An intelligent electronic device capable of operating under power fluctuation state and an operating method thereof

Abstract

An example of operating an intelligent electronic device (IED) during power fluctuations is described herein. In the example, voltage measurements for phases are received and sampled. A root mean square (RMS) value of the voltage sample is calculated based on the voltage measurements. A delta quantity for each phase is calculated based on the RMS value. Each of the RMS value and the delta quantity is associated with a corresponding sampling moment. In response to the delta quantity being greater than a predetermined threshold, a peak delta quantity is detected. A time interval between a sampling moment associated with the peak delta quantity and a sampling moment associated with a first delta quantity is determined. Based on a comparison of the time interval with a threshold time, a disturbance state can be detected as a power fluctuation, and thus a fault detection at the IED can be prevented.

Description

Technical Field

[0001] The present invention relates generally to power transmission systems. More particularly, the present invention relates to operating intelligent electronic devices (IEDs) under power fluctuation conditions. Background Art

[0002] One or more power system devices, such as impedance distance relays and intelligent electronic devices (IEDs), are typically used to monitor and protect transmission lines in a power grid. The power system of a power grid typically operates under steady-state conditions. Under steady-state conditions, power system equipment and transmission lines carry nominal voltages and currents, which causes the power system and the power grid to operate normally. When electrical disturbances occur in the transmission lines, the steady state of the power grid is affected.

[0003] Electrical disturbances, such as electrical faults and power fluctuations, can cause the power system to deviate from a steady state. These faults can cause current interruptions, damage to equipment, and endanger human life. Electrical faults cause voltage and current to deviate from nominal values. When a fault occurs, excessive current flows, which is detrimental to power system equipment and devices. Power fluctuations are oscillations in the flow of active and reactive power on a transmission line. Power fluctuations can occur due to power system faults, line switching, generator disconnection, and switching on / off of large loads.

[0004] Protection devices, such as distance relays / intelligent electronic devices (IEDs), are designed to provide primary and backup protection for transmission lines. Under steady-state conditions of the power grid, the value of the line voltage remains greater than the line current. When a fault occurs, the magnitude of the current rises and the voltage decreases, thereby reducing the line impedance (ratio of line voltage to current) of the fault section of the transmission line. The distance relay / IED continuously monitors the line current and voltage flow. If the ratio of the voltage to the current phasor (impedance) is lower than a predetermined threshold value set in the relay / IED, the relay / IED enters its operating area and sends a trip command to the switching component (e.g., a circuit breaker) to disconnect the circuit, thereby protecting the components of the power system from damage. This is expected to occur only during normal short-circuit fault conditions. However, during special circumstances (e.g., load intrusion and power fluctuation conditions), the impedance measured by the relay / IED may enter the tripping boundary. Due to severe load conditions, load intrusion may cause the impedance relay to perform undesirable operations. There are several methods to prevent erroneous operation due to load intrusion, for example, by changing the shape of the impedance characteristic and by implementing a load blinder scheme, among others.

[0005] Another scenario is power fluctuations. Power fluctuations are often caused by severe disturbances, such as tripping of transmission lines, loss of generation, and switching of large loads. During power fluctuations, the apparent impedance of the transmission line can enter the operating characteristics of the IED, since the maximum amplitude of the current and the minimum amplitude of the voltage can occur simultaneously during power fluctuations. As a result, the IED may enter its operating area and tend to trip in view of the apparent impedance measured by the IED, even in the absence of a fault. Based on this, the power fluctuation may be misinterpreted as a fault, and the IED may trip, resulting in a cascade line interruption. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] The following detailed description refers to the accompanying drawings, in which:

[0007] Figure 1 A block diagram showing a dual-source equivalent power grid according to an example;

[0008] Figure 2 A block diagram showing an intelligent electronic device (IED) according to an example;

[0009] Figure 3 shows a graph depicting RMS values ​​of voltage associated with sampling instants plotted against time according to an example;

[0010] Figure 4 showing a graph depicting RMS values ​​of voltage associated with sampling instants plotted against time after filtering according to an example;

[0011] Figure 5 showing a graph depicting delta quantities of voltage associated with respective sampling instants plotted against time according to an example;

[0012] Figure 6 showing a graph depicting delta quantities of voltage associated with respective sampling instants plotted against time after filtering according to an example;

[0013] Figure 7 shows a graph depicting a magnitude difference between two successive delta quantities plotted against time according to an example;

[0014] Figure 8 showing a graph indicating the time taken by a delta quantity to reach its peak value under different scenarios of electrical disturbances according to an example; and

[0015] Fig. 9A and Fig. 9B A method for operating an intelligent electronic device (IED) during power fluctuations according to an example is shown. DETAILED DESCRIPTION

