# US 11,451,042 B2 · Method for identifying a fault event in an electric power distribution grid sector > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,451,042 B2 - Document ID: US11451042B2 - Status: Granted - Kind: B2 - Application number: 15/961,180 - Filed: 2018-04-24 - Published: 2018-11-01 - Granted: 2022-09-20 - Earliest claimed: 2017-04-26 - Assignees: ABB AB - Applicants: ABB S.p.A. - Inventors: Enrico Ragaini; Daniele Angelosante; Lorenzo Fagiano - Web page: https://patentgrep.com/patent/US11451042B2 ## CPC - H02H 1/0092: {concerning the data processing means, e.g. expert systems, neural networks} - G01R 19/16528: {using digital techniques or performing arithmetic operations (using digital techniques to measure a voltage or a current, see G01R19/25)} - G01R 31/086: {in power transmission or distribution networks, i.e. with interconnected conductors} - H02H 1/043: {to inrush currents (H02H1/046 takes precedence; differential protection of transformers H02H7/045)} - H02H 3/083: {for three-phase systems} - H02H 7/26: Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured (locating faults in cables G01R31/08) - H02H: EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS (indicating or signalling undesired working conditions G01R, e.g. G01R31/00, G08B; locating faults along lines G01R31/08; emergency protective devices H01H) - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) ## Abstract A method for identifying a fault event in an electric power distribution grid sector including one or more electric loads and having a coupling node with a main grid, at which a grid current adsorbed by said electric loads is detectable. The method allows determining whether a detected anomalous variation of the grid current, adsorbed at the electric coupling node, is due to the start of a characteristic transitional operating period of an electric load or is due to an electric fault. ## Claims ### Claim 1 A method for identifying a fault event in an electric power distribution grid sector, said grid sector including one or more electric loads and having a coupling node with a main grid, at which a grid current of said grid sector is detectable, said method comprising: acquiring, for each electric phase, first data values indicative of said grid current, said first data values being acquired at subsequent sampling instants subdivided in a sequence of time windows; processing a first portion of said first data values acquired, for each electric phase, at first sampling instants at least partially included in a time window and a second portion of said first data values acquired, for each electric phase, at second sampling instants preceding said first sampling instants and at least partially included in a previous time window preceding said time window to check whether said grid current, at said time window, is subject to an anomalous variation with respect to said previous time window; if it is determined that said grid current is not subject to an anomalous variation with respect to said previous time window, repeating said processing said first portion of said first data values for subsequent sampling instants; if it is determined that said grid current, starting from an event instant of said time window, is subject to an anomalous variation with respect to said previous time window, processing a third portion of one or more of said first data values acquired, for each electric phase, at sampling instants following said event instant to calculate, for each electric phase, second data values indicative of the anomalous variation of said grid current; processing said second data values calculated for each electric phase to check whether the anomalous variation of said grid current is due to a characteristic transitional operating period of an electric load of said grid sector; processing said second data values calculated for each electric phase to calculate third data values indicative of the anomalous variation of said grid current; for each electric load, selecting second reference data values indicative of a predicted current absorbed by said electric load during a characteristic transitional operating period of said electric load; for each electric load, processing said third data values and said second reference data values to calculate an error value indicative of a difference between the anomalous variation of said grid current and the predicted current absorbed by said electric load during said characteristic transitional operating period; selecting a minimum error value among the error values calculated for said electric loads; comparing said minimum error value with a second threshold value; repeating the previous steps for a second number of sampling instants following said event instant; and checking whether said minimum error value exceeds said second threshold value for said second number of sampling instants. ### Claim 2 (depends on 1) The method, according to claim 1, wherein said processing said first portion of said first data values further comprises the following: for each electric phase of said grid sector, executing the following steps: selecting a first vector of said first portion of said first data values acquired at said first sampling instants; selecting a second vector of said second portion of said first data values acquired at said second sampling instants; processing said first and second vectors to calculate a phase current variation value indicative of a variation in a phase current of said grid current with respect to said previous time window; processing the phase current variation values calculated for each electric phase to calculate an overall current variation value indicative of an overall variation of said grid current with respect to said previous time window; comparing said overall current variation value with a first threshold value; repeating the previous steps for a first number of sampling instants included in said time window; and checking whether said overall current variation value exceeds said first threshold value for said first number of sampling instants. ### Claim 3 (depends on 1) The method, according to claim 1, wherein said starting from said event instant of said time window comprises the