Parameter estimation for multi-terminal lines

Abstract

The present disclosure relates to a method for determining at least one network parameter of a network comprising a power line terminated by at least three terminals. The method comprises: obtaining measurements of the at least three terminals terminating the power line at respective ends of the power line; obtaining at least one input parameter of a network model of the network based on the obtained measurements of the at least three terminals; determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and providing the at least one network parameter to a device configured to control, monitor and / or analyze the network. The invention also relates to a corresponding device and system.

Description

Technical Field

[0001] The present disclosure relates to a method, an apparatus, a computer-readable medium, and a system for determining at least one network parameter of a network comprising a power line terminated by at least three terminals. Background Art

[0002] In power system protection, fault location and control, parameters, especially transmission line parameters, are usually assumed to be known, but may contain errors, which in turn may affect the performance of the results. Therefore, parameter estimation and verification are increasingly important parts for power systems. Transmission line parameters may depend on environmental system conditions, including temperature, line aging, etc. Therefore, online estimation of line parameters is very desirable and beneficial to obtain accurate line parameters, especially for fault location and protection applications. In particular, parameter estimation for lines connected to renewable resources is challenging and very important for adaptive protection applications.

[0003] The first method can estimate the line parameters of the three-terminal hybrid line using the positive and negative sequence, pre-fault and during-fault voltages and currents, and further identify the fault section and fault location, but is limited to the case where the transmission line is only coupled to conventional sources such as synchronous sources. In scenarios where negative sequence quantities are not available, especially in networks connected to inverter-based resources IBR, the first method may require multiple pre-fault measurement sets (depending on the IBR type and control) to solve the line parameters.

[0004] The second method can estimate the line parameters of a three-terminal transmission line using the nonlinear weighted least squares error (NWLSE) of the measurements from the phasor measurement unit (PMU) and the supervisory control and data acquisition (SCADA). This method may require a minimum of three different measurement sets to estimate the line parameters. Recording multiple sets of data requires a large storage space and this places a computational burden on the IED.

[0005] The third approach can utilize analytical optimization techniques such as Newton's method and least squares method, the convergence of which depends heavily on the initial guess. This approach can use a meta-heuristic algorithm in the first step to solve the nonlinear objective function and provide the result of the first step as an initial guess to the Newton-Raphson method in the second step to estimate the line parameters of the double-terminal hybrid line. In the meta-heuristic optimization method, the global optimal solution cannot be guaranteed and local minima may occur and are difficult to implement in the IED platform.

[0006] The above method may have limitations when the transmission line is connected to the IBR and the initial guess is not ideal.Therefore, there is a need for an improved method, apparatus, computer readable medium, and system for determining at least one network parameter of a network including power lines terminated by at least three terminals. Summary of the invention

[0007] It would be advantageous to implement parameter estimation, in particular for a network comprising at least one inverter-based resource connected to at least one terminal of a transmission line. In doing so, it would be desirable to implement a single-step approach or a two-step approach to solve for line parameters of a three-terminal homogeneous or hybrid line by eliminating the risk of an initial guess being suboptimal using only one set of measured data (pre-fault).

[0008] The present disclosure relates to a method for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the method comprising: obtaining measurement results of the at least three terminals, in particular measurement results measured before a fault occurs, the at least three terminals terminating the power line at respective ends of the power line, the power line comprising respective sections, the respective sections being portions of the power line starting from a position on the power line to the respective ends, wherein electrical parameters of at least one of the respective sections are different from electrical parameters of other respective sections; obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line; determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and providing the at least one network parameter to a device configured to control, monitor and / or analyze the network.

[0009] The present disclosure also relates to a method for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the method comprising: obtaining measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising respective sections, the respective sections being portions of the power line starting from a position on the power line to the respective ends, wherein the measurement results are measured before a fault occurs, and wherein electrical parameters of at least one of the respective sections are different from electrical parameters of other respective sections; obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line; determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and providing the at least one network parameter to a device configured to control, monitor and / or analyze the network.

[0010] The skilled person will appreciate that measurements before a fault may refer to measurements performed when the fault has not occurred (ie, in the absence of the fault).

[0011] The network may be an electricity transmission network.

[0012] A power line may be a cable or other structure that carries electrical energy in an electrical system / network, in particular by conducting electromagnetic waves. A power line may be a transmission line.

[0013] A terminal may refer to an end point of a conductor, in particular a transmission line or network. A terminal may refer to an electrical connector at that end point, acting as an interface to another conductor and creating a point to which an external circuit may be connected. A terminal may be an electrical bus, in particular a busbar and / or bus conduit, for connecting high voltage equipment.

[0014] The network parameters may be one or more line parameters, such as resistance, inductance and / or capacitance.

[0015] The electrical parameters of a section may refer to the impedance of the section, in particular the modeling impedance. The electrical parameters of a section may refer to the positive-sequence series impedance, negative-sequence series impedance or zero-sequence series impedance of the section, in particular, the positive-sequence series impedance, negative-sequence series impedance or zero-sequence series impedance includes the positive-sequence resistance, negative-sequence resistance or zero-sequence resistance of the section and / or the positive-sequence inductance, negative-sequence inductance or zero-sequence inductance of the section. The electrical parameters of a section may refer to the shunt admittance of the section, in particular the modeling shunt admittance. The electrical parameters of a section may refer to the positive-sequence shunt admittance, negative-sequence shunt admittance or zero-sequence shunt admittance of the section, and the positive-sequence shunt admittance, negative-sequence shunt admittance or zero-sequence susceptance includes the positive-sequence susceptance, negative-sequence susceptance or zero-sequence susceptance of the section.

[0016] The electrical parameter of a segment may refer to a voltage and / or a current and / or a propagation constant of the segment.The electrical parameter of a segment may specifically refer to a value of an electrical parameter, such as a voltage value and / or a current value and / or a propagation constant of the segment.

[0017] The propagation constant can be expressed as γ=α+jβ, where α is the attenuation constant and β is the phase constant.

[0018] The input parameters of the network model are electrical parameters of the network model, for example, impedance and / or inductance of the network model.

[0019] The terminal may be an electrical connector that terminates the first cable and is connected to the second cable, thereby passing current between the two. The transmission line may be an overhead line or a cable, in particular an underground cable. Each section of the transmission line may be the same or different and may be an overhead line or a cable.