[0016] A power fluctuation prevention function is included in the IED to distinguish between power fluctuations and faults and to prevent the IED from operating during power fluctuations. Conventionally, different methods are used to detect power fluctuations and to prevent the IED from operating during power fluctuations. A blinder or concentric characteristic based differentiation between faults and power fluctuations can be used. Depending on the line and power system impedance and the fluctuation frequency, the concentric characteristic based differentiation involves determining the values ​​of several parameters, such as the blinder position and time settings. Therefore, in order to use the blinder based differentiation, a meticulous and detailed fault study and stability study procedure will be performed under various operating scenarios of the power system. In addition, with the introduction of renewable power sources, the fluctuation frequency will tend to decrease, which will make the timer based differentiation between power fluctuations and faults complicated and prone to errors.

[0017] Another method that can be used to distinguish between power fluctuations and faults can be based on determining the fluctuation center voltage (SCV). The SCV is the voltage at the point where the voltage amplitude is zero when the angle between the two sources is 180 degrees in a dual-source equivalent system. During power fluctuations, the SCV changes continuously, but during a fault, the SCV remains almost constant except for a sudden change during the initial stage after the fault. Therefore, the rate of change of the amplitude of the SCV can be used to detect power fluctuations and operate the IED accordingly. However, one problem associated with this method is the setting of a reliable threshold. For example, the threshold should be kept very low for detecting low-frequency (0.2Hz-0.5Hz) power fluctuations. Moreover, if a high-resistance fault occurs at the 180-degree power angle (a fault closer to the fluctuation center point), undetected changes in the SCV voltage will occur.

[0018] Yet another approach may be to differentiate between power fluctuations and faults based on reduced resistance and the rate of change of resistance. During power fluctuations, the resistance value of the measured impedance changes continuously. But when a fault occurs, the resistance value of the measured impedance does not change except at the initial moment of the fault. The rate of change of resistance during power fluctuations with low slip frequency is significantly reduced, and therefore this approach may not be able to differentiate between a three-phase fault and a power fluctuation. Additionally, superimposed current and voltage signals may be used to detect power fluctuations. However, this technique may not be able to detect high impedance faults that occur near the center voltage of the fluctuation at a power angle close to 180 degrees, since the amount of superposition under these conditions tends to be negligibly small.

[0019] The present invention relates to operating an intelligent electronic device (IED) under power fluctuation conditions. In an example, the IED is associated with a terminal of a power transmission line in an electric power network of an electric power system. According to the present invention, the IED can reliably and accurately identify the occurrence of power fluctuations, and thus fault detection at the IED can be blocked during power fluctuations to prevent unexpected tripping. The method according to the present invention is capable of identifying power fluctuations originating from steady-state conditions, regardless of stability study parameters, such as blind zone position settings and time settings. In addition, the technology of the present invention is also independent of power system parameters, such as line and system impedances and fluctuation frequencies. In addition, the technology of the present invention is capable of distinguishing between three-phase faults and power fluctuations.

[0020] According to an example of the present invention, an IED may receive a voltage measurement for each phase of a terminal of a power transmission line. In an example, the IED may receive a voltage measurement from a voltage transformer (PT). The voltage measurement may be an instantaneous voltage reading of a line voltage of a transmission line. The voltage measurement is sampled to obtain a plurality of samples, each of which corresponds to such a sampling moment, i.e., the sampling moment is the moment of capturing the sample. The IED determines a plurality of root mean square (RMS) values ​​for each phase based on the voltage measurement of the corresponding phase. Each of the plurality of RMS values ​​is associated with a corresponding sampling moment among the plurality of sampling moments. Each of the plurality of RMS values ​​is calculated using a predetermined number of samples. The predetermined number of samples includes samples captured at the corresponding sampling moment and samples captured at the previous sampling moment. In an example, the predetermined number of samples depends on the sampling rate and hardware capabilities of the IED. In an example, the predetermined number of samples may be 20 samples or more than 20 samples. The IED determines a plurality of delta quantities for the voltage of each phase. The delta quantity of the voltage may also be referred to as a delta quantity. Each of the plurality of delta quantities is associated with a corresponding sampling moment. Each of the plurality of delta quantities is a difference between an RMS value associated with a corresponding sampling instant and an RMS value associated with a sampling instant a predetermined number of samples ago. In addition, a delta quantity among the plurality of delta quantities is detected whether it is greater than a predetermined threshold. In response to determining that the delta quantity is greater than the predetermined threshold, the IED detects a peak delta quantity of the voltage. A time interval between a sampling instant associated with the peak delta quantity and a sampling instant associated with the first delta quantity is determined. A disturbance state is detected based on a comparison of the time interval with a threshold time. In response to detecting that the disturbance state is a power fluctuation, a fault detection at the IED is prevented.

