WO2016058435A1 - 变压器外部故障下绕组状态评估方法 - Google Patents

变压器外部故障下绕组状态评估方法 Download PDF

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WO2016058435A1
WO2016058435A1 PCT/CN2015/085341 CN2015085341W WO2016058435A1 WO 2016058435 A1 WO2016058435 A1 WO 2016058435A1 CN 2015085341 W CN2015085341 W CN 2015085341W WO 2016058435 A1 WO2016058435 A1 WO 2016058435A1
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winding
fault
transformer
current
leakage inductance
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PCT/CN2015/085341
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English (en)
French (fr)
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何菲
孙素娟
陈国珍
郝治国
张晓静
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江苏省电力公司泰州供电公司
国家电网公司
江苏省电力公司
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Publication of WO2016058435A1 publication Critical patent/WO2016058435A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
    • G01R31/72—Testing of electric windings
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass

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  • the invention belongs to the field of power equipment monitoring, and relates to a method for evaluating the state of a transformer winding under an external fault condition.
  • the electromagnetic force of the wire is proportional to the square of the current flowing through the winding.
  • the electromagnetic force of the winding is small.
  • the electromagnetic force caused by the short-circuit current will cause deformation of the transformer winding, deformation degree and short circuit.
  • the magnitude of the current and the duration of the action are related.
  • the length of the running time depends on the severity of the deformation.
  • the main manifestations are as follows: 1. The geometrical dimensions of the windings change directly, the insulation distance changes or the insulation paper is damaged; 2. The windings that do not affect the normal operation of the transformer are slightly deformed, the mechanical properties are degraded, and the short-circuit resistance is reduced. When the short-circuit accident is hit again or again, the degree of deformation of the transformer winding is gradually increased, and under the effect of cumulative deformation, a vicious cycle occurs until damage occurs.
  • the state of power equipment maintenance that is being developed only considers the deformation and state of the transformer winding after the fault, and does not take into account the deformation of the winding during the fault process. Therefore, important information such as deterioration of the winding material and accumulation of deformation is missed, and the transformer is operated.
  • the safety and reliability brings great hidden dangers.
  • the transformer winding is affected by short-circuit shock and state evaluation for the safe operation of the transformer and the construction of the smart grid in the future, the technology has not been widely promoted due to limitations in field installation conditions and hardware investment.
  • the object of the present invention is to provide a method for evaluating the state of a winding under external faults of a transformer.
  • the current flows through the windings of the transformer, and the magnitude of the electromagnetic force received is proportional to the square of the current.
  • the electromagnetic force of the winding is affected by the large current. It is several hundred times under normal conditions. Winding deformation will occur when the winding strength is insufficient. The elastic deformation will partially recover after the fault is eliminated. However, the cumulative effect of winding deformation will cause a big accident in the next fault condition; therefore, timely It is of great practical significance to discover and detect minor deformations that are repaired to prevent large accidents caused by cumulative effects.
  • the invention relates to a winding state evaluation method under external fault of a transformer; the invention utilizes the voltage and current data before and during the fault on both sides of the collected transformer, and uses a suitable numerical algorithm to identify the value of the leakage inductance of the transformer before and during the fault, Calculate and analyze the deviation of the leakage inductance of the winding at each moment in the fault, and make the trend graph of the deviation amount with time as the abscissa; evaluate the impact of the fault on the transformer winding and the state of the winding according to the trend graph of the deviation amount;
  • step (B) If the transformer tap adjustment is satisfied, the current effective value continues for three cycles greater than 1.2I N (I N is the rated current of the transformer), the timing is started, the transformer is re-input after the shutdown, and the peak value is greater than 3I N Initiating the parameter identification unit by any one of five conditions of the inrush current; otherwise returning to step (A);
  • the recursive least squares identification method is used to identify the leakage inductance L kq of the pre-fault winding by using the information before and during the fault. Calculate the leakage inductance L kz (k) at each moment in the fault process, where k is a different moment in the fault process;
  • the method for identifying the winding parameters in the step (C) is as follows:
  • the original secondary winding voltage loop equation is:
  • u 1 is the primary winding voltage
  • u 2 is the secondary winding voltage
  • i 1 is the primary winding current
  • i 2 is the secondary winding current
  • n 1 is the number of primary winding turns
  • n 2 is the number of turns of the secondary winding
  • r 1 is the primary winding resistance
  • r 2 is the secondary winding resistance
  • L 1 is the primary winding leakage inductance
  • L 2 is the secondary winding leakage inductance
  • ⁇ m is the mutual magnetic flux of the primary winding and the secondary winding
  • Equation (3) is used as the parameter identification equation for transformer winding state parameters.