following: for each electric phase, selecting a first data set of said third portion of said first data values acquired at sampling instants following said event instant; selecting a second data set of first reference data values indicative of a background condition of said grid current; and processing said first and second data sets of data values to calculate a third data set of said second data values. ### Claim 4 (depends on 3) The method, according to claim 3, wherein said reference data values are a fourth portion of said first data values acquired at one or more sampling instants preceding said event instant. ### Claim 5 (depends on 4) The method, according to claim 4, wherein said reference data values are a fourth portion of said first data values acquired at the previous time window preceding said event instant. ### Claim 6 (depends on 1) The method, according to claim 1, wherein said second reference data values are calculated by simulating behavior of each electric load using a time-discrete model describing the operation of said electric load during said characteristic transitional operating period. ### Claim 7 (depends on 6) The method, according to claim 6, wherein said time-discrete model is calculated by performing a modelling procedure that comprises the following steps: activating an electric load of said one or more electric loads of said grid sector; deactivating remaining electric loads of said one or more electric loads of said grid sector; acquiring detection data indicative of an operating voltage and of a predicted current of said electric load during said characteristic transitional operating period of said electric load; and processing said detection data to estimate one or more actual electrical and/or mechanical parameters of said electric load to be used in said time-discrete model. ### Claim 8 (depends on 7) The method, according to claim 7, wherein said actual electrical and mechanical parameters of said electric load are estimated by solving a non-linear least squares (NLS) problem based on one or more installation constraints provided for said electric load. ### Claim 9 (depends on 1) The method, according to claim 1, wherein said electric loads are formed by electric rotating machines or groups of electric rotating machines, the characteristic transitional operating period of said electric loads being a start-up phase of said electric rotating machines or groups of electric rotating machines. ### Claim 10 A non-transitory computer readable medium containing computer instructions stored therein for causing a computer processor to: acquire, for each electric phase, first data values indicative of a grid current, said first data values being acquired at subsequent sampling instants subdivided in a sequence of time windows; process a first portion of said first data values acquired, for each electric phase, at first sampling instants at least partially included in a time window and a second portion of said first data values acquired, for each electric phase, at second sampling instants preceding said first sampling instants and at least partially included in a previous time window preceding said time window to check whether said grid current, at said time window, is subject to an anomalous variation with respect to said previous time window; if it is determined that said grid current is not subject to an anomalous variation with respect to said previous time window, repeat said processing said first portion of said first data values for subsequent sampling instants; if it is determined that said grid current, starting from an event instant of said time window, is subject to an anomalous variation with respect to said previous time window, process a third portion of one or more of said first data values acquired, for each electric phase, at sampling instants following said event instant to calculate, for each electric phase, second data values indicative of the anomalous variation of said grid current; process said second data values calculated for each electric phase to check whether the anomalous variation of said grid current is due to a characteristic transitional operating period of an electric load of a grid sector of a main grid; process said second data values calculated for each electric phase to calculate third data values indicative of the anomalous variation of said grid current; for each electric load, select second reference data values indicative of a predicted current absorbed by said electric load during a characteristic transitional operating period of said electric load; for each electric load, process said third data values and said second reference data values to calculate an error value indicative of a difference between the anomalous variation of said grid current and the predicted current absorbed by said electric load during said characteristic transitional operating period; select a minimum error value among the error values calculated for said electric loads; compare said minimum error value with a second threshold value; repeat the previous steps for a second number of sampling instants following said event instant; and check whether said minimum error value exceeds said second threshold value for said second number of sampling instants. ### Claim 11 A computerized device for operating a switching device comprising: a processor; and a memory device including instructions configured to be executable by the processor effective to: acquire, for each electric phase, first data values indicative of a grid current, said first data values being acquired at subsequent sampling instants subdivided in a sequence of time windows; process a first portion of said first data values acquired, for each electric phase, at first sampling instants at least partially included in a time window and a second portion of said first data values acquired, for each electric phase, at second sampling instants preceding said first sampling instants and at least partially included in a previous time window preceding said time window to check whether said grid current, at said time window, is subject to an anomalous variation with respect to said previous time window; if it is determined that said grid current is not subject