• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1288-1295
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• 2012

Korea Ministry of Knowledge Economy has estimated that wind power (WP) will be occupied 37% in 2020 and 42% in 2030 of the new energy sources, and also green energies such as photovoltaic (PV) and WP are expected to be interconnected with the distribution system because of Renewable Portfolio Standard (RPS) starting from 2012. However, when a large scale wind power plant (over 3[MW]) is connected to the traditional distribution system, protective devices (mainly OCR and OCGR of re-closer) will be occurred mal-function problems due to changed fault currents it be caused by Wye-grounded/Delta winding of interconnection transformer and %impedance of WP's turbine. Therefore, when Double-Fed Induction Generator (DFIG) of typical WP's Generator is connected into distribution system, this paper deals with analysis three-phase short, line to line short and a single line ground faults current by using the symmetrical components of fault analysis and PSCAD/EMTDC modeling.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.99-108
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• 2022

Among induced polarization (IP) methods, spectral IP (SIP) uses alternating current as a transmission source to measure amplitudes and phase of complex electrical resistivity at each source frequency, which disperse with respect to source frequencies. The frequency dependence, which can be explained by a relaxation model such as Cole-Cole model or equivalent models, is analyzed to estimate SIP parameters from dispersion curves of complex resistivity employing multi-objective optimization (MOO). The estimation uses a generic algorithm to optimize two objective functions minimizing data misfits of amplitude and phase based on Cole-Cole model, which is most widely used to explain IP relaxation effects. The MOO-based estimation properly recovered Cole-Cole model parameters for synthetic examples but hardly fitted for the real laboratory measures ones, which have relatively smaller values of phases (less than about 10 mrad). Discrepancies between scales for data misfits of amplitude and phase, used as parameters of MOO method, and it is in necessity to employ other methods such as machine learning, which can deal with the discrepancies, to estimate SIP parameters from dispersion curves of complex resistivity.