  • the online identification of r k and L k can be realized by recursive least squares method.
  • the recursive least squares identification model can be expressed as:
  • ⁇ T is the interval, and i 1 (n), u 1 (n), and u 2 (n) are sampled values at time n;
  • the previous identification result g(n) is corrected to recursively obtain a new parameter identification value g(n+1);
  • ⁇ be the error allowed by the identification parameter
  • the identification result is continuously corrected until the equation (9) is established, and the winding parameters are identified.
  • the calculation formula of the winding parameter deviation amount ⁇ L k (k) at each moment in the step (D) is as follows:
  • L kq is the winding leakage inductance value (reference value) obtained by using the voltage and current information before the fault
  • L kz (k) is the winding equivalent leakage inductance at each moment obtained by using the voltage and current information in the fault process
  • k is the time when the fault is different.
  • the present invention has the following advantages compared with the prior art: the winding state evaluation method of the transformer external fault provided by the present invention can utilize the transformer voltage and current signals before and during the fault to realize the transformer winding state. Monitoring; using the data obtained before the fault to identify the parameters as the reference value, does not need the calculation of the nameplate parameters; according to the voltage loop equation, applying the excitation current compensation and identification theory, using the extracted fault recording information to obtain the voltage on both sides of the transformer during the fault process The current information is used to identify the leakage inductance L kz (k) of the transformer winding, and the leakage inductance L kq before the fault is used as the reference value to find the deviation amount ⁇ L k (k) in the fault, and the time t is the horizontal axis to make ⁇ L k - The graph of t, observes the trend of the variation of the parameters and the recovery of the parameters in the graph, analyzes the impact of the fault on the winding and its influence, and the degree of recovery and health of the winding
  • Figure 1 is a flow chart of a method for evaluating winding state under external fault of a transformer
  • Figure 3 shows the B-phase high-voltage side current after the failure of the No. 1 main transformer of a substation
  • Figure 4 shows the variation of the B-phase winding L k1 after the failure of the main transformer No. 1 in a substation.
  • the main transformer of No. 1 of a substation is taken as an example to illustrate the winding state evaluation method of the external fault of the transformer of the present invention: the transformer is a three-phase three-winding autotransformer, and the voltages of the high, medium and low sides of the transformer are respectively 345kV.
  • 121kV, 35kV, rated capacity is 240MVA, 240MVA, 72MVA, equipped with fault recorder, used to record the voltage and current information before and after the fault;
  • the fault time is the starting point of the time, that is, zero time, the fault type is medium voltage Side BC two-phase short circuit, 070msB phase high-voltage winding current is short-circuit fault current, reaching 78 times of rated current, the winding is deformed due to the huge short-circuit electromagnetic force.
  • step (B) If the transformer tap adjustment is satisfied, the current effective value continues for three cycles greater than 1.2I N (I N is the rated current of the transformer), the timing is started, the transformer is re-input after the shutdown, and the peak value is greater than 3I N Initiating the parameter identification unit by any one of five conditions of the inrush current; otherwise returning to step (A);
  • the recursive least squares identification method is used to identify the leakage inductance L kq of the pre-fault winding by using the information before and during the fault. Calculate the leakage inductance L kz (k) at each moment in the fault process, where k is a different moment in the fault process;
  • the identification method of the winding parameters is as follows:
  • the original secondary winding voltage loop equation is:
  • u 1 is the primary winding voltage
  • u 2 is the secondary winding voltage
  • i 1 is the primary winding current
  • i 2 is the secondary winding current
  • n 1 is the number of primary winding turns
  • n 2 is the number of turns of the secondary winding
  • r 1 is the primary winding resistance
  • r 2 is the secondary winding resistance
  • L 1 is the primary winding leakage inductance
  • L 2 is the secondary winding leakage inductance
  • ⁇ m is the mutual magnetic flux of the primary winding and the secondary winding
  • Equation (3) is used as the parameter identification equation for transformer winding state parameters.
  • the online identification of r k and L k can be realized by recursive least squares method.