to an anomalous variation with respect to said previous time window, repeat said processing said first portion of said first data values for subsequent sampling instants; if it is determined that said grid current, starting from an event instant of said time window, is subject to an anomalous variation with respect to said previous time window, process a third portion of one or more of said first data values acquired, for each electric phase, at sampling instants following said event instant to calculate, for each electric phase, second data values indicative of the anomalous variation of said grid current; process said second data values calculated for each electric phase to check whether the anomalous variation of said grid current is due to a characteristic transitional operating period of an electric load of a grid sector of a main grid; process said second data values calculated for each electric phase to calculate third data values indicative of the anomalous variation of said grid current; for each electric load, select second reference data values indicative of a predicted current absorbed by said electric load during a characteristic transitional operating period of said electric load; for each electric load, process said third data values and said second reference data values to calculate an error value indicative of a difference between the anomalous variation of said grid current and the predicted current absorbed by said electric load during said characteristic transitional operating period; select a minimum error value among the error values calculated for said electric loads; compare said minimum error value with a second threshold value; repeat the previous steps for a second number of sampling instants following said event instant; and check whether said minimum error value exceeds said second threshold value for said second number of sampling instants. ### Claim 12 An electronic protection system comprising: a switching device; a processor; and a memory device including instructions configured to be executable by the processor effective to: acquire, for each electric phase, first data values indicative of a grid current, said first data values being acquired at subsequent sampling instants subdivided in a sequence of time windows; process a first portion of said first data values acquired, for each electric phase, at first sampling instants at least partially included in a time window and a second portion of said first data values acquired, for each electric phase, at second sampling instants preceding said first sampling instants and at least partially included in a previous time window preceding said time window to check whether said grid current, at said time window, is subject to an anomalous variation with respect to said previous time window; if it is determined that said grid current is not subject to an anomalous variation with respect to said previous time window, repeat said processing said first portion of said first data values for subsequent sampling instants; if it is determined that said grid current, starting from an event instant of said time window, is subject to an anomalous variation with respect to said previous time window, process a third portion of one or more of said first data values acquired, for each electric phase, at sampling instants following said event instant to calculate, for each electric phase, second data values indicative of the anomalous variation of said grid current; process said second data values calculated for each electric phase to check whether the anomalous variation of said grid current is due to a characteristic transitional operating period of an electric load of a grid sector of a main grid; process said second data values calculated for each electric phase to calculate third data values indicative of the anomalous variation of said grid current; for each electric load, select second reference data values indicative of a predicted current absorbed by said electric load during a characteristic transitional operating period of said electric load; for each electric load, process said third data values and said second reference data values to calculate an error value indicative of a difference between the anomalous variation of said grid current and the predicted current absorbed by said electric load during said characteristic transitional operating period; select a minimum error value among the error values calculated for said electric loads; compare said minimum error value with a second threshold value; repeat the previous steps for a second number of sampling instants following said event instant; and check whether said minimum error value exceeds said second threshold value for said second number of sampling instants. ### Claim 13 (depends on 11) The computerized device, according to claim 11, wherein the computerized device is a controller for an electric power distribution grid. ### Claim 14 (depends on 2) The method, according to claim 2, wherein said starting from said event instant of said time window comprises the following: for each electric phase: selecting a first data set of said third portion of said first data values acquired at sampling instants following said event instant; selecting a second data set of first reference data values indicative of a background condition of said grid current; and processing said first and second data sets of data values to calculate a third data set of said second data values. ### Claim 15 (depends on 14) The method, according to claim 14, wherein said reference data values are a fourth portion of said first data values acquired at one or more sampling instants preceding said event instant. ### Claim 16 (depends on 15) The method, according to claim 15, wherein said reference data values are a fourth portion of said first data values acquired at the previous time window preceding said event instant. ### Claim 17 (depends on 2) The method, according to claim 2, wherein said electric loads are formed by electric rotating machines or groups of electric rotating machines, the characteristic transitional operating period of said electric loads being a start-up phase of said electric rotating machines or groups of electric rotating machines.