Matching Items (2)
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
Description
The utilization of power cables is increasing with the development of renewable energy and the maintenance replacement of old overhead power lines. Therefore, effective monitoring and accurate fault location for power cables are very important for the sake of a stable power supply.
The recent technologies for power cable diagnosis and temperature monitoring system are described including their intrinsic limitations for cable health assessment. Power cable fault location methods are reviewed with two main categories: off-line and on-line data based methods.
As a diagnostic and fault location approach, a new passive methodology is introduced. This methodology is based on analyzing the resonant frequencies of the transfer function between the input and output of the power cable system. The equivalent pi model is applied to the resonant frequency calculation for the selected underground power cable transmission system.
The characteristics of the resonant frequencies are studied by analytical derivations and PSCAD simulations. It is found that the variation of load magnitudes and change of positive power factors (i.e., inductive loads) do not affect resonant frequencies significantly, but there is considerable movement of resonant frequencies under change of negative power factors (i.e., capacitive loads).
Power cable fault conditions introduce new resonant frequencies in accordance with fault positions. Similar behaviors of the resonant frequencies are shown in a transformer (TR) connected power cable system with frequency shifts caused by the TR impedance.
The resonant frequencies can be extracted by frequency analysis of power signals and the inherent noise in these signals plays a key role to measure the resonant frequencies. Window functions provide an effective tool for improving resonant frequency discernment. The frequency analysis is implemented on noise laden PSCAD simulation signals and it reveals identical resonant frequency characteristics with theoretical studies.
Finally, the noise levels of real voltage and current signals, which are acquired from an operating power plant, are estimated and the resonant frequencies are extracted by applying window functions, and these results prove that the resonant frequency can be used as an assessment for the internal changes in power cable parameters such as defects and faults.
The recent technologies for power cable diagnosis and temperature monitoring system are described including their intrinsic limitations for cable health assessment. Power cable fault location methods are reviewed with two main categories: off-line and on-line data based methods.
As a diagnostic and fault location approach, a new passive methodology is introduced. This methodology is based on analyzing the resonant frequencies of the transfer function between the input and output of the power cable system. The equivalent pi model is applied to the resonant frequency calculation for the selected underground power cable transmission system.
The characteristics of the resonant frequencies are studied by analytical derivations and PSCAD simulations. It is found that the variation of load magnitudes and change of positive power factors (i.e., inductive loads) do not affect resonant frequencies significantly, but there is considerable movement of resonant frequencies under change of negative power factors (i.e., capacitive loads).
Power cable fault conditions introduce new resonant frequencies in accordance with fault positions. Similar behaviors of the resonant frequencies are shown in a transformer (TR) connected power cable system with frequency shifts caused by the TR impedance.
The resonant frequencies can be extracted by frequency analysis of power signals and the inherent noise in these signals plays a key role to measure the resonant frequencies. Window functions provide an effective tool for improving resonant frequency discernment. The frequency analysis is implemented on noise laden PSCAD simulation signals and it reveals identical resonant frequency characteristics with theoretical studies.
Finally, the noise levels of real voltage and current signals, which are acquired from an operating power plant, are estimated and the resonant frequencies are extracted by applying window functions, and these results prove that the resonant frequency can be used as an assessment for the internal changes in power cable parameters such as defects and faults.
ContributorsKim, Youngdeug (Author) / Holbert, Keith Edwin (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2015