[0021] Therefore, the present invention is able to detect power fluctuations in a simpler way without using fault and stability study parameters and power system parameters, as would be required in other techniques based on the difference between faults and power fluctuations, either blind or concentric characteristics. In addition, with the aid of the techniques of the present invention, power fluctuations can also be reliably distinguished from three-phase faults. Therefore, in response to the detection of power fluctuations, fault detection at the IED can be prevented, thereby preventing the switch components (e.g., circuit breakers) in the power system from tripping unexpectedly. In addition, the method can also be implemented in a two-phase system by monitoring the delta quantity of the voltage of the two phases.

[0022] The following detailed description refers to the accompanying drawings. Where possible, the same reference numerals are used in the drawings and the following description to refer to the same or similar parts. Although several examples are described in this description, there can be modifications, adaptations and other implementations. Therefore, the following detailed description does not limit the disclosed examples. Instead, the proper scope of the disclosed examples can be defined by the appended claims.

[0023] Figure 1 A block diagram of a dual-source equivalent power grid 100 according to an example is shown. The power grid 100 includes a dual-circuit line including transmission lines 102 and 104 and two power sources, namely, power sources 106 and 108. The power grid 100 can transmit power over long distances (e.g., tens or hundreds of kilometers) at high voltages (e.g., in the kilovolt range).

[0024] Transmission lines 102 and 104 are connected between two buses 110 and 112. Transmission lines 102, 104 are also provided with one or more circuit breakers 114-1, 114-2, 114-3 and 114-4 (collectively referred to as circuit breakers 114). Circuit breakers 114 allow the circuit to be opened to limit the flow of current in the power grid 100. The power grid 100 may include additional components without departing from the scope of the present invention.

[0025] The power grid 100 is also equipped with an intelligent electronic device (referred to as IED 116). The IED 116 can be electrically connected to the transmission lines 102, 104 directly or through other connection devices. Figure 1 As shown, IED 116 is placed at bus 110 and measures voltage and current signals of the protected line. Thus, IED 116 is associated with the terminal of power transmission line 104. During operation, IED 116 may receive data from one or more sensors and voltage transformers (PTs) that may be installed within power grid 100. Based on the received data, IED 116 may generate one or more signals to control circuit breaker 114.

[0026] The IED 116 also includes a disturbance state detection module 118. The disturbance state detection module 118 may be implemented as software installed within the IED 116 or implemented as hardware in the form of an electronic circuit. In an example, the disturbance state detection module 118 may be coupled to a processor of the IED 116. The present invention is capable of detecting power fluctuations occurring in the power grid 100 and may accordingly prevent fault detection at the IED, thereby preventing unnecessary tripping of the circuit breaker 114.

[0027] In operation, the interference state detection module 118 receives voltage measurements for each phase of the terminal of the power transmission line 104. In an example, the voltage measurement can be an instantaneous voltage reading of the line voltage of the transmission line 104 received from the PT in the transmission line. Based on the analysis of these voltage measurements for each phase, the IED 116 can detect the occurrence of power fluctuations in the corresponding phase. In an example, in a three-phase power system, power fluctuations can be detected by using the voltage measurement for one phase to perform the method explained below. In another example, power fluctuations in the transmission line can be detected when detecting power fluctuations in all phases of the three-phase power system. Although the following description is detailed with reference to one phase, the same situation is applicable to all phases of the power grid 100 with necessary modifications.

[0028] In an example, the IED 116 may sample the voltage measurement based on a predetermined sampling rate. In an example, the predetermined sampling rate may be 20 samples per cycle. In an example, depending on the hardware capabilities of the IED 116, the IED 116 may perform sampling at different sampling frequencies ranging from the order of magnitude of kilohertz (KHz) to megahertz (MHz). Therefore, different numbers of samples per cycle may be obtained. Therefore, a plurality of samples are obtained after sampling by the IED 116. Each of the plurality of samples corresponds to a sampling instant, i.e., the sampling instant is the instant at which the sample is captured.

[0029] Once the received voltage measurement values ​​are sampled, the interference state detection module 118 can determine multiple root mean square (RMS) values ​​for each phase based on the voltage measurement values ​​of the corresponding phase. Each of the multiple RMS values ​​is associated with a corresponding sampling moment among the multiple sampling moments. Each of the multiple RMS values ​​is calculated using a predetermined number of samples. The predetermined number of samples includes samples captured at the corresponding sampling moment and samples captured at the previous sampling moment. In an example, depending on the sampling rate and configuration of the IED 116, the predetermined number of samples can be 20 samples.

