In this paper the dynamic behavior of different wind turbine generator configurations including doubly fed induction generators (DFIG), squirrel cage induction generator (SCIG), wound rotor induction generator (WRIG), and permanent magnet synchronous generator (PMSG) under ferroresonant conditions of energization and de-energization was investigated using Simulink/MATLAB (version 2017B, MathWorks, Natick, MA, USA). The result showed that SCIG had the highest overvoltage of 10.1 PU during energization, followed by WRIG and PMSG, while the least was DFIG. During de-energization, PMSG had the highest overvoltage of 9.58 PU while WRIG had the least. Characterization of the ferroresonance was done using a phase plane diagram to identify the harmfulness of the ferroresonance existing in the system. It was observed that for most of the wind turbine configurations, a chaotic mode of ferroresonance exists for both energization and de-energization scenarios. Although overvoltage during energization for wind turbine generator configurations was higher than in the de-energization with an exception of PMSG, their phase plane diagrams showed that de-energization scenarios were more chaotic than energization scenarios. The study showed that WRIG was the least susceptible to ferroresonance while PMSG was the most susceptible to ferroresonance.
The health index is a part of the life cycle management tools for key assets. It allows for customization of maintenance plans for transformers depending on their condition. This optimises resources and allows for early detection of faults while allowing sufficient time to plan interventions to address problematic transformers. The index addresses the weighting between long term assessments (paper degradation), and short to medium term assessments (dissolved gas analysis). In addition to the Total Dissolved Combustible Gases method of dissolved gas analysis, methods looking at the ratio of the various gases present in the oil were employed for more accurate dissolved gas analysis interpretation. Oil quality indicators were also used in the index as the life of the paper relies on the quality of the insulating oil, which if allowed to oxidize, sludge and degrade would put the transformer in worse condition, it should also be represented in any health assessment of transformers. A case study was presented and indicated that with the correct weightings of the criteria, the plant health index would correctly predict whether a transformer would fail. For the transformers where the plant health index did not predict failure, a network performance and ancillary equipment score was introduced and combined with the plant health index for a risk index. It was shown that healthy transformers on poorly performing networks could be better categorised. It was also shown that a score for the ancillary equipment could be used to better categorise the transformers. The risk index allows for better inspection, maintenance and replacement of equipment.
Abstract. The exchange of trace gases between the Earth's surface and its atmosphere drives atmospheric composition.Airborne eddy covariance can provide observational constraints on surface fluxes at regional scales, helping to bridge the gap between top-down and bottom-up flux estimates and offering novel insights into biophysical and biogeochemical processes. The NASA Carbon Airborne Flux Experiment (CARAFE) utilizes the NASA C-23 Sherpa aircraft with a suite of commercial and custom instrumentation to acquire fluxes of carbon dioxide, methane, sensible heat, and latent heat at high 20 spatial resolution. Key components of the CARAFE payload are described, including the meteorological, greenhouse gas, water vapor, and surface imaging systems. Continuous wavelet transforms deliver spatially-resolved fluxes along aircraft flight tracks. Flux analysis methodology is discussed in depth, with special emphasis on evaluation of uncertainties and vertical flux divergence. CARAFE has successfully flown two missions in the Eastern U.S. in 2016 and 2017, quantifying fluxes over forest, cropland, wetlands, and water. Results from these campaigns highlight the performance of this system and 25 its potential to further our understanding of ecosystem exchange.
Different developers have produced several software packages as solutions to model electrical power systems for the purpose of carrying out diverse analyses to solve immediate and unforeseen problems in power systems. In this study, ATP/EMTP and Matlab/Simulink packages were compared in regards to their capability to give accurate results, time of simulation and ease of simulation when modeling DFIG wind turbine. Furthermore, ferroresonance caused by one stuck pole during switching operations were analyzed on both software. Characterization of resulting ferroresonance was done using Fast Fourier Transformation (FFT) analysis, phase plane diagram and Poincaré mapping. Chaotic mode ferroresonance was found in both ferroresonance events. However, ATP could only perform FFT analysis while other analyses were performed on Matlab/Simulink. There are differences in the results obtained from the two packages; overvoltage of 4.22 P.U. and 3.77 P.U. was experienced during opening and closing operation on ATP/EMTP model while 6.36 P.U. and 4.63 P.U. respectively was obtained on Matlab. However, ATP is faster in regards to time of simulation with CPU time of 110.58 secs and simulink simulation time was 130.81 secs. Finally, it was easier to carry out the simulation on Simulink.
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