[0020] The network model may be a distributed model or a series impedance model, as further exemplarily described below. The line capacitance of a segment may be the capacitance between a segment of a transmission line and another object, in particular a conductive material (e.g., another segment of a transmission line). The line capacitance of a segment may be the capacitance between two phases or lines of the same segment of a transmission line. The line capacitance of a segment may couple the segment of a transmission line to an electrical ground potential.

[0021] A fault may refer to a fault condition in a transmission line or a section of a transmission line. A fault location is the location where the fault occurs on a transmission line. A fault may refer to any form of anomaly in a system, i.e., any operating state that differs from the normal operating state of the system.

[0022] According to an embodiment, obtaining the at least one input parameter of the network model comprises or determines the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and a further network model.

[0023] According to an embodiment, the further network model is different from the network model used to determine the at least one network parameter, and wherein the network model comprises at least one more electrical parameter than the further network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, the line capacitance coupling the one of the corresponding sections to an electrical ground potential.

[0024] According to an embodiment, the at least one input parameter of the network model is determined adapted to differences in the electrical parameters between respective sections of the power line modeled in the further network model.

[0025] According to an embodiment, the at least one network parameter is determined adapted to differences in electrical parameters between respective sections of the power line modeled in the further network model.

[0026] According to an embodiment, the method further comprises determining a faulty section based on the at least one input parameter of the network model.

[0027] According to an embodiment, the method further comprises controlling an electric power device, in particular an automatic recloser for the power line, based on the determined faulty section.

[0028] According to an embodiment, the method further comprises estimating the fault location in response to the control based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault, in particular when the power device is operated in the first operating mode.

[0029] According to an embodiment, the method further comprises providing the at least one network parameter to the device configured to control, monitor and / or analyze the network.

[0030] The present disclosure also relates to a device for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the device comprising a processor, the processor being configured to: obtain measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising respective sections, the respective sections being portions of the power line starting from a position on the power line to the respective ends, wherein electrical parameters of at least one of the respective sections are different from electrical parameters of other respective sections; obtain at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular, an impedance of a section among the respective sections of the power line; determine the at least one network parameter based on the at least one input parameter of the network model and the network model; and provide the at least one network parameter to a device configured to control, monitor and / or analyze the network.

[0031] The present disclosure also relates to a device for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the device comprising a processor, the processor being configured to: obtain measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising respective sections, the respective sections being portions of the power line starting from a position on the power line to the respective ends, wherein the measurement results are measured before a fault occurs, and wherein electrical parameters of at least one of the respective sections are different from electrical parameters of other respective sections; obtain at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line; determine the at least one network parameter based on the at least one input parameter of the network model and the network model; and provide the at least one network parameter to a device configured to control, monitor and / or analyze the network.

[0032] The skilled person will appreciate that measurements before a fault may refer to measurements performed when the fault has not occurred (ie, in the absence of the fault).

[0033] According to an embodiment, the processor is configured to obtain the at least one input parameter of the network model by determining the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and a further network model.

[0034] According to an embodiment, the further network model is different from the network model used for determining the at least one network parameter.

[0035] According to an embodiment, the network model includes at least one more electrical parameter than the other network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, the line capacitance coupling the one of the corresponding sections to an electrical ground potential.

[0036] According to an embodiment, the processor is configured to determine the at least one input parameter of the network model adapted to differences in the electrical parameters between respective sections of the power line modeled in the further network model.

[0037] According to an embodiment, the processor is configured to determine the at least one network parameter adapted to differences in electrical parameters between respective sections of the power line modelled in the further network model.

[0038] According to an embodiment, the processor is further configured to determine a faulty section based on the at least one input parameter of the network model.

[0039] According to an embodiment, the processor is further configured to control an electric power device, in particular an automatic recloser for the power line, based on the determined faulty section.

[0040] According to an embodiment, the processor is further configured to estimate the fault location in response to the control based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault, in particular when the power device is operated in the first operating mode.

[0041] According to an embodiment, the processor is further configured to provide the at least one network parameter to the device configured to control, monitor and / or analyze the network.

[0042] The present disclosure also relates to a computer-readable medium for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the computer-readable medium carrying instructions for executing the method as described in any one of the above embodiments.

[0043] According to an embodiment, the device configured to control, monitor and / or analyze the network is or includes the computer-readable medium according to the above-mentioned embodiments.

[0044] The present disclosure further relates to a system, the system comprising a network and the device as described in any one of the above embodiments, the network comprising a power line terminated by at least three terminals.

[0045] According to an embodiment, the system further comprises an electric power device, in particular an automatic recloser for the power line.

[0046] The following aspects are directed to specific embodiments of the invention.

[0047] 1. A method for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the method comprising:

[0048] obtaining measurements of the at least three terminals terminating the power line at respective ends of the power line, in particular measurements measured before a fault occurs, the at least three terminals terminating the power line at respective ends of the power line, the power line comprising a respective section, the respective section being a portion of the power line starting from a position on the power line to the respective end,

[0049] wherein the electrical parameters of at least one of the corresponding sections are different from the electrical parameters of the other corresponding sections;

[0050] obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals,

[0051] wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line;

[0052] determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and

[0053] The at least one network parameter is provided to a device configured to control, monitor and / or analyze the network.

[0054] 2. The method of aspect 1, wherein obtaining the at least one input parameter of the network model comprises or determines the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and another network model,

[0055] wherein the further network model is different from the network model used to determine the at least one network parameter, and

[0056] Therein, the network model includes at least one more electrical parameter than the other network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, wherein the line capacitance couples the one of the corresponding sections to an electrical ground potential.

[0057] 3. A method as described in aspect 2, wherein at least one input parameter of the network model is determined by adapting to the difference in electrical parameters between corresponding sections of the power line modeled in the other network model, and / or wherein at least one network parameter is determined by adapting to the difference in electrical parameters between corresponding sections of the power line modeled in the other network model.

[0058] 4. The method according to any one of aspects 1 to 3, further comprising:

[0059] determining a faulty section based on the at least one input parameter of the network model; and

[0060] Based on the determined fault section, power equipment, in particular an automatic reclosing device for the power line, is controlled.

[0061] 5. The method according to aspect 4, further comprising:

[0062] estimating the fault location in response to the control, in particular when the power device is operated in a first operating mode, based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault; and

[0063] The at least one network parameter is provided to the device configured to control, monitor and / or analyze the network.

