The Experts below are selected from a list of 186 Experts worldwide ranked by ideXlab platform

R. H. Steinberg - One of the best experts on this subject based on the ideXlab platform.

Ron P. Gallemore - One of the best experts on this subject based on the ideXlab platform.

George Michailidis - One of the best experts on this subject based on the ideXlab platform.

  • CDC - A decentralized ID algorithm for detecting slow-Fast Oscillations in power systems from overwhelming volumes of phasor data
    2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
    Co-Authors: Aranya Chakrabortty, George Michailidis
    Abstract:

    As the number of sensors, namely Phasor Measurement Units or PMUs, in the US power transmission grid scales up into the thousands within the next few years, the current state-of-the-art centralized data processing architecture will no longer be sustainable, and decentralized algorithms must be developed instead. In this paper we propose such an algorithm for one of the most critical applications in power system monitoring- namely, modal decomposition of swing dynamics for detecting slow and Fast Oscillation modes in the system with evaluation of their respective damping factors. Given a multiple set of coherent generation clusters in the system, we first use data from all PMU sources to calculate the oscillatory modes, their damping and participation in a centralized fashion. Next, we categorize the PMUs into several disjoint sets, and use the data from each of these sets to evaluate the modal frequencies for the entire system individually, assuming that the network has a connected topology guaranteeing system observability. A global estimate for any specific eigenvalue of interest is then computed from the geometric mean of those obtained from the disjoint estimation, and analytical expressions are derived to indicate how this geometric mean, representing the ‘fused distributed solution’ compares to the centralized solution. A discussion on how the output nodes in the network should be chosen appropriately contingent on the topological structure of the network, in order to minimize the error between the two estimates is also presented. We illustrate our results with prototype power system network models inspired by two well-known transfer paths in the US west coast grid.

  • A decentralized ID algorithm for detecting slow-Fast Oscillations in power systems from overwhelming volumes of phasor data
    2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
    Co-Authors: Aranya Chakrabortty, George Michailidis
    Abstract:

    As the number of sensors, namely Phasor Measurement Units or PMUs, in the US power transmission grid scales up into the thousands within the next few years, the current state-of-the-art centralized data processing architecture will no longer be sustainable, and decentralized algorithms must be developed instead. In this paper we propose such an algorithm for one of the most critical applications in power system monitoring- namely, modal decomposition of swing dynamics for detecting slow and Fast Oscillation modes in the system with evaluation of their respective damping factors. Given a multiple set of coherent generation clusters in the system, we first use data from all PMU sources to calculate the oscillatory modes, their damping and participation in a centralized fashion. Next, we categorize the PMUs into several disjoint sets, and use the data from each of these sets to evaluate the modal frequencies for the entire system individually, assuming that the network has a connected topology guaranteeing system observability. A global estimate for any specific eigenvalue of interest is then computed from the geometric mean of those obtained from the disjoint estimation, and analytical expressions are derived to indicate how this geometric mean, representing the `fused distributed solution' compares to the centralized solution. A discussion on how the output nodes in the network should be chosen appropriately contingent on the topological structure of the network, in order to minimize the error between the two estimates is also presented. We illustrate our results with prototype power system network models inspired by two well-known transfer paths in the US west coast grid.

Anthony J Adams - One of the best experts on this subject based on the ideXlab platform.

  • the Fast Oscillation of the eog in diabetes with and without mild retinopathy
    Documenta Ophthalmologica, 2008
    Co-Authors: Marilyn E Schneck, Leslie Shupenko, Anthony J Adams
    Abstract:

    There is ample evidence that the retinal pigment epithelium (RPE) is affected in diabetes, and that epitheliopathy may be among the early changes. The Fast Oscillation (FO) of the electro-oculogram (EOG) reflects the activity of the RPE, most notably the mechanisms responsible for pumping fluid and ions in the retina-to-choroid direction. The FO was measured in three groups of subjects: normal controls, eyes of diabetic individuals with no evidence of retinopathy, and eyes of diabetics with mild background retinopathy. FO amplitude, light trough voltage and dark peak voltage in both diabetic groups were all significantly reduced, independent of retinopathy status. The peak to trough ratio was unaffected. These changes, reduced voltages and smaller light-evoked voltage changes, are consistent with a decrease in the resistance of the RPE and may relate to accumulation of fluid in the sub-retinal space.