[0030] Once the RMS value for each phase is determined, the disturbance state detection module 118 determines a plurality of delta quantities for each phase. Each of the plurality of delta quantities is associated with a corresponding sampling instant, and each of the plurality of delta quantities is a difference between the RMS value associated with the corresponding sampling instant and the RMS value associated with the sampling instant a predetermined number of samples ago.

[0031] The interference state detection module 118 can detect whether the delta quantity is greater than a predetermined threshold. In an example, the interference state detection module 118 can continuously compare the delta quantity with a predetermined threshold to detect whether the delta quantity of the voltage has exceeded the predetermined threshold. In an example, the predetermined threshold is approximately 0.5 kilovolts. In response to determining that the delta quantity is greater than the predetermined threshold, the IED 116 detects a peak delta quantity. The peak delta quantity represents a maximum value of the delta quantity. Then, the interference state detection module 118 determines a time interval between a sampling time associated with the peak delta quantity and a sampling time associated with a first delta quantity among a plurality of delta quantities. The interference state detection module 118 compares the time interval with a threshold time to detect an interference state. In response to detecting that the interference state is a power fluctuation, fault detection at the IED 116 can be prevented. Therefore, the IED 116 can be prevented from tripping during a power fluctuation. Therefore, by detecting power fluctuations, the present invention is able to distinguish power fluctuations from faults and can prevent power fluctuations from being misinterpreted as faults, thereby preventing unexpected tripping during power fluctuations. In combination Figures 2 to 9B These and other aspects are described further below.

[0032] Figure 2 A block diagram of an intelligent electronic device (IED) 116 according to an example is shown. The IED 116 includes one or more processors 202 and a memory 204. The one or more processors 202 may be a single processing unit or multiple units, all of which may include multiple computing units. The one or more processors 202 may be implemented as one or more microprocessors, microcomputers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operational instructions. Among other capabilities, the one or more processors 202 are adapted to retrieve and execute processor-readable instructions stored in the memory 204 to implement one or more functions.

[0033] Memory 204 may be coupled to one or more processors 202. Memory 206 may include any computer-readable medium known in the art, including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM); and / or non-volatile memory, such as read-only memory (ROM), erasable programmable ROM (EPROM), flash memory, hard disk, optical disk, and magnetic tape.

[0034] The IED 116 includes one or more interfaces 206. The one or more interfaces 206 may include various software and hardware enabled interfaces. The one or more interfaces 206 may enable communication and connection between the IED 116 and other components of the power grid (e.g., the power grid 100). Examples of such components include, but are not limited to, one or more circuit breakers 114 and sensors. The one or more interfaces 206 may facilitate a variety of communications within a wide variety of protocols, and may also enable communication with one or more computer enabled terminals or similar network components.

[0035] The IED 116 also includes one or more modules 208. The one or more modules 208 may be implemented as a combination of hardware and programming (e.g., programmable instructions) to implement various functions of the one or more modules 208. In the examples described herein, this combination of hardware and programming may be implemented in several different ways. For example, the programming for the one or more modules 208 may be executable instructions. Such instructions may in turn be stored on a non-transitory machine-readable storage medium, which may be coupled to the IED 116 directly or indirectly (e.g., by networking means). In the case of being implemented as hardware, the one or more modules 208 may include processing resources (e.g., a single processor or a combination of multiple processors) to execute such instructions. In this example, the processor-readable storage medium may store such instructions, that is, the instructions implement the one or more modules 208 when executed by the processing resources. In other examples, the one or more modules 208 may be implemented by electronic circuits.

[0036] In an example, the one or more modules 208 include one or more interference state detection modules 118. In addition, the one or more modules 208 may also include a blocking module 210, a delta peak detection module 212, and one or more other modules 214. The one or more other modules 214 may implement such functions, that is, the functions are complementary to the applications or functions performed by the IED 116 or by any of the one or more modules 208. In addition, the IED 116 may also include one or more other components 216. Such one or more other components 216 may include various other electrical components that implement functions for managing and controlling the operation of the power grid 100. Examples of such one or more other components 230 include, but are not limited to, relays, controllers, switches, and voltage regulators.