  • the recursive least squares identification model can be expressed as:
  • ⁇ T is the interval, and i 1 (n), u 1 (n), and u 2 (n) are sampled values at time n;
  • the previous identification result g(n) is corrected to recursively obtain a new parameter identification value g(n+1);
  • ⁇ be the error allowed by the identification parameter
  • the identification result is continuously corrected until the equation (9) is established, and the winding parameters are identified.
  • L kq is the winding leakage inductance value (reference value) obtained by using the voltage and current information before the fault
  • L kz (k) is the winding equivalent leakage inductance at each moment obtained by using the voltage and current information in the fault process
  • k is the time when the fault is different.
  • Figure 3 shows the B-phase high-voltage side current after the transformer failure.
  • Figure 4 shows the change trend of the leakage inductance change ⁇ L k1 of the B-phase winding after the transformer failure. It can be seen from the figure that the winding is subjected to electromagnetic force during the fault. Large, the deformation is more serious; after the fault is eliminated, the elastic deformation recovers to a certain extent, but there is still some unrecoverable shaping deformation, that is, there is a cumulative effect of deformation, from which the cumulative situation can be analyzed to judge The winding is subjected to the impact of the short-circuit current and the state of the winding after the fault is recovered, thereby printing a report, prompting the staff to make corresponding adjustments and arrange for overhaul.
  • the voltage and current data before and after the fault of the invention are based on the collection of voltage and current information before and during the fault, the identification of the winding parameters before and during the fault, the calculation of the parameter change during the fault and the trend analysis, and the fault.
  • the winding impact, as well as the organic combination and reasonable matching of the printed data report and return parts, make the whole winding state evaluation method simple, easy to implement, correct and efficient, and can be directly programmed on the equipment.