  • the Fast Oscillation of the electrooculogram reveals sensitivity of the human outer retina retinal pigment epithelium to glucose level
    Vision Research, 2000
    Co-Authors: Marilyn E Schneck, Brad Fortune, Anthony J Adams
    Abstract:

    Abstract The effect of acute blood glucose elevations on human outer retinal function was examined. Electrooculograms were recorded as the background light cycled on/off with a 2-min period, eliciting rapid changes in the corneo-retinal standing potential known as the Fast-Oscillation of the electrooculogram. Recordings were made while subjects Fasted and after they consumed 100 g of d -glucose. In all subjects, blood glucose levels strongly affected Fast Oscillation amplitude, which reflects photoreceptor-driven changes in RPE cell chloride concentration. The sensitivity of RPE metabolism to glucose fluctuations may relate to changes in the blood-retinal barrier that are known to occur in diabetes (e.g. macular edema).

  • The Fast Oscillation of the electrooculogram reveals sensitivity of the human outer retina/retinal pigment epithelium to glucose level
    Vision Research, 2000
    Co-Authors: Marilyn E Schneck, Brad Fortune, Anthony J Adams
    Abstract:

    Abstract The effect of acute blood glucose elevations on human outer retinal function was examined. Electrooculograms were recorded as the background light cycled on/off with a 2-min period, eliciting rapid changes in the corneo-retinal standing potential known as the Fast-Oscillation of the electrooculogram. Recordings were made while subjects Fasted and after they consumed 100 g of d -glucose. In all subjects, blood glucose levels strongly affected Fast Oscillation amplitude, which reflects photoreceptor-driven changes in RPE cell chloride concentration. The sensitivity of RPE metabolism to glucose fluctuations may relate to changes in the blood-retinal barrier that are known to occur in diabetes (e.g. macular edema).

Aranya Chakrabortty - One of the best experts on this subject based on the ideXlab platform.

  • CDC - A decentralized ID algorithm for detecting slow-Fast Oscillations in power systems from overwhelming volumes of phasor data
    2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
    Co-Authors: Aranya Chakrabortty, George Michailidis
    Abstract:

    As the number of sensors, namely Phasor Measurement Units or PMUs, in the US power transmission grid scales up into the thousands within the next few years, the current state-of-the-art centralized data processing architecture will no longer be sustainable, and decentralized algorithms must be developed instead. In this paper we propose such an algorithm for one of the most critical applications in power system monitoring- namely, modal decomposition of swing dynamics for detecting slow and Fast Oscillation modes in the system with evaluation of their respective damping factors. Given a multiple set of coherent generation clusters in the system, we first use data from all PMU sources to calculate the oscillatory modes, their damping and participation in a centralized fashion. Next, we categorize the PMUs into several disjoint sets, and use the data from each of these sets to evaluate the modal frequencies for the entire system individually, assuming that the network has a connected topology guaranteeing system observability. A global estimate for any specific eigenvalue of interest is then computed from the geometric mean of those obtained from the disjoint estimation, and analytical expressions are derived to indicate how this geometric mean, representing the ‘fused distributed solution’ compares to the centralized solution. A discussion on how the output nodes in the network should be chosen appropriately contingent on the topological structure of the network, in order to minimize the error between the two estimates is also presented. We illustrate our results with prototype power system network models inspired by two well-known transfer paths in the US west coast grid.

  • A decentralized ID algorithm for detecting slow-Fast Oscillations in power systems from overwhelming volumes of phasor data
    2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
    Co-Authors: Aranya Chakrabortty, George Michailidis
    Abstract:

    As the number of sensors, namely Phasor Measurement Units or PMUs, in the US power transmission grid scales up into the thousands within the next few years, the current state-of-the-art centralized data processing architecture will no longer be sustainable, and decentralized algorithms must be developed instead. In this paper we propose such an algorithm for one of the most critical applications in power system monitoring- namely, modal decomposition of swing dynamics for detecting slow and Fast Oscillation modes in the system with evaluation of their respective damping factors. Given a multiple set of coherent generation clusters in the system, we first use data from all PMU sources to calculate the oscillatory modes, their damping and participation in a centralized fashion. Next, we categorize the PMUs into several disjoint sets, and use the data from each of these sets to evaluate the modal frequencies for the entire system individually, assuming that the network has a connected topology guaranteeing system observability. A global estimate for any specific eigenvalue of interest is then computed from the geometric mean of those obtained from the disjoint estimation, and analytical expressions are derived to indicate how this geometric mean, representing the `fused distributed solution' compares to the centralized solution. A discussion on how the output nodes in the network should be chosen appropriately contingent on the topological structure of the network, in order to minimize the error between the two estimates is also presented. We illustrate our results with prototype power system network models inspired by two well-known transfer paths in the US west coast grid.