[0064] 6. A device for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the device comprising a processor, the processor being configured to:

[0065] obtaining measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising a respective section, the respective section being a portion of the power line starting from a location on the power line to the respective end,

[0066] wherein the electrical parameters of at least one of the corresponding sections are different from the electrical parameters of the other corresponding sections;

[0067] obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals,

[0068] wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line;

[0069] determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and

[0070] The at least one network parameter is provided to a device configured to control, monitor and / or analyze the network.

[0071] 7. The apparatus according to aspect 6, wherein the processor is configured to obtain the at least one input parameter of the network model by determining the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and another network model,

[0072] wherein the further network model is different from the network model used to determine the at least one network parameter, and

[0073] Therein, the network model includes at least one more electrical parameter than the other network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, wherein the line capacitance couples the one of the corresponding sections to an electrical ground potential.

[0074] 8. An apparatus as described in aspect 7, wherein the processor is configured to adapt to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model to determine at least one input parameter of the network model, and / or the processor is configured to adapt to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model to determine at least one network parameter.

[0075] 9. The apparatus of any one of clauses 6 to 8, wherein the processor is further configured to:

[0076] determining a faulty section based on the at least one input parameter of the network model; and

[0077] Based on the determined fault section, power equipment, in particular an automatic reclosing device for the power line, is controlled.

[0078] 10. The apparatus of clause 9, wherein the processor is further configured to:

[0079] estimating the fault location in response to the control, in particular when the power device is operated in a first operating mode, based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault; and

[0080] The at least one network parameter is provided to the device configured to control, monitor and / or analyze the network.

[0081] 11. A computer-readable medium for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the computer-readable medium carrying instructions for executing the method of any one of aspects 1 to 5.

[0082] 12. A system comprising a network and a device as described in any one of aspects 6 to 10, the network comprising a power line terminated by at least three terminals.

[0083] 13. The system according to aspect 12, further comprising an electric power device, in particular an automatic reclosing device for the power line.

[0084] Various exemplary embodiments of the present disclosure are intended to provide features that will become apparent by reference to the following description when taken in conjunction with the accompanying drawings. According to various embodiments, exemplary systems, methods, and devices are disclosed herein. However, it should be understood that these embodiments are presented by way of example and not limitation, and it will be apparent to those of ordinary skill in the art reading this disclosure that various modifications may be made to the disclosed embodiments while still within the scope of this disclosure.

[0085] Therefore, the present disclosure is not limited to the exemplary embodiments and applications described and illustrated herein. In addition, the specific order and / or hierarchy of steps in the methods disclosed herein are merely exemplary methods. Based on design preferences, the specific order or hierarchy of steps of the disclosed methods or processes can be rearranged while still within the scope of the present disclosure. Therefore, it will be understood by those of ordinary skill in the art that the methods and techniques disclosed herein present various steps or actions in an example order, and unless otherwise expressly stated, the present disclosure is not limited to the specific order or hierarchy presented.

[0086] In the following, exemplary embodiments of the present disclosure will be described. Note that, unless otherwise stated or apparent, some aspects of any of the described embodiments may also be found in some other embodiments. However, in order to improve understandability, each aspect will be described in detail only when first mentioned, and any repeated description of the same aspect will be omitted.

[0087] The above and other aspects and embodiments thereof are described in more detail in the drawings, the description and the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1a ) illustrates a flowchart of a method according to an embodiment of the present disclosure. Figure 1b ) illustrates a flowchart of a method according to an embodiment of the present disclosure.

[0089] Figure 2 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0090] Figure 3 A series impedance (RL) model of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0091] Figure 4 A distributed (RLC) model of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0092] Figure 5 A flow chart of a method according to an embodiment of the present disclosure is illustrated.

[0093] Figure 6 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0094] Figure 7 FIG. 1 illustrates a graphical simulation result of a three-terminal network according to an embodiment of the present disclosure.

[0095] Figure 8 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0096] Fig. 9 The percentage errors of the parameters calculated based on the method according to the embodiment of the present disclosure are illustrated.

[0097] Fig.10 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0098] Fig.11 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0099] Fig.12 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0100] Fig.13 FIG. 1 illustrates a graphical simulation result of a three-terminal network according to an embodiment of the present disclosure.

[0101] Fig.14 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0102] Fig.15The percentage errors of the parameters calculated based on the method according to the embodiment of the present disclosure are illustrated.

[0103] Fig.16 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0104] Fig.17 FIG. 1 illustrates a graphical simulation result of a three-terminal network according to an embodiment of the present disclosure.

[0105] Fig.18 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0106] Fig.19 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0107] Fig. 20 FIG. 1 illustrates a graphical simulation result of a three-terminal network according to an embodiment of the present disclosure.

[0108] Fig.21 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0109] Fig. 22 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated.

[0110] Fig.23 FIG. 1 illustrates a graphical simulation result of a three-terminal network according to an embodiment of the present disclosure.

[0111] Fig.24 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0112] Figure 1a) illustrates a flow chart of a method according to an embodiment of the present disclosure. In particular, the flow chart illustrates a two-step method for a network, the network comprising a power line terminated by at least three terminals, wherein the at least three terminals terminate the power line at respective ends of the power line, the power line comprising respective sections, the respective sections being portions of the power line starting from a position on the power line to the respective ends, and wherein the electrical parameters of at least one of the respective sections are different from the electrical parameters of the other respective sections, in particular different in value. Such a network is also referred to as a hybrid line network. A network in which the electrical parameters of all respective sections are equal, in particular equal in value, may also be referred to as a homogeneous line network. The power line may be a transmission line. The terminal may refer to an end point of a conductor, in particular a transmission line or a network. The terminal may refer to an electrical connector at the end point, acting as an interface to another conductor and creating a point to which an external circuit may be connected. The terminal may be an electrical bus, in particular a busbar and / or a busbar conduit, for connecting high voltage equipment. The transmission line may be connected to a load or a source via a terminal terminating the transmission line. At S101, the pre-fault voltage and current from all terminals (i.e., three terminals in this embodiment) are obtained, which can be obtained using digital fault recorder (DFR) data. This data can be recorded by the IED at fixed intervals for analysis. It should be understood by the technician that the power line can be further terminated by a fourth terminal coupled to a fourth power source, a fifth terminal coupled to a fifth power source, and so on. At S102, a two-step method algorithm is performed. At step-1, the series impedance of each section is calculated using a first model of the network (e.g., an RL model). At step-2, the series impedance obtained from step-1 is given as an initial guess for the least squares method, and the second model of the network (e.g., a distributed parameter model) is used to estimate additional line parameters. The additional line parameters calculated at step-2 can be the same parameters as those calculated at step 1, especially with higher accuracy. At S103, the line parameters are output, especially for further use in systems including protection, control and fault location applications.