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Testing Of Short-Circuits, Discontinuities, Leakage, Or Incorrect Line Connections (AREA)

Abstract

一种变压器外部故障下绕组状态评估方法；变压器绕组导线中流过电流，受到的电磁力的大小和经过电流的平方成正比，故障大电流情况下，绕组所承受的电磁力是正常状况下的几百倍，绕组强度不足时会发生绕组形变，弹性形变在故障消除后会部分恢复，但是，绕组变形的累积效应会使在下次故障情况下发生大的事故；利用采集到的变压器两侧故障前和故障中的电压电流数据，利用合适的数值算法，辨识得到故障前和故障中变压器的漏电感的值，计算分析故障中各个时刻绕组漏电感的偏差量，并以时间为横坐标做出偏差量的趋势图；根据偏差量趋势图，评估故障对变压器绕组的冲击以及绕组的状态。

Description

变压器外部故障下绕组状态评估方法 技术领域
本发明属于电力设备监测领域，涉及一种外部故障情况下变压器绕组状态评估方法。
背景技术
电力变压器作为电力系统电能传输中的枢纽设备，其故障会对电力系统供电可靠性和运行稳定性带来严重影响。有关变压器故障的历年统计资料表明，每年绕组故障占变压器故障的绝大部分，而绕组短路强度不足是造成绕组故障的主要原因，其损坏率约占整个变压器故障的60％～70％。绕组变形作为一种潜伏性的亚健康状态的积累，其故障的发展性和不确定性必定会给电力系统运行带来不可预知的重大隐患。
导线所承受的电磁力与流经绕组的电流的平方成正比，变压器正常稳态运行时，绕组所受电磁力很小，短路电流引起的电磁力作用将导致变压器绕组发生变形，变形程度与短路电流大小及作用时间长短有关。
变压器发生绕组变形后，有的立即发生损坏事故，有的则可以长时间继续运行，运行时间的长短取决于变形的严重程度。其主要表现形式有：1、绕组的几何尺寸直接发生变化，绝缘距离发生改变或绝缘纸发生损坏；2、发生不至于影响变压器正常运行的绕组轻微变形，机械性能下降，抗短路能力降低。当再次或多次遭受短路事故冲击时，变压器绕组变形程度逐步增加，在累积变形效应的作用下，出现恶性循环直至损坏。
目前正在发展的电力设备状态检修，仅仅考虑故障后变压器绕组的形变及状态，并未将故障过程中绕组的形变考虑在内，因此会漏掉绕组材料劣化以及变形累积等重要信息，给变压器运行的安全可靠性带来很大的隐患。尽管变压器绕组受短路冲击以及状态评估对变压器安全运行以及未来智能电网的构建具有重要意义，但是由于现场装设条件以及硬件投资等方面的限制，该项技术并没有得到大面积推广。
发明内容
本发明的目的是提出一种变压器外部故障下绕组状态评估方法，变压器绕组导线中流过电流，受到的电磁力的大小和经过电流的平方成正比，故障大电流情况下，绕组所承受的电磁力是正常状况下的几百倍，绕组强度不足时会发生绕组形变，弹性形变在故障消除后会部分恢复，但是，绕组变形的累积效应会使在下次故障情况下发生大的事故；所以，及时发现并检测维修微小变形，防止累积效应造成的大事故，有重要的现实意义。
为实现上述目的，本发明采用的技术方案是：
一种变压器外部故障下绕组状态评估方法；本发明利用采集到的变压器两侧故障前和故障中的电压电流数据，利用合适的数值算法，辨识得到故障前和故障中变压器的漏电感的值，计算分析故障中各个时刻绕组漏电感的偏差量，并以时间为横坐标做出偏差量的趋势图；根据偏差量趋势图，评估故障对变压器绕组的冲击以及绕组的状态；
具体步骤如下：
(A)实时采集变压器分接头调节信号以及变压器原边、变压器副边两侧电压电流信号uA、uB、uC、iA、iB、iC、ua、ub、uc、ia、ib、ic；
(B)若满足变压器分接头调节、电流有效值持续三个周波大于1.2IN，(IN为变压器的额定电流)，定时启动、变压器停运后的再次投入、经历一次峰值大于3IN的冲击电流五个条件中的任意一个，启动参数辨识单元；否则返回步骤(A)；
(C)将变压器原副边的电压回路方程整理和化简后，利用递推最小二乘辨识方法，分别利用故障前和故障中的信息，先辨识得到故障前绕组的漏电感Lkq，再计算故障过程中各个时刻的漏电感Lkz(k)，其中k为故障过程中不同的时刻；
(D)以故障前的漏电感Lkq为基准值，进行故障中各个时刻绕组漏电感偏差量δLk(k)的计算：
(E)以时间t为横轴，以Lkz为纵轴，做出δLk-t的图形，在图形中观察参数的变化量趋势及其恢复情况，分析故障对绕组的冲击及其影响。
更优的是，所述的步骤(C)中的绕组参数的辨识方法如下：
原副边绕组电压回路方程为：
Figure PCTCN2015085341-appb-000001
其中：
u1为原边绕组电压，
u2为副边绕组电压，
i1为原边绕组电流，
i2为副边绕组电流，
n1为原边绕组匝数，
n2为副边绕组匝数，
r1为原边绕组电阻，
r2为副边绕组电阻，
L1为原边绕组漏电感，
L2为副边绕组漏电感，
Φm为原边绕组与副边绕组的互感磁通；
利用变压器原、副边电压回路方程(1)，消去互感磁通，从而得到只包含原边绕组、副边绕组的电压和电流的等值方程：