[0037] In operation, the IED 116 may receive a voltage measurement for each phase of a terminal of a power transmission line, to which the IED 116 is connected from a PT in the transmission line. In an example, the voltage measurement may be received by the interference state detection module 118. In an example, the IED 116 may sample the voltage measurement at a predetermined sampling rate to obtain a plurality of samples. In an example, the sampling rate may be in the range of the order of magnitude of KHz to MHz. Each of the plurality of samples corresponds to a sampling instant, i.e., the sampling instant is the instant at which the sample is captured. Each of the plurality of samples represents a phase voltage value of a certain phase at a particular sampling instant. Therefore, each of the plurality of samples may be represented as V(1), V(2), V(3) ... V(k), etc., where "k" represents the sampling instant associated with the voltage. Although the present description is provided with reference to one phase, the same may apply to all phases of the power grid 100 with necessary modifications. In an example, in a three-phase power system, power fluctuations may be detected by using the voltage measurement for one phase to perform the method explained below. In another example, power fluctuations in the three-phase power system may be detected only when power fluctuations in all phases of the three-phase power system are detected.

[0038] The interference state detection module 118 determines multiple root mean square (RMS) values ​​for each phase based on the voltage measurement value of the corresponding phase. Each of the multiple RMS values ​​is associated with a corresponding sampling moment among multiple sampling moments and is calculated using a predetermined number of samples. The predetermined number of samples based on which the RMS value is calculated can be referenced as "N". In the example, the predetermined number of samples "N" is the number of samples captured within a time period of the basic voltage / current cycle.

[0039] Consider that the interference state detection module 118 calculates the RMS value based on assuming 20 samples. In an example, depending on the configuration and hardware capabilities of the IED, the predetermined number of samples may be more than 20 or less than 20. Therefore, the RMS value associated with the twentieth sampling instant may be calculated as shown in the following equation (1).

[0040]

[0041] In equation (1), V(20), V(19), V(18) ... and V(1) correspond to samples collected at the 20th, 19th, 18th ... and 1st sampling instants, respectively. Similarly, the RMS value associated with the 40th sampling instant can be calculated as shown in equation (2).

[0042]

[0043] In equation (2), V(40), V(39), V(38) ... and V(21) correspond to samples collected at the 40th, 39th, 38th ... and 21st sampling moments, respectively.

[0044] Although the RMS values ​​associated with the 20th sampling instant and the 40th sampling instant are shown to be calculated in the above example, the RMS value is calculated for each sampling instant between the 20th sampling instant and the 40th sampling instant and for each sampling instant thereafter in the example. Therefore, the RMS value is calculated using a predetermined number of samples including samples captured at the corresponding sampling instant and samples captured at the previous sampling instant.

[0045] Therefore, calculation of the RMS value can be expressed as shown in the following equations (3) and (4).

[0046]

[0047] In equation (3) and equation (4), "k" represents a sampling instant associated with the RMS value, and N represents a predetermined number of samples used to calculate the RMS value.

[0048] Figure 3 A graph 300 depicting RMS values ​​of voltage associated with sampling instants plotted against time is shown according to an example. Figure 3 The Y-axis of the graph represents the RMS value of the voltage in kilovolts (kV) associated with the corresponding sampling instant, and the X-axis represents the time in seconds. Figure 3 It can be noticed that the RMS value changes dramatically between 1 second and 1.5 seconds.

[0049] In an example, after obtaining the RMS value, the interference state detection module 118 may apply a moving average filter to the RMS value to reduce the ripple effect in the voltage. Therefore, the interference state detection module 118 may smooth the obtained RMS value to remove the effect of noise. Figure 4 Graph 400 is shown in FIG. 4 , which depicts RMS values ​​of voltage associated with sampling instants plotted against time after filtering.

[0050] Once the RMS values ​​are calculated, the interference state detection module 118 determines a plurality of delta quantities for each phase. The delta quantity represents the voltage difference between the two RMS values. Each of the plurality of delta quantities is associated with a corresponding sampling instant. The interference state detection module 118 may calculate the delta quantity as follows. Considering that the delta quantity associated with the 40th sampling instant is ΔV rms (40), then,

[0051] ΔV rms (40) = Vrms (40)-V rms (20) (5)

[0052] Similarly, the delta quantity associated with the 41st sampling instant is ΔV rms (41), which is calculated as follows:

[0053] ΔV rms (41) = V rms (41)-V rms (21) (6)

[0054] Therefore, the delta quantity can be expressed as,

[0055] ΔV rms (k) = V rms (k)-V rms (kN) (7)

[0056] In equation (7), k is the sampling instant and N is the predetermined number of samples used to calculate the RMS value. Thus, each delta quantity is calculated as the difference between the RMS value associated with the corresponding sampling instant and the RMS value associated with the sampling instant a predetermined number of samples earlier.

[0057] Figure 5 A graph 500 depicting delta quantities of voltage associated with respective sampling instants plotted against time is shown according to an example. Figure 5 The Y-axis of the graph represents the delta voltage (ΔV) in kilovolts (kV) associated with the corresponding sampling instant. rms ), and the X-axis represents time in milliseconds. Figure 5 It can be noticed that the difference between the RMS values ​​of the voltages increases dramatically between 1000 milliseconds and 1100 milliseconds.