[0113] Figure 1b) illustrates a flow chart of a method according to an embodiment of the present disclosure. At S151, measurement results of the at least three terminals are obtained, in particular, measurement results measured before a fault occurs, the at least three terminals terminate the power line at the respective ends of the power line, the power line includes a respective section, the respective section is a portion of the power line starting from a position on the power line to the respective end, wherein the electrical parameters of at least one section of the respective sections are different from the electrical parameters of the other respective sections. It should be understood by the technician that the measurement before the fault may refer to a measurement performed when no fault occurs (i.e., in the absence of a fault). At S152, at least one input parameter of a network model of the network is obtained based on the measurement results of the at least three terminals obtained, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular, the impedance of one section of the respective sections of the power line. At S153, the at least one network parameter is determined based on the at least one input parameter of the network model and the network model. At S154, the at least one network parameter is provided to a device configured to control, monitor and / or analyze the network.

[0114] According to an embodiment, obtaining the at least one input parameter of the network model includes or determining the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and another network model, wherein the other network model is different from the network model used to determine the at least one network parameter, and wherein the network model includes at least one more electrical parameter than the other network model, in particular, a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, the line capacitance coupling the one of the corresponding sections to the electrical ground potential.

[0115] According to an embodiment, the at least one input parameter of the network model is determined by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model, and / or wherein the at least one network parameter is determined by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model.

[0116] According to an embodiment, the method further comprises: determining a fault section based on the at least one input parameter of the network model; and controlling power equipment, in particular an automatic reclosing device for the power line, based on the determined fault section.

[0117] According to an embodiment, the method further includes: estimating the fault location in response to the control based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault, in particular when the power device operates in the first operating mode; and providing the at least one network parameter to the device configured to control, monitor and / or analyze the network.

[0118] Figure 2 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, the network 200 includes a power line terminated at respective ends by three terminals busbar M 231, busbar N 232, and busbar P 233. The portions of the power line from point J to the respective three terminals 231, 232, and 233 are referred to as a first section MJ 241, a second section NJ 242, and a third section PJ 243, respectively. Each of the three terminals 231, 232, and 233 is coupled to a respective power source 211, 212, and 213, the respective power sources being measured with a source voltage parameter (E M , E N ,,δ N , E P , δ P ) and the corresponding source impedance Z sM 221, Z SN 222 and Z SP 223 is modeled. The modeling parameters of the source describe the pre-fault operating state.

[0119] In the following, two scenarios are considered: 1) the parameters of all sections MJ 241, NJ 242 and PJ 243 are the same; 2) the parameters of MJ 241 and NJ 242 (also called main sections) are the same, while the parameters of PJ (also called tap lines) are different from those of MJ241 and NJ 242, especially the values ​​are different.

[0120] In the following, the first scenario is considered.

[0121] - Scenario 1: The parameters of all sections MJ 241, NJ 242 and PJ 243 are the same.

[0122] Figure 3 The series impedance model of the three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, Figure 3A series impedance (RL) model 300 of the network 200 is illustrated. According to an embodiment, the series impedance model 300 is used in step-1 of FIG. 1 . According to an embodiment, the series impedance model is referred to as a network model of the network 200. According to an embodiment, step-1 of FIG. 1 is a non-iterative method for parameter estimation. The modeling network 300 includes a power line terminated at respective ends by three terminals busbar M 331, busbar N 332, and busbar P 333. The parameters of the network are as follows:

[0123] Z1=R1+jX1; Y1=JB1; X1=jωL1; B1=jωC1; ω=2πf;

[0124] Z2=R2+jX2; Y2=jB2; X2=jωL2; B2=jωC2;

[0125]

[0126] Z1, Z2 = positive sequence series impedance of sections MJ, NJ and PJ, in ohm / m

[0127] Y1, Y2 = positive sequence parallel admittance of sections MJ, NJ and PJ, in mho / m

[0128] R1, R2 = positive sequence resistance of sections MJ, NJ and PJ, in ohm / m

[0129] X1, X2 = positive sequence inductance of sections MJ, NJ and PJ, in ohm / m

[0130] B1, B2 = positive sequence susceptance of sections MJ, NJ and PJ, in mho / m

[0131] ω = angular velocity in radians per second

[0132] f = system frequency, in Hz

[0133] L1, L2 = positive sequence inductance of sections MJ, NJ and PJ, in H / m

[0134] C1, C2 = positive sequence capacitance of sections MJ, NJ and PJ, in F / m

[0135] l MJ = length of segment MJ in meters

[0136] l NJ = length of segment NJ in meters

[0137] l PJ = length of segment PJ in meters

[0138] Considering scenario 1, Z2 = Z1, since the parameters of all zones are the same.

[0139] according to Figure 3 , applying Kirchhoff's voltage law KVL on MP yields:

[0140]

[0141] And similarly, applying KVL on NP yields:

[0142]

[0143] According to the above equations (1) and (2), Z1 is calculated as follows:

[0144]

[0145] By substituting Z1 in equation (2), Z2 is given as follows:

[0146]

[0147] Here, Z2 = Z1, since the parameters of all zones are the same.