Figure PCTCN2015085341-appb-000002
其中
Figure PCTCN2015085341-appb-000003
考虑励磁电流时，i2＝-(i1-im)，有：
Figure PCTCN2015085341-appb-000004
其中：
Figure PCTCN2015085341-appb-000005
为绕组归算到一次侧的等值电阻，
Figure PCTCN2015085341-appb-000006
为绕组归算到一次侧的漏电感，
Figure PCTCN2015085341-appb-000007
为励磁电流补偿项，用相量的形式表达即为
Figure PCTCN2015085341-appb-000008
其中
Figure PCTCN2015085341-appb-000009
为im的相量表达式；
由
Figure PCTCN2015085341-appb-000010
得：
Figure PCTCN2015085341-appb-000011
其中：r2＜＜ωL2、rm＜＜ωLm、
Figure PCTCN2015085341-appb-000012
a＝0.002、θ≈0；
将公式(3)作为变压器绕组状态参数辨识方程，利用递推最小二乘法可实现对rk、Lk的在线辨识，递推最小二乘法辨识模型可表示为：
Figure PCTCN2015085341-appb-000013
其中：ΔT为采用间隔，i1(n)、u1(n)、u2(n)为n时刻采样值；
连续采样n次，得到：
Figure PCTCN2015085341-appb-000014
由式(6)得到模型参数的最小二乘解g为：
g＝(XTX)-1XTY       (7)
为提高最小二乘的辨识精度，采用递推估计的最小二乘法，即利用新引入的x1(n+1)g1+x2(n+1)g2＝y(n+1)对前次辨识结果g(n)进行修正，从而递推地得到新的参数辨识值g(n+1)；
令
Figure PCTCN2015085341-appb-000015
最小二乘递推法表达式为：
Figure PCTCN2015085341-appb-000016
设ε为辨识参数允许的误差；
Figure PCTCN2015085341-appb-000017
不断修正辨识结果直至式(9)成立，则辨识得到绕组参数。
更优的是，所述的步骤(D)中各个时刻绕组参数偏差量δLk(k)的计算公式如下：
Figure PCTCN2015085341-appb-000018
其中：
Lkq为利用故障前电压电流信息辨识得到的绕组漏电感值(基准值)；
Lkz(k)为利用故障过程中的电压电流信息得到的各个时刻的绕组等值漏电感；
k为故障不同的时刻。
综上所述，本发明与现有技术相比，具有以下优点：本发明所提供的变压器外部故障下绕组状态评估方法能够利用故障前和故障中的变压器电压、电流信号，实现对变压器绕组状态的监控；利用故障前的数据辨识所得参数为基准值，不需要铭牌参数的计算；根据电压回路方程，应用励磁电流补偿和辨识理论，利用提取故障录波信息得到故障过程中的变压器两侧电压、电流信息来辨识变压器绕组漏电感Lkz(k)，利用故障前的漏电感Lkq为基准值求故障中的偏差量δLk(k)，以时间t为横轴，做出δLk-t的图形，在图形中观察参数的变化量趋势及其恢复情况，分析故障对绕组的冲击及其影响，及绕组变形的恢复程度和健康情况。
附图说明
图1为变压器外部故障下绕组状态评估方法的流程图；
图2为该方法结构框图；
图3为某变电站1号主变压器故障后B相高压侧电流；
图4为某变电站1号主变压器故障后B相绕组Lk1的变化量。
具体实施方式
下面结合附图对本发明的优选实施例进行详细阐述，以使本发明的优点和特征能更易于被本领域技术人员理解，从而对本发明的保护范围做出更为清楚明确的界定。
现以某变电站1号主变压器为例来具体说明本发明的变压器外部故障下绕组状态评估方法：该变压器为三相三绕组自耦变压器，变压器的高，中，低三侧的电压分别为345kV、121kV、35kV，额定容量分别为240MVA、240MVA、72MVA，装设有故障录波装置，用来记录故障前后的电压电流信息；以故障时刻为计时起点，即为零时刻，故障类型为中压侧BC两相短路，070msB相高压绕组电流为短路故障电流，达到额定电流的78倍，绕组由于承受巨大短路 电磁力而发生变形，现利用变压器故障期间的B相高压绕组录波数据对B相高压绕组等值漏电感参数进行辨识，计算故障过程中高压绕组的等值漏电感的变化量δLk1，并做出其趋势图，分析短路电流对绕组的冲击作用以及绕组变形的恢复和积累效应。
具体步骤如下：
(A)实时采集变压器分接头调节信号以及变压器原边、变压器副边两侧电压电流信号uA、uB、uC、iA、iB、iC、ua、ub、uc、ia、ib、ic；
(B)若满足变压器分接头调节、电流有效值持续三个周波大于1.2IN，(IN为变压器的额定电流)，定时启动、变压器停运后的再次投入、经历一次峰值大于3IN的冲击电流五个条件中的任意一个，启动参数辨识单元；否则返回步骤(A)；
(C)将变压器原副边的电压回路方程整理和化简后，利用递推最小二乘辨识方法，分别利用故障前和故障中的信息，先辨识得到故障前绕组的漏电感Lkq，再计算故障过程中各个时刻的漏电感Lkz(k)，其中k为故障过程中不同的时刻；