[0058] In an example, after obtaining the delta amount, the interference state detection module 118 may apply a moving average filter to the delta amount of the voltage to reduce the ripple effect in the voltage. Therefore, the interference state detection module 118 may smooth the obtained delta amount to remove the effect of noise. Figure 6 Graph 600 is shown in FIG. 6 , which depicts delta quantities of voltage associated with respective sampling instants plotted against time after filtering.

[0059] Then, the interference state detection module 118 detects whether a delta quantity among the plurality of delta quantities is greater than a predetermined threshold. In an example, the predetermined threshold is set within the IED 116. The predetermined threshold may be approximately 0.5 kilovolts.

[0060] In response to determining that the delta quantity is greater than a predetermined threshold, the interference state detection module 118 may detect a peak delta quantity. The peak delta quantity corresponds to a maximum value of the delta quantity. In an example, the interference state detection module 118 may initialize a delta peak detection module 212 to detect the peak delta quantity. The delta peak detection module 212 may determine a magnitude difference between two delta quantities associated with two consecutive sampling moments among the plurality of sampling moments. In an example, the delta peak detection module 212 may initialize a delta peak detection module 212 to detect the peak delta quantity. rms (41) and ΔV rms (40) is determined as,

[0061] X=|(ΔV rms (41)|-|ΔV rms (40)| (8)

[0062] In equation (8), the amplitude difference is represented as X.

[0063] The delta peak detection module 212 can identify the zero crossing of the amplitude difference. In an example, the delta peak detection module 212 can use a zero crossing detector to identify the sign change of the amplitude difference. When the value of X changes from positive to negative, it can be identified that the peak of the delta quantity has occurred. Therefore, the delta peak detection module 212 can determine the peak delta quantity based on the zero crossing of the amplitude difference. In an example, other maximum determination techniques can be used to determine the peak delta quantity.

[0064] Figure 7 A graph obtained by plotting the difference in amplitude between two consecutive delta quantities against time is shown. Figure 7 The Y-axis of the graph represents the amplitude difference, and the X-axis represents the time in milliseconds. Figure 7 It may be noted that the difference in magnitude between the two delta quantities of the voltage has changed from +ve to -ve between 1600 ms and 1800 ms. Therefore, a peak in the delta quantity may occur between 1600 ms and 1800 ms.

[0065] Once the peak delta quantity is determined, the interference state detection module 118 determines the time interval between the sampling instant associated with the peak delta quantity and the sampling instant associated with the first delta quantity among the plurality of delta quantities. The time interval between the peak delta quantity and the first delta quantity represents the time taken by the delta quantity to reach the peak value. In the above example, considering that the peak delta quantity is determined as ΔV rms (41). Therefore, the interference state detection module 118 determines the rms (41) The sampling time associated with ΔV rms (40) The time interval between the associated sampling moments.

[0066] The time interval is compared to a threshold time. In an example, the threshold time is in a range between 50 milliseconds and 55 milliseconds. If the time interval is greater than the threshold time, it is identified that a power fluctuation has occurred. Therefore, the interference state detection module 118 can detect an interference state based on the comparison of the time interval to the threshold time. In response to detecting that the interference state is a power fluctuation, the blocking module 210 can be initialized to block fault detection at the IED 116 or prevent the IED 116 from sending a trip command to the circuit breaker 114. Therefore, the present invention is capable of detecting a power fluctuation and blocking a fault detection at the IED in response to detecting a power fluctuation.

[0067] Figure 8 A graph 800 is shown indicating the time taken by a delta quantity to reach its peak value under different scenarios of electrical disturbances according to an example. Figure 8 It is obtained from test results based on the simulation of a power system consisting of a 400kV, 50Hz double-circuit transmission line with a length of 100km. Figure 8 The graph in illustrates the delta voltage plotted against time for four test cases including a three-phase fault with a fault resistance of 50Ω occurring at 95% of the protected line and three power fluctuation cases with fluctuation frequencies of 1 Hz, 3 Hz and 5 Hz. Figure 8 In the example of , a signal is measured at bus 110, such as Figure 1 shown.