[0148] Figure 4 The diagram illustrates a distributed (RLC) model of a three-terminal network according to an embodiment of the present disclosure. In particular, Figure 4 The distributed parameter model 400 of the network 200 is shown. According to an embodiment, the approximation model 400 is used in step 2 of FIG. 1 . According to an embodiment, the distributed model is referred to as a further network model of the network 200. According to an embodiment, step 2 of FIG. 1 is an iterative method for parameter estimation, in particular a least squares iterative method or a root-finding algorithm, such as Newton's method. According to an embodiment, given the result from step-1 (in particular using Figure 3 The parameters obtained from the model are used as step-2 (specifically using Figure 4 The modeled network 400 includes power lines terminated at respective ends by three terminals busbar M 431, busbar N 432, and busbar P 433. The parameters of the network are as follows:

[0149]

[0150]

[0151]

[0152]

[0153] γ MJ =γ NJ = propagation constant of the main line

[0154] γ PJ = propagation constant of the tapped line

[0155] Consider the first scenario, that is, all segments have the same parameters, And γ PJ =γ MJ The initial guess for the following method (least squares iterative method) can be provided from the following steps-1: R and L in Z1 are considered as initial guesses, and C is varied from -50% to +50% of the actual value. That is,

[0156] R O =Re{Z1};X o =Im{Z1};B o =ωC o

[0157] v o =(R o , X Lo , B o ) T

[0158] The ABCD parameters for each segment are described as follows:

[0159]

[0160] The ABCD parameter converts the junction voltage V JM , V JN , and V JP and current I JM , V JN , and V JP The measured voltage and current at terminals 431, 432 and 433 are related as follows:

[0161]

[0162] When calculated from terminals M 431 and P 433, by making the junction voltages equal, we get V JM -V JP =0,

[0163]

[0164] Substituting equations (5) to (7) into equation (11) yields:

[0165]

[0166] When calculated from terminals N and P, by making the junction voltages equal, we get V JN -V JP =0,

[0167]

[0168] Substituting equations (5) to (7) into equation (13) yields:

[0169]

[0170] Applying KCL at junction J yields:

[0171] I MJ +I NJ +I PJ =0 (15)

[0172] According to equations (8) to (10), I MJ ,I NJ and I PJ The calculation of is as follows:

[0173]

[0174] Equations (12), (14) and (15) are in the form of F(X) = 0, so the objective function is expressed as:

[0175]

[0176] Each objective function is divided into real and imaginary terms and then solved using the least squares iterative method. The unknowns in the above nonlinear equations are R1, X1, and B1. Objective Function and Used to solve unknowns. The line parameters are obtained as follows:

[0177] R1=R1;

[0178] Figure 5 A flow chart of a method according to an embodiment of the present disclosure is illustrated. Figure 5It can be a detailed embodiment of Figure 1. At 511, the voltage and current measurements from all terminals are recorded. The voltage and current measurements from all terminals can be obtained, received, stored or similar operations. At 512, the availability of the initial guess is determined. In the negative case, at 513, the parameters of the power line are calculated using the RL model of the network. In the affirmative case, the initial guess, in particular the line parameters, are fed directly to 514. At 514, based on the line parameters of the previous step, the distributed model of the network is used to estimate other parameters. According to an embodiment, the decision of 512 is omitted, and the recorded voltage and current measurements from all terminals are fed directly to 513. According to an embodiment, 513 is omitted, and the initial guess and / or the recorded voltage and current measurements from all terminals are fed directly to 514. The line parameters estimated at 514 can be more accurate than the line parameters calculated at 513. At 513, based on the parameter differences of the three segments, parameter 531 is calculated based on equation (3) 535 or based on equation (3) and equation (4) 536. Similarly, at 514, based on the parameter differences of the three segments, parameter 541 is calculated based on equation (19) and equation (21) 545 or based on equation (19) to equation (21) 546. For example, at block 545, according to equations (19) and (21), respectively, it is possible to solve and The line parameters are as follows, and at block 546, according to equations (19), (20) and (21), respectively, it is possible to solve and The line parameters, whether from an initial guess or calculated at 513, are fed to 521 where the faulty section is identified. At 522, it is determined whether the fault occurs on an overhead line. In the negative case, automatic reclosing is blocked at 523, i.e., an operation, action, etc. is disabled. In the positive case, automatic reclosing is enabled at 524. Then, at 525, it is determined whether automatic reclosing is successful. In the positive case, the algorithm is terminated. In the negative case, 515 is executed. According to an embodiment, 514 and 520 are performed simultaneously.

[0179] Figure 6A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, the network 600 includes a power line terminated by three terminals busbar M 631, busbar N 632 and busbar P 633 at the respective ends. The portions of the power line from point J to the respective three terminals 631, 632 and 633 are respectively referred to as the first section MJ 641, the second section NJ 642 and the third section PJ 643. Each of the three terminals 631, 632 and 633 is coupled to a respective power source 611, 612 and 613. The first power source 611 and the second power source 612 are conventional power sources, including but not limited to synchronous generators. The third power source 613 is an unconventional power source, including but not limited to an asynchronous generator, more particularly a type IV wind turbine generator WTG, and is coupled to the third terminal 633 via a first transformer 661 and a second transformer 662. According to an embodiment, the first transformer 661 and the second transformer 662 are omitted.

[0180] The network 600 is simulated in the EMTDC (Electromagnetic Transients including DC) tool. The proposed algorithm has been implemented in a MATLAB script. Figure 5 The method of FIG. 691 (flow chart) has been implemented on a 220 kV 50 Hz network 600, where the line length of each section is as follows: MJ = 80 km, NJ = 40 km, and PJ = 20 km. Tables 691, 692 and 693 illustrate source parameters, line parameters and Type IV WTG parameters, respectively. Figure 7 , Figure 8 and Fig. 9 64 , 642 , and 643 , considering the scenario where the parameters of all three sections MJ 641 , NJ 642 , and PJ 643 are the same and the WTG 613 is at full load.

[0181] Figure 7 The figure shows the results of a graphical simulation of a three-terminal network according to an embodiment of the present disclosure. In particular, Figure 7 Illustration of voltage and current phasors obtained using discrete Fourier transform Figure 8 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0182] refer to Figure 1a )and Figure 5 , a method according to an embodiment of the present disclosure is shown below, wherein it is assumed that an initial guess is not available, that is, the line parameters input to 514 are calculated at 513 using the RL model.

[0183] In the following, the first scenario is considered.

[0184] - Scenario 1: The parameters of all segments MJ 641, NJ 642 and PJ 643 are the same.

[0185] • Step-1: Initial guess calculation 513 .

[0186] Calculate 535Z1 using equation (3) as follows:

[0187]

[0188] • Step-2: Line parameter estimation 514.

[0189] Provide the parameters obtained from step-1 as initial guesses to the least squares iterative method:

[0190] R o =3.6096×10 -5 , X o =3.2365×10 -4 , C o =0.5 act (twenty three)

[0191] v0=[Reak{Z1};Imag{Z1};1.5×Imag(Y1 act )] (twenty four)

[0192] v0=[3.6096×10 -5 ;3.2365×10 -4 ;7.6253×10 -9 ] (25)

[0193] Where v0 represents the initial guess calculated in step 1 above. The unknown vector is estimated using the least squares method as follows:

[0194] v est =[1.8861×10 -5 ;3.263×10 -4 ; 5.0797×10 -9 ] (26)

[0195] Use R1=RR1; The estimated parameters are obtained as follows:

[0196]

[0197] The percentage error for each parameter can be calculated as follows:

[0198]

[0199] Fig. 9 The percentage errors of the parameters calculated based on the method according to the embodiment of the present disclosure are illustrated.