绕组参数的辨识方法如下：
原副边绕组电压回路方程为：
Figure PCTCN2015085341-appb-000019
其中：
u1为原边绕组电压，
u2为副边绕组电压，
i1为原边绕组电流，
i2为副边绕组电流，
n1为原边绕组匝数，
n2为副边绕组匝数，
r1为原边绕组电阻，
r2为副边绕组电阻，
L1为原边绕组漏电感，
L2为副边绕组漏电感，
Φm为原边绕组与副边绕组的互感磁通；
利用变压器原、副边电压回路方程(1)，消去互感磁通，从而得到只包含原边绕组、副边绕组的电压和电流的等值方程：
Figure PCTCN2015085341-appb-000020
其中
Figure PCTCN2015085341-appb-000021
考虑励磁电流时，i2＝-(i1-im)，有：
Figure PCTCN2015085341-appb-000022
其中：
Figure PCTCN2015085341-appb-000023
为绕组归算到一次侧的等值电阻，
Figure PCTCN2015085341-appb-000024
为绕组归算到一次侧的漏电感，
Figure PCTCN2015085341-appb-000025
为励磁电流补偿项，用相量的形式表达即为
Figure PCTCN2015085341-appb-000026
其中
Figure PCTCN2015085341-appb-000027
为im的相量表达式；
由
Figure PCTCN2015085341-appb-000028
得：
Figure PCTCN2015085341-appb-000029
其中：r2＜＜ωL2、rm＜＜ωLm、
Figure PCTCN2015085341-appb-000030
a＝0.002、θ≈0；
将公式(3)作为变压器绕组状态参数辨识方程，利用递推最小二乘法可实现对rk、Lk的在线辨识，递推最小二乘法辨识模型可表示为：
Figure PCTCN2015085341-appb-000031
其中：ΔT为采用间隔，i1(n)、u1(n)、u2(n)为n时刻采样值；
连续采样n次，得到：
Figure PCTCN2015085341-appb-000032
由式(6)得到模型参数的最小二乘解g为：
g＝(XTX)-1XTY      (7)
为提高最小二乘的辨识精度，采用递推估计的最小二乘法，即利用新引入的x1(n+1)g1+x2(n+1)g2＝y(n+1)对前次辨识结果g(n)进行修正，从而递推地得到新的参数辨识值g(n+1)；
令
Figure PCTCN2015085341-appb-000033
最小二乘递推法表达式为：
Figure PCTCN2015085341-appb-000034
设ε为辨识参数允许的误差；
Figure PCTCN2015085341-appb-000035
不断修正辨识结果直至式(9)成立，则辨识得到绕组参数。
(D)以故障前的漏电感Lkq为基准值，进行故障中各个时刻绕组漏电感偏差量δLk(k)的计算：
Figure PCTCN2015085341-appb-000036
其中：
Lkq为利用故障前电压电流信息辨识得到的绕组漏电感值(基准值)；
Lkz(k)为利用故障过程中的电压电流信息得到的各个时刻的绕组等值漏电感；
k为故障不同的时刻。
(E)以时间t为横轴，以Lkz为纵轴，做出δLk-t的图形，在图形中观察参数的变化量趋势及其恢复情况，分析故障对绕组的冲击及其影响。
图3为该变压器故障后B相高压侧电流，图4为该变压器故障后B相绕组对应时刻漏电感变化量δLk1的变化趋势图；从图中可以看出，故障期间绕组承受电磁力很大，变形比较严重；故障消除后，弹性形变在一定程度内恢复，但是，还有部分不可恢复的塑形形变存在，即存在形变的累积效应，从该图中可以分析累积的情况，从而判断绕组承受短路电流的冲击情况，及其故障后绕组的状态恢复情况，从而打印报告，提示工作人员作出相应的调整和安排检修。
本发明故障前后的电压电流数据为基础，包括对故障前和故障过程中电压电流信息的采集，故障前和故障过程中绕组参数的辨识，故障过程中参数变化量的计算及其趋势分析，故障对绕组冲击情况，以及打印数据报告和返回几个部分的有机组合及合理配搭，使整个绕组状态评估方法具有构成简单，易于实现，正确高效等优点，可直接在设备上通过编程实现。
以上内容是结合具体的优选实施方式对本发明所作的进一步详细说明，不能认定本发明的具体实施方式仅限于此，对于本发明所属技术领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干简单的推演或替换，都应当视为属于本发明由所提交的权利要求书确定专利保护范围。

Claims (3)

  1. 一种变压器外部故障下绕组状态评估方法，其特征在于：包括以下步骤，
    (A)实时采集变压器分接头调节信号以及变压器原边、变压器副边两侧电压电流信号uA、uB、uC、iA、iB、iC、ua、ub、uc、ia、ib、ic；
    (B)若满足变压器分接头调节、电流有效值持续三个周波大于1.2IN，(IN为变压器的额定电流)，定时启动、变压器停运后的再次投入、经历一次峰值大于3IN的冲击电流五个条件中的任意一个，启动参数辨识单元；否则返回步骤(A)；