[0068] Reference Figure 8 , the line marked with A represents the curve of the delta quantity in the case of a fault. The line marked with B represents the curve of the delta quantity in the case of a power fluctuation with a fluctuation frequency of 5 Hz. The line marked with C represents the curve of the delta quantity in the case of a power fluctuation with a fluctuation frequency of 3 Hz. The line marked with D represents the curve of the delta quantity in the case of a power fluctuation with a fluctuation frequency of 1 Hz. Figure 8 The time required for each of these curves to reach the peak point from the moment of the fault or fluctuation is marked in FIG. From the figure, it can be observed that the time required to reach the peak point for the three-phase fault case is 21 milliseconds (ms), while the time intervals for the power fluctuation cases with fluctuation frequencies of 1 Hz, 3 Hz and 5 Hz are 293 ms, 126 ms and 85 ms, respectively. Therefore, by monitoring the time interval between the peak delta quantity and the first delta quantity, power fluctuations in the frequency range from about 0.1 Hz to 5 Hz can be reliably detected, and fault detection at the IED 116 can be prevented accordingly.

[0069] Fig. 9A and Fig. 9BA method 900 for operating an intelligent electronic device (IED) during power fluctuations according to an example is shown. The method 900 may be performed by a system such as an IED 116. The method 900 may be implemented by one or more processing resources or electrical control systems through any suitable hardware, programmable instructions, or a combination thereof. In an example, one or more steps of the method 900 may be performed by hardware or programming modules, such as the interference state detection module 118, the delta peak detection module 212, and the blocking module 210. In addition, although the method 900 is described in the context of the above-mentioned IED 116, other suitable systems may be used to perform the method 900. It is understood that the processing involved in the method 900 may be performed based on instructions stored in a non-transitory computer-readable medium. The non-transitory computer-readable medium may include, for example, a digital memory, a magnetic storage medium (e.g., a disk and tape), a hard drive, or an optically readable digital data storage medium.

[0070] Reference Fig. 9A At block 902, a voltage measurement for each phase of a terminal of a power transmission line is received. In an example, the terminal may be a bus, e.g., Figure 1 The bus 110, and the power transmission line may be Figure 1 1 , which is coupled to an IED such as IED 116. In an example, voltage measurements are continuously received from voltage transformers (PTs) in the transmission line.

[0071] In an example, in a three-phase power system, power fluctuations may be detected by using voltage measurements for one phase to perform the method explained below. In another example, power fluctuations in a three-phase power system may be detected only when power fluctuations in all phases of the three-phase power system are detected.

[0072] At block 904, the voltage measurement of each phase is sampled at a predetermined sampling rate to obtain a plurality of samples. Each of the plurality of samples corresponds to a sampling instant, that is, the sampling instant is the instant at which the sample is captured.

[0073] At block 906, a plurality of root mean square (RMS) values ​​for each phase are determined based on the voltage measurements of the corresponding phases. Each of the plurality of RMS values ​​is associated with a corresponding sampling instant among a plurality of sampling instants and is calculated using a predetermined number of samples. The predetermined number of samples includes samples including samples captured at the corresponding sampling instant and samples captured at previous sampling instants.

[0074] At block 908, a plurality of delta quantities are determined for each phase based on the RMS value of the corresponding phase. Each of the plurality of delta quantities is associated with a corresponding sampling instant and is calculated as a difference between the RMS value associated with the corresponding sampling instant and the RMS value associated with the sampling instant a predetermined number of samples ago.

[0075] At block 910, it is detected whether the delta quantity is greater than a predetermined threshold. In an example, a plurality of delta quantities are continuously monitored and compared to a predetermined threshold to detect whether the delta quantity has exceeded the predetermined threshold. In an example, the predetermined threshold is approximately 0.5 kilovolts. Fig. 9A The connection point A at the end of the figure indicates that the illustration of the figure continues to the next figure.

[0076] refer to Fig. 9B In response to determining that the delta quantity is greater than a predetermined threshold, a peak delta quantity is detected at block 912. In an example, a magnitude difference between two delta quantities associated with two consecutive sampling moments among a plurality of sampling moments is determined. A zero crossing of the magnitude difference is identified. Based on the zero crossing of the magnitude difference, a peak delta quantity may be determined.

[0077] At block 914, a time interval between a sampling instant associated with the peak delta quantity and a sampling instant associated with a first delta quantity among the plurality of delta quantities is determined. In an example, the time interval is compared to a threshold time. In an example, the threshold time is in a range between 50 milliseconds and 55 milliseconds.

[0078] At block 916, a disturbance condition is detected based on a comparison of the time interval to a threshold time. In response to determining that the time interval is greater than the threshold time, the disturbance condition is detected as a power fluctuation. At block 918, in response to detecting that the disturbance condition is a power fluctuation, a fault detection at the IED is prevented or the IED is prevented from sending a signal to a circuit breaker to trip the circuit.

[0079] Although embodiments of the present invention have been described in language specific to structural features and / or methods, it will be noted that the present invention is not necessarily limited to the specific features or methods described. Instead, specific features and methods are disclosed and explained in the context of some embodiments of the present invention.