[0200] In the following, the second scenario is considered.

[0201] - Scenario 2: The parameters of MJ 641 and NJ 642 are the same, while the parameters of PJ 643 are different from those of MJ 641 and NJ 642. In particular, the sections 641 and 642 of the main line are considered as overhead lines, while the tap line PJ is considered as an underground cable.

[0202] • Step-1: Initial guess calculation 513. In particular, at 536, line parameters are calculated.

[0203] • Step-2: Line parameter estimation 514.

[0204] The initial guess for the least squares iterative method is provided from the first step as follows: The following R and L in Z1 and Z2 are considered as initial guesses, and C is varied from -50% to +50% of the actual value:

[0205] R10=RE{Z1}, X10=Im{Z1}, B10=ωC10

[0206] R20=RE{Z2}, X20=Im{Z2}, B20=ωC2

[0207] v0=(R10,X1 L0 ,B10,R20,X2 L0 ,B20) T

[0208] Each objective function is divided into real and imaginary parts and then solved using the least squares iterative method. The unknowns in the above nonlinear equations are R1, X1, B1, R2, X2, and B2. Objective Function to (Equation (19) to equation (21)) are used to solve the unknowns. The line parameters are obtained as follows:

[0209] R1=RR1, R2=R2,

[0210] In the following, the following configuration is used for Figure 2 The logical method is to test: 1) a common source at all terminals (e.g. Fig.10 ); 2) Type IV wind farm at terminal P (e.g. Fig.11 ); and 3) a solar power plant at terminal N and a type IV wind farm at terminal P (e.g., Fig.12 ).

[0211] Fig.10A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, the network 1000 includes a power line terminated at respective ends by three terminals busbar M 1031, busbar N 1032, and busbar P 1033. The portions of the power line from point J to the respective three terminals 1031, 1032, and 1033 are referred to as the first section MJ 1041, the second section NJ 1042, and the third section PJ 1043, respectively. Each of the three terminals 1031, 1032, and 1033 is coupled to a respective power source 1011, 1012, and 1013. The first power source 1011, the second power source 1012, and the third power source 1013 are conventional power sources, including but not limited to synchronous generators. Tables 1091 and 1092 illustrate source parameters and line parameters (positive sequence).

[0212] Fig.11 A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, the network 1100 includes a power line terminated by three terminals busbar M 1131, busbar N 1132 and busbar P 1133 at the respective ends. The portions of the power line from point J to the respective three terminals 1131, 1132 and 1133 are respectively referred to as the first section MJ 1141, the second section NJ 1142 and the third section PJ 1143. Each of the three terminals 1131, 1132 and 1133 is coupled to a respective power source 1111, 1112 and 1113. The first power source 1111 and the second power source 1112 are conventional power sources, including but not limited to synchronous generators. The third power source 1113 is an unconventional power source, including but not limited to an asynchronous generator, more particularly a type IV wind turbine generator WTG, and is coupled to the third terminal 1133 via a first transformer 1161 and a second transformer 1162. According to an embodiment, the first transformer 1161 and the second transformer 1162 are omitted. Tables 1191, 1192, and 1193 illustrate source parameters, line parameters (positive sequence), and type IV WTG parameters, respectively.

[0213] Fig.12A diagram of a three-terminal network according to an embodiment of the present disclosure is illustrated. In particular, the network 1200 includes a power line terminated at respective ends by three terminals busbar M 1231, busbar N 1232, and busbar P 1233. The portions of the power line from point J to the respective three terminals 1231, 1232, and 1233 are referred to as the first section MJ 1241, the second section NJ 1242, and the third section PJ 1243, respectively. Each of the three terminals 1231, 1232, and 1233 is coupled to a respective power source 1211, 1212, and 1213. The first power source 1211 is a conventional power source, including, but not limited to, a synchronous generator. The second power source 1212 is an unconventional power source, including, but not limited to, an asynchronous generator, and more particularly a solar power plant. The third power source 1213 is an unconventional power source, including but not limited to an asynchronous generator, more particularly a type IV wind turbine generator WTG, and is coupled to the third terminal 1233 via a first transformer 1261 and a second transformer 1262. According to an embodiment, the first transformer 1261 and the second transformer 1262 are omitted. Tables 1291, 1292, 1293 and 1294 illustrate source parameters, line parameters (positive sequence), type IV WTG parameters and solar power plant parameters, respectively.

[0214] Figures 13 to 15 Shows consideration Fig.11 Simulation results obtained with the network 1100. Fig.13 The figure shows the results of a graphical simulation of a three-terminal network according to an embodiment of the present disclosure. In particular, Fig.13 The voltage and current phasors obtained using discrete Fourier transform are shown. Fig.14 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure. Fig.15 The percentage errors of the parameters calculated based on the method according to the embodiment of the present disclosure are illustrated.

[0215] In the following, for Fig.11 The network 1100 shows a Figure 5 Embodiment of the invention.

[0216] • Step-1: Initial guess calculation 513 .

[0217] Using equation (3), Z1 is calculated as follows:

[0218]

[0219] And use equation (4) to calculate Z2 as follows:

[0220]

[0221] • Step-2: Line parameter estimation 514.

[0222] The parameters obtained from step-1 (R, L) are provided as initial guesses to the least squares iterative method.

[0223] R10=2.2376×10 -5 ,X10=3.2664×10 -4 ,C10=0.5C1 act

[0224] R20=4.246×10 -5 ,X20=8.0114×10 -5 ,C20=0.5C2 act

[0225]

[0226] Estimate the unknown vector using the least squares method.

[0227]

[0228] The estimated parameters are obtained using equation (33) as follows:

[0229]

[0230] The percentage error for each parameter can be calculated as follows:

[0231]

[0232] Fig.15 The percentage errors of the parameters calculated based on the method according to the embodiment of the present disclosure are illustrated.