    (C)将变压器原副边的电压回路方程整理和化简后，利用递推最小二乘辨识方法，分别利用故障前和故障中的信息，先辨识得到故障前绕组的漏电感Lkq，再计算故障过程中各个时刻的漏电感Lkz(k)，其中k为故障过程中不同的时刻；
    (D)以故障前的漏电感Lkq为基准值，进行故障中各个时刻绕组漏电感偏差量δLk(k)的计算：
    (E)以时间t为横轴，以Lkz为纵轴，做出δLk-t的图形，在图形中观察参数的变化量趋势及其恢复情况，分析故障对绕组的冲击及其影响。
  2. 根据权利要求1所述的变压器外部故障下绕组状态评估方法，其特征在于，所述的步骤(C)中的绕组参数的辨识方法如下：
    原副边绕组电压回路方程为：
    Figure PCTCN2015085341-appb-100001
    其中：
    u1为原边绕组电压，
    u2为副边绕组电压，
    i1为原边绕组电流，
    i2为副边绕组电流，
    n1为原边绕组匝数，
    n2为副边绕组匝数，
    r1为原边绕组电阻，
    r2为副边绕组电阻，
    L1为原边绕组漏电感，
    L2为副边绕组漏电感，
    Φm为原边绕组与副边绕组的互感磁通；
    利用变压器原、副边电压回路方程(1)，消去互感磁通，从而得到只包含原边绕组、副边绕组的电压和电流的等值方程：
    Figure PCTCN2015085341-appb-100002
    其中
    Figure PCTCN2015085341-appb-100003
    考虑励磁电流时，i2＝-(i1-im)，有：
    Figure PCTCN2015085341-appb-100004
    其中：
    Figure PCTCN2015085341-appb-100005
    为绕组归算到一次侧的等值电阻，
    Figure PCTCN2015085341-appb-100006
    为绕组归算到一次侧的漏电感，
    Figure PCTCN2015085341-appb-100007
    为励磁电流补偿项，用相量的形式表达即为
    Figure PCTCN2015085341-appb-100008
    其中
    Figure PCTCN2015085341-appb-100009
    为im的相量表达式；
    由
    Figure PCTCN2015085341-appb-100010
    得：
    Figure PCTCN2015085341-appb-100011
    其中:r2＜＜ωL2、rm＜＜ωLm、
    Figure PCTCN2015085341-appb-100012
    a＝0.002、θ≈0；
    将公式(3)作为变压器绕组状态参数辨识方程，利用递推最小二乘法可实现对rk、Lk的在线辨识，递推最小二乘法辨识模型可表示为：
    Figure PCTCN2015085341-appb-100013
    其中：ΔT为采用间隔，i1(n)、u1(n)、u2(n)为n时刻采样值；
    连续采样n次，得到：
    Figure PCTCN2015085341-appb-100014
    由式(6)得到模型参数的最小二乘解g为：
    g＝(XTX)-1XTY        (7)
    为提高最小二乘的辨识精度，采用递推估计的最小二乘法，即利用新引入的x1(n+1)g1+x2(n+1)g2＝y(n+1)对前次辨识结果g(n)进行修正，从而递推地得到新的参数辨识值g(n+1)；
    令
    Figure PCTCN2015085341-appb-100015
    最小二乘递推法表达式为：
    Figure PCTCN2015085341-appb-100016
    设ε为辨识参数允许的误差；
    Figure PCTCN2015085341-appb-100017
    不断修正辨识结果直至式(9)成立，则辨识得到绕组参数。
  3. 根据权利要求1所述的变压器外部故障下绕组状态评估方法，其特征在于，所述的步骤(D)中各个时刻绕组参数偏差量δLk(k)的计算公式如下：
    Figure PCTCN2015085341-appb-100018
    其中：
    Lkq为利用故障前电压电流信息辨识得到的绕组漏电感值(基准值)；
    Lkz(k)为利用故障过程中的电压电流信息得到的各个时刻的绕组等值漏电感；
    k为故障不同的时刻。
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CN117269843A (zh) * 2023-11-21 2023-12-22 云南电网有限责任公司 一种二次电流回路中性线运行状态在线监测方法及系统
CN117269843B (zh) * 2023-11-21 2024-04-19 云南电网有限责任公司 一种二次电流回路中性线运行状态在线监测方法及系统

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