Generator dynamic model parameter estimation and tuning using online data and subspace state space model
First Claim
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1. A system for optimizing generator parameters comprising:
- at least one generator;
an online dynamic generator parameter estimation and tuning system, comprising;
a server including an identification and tuning engine, wherein the server is in communication with;
an online data acquisition network comprising one or more sensors;
a user console; and
a database comprising one or more generator models associated with one or more generators,wherein a processor of the identification and tuning engine selectively executes steps stored in non-transitory memory, such that the processor operably;
receives monitoring data from the data acquisition network;
determines whether a user-defined event has occurred;
identifies current parameters associated with the user-defined event for inclusion in an execution of the one or more generator models, to create a current model;
tunes the current parameters, after estimation, for the one or more generator models while the generator is online, based on a comparison of the current parameters and current model with a predefined deviation threshold;
generate and send an output to the user console to validate and update one or more generator model based on the comparison of the current parameters and the current model with a predefined deviation; and
wherein at least one generator'"'"'s parameters are modified by analyzing them with the output generated by the online dynamic generator parameter estimation and tuning system and ensuring minimum deviation between the generator'"'"'s parameters and the output.
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Abstract
Generator dynamic model parameter estimation and tuning using online data and subspace state space models are disclosed. According to one embodiment, a system comprises a sensor, a data acquisition network in communication with the sensor; a user console and an identification and tuning engine in communication with the data acquisition network, the user console, and a database. The database comprises one or more generator models, and the identification and tuning engine identifies and tunes parameters associated with a selected generator model.
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Citations
13 Claims
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1. A system for optimizing generator parameters comprising:
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at least one generator; an online dynamic generator parameter estimation and tuning system, comprising; a server including an identification and tuning engine, wherein the server is in communication with; an online data acquisition network comprising one or more sensors; a user console; and a database comprising one or more generator models associated with one or more generators, wherein a processor of the identification and tuning engine selectively executes steps stored in non-transitory memory, such that the processor operably; receives monitoring data from the data acquisition network; determines whether a user-defined event has occurred; identifies current parameters associated with the user-defined event for inclusion in an execution of the one or more generator models, to create a current model; tunes the current parameters, after estimation, for the one or more generator models while the generator is online, based on a comparison of the current parameters and current model with a predefined deviation threshold; generate and send an output to the user console to validate and update one or more generator model based on the comparison of the current parameters and the current model with a predefined deviation; and wherein at least one generator'"'"'s parameters are modified by analyzing them with the output generated by the online dynamic generator parameter estimation and tuning system and ensuring minimum deviation between the generator'"'"'s parameters and the output. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer implemented method of optimizing at least one generator'"'"'s parameters, comprising:
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instructions, stored in non-transitory computer readable memory that, when executed by a processor, perform the steps of; upon receiving online monitoring data from at least one network connected sensor, identifying if the monitoring data indicates that a user-defined event has occurred, and if so, whether the monitoring data comprises bad data before rejecting or filtering the bad data from good data; identifying and tuning current model parameters while online for a received machine model from a network connected database, including model controls, for inclusion of the good data in an execution of the machine model; comparing the identified and tuned current model parameters associated with the good data to a predefined deviation threshold; based on the comparing, selecting one option between; (a) the identified and tuned current parameters associated with the good data, or (b) the identified and tuned parameters associated with a previous event; and based on the selecting, modifying at least one generator'"'"'s parameters to ensure minimum deviation between the selected option and the generator'"'"'s parameters. - View Dependent Claims (9, 10, 11, 12, 13)
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Specification