[0233] Fig.17 and Fig.18 Shows consideration Fig.16 The simulation results are obtained for a network of , where an AG fault occurs at F1 on the PJ section of the line at 25% (5km) from the busbar P, and the fault resistance is 2Ω. According to an embodiment, Fig.16 The network is Fig.10 Network 1000. Fig.17 The figure shows the results of a graphical simulation of a three-terminal network according to an embodiment of the present disclosure. In particular, Fig.17 The voltage and current phasors obtained using discrete Fourier transform are shown. Fig.18 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0234] In the following, for Fig.16 The network shows that the Figure 5 Embodiment of the invention.

[0235] • Step-1: Initial guess calculation 513 .

[0236] Using equation (3), Z1 is calculated as follows:

[0237]

[0238] And use equation (4) to calculate Z2 as follows:

[0239]

[0240] • Step-2: Line parameter estimation 514.

[0241] The parameters obtained from step-1 (R, L) are provided as initial guesses to the least squares iterative method.

[0242] R10=2.1277×10 -5 , X10=3.2640×10 -4 , C10=0.5C1 act

[0243] R20=3.9098×10 -5 , X20=8.3618×10 -5 , C20=0.5C2 act

[0244]

[0245] Estimate the unknown vector using the least squares method.

[0246]

[0247] The estimated parameters are obtained using equation (33) as follows:

[0248]

[0249] The percentage error for each parameter can be calculated as follows:

[0250]

[0251]

[0252] According to an embodiment, an automatic reclosing protection scheme is implemented. According to an embodiment, "Section PJ" is identified as the fault section. According to an embodiment, a corresponding fault loop is executed according to the fault section information, and the fault location is calculated to be 5.01 km away from the bus M. According to an embodiment, for the simulation case, for a 120 km transmission line, the absolute percentage of the fault location error is 0.01%.

[0253] Fig. 20 and Fig.21 Shows consideration Fig.19 The simulation results are obtained for a network of , where an AB fault occurs at F2 on the MJ section of the line at 87.5% (70km) from the busbar M, and the fault resistance is 10Ω. According to an embodiment, Fig.19 The network is Fig.11 network 1100. Fig. 20 The figure shows the results of a graphical simulation of a three-terminal network according to an embodiment of the present disclosure. In particular, Fig. 20 The voltage and current phasors obtained using discrete Fourier transform are shown. Fig.21 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0254] • Step-1: Initial guess calculation 513 .

[0255] Using equation (3), Z1 is calculated as follows:

[0256]

[0257] And use equation (4) to calculate Z2 as follows:

[0258]

[0259] • Step-2: Line parameter estimation 514.

[0260] The parameters obtained from step-1 (R, L) are provided as initial guesses to the least squares iterative method.

[0261] R10=2.1758×10 -5 ,X10=3.2659×10 -4 ,C10=0.5C1 act

[0262] R20=3.9379×10 -5 , X20=7.8460×10 -5 , C20=0.5C2 act

[0263]

[0264] Estimate the unknown vector using the least squares method.

[0265]

[0266] The estimated parameters are obtained using equation (33) as follows:

[0267]

[0268] The percentage error for each parameter can be calculated as follows:

[0269]

[0270]

[0271] According to an embodiment, an automatic reclosing protection scheme is implemented. According to an embodiment, "Section MJ" is identified as the fault section. According to an embodiment, a corresponding fault loop is executed according to the fault section information, and the fault location is calculated to be 69.90 km away from bus M. According to an embodiment, for the simulation case, for a 120 km transmission line, the absolute percentage of the fault location error is 0.01%.

[0272] Fig.23 and Fig.24 Shows consideration Fig. 22 The simulation results are obtained from a network of , where a BCG fault occurs on the NJ section 105 km away from the busbar M, and the fault resistance is 20Ω. According to an embodiment, Fig. 22 The network is Fig.12 network 1200. Fig.23 The figure shows the results of a graphical simulation of a three-terminal network according to an embodiment of the present disclosure. In particular, Fig.23 The voltage and current phasors obtained using discrete Fourier transform are shown. Fig.24 A table illustrating simulation results of a three-terminal network according to an embodiment of the present disclosure.

[0273] • Step-1: Initial guess calculation 513 .

[0274] Using equation (7.3.3) Z1 is calculated as follows:

[0275]

[0276] Using equation (7.3.4) Z2 is calculated as follows:

[0277]

[0278] • Step-2: Line parameter estimation 514.

[0279] The parameters obtained from step-1 (R, L) are provided as initial guesses to the least squares iterative method.

[0280] R10=1.5150×10 -5 , X10=3.2736×10 -4 , C10=0.5C1 act

[0281] R20=3.9465×10 -5, X20=8.7023×10 -5 , C20=0.5C2 act

[0282] Estimate the unknown vector using the least squares method.

[0283]

[0284] The estimated parameters are obtained using equation (33) as follows:

[0285]

[0286] The percentage error for each parameter can be calculated as follows:

[0287]

[0288]

[0289] According to an embodiment, an automatic reclosing protection scheme is implemented. According to an embodiment, "Section NJ" is identified as a fault section. According to an embodiment, a corresponding fault loop is executed according to the fault section information, and the fault location is calculated to be 105.08 km away from bus M. According to an embodiment, for the simulation case, for a 120 km transmission line, the absolute percentage of the fault location error is 0.08%.

[0290] Although various embodiments of the present disclosure have been described above, it should be understood that these embodiments are presented only by way of example rather than by way of limitation. Similarly, various figures may depict example architectures or configurations, which are provided to enable those of ordinary skill in the art to understand the exemplary features and functions of the present disclosure. However, those of ordinary skill in the art will appreciate that the present disclosure is not limited to the illustrated example architectures or configurations, but may be implemented using various alternative architectures and configurations. In addition, as will be appreciated by those of ordinary skill in the art, one or more features of an embodiment may be combined with one or more features of another embodiment described herein. Therefore, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments.

[0291] It should also be understood that any reference to an element using names such as "first," "second," etc. herein does not generally limit the number or order of those elements. Rather, these names may be used herein as a convenient way to distinguish between two or more elements or element instances. Thus, reference to a first and a second element does not mean that only two elements can be used, or that the first element must precede the second element in some manner.

[0292] In addition, those of ordinary skill in the art will appreciate that information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, and symbols (such as may be mentioned in the above description) may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0293] Those of skill will further understand that any of the various illustrative logical blocks, units, processors, devices, circuits, methods, and functions described in conjunction with the aspects disclosed herein may be implemented by electronic hardware (e.g., digital implementations, analog implementations, or a combination of the two), firmware, various forms of programs or design codes containing instructions (which, for convenience, may be referred to herein as "software" or "software units"), or any combination of these technologies.

