This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is... more
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is represented at the substation level, in order to include the circuit breakers suspected of being erroneously modeled. The detection of topology errors relies on tests performed on the normalized residuals associated with information about the status of those circuit breakers. A hypothesis testing procedure is then employed to identify the correct switching branch status, where each possible combination of suspect status compose a distinct alternative hypothesis. The hypothesis which receives the largest support from the measurement set is determined through an application of Bayes' theorem, which provides the conditional a posteriori probability for each alternative hypothesis. Subnetworks of the IEEE 14-bus and 30-bus test systems are used to evaluate the performance of the proposed methodology
Research Interests:
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is... more
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is represented at the substation level, in order to include the circuit breakers suspected of being erroneously modeled. The detection of topology errors relies on tests performed on the normalized residuals associated with information about the status of those circuit breakers. A hypothesis testing procedure is then employed to identify the correct switching branch status, where each possible combination of suspect status compose a distinct alternative hypothesis. The hypothesis which receives the largest support from the measurement set is determined through an application of Bayes' theorem, which provides the conditional a posteriori probability for each alternative hypothesis. Subnetworks of the IEEE 14-bus and 30-bus test systems are used to evaluate the performance of the proposed methodology
Research Interests:
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is... more
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is represented at the substation level, in order to include the circuit breakers suspected of being erroneously modeled. The detection of topology errors relies on tests performed on the normalized residuals associated with information about the status of those circuit breakers. A hypothesis testing procedure is then employed to identify the correct switching branch status, where each possible combination of suspect status compose a distinct alternative hypothesis. The hypothesis which receives the largest support from the measurement set is determined through an application of Bayes' theorem, which provides the conditional a posteriori probability for each alternative hypothesis. Subnetworks of the IEEE 14-bus and 30-bus test systems are used to evaluate the performance of the proposed methodology
Research Interests:
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is... more
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is represented at the substation level, in order to include the circuit breakers suspected of being erroneously modeled. The detection of topology errors relies on tests performed on the normalized residuals associated with information about the status of those circuit breakers. A hypothesis testing procedure is then employed to identify the correct switching branch status, where each possible combination of suspect status compose a distinct alternative hypothesis. The hypothesis which receives the largest support from the measurement set is determined through an application of Bayes' theorem, which provides the conditional a posteriori probability for each alternative hypothesis. Subnetworks of the IEEE 14-bus and 30-bus test systems are used to evaluate the performance of the proposed methodology
Research Interests:
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is... more
This paper proposes a method for topology error detection and identification to be used in connection with orthogonal state estimators based on Givens rotations without square roots. The relevant portion of the electric network is represented at the substation level, in order to include the circuit breakers suspected of being erroneously modeled. The detection of topology errors relies on tests performed on the normalized residuals associated with information about the status of those circuit breakers. A hypothesis testing procedure is then employed to identify the correct switching branch status, where each possible combination of suspect status compose a distinct alternative hypothesis. The hypothesis which receives the largest support from the measurement set is determined through an application of Bayes' theorem, which provides the conditional a posteriori probability for each alternative hypothesis. Subnetworks of the IEEE 14-bus and 30-bus test systems are used to evaluate the performance of the proposed methodology