Claims

1. A method for operating an intelligent electronic device (IED) under power fluctuation conditions, wherein: The IED is associated with a terminal of a power transmission line, the method comprising: receiving a voltage measurement for each phase of a terminal of the power transmission line, wherein the voltage measurement is sampled to obtain a plurality of samples, each sample in the plurality of samples corresponding to a sampling instant when the sample is captured; determining a plurality of root mean square (RMS) values ​​of the measured values ​​in each phase based on the voltage measurements of the corresponding phase, wherein each RMS value of the plurality of RMS values ​​is associated with a corresponding sampling instant of the plurality of sampling instants and is calculated using a predetermined number of samples, the predetermined number of samples including samples captured at the corresponding sampling instant and samples captured at previous sampling instants; determining a plurality of delta quantities for each phase, wherein each delta quantity of the plurality of delta quantities is associated with the corresponding sampling instant and is calculated as a difference between an RMS value associated with the corresponding sampling instant and an RMS value associated with the sampling instant the predetermined number of samples prior; Based on the continuous monitoring of the plurality of delta quantities, detecting whether a delta quantity among the plurality of delta quantities is greater than a predetermined threshold; responsive to determining that the delta amount is greater than the predetermined threshold, detecting a peak delta amount; determining a time interval between a sampling instant associated with the peak delta quantity and a sampling instant associated with a first delta quantity among the plurality of delta quantities; detecting an interference state based on a comparison of the time interval with a threshold time; and In response to detecting that the disturbance condition is a power fluctuation, fault detection at the IED is prevented.

2. The method according to claim 1, wherein: In response to determining that the time interval is greater than the threshold time, the interference state is detected as a power fluctuation.

3. The method according to claim 1 or 2, wherein: Detecting the peak delta quantity includes: determining a magnitude difference between two delta quantities in the plurality of delta quantities, the two delta quantities being associated with two consecutive sampling instants in the plurality of sampling instants; identifying a zero crossing of the amplitude difference; and The peak delta quantity is determined based on the zero crossing of the amplitude difference.

4. The method according to claim 1 or 2, wherein: The predetermined threshold is approximately 0.5 kilovolts.

5. The method according to claim 1 or 2, wherein: The threshold time is in the range of 50 milliseconds to 55 milliseconds.

6. An intelligent electronic device (IED) capable of operating under power fluctuation conditions, wherein: The IED is associated with a terminal of a power transmission line, the IED comprising: Processor; and an interference status detection module coupled to the processor, the interference status detection module being configured to: receiving a voltage measurement for each phase of a terminal of the power transmission line, wherein the voltage measurement is sampled to obtain a plurality of samples, each sample in the plurality of samples corresponding to a sampling instant when the sample is captured; determining a plurality of root mean square (RMS) values ​​for each phase based on the voltage measurements of the corresponding phase, wherein each of the plurality of RMS values ​​is associated with a corresponding sampling instant among the plurality of sampling instants and each of the plurality of RMS values ​​is calculated using a predetermined number of samples, the predetermined number of samples including samples captured at the corresponding sampling instant and samples captured at previous sampling instants; determining a plurality of delta quantities for each phase, wherein each delta quantity in the plurality of delta quantities is associated with the corresponding sampling instant and each delta quantity in the plurality of delta quantities is a difference between an RMS value associated with the corresponding sampling instant and an RMS value associated with the sampling instant the predetermined number of samples prior; Based on the continuous monitoring of the plurality of delta quantities, detecting whether a delta quantity among the plurality of delta quantities is greater than a predetermined threshold; responsive to determining that the delta amount is greater than the predetermined threshold, detecting a peak delta amount; determining a time interval between a sampling instant associated with the peak delta quantity and a sampling instant associated with a first delta quantity of the plurality of delta quantities; and detecting an interference state based on a comparison of the time interval with a threshold time; and a blocking module coupled to the processor, the blocking module configured to: In response to detecting that the disturbance condition is a power fluctuation, fault detection at the IED is prevented.

7. The IED according to claim 6, wherein: In response to determining that the time interval is greater than the threshold time, the interference state is detected as a power fluctuation.

8. The IED according to claim 6 or 7, further comprising a peak detection module, wherein the peak detection module is configured to: determining a magnitude difference between two delta quantities among the plurality of delta quantities, the two delta quantities being associated with two consecutive sampling instants among the plurality of sampling instants; identifying a zero crossing of the amplitude difference; and The peak delta quantity is determined based on the zero crossing of the amplitude difference.

9. The IED according to claim 6 or 7, wherein: The predetermined threshold is approximately 0.5 kilovolts.

10. The IED according to claim 6 or 7, wherein: The threshold time is in the range of 50 milliseconds to 55 milliseconds.

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