[0294] In order to clearly illustrate this interchangeability of hardware, firmware and software, various illustrative components, blocks, units, circuits and steps have been described above generally in terms of their functions. Whether such functions are implemented as hardware, firmware or software, or the combination of these technologies depends on the specific application and design constraints imposed on the overall system. The technician can implement the described functions in various ways for each specific application, but such implementation decision will not lead to deviation from the scope of this disclosure. According to various embodiments, processors, devices, components, circuits, structures, machines, units, etc. can be configured to perform one or more functions described herein. The term "configured to" or "configured for" used herein with respect to a specified operation or function refers to a processor, device, component, circuit, structure, machine, unit, etc. that is physically constructed, programmed and / or arranged to perform a specified operation or function.

[0295] In addition, the technician will understand that the various illustrative methods, logic blocks, units, devices, components and circuits described herein can be implemented or performed in an integrated circuit (IC) that can include a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device or any combination thereof. The logic blocks, units and circuits may further include antennas and / or transceivers to communicate with various components within the network or within the device. The general-purpose processor can be a microprocessor, but in an alternative, the processor can be any traditional processor, controller or state machine. The processor can also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors combined with a DSP core, or any other suitable configuration to perform the functions described herein. If implemented in software, these functions can be stored as one or more instructions or codes on a computer-readable medium. Therefore, the steps of the method or algorithm disclosed herein can be implemented as software stored on a computer-readable medium.

[0296] Computer-readable media include both computer storage media and communication media, including any medium capable of transferring a computer program or code from one place to another. Storage media can be any available medium that a computer can access. By way of example and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, or any other medium that can be used to store the desired program code in the form of instructions or data structures and can be accessed by a computer.

[0297] In addition, memory or other storage devices and communication components can be used in embodiments of the present disclosure. It should be appreciated that, for the sake of clarity, the above description has described embodiments of the present disclosure with reference to different functional units and processors. However, it is apparent that any suitable functional distribution between different functional units, processing logic elements or domains can be used without departing from the present disclosure. For example, the functions illustrated as being performed by a separate processing logic element or controller can be performed by the same processing logic element or controller. Therefore, references to specific functional units are only references to suitable devices for providing the described functions, rather than representing a strict logical or physical structure or organization.

[0298] Various modifications to the embodiments described in this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the embodiments shown herein, but is intended to be consistent with the maximum scope consistent with the novel features and principles disclosed in the appended claims.

Claims

1. A method for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the method comprising: obtaining measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising a respective section, the respective section being a portion of the power line starting from a location on the power line to the respective end, wherein the measurement result is measured before the failure occurs, and wherein the electrical parameters of at least one of the corresponding sections are different from the electrical parameters of the other corresponding sections; obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line; determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and The at least one network parameter is provided to a device configured to control, monitor and / or analyze the network.

2. The method of claim 1, wherein: Obtaining the at least one input parameter of the network model comprises or determines the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and another network model, wherein the further network model is different from the network model used to determine the at least one network parameter, and Therein, the network model includes at least one more electrical parameter than the other network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, wherein the line capacitance couples the one of the corresponding sections to an electrical ground potential.

3. The method of claim 2, wherein: The at least one input parameter of the network model is determined by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model, and / or wherein the at least one network parameter is determined by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the other network model.

4. The method according to any one of claims 1 to 3, further comprising: determining a faulty section based on the at least one input parameter of the network model; as well as Based on the determined fault section, power equipment, in particular an automatic reclosing device for the power line, is controlled.

5. The method of claim 4, further comprising: estimating the fault location in response to the control, in particular when the power device is operated in a first operating mode, based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault; as well as The at least one network parameter is provided to the device configured to control, monitor and / or analyze the network.

6. A device for determining at least one network parameter of a network, the network comprising a power line terminated by at least three terminals, the device comprising a processor, the processor being configured to: obtaining measurement results of the at least three terminals terminating the power line at respective ends of the power line, the power line comprising a respective section, the respective section being a portion of the power line starting from a location on the power line to the respective end, in, The measurements are taken before the failure occurs, and wherein the electrical parameters of at least one of the corresponding sections are different from the electrical parameters of the other corresponding sections; obtaining at least one input parameter of a network model of the network based on the obtained measurement results of the at least three terminals, wherein the at least one input parameter of the network model is an electrical parameter of the network model, in particular an impedance of one of the respective sections of the power line; determining the at least one network parameter based on the at least one input parameter of the network model and the network model; and The at least one network parameter is provided to a device configured to control, monitor and / or analyze the network.

7. The device of claim 6, wherein: The processor is configured to obtain the at least one input parameter of the network model by determining the at least one input parameter of the network model based on the obtained measurement results of the at least three terminals and a further network model, wherein the further network model is different from the network model used to determine the at least one network parameter, and Therein, the network model includes at least one more electrical parameter than the other network model, in particular a propagation constant of one of the corresponding sections of the power line or a line capacitance of one of the corresponding sections of the power line, wherein the line capacitance couples the one of the corresponding sections to an electrical ground potential.

8. The device of claim 7, wherein: The processor is configured to determine at least one input parameter of the network model by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the further network model, and / or the processor is configured to determine at least one network parameter by adapting to the differences in electrical parameters between corresponding sections of the power line modeled in the further network model.

9. The apparatus as claimed in any one of claims 6 to 8, wherein: The processor is further configured to: determining a faulty section based on the at least one input parameter of the network model; and Based on the determined fault section, power equipment, in particular an automatic reclosing device for the power line, is controlled.

10. The device of claim 9, wherein: The processor is further configured to: estimating the fault location in response to the control, in particular when the power device is operated in a first operating mode, based on the determined fault section, at least one electrical parameter of the network model, and in particular voltage and current fault phasors measured during the fault; as well as The at least one network parameter is provided to the device configured to control, monitor and / or analyze the network.

11. A computer readable medium for determining at least one network parameter of a network comprising a power line terminated by at least three terminals, the computer readable medium carrying instructions for executing the method of any one of claims 1 to 5.

12. A system comprising a network and a device as claimed in any one of claims 6 to 10, the network comprising power lines terminated by at least three terminals.

13. System according to claim 12, further comprising power equipment, in particular an automatic recloser for the power line.

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