those of ordinary skill in the art, without departing from the technical principle of the present invention, some improvements and modifications can also be made. It should also be regarded as the protection scope of the present invention.

Claims (10)

1. An online evaluation method for equivalent virtual inertia constants of a wind power plant is characterized by comprising the following steps:
preprocessing measured data of the wind power plant;
establishing an equivalent swing equation of the wind power plant according to the swing equation of the synchronous unit;
constructing a station-level inertia constant evaluation model according to the equivalent oscillation equation of the wind power plant by using a time-frequency transformation method;
inputting the preprocessed wind power plant actual measurement data into the station-level inertia constant evaluation model to output an evaluation result;
performing singular point removing operation on the evaluation result to obtain an equivalent virtual inertia constant of the wind power plant;
the measured data of the wind power plant comprise a system frequency signal and an active power signal of the wind power plant.
2. The wind farm equivalent virtual inertia constant online evaluation method according to claim 1, wherein the preprocessing comprises: per unit, detrending, and pre-filtering.
3. The wind farm equivalent virtual inertia constant online evaluation method according to claim 1, wherein the wind farm equivalent oscillation equation has an expression shown in formula (1):
Figure FDA0003963636730000011
in the formula (1), H WF Is equivalent virtual inertia constant of wind power plant, D WF For damping coefficient of wind farm, P m Is mechanical power, P e Is electromagnetic power, omega s Is the system frequency, ω s0 The system nominal frequency.
4. The wind power plant equivalent virtual inertia constant online evaluation method according to claim 1, wherein constructing a plant-level inertia constant evaluation model according to the wind power plant equivalent oscillation equation by using a time-frequency transformation method comprises:
converting the equivalent oscillation equation of the wind power plant from a differential form to an integral form according to Laplace transform and Laplace inverse transform to obtain an equivalent oscillation integral equation of the wind power plant;
and converting the equivalent swing integral equation of the wind power plant from a continuous domain to a discrete domain according to a gradient method of numerical integration to obtain a station-level inertia constant evaluation model.
5. The wind farm equivalent virtual inertia constant online evaluation method according to claim 4, wherein converting the wind farm equivalent oscillation equation from a differential form to an integral form according to the Laplace transform and the Laplace inverse transform to obtain the wind farm equivalent oscillation integral equation comprises:
performing Laplace transformation on the wind power plant equivalent swing equation, replacing system frequency variation with an output variable, replacing active power variation of the wind power plant with an input variable, and neglecting mechanical power variation of the wind power plant to obtain a wind power plant equivalent swing algebraic equation;
according to the wind power plant equivalent swing algebraic equation, derivation is carried out on an arithmetic operator, and s is multiplied on two sides of the derived equation at the same time -2 Performing inverse Laplace transform to obtain an equivalent swing integral equation of the wind power plant;
the wind power plant equivalent swing algebraic equation has an expression shown in formula (2):
Figure FDA0003963636730000021
in formula (2), s is an operator, Y is an output variable, U is an input variable, and D WF Damping coefficient for wind farms, H WF The equivalent virtual inertia constant of the wind power plant is obtained;
the expression of the wind power plant equivalent swing integral equation is shown in formula (3):
Figure FDA0003963636730000022
in the formula (3), H WF Is equivalent virtual inertia constant of wind power plant, D WF Damping coefficient for wind farms, T F =n F T,T F Is a time interval, n F Is the length of the time windowDegree, T is the sampling period, δ is the integral variable, Y (δ) is the time domain expression of the output variable Y, and U (δ) is the time domain expression of the input variable U.
6. The wind farm equivalent virtual inertia constant online evaluation method according to claim 4, wherein the expression of the station-level inertia constant evaluation model is shown in formula (4):
Figure FDA0003963636730000031
in the formula (4), H WF Is equivalent virtual inertia constant of wind power plant, D WF Is damping coefficient of wind power plant, T is sampling period, i is ith sampling point, n F For the length of the time window, k is a sampling point at the current moment, y (i) is an output quantity at the ith sampling moment, y (i-1) is an output quantity at the ith-1 sampling moment, and y (i) = delta omega (k- (n) = delta omega F -i)), Δ ω is the system frequency variation, u (i) is the input at the i-th sampling time, u (i) = Δ P e (k-(n F -i)),ΔP e The active power variation of the wind power plant.
7. The wind farm equivalent virtual inertia constant online evaluation method according to claim 1, wherein the formula used by the de-singular point operation is shown in formula (5):
Figure FDA0003963636730000032
in the formula (5), H WF (k) Is the equivalent virtual inertia constant H of the wind power plant at the current sampling moment WF (k-1) is an equivalent virtual inertia constant of the wind power plant at the previous sampling moment, k is a sampling point at the current moment,
Figure FDA0003963636730000033
Figure FDA0003963636730000034
t is the sampling period, i is the ith sampling point, n F Is the length of the time window, D WF As the damping coefficient of the wind power plant, y (i) is the output quantity of the ith sampling moment, n (i) is the input quantity of the ith sampling moment,
Figure FDA0003963636730000035
y (i-1) is the output quantity of the i-1 th sampling moment, epsilon is a threshold value for preventing numerical errors, beta is a proportionality coefficient for preventing numerical errors, and beta < 1.
8. The utility model provides an online evaluation device of wind-powered electricity generation field equivalent virtual inertia constant which characterized in that includes:
a preprocessing module: the method is used for preprocessing the measured data of the wind power plant;
an equation building module: the wind power plant equivalent oscillation equation is established according to the oscillation equation of the synchronous unit;
a model construction module: the system comprises a wind power plant equivalent oscillation equation, a station level inertia constant evaluation model, a time-frequency transformation method and a power station level inertia constant evaluation model, wherein the wind power plant equivalent oscillation equation is used for establishing the station level inertia constant evaluation model;
an evaluation module: the system comprises a wind power plant level inertia constant evaluation model, a wind power plant level inertia constant evaluation model and a wind power plant level inertia constant evaluation model, wherein the wind power plant level inertia constant evaluation model is used for inputting preprocessed wind power plant measured data to the wind power plant level inertia constant evaluation model so as to output an evaluation result;
a singular point removing module: the method is used for performing singular point removing operation on the evaluation result to obtain the equivalent virtual inertia constant of the wind power plant;
the measured data of the wind power plant comprise a system frequency signal and an active power signal of the wind power plant.
9. An online evaluation device for equivalent virtual inertia constants of a wind power plant is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate in accordance with the instructions to perform the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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Publication number Priority date Publication date Assignee Title
CN116667462A (en) * 2023-07-28 2023-08-29 昆明理工大学 A method for quantifying inertia demand of new energy grid-connected power system

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116667462A (en) * 2023-07-28 2023-08-29 昆明理工大学 A method for quantifying inertia demand of new energy grid-connected power system
CN116667462B (en) * 2023-07-28 2023-09-29 昆明理工大学 A method for quantifying inertia demand of new energy grid-connected power systems

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