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This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including cut-off and cut-in behaviours. The wind turbine is modeled as a stochastic hybrid system with three operation modes. Numerical results, obtained using Monte-Carlo...
The impact of a pulse load charging event on a notional all-electric ship is investigated through simulation in the context of uncertainty in the parameters of the system and event. In order to efficiently carry out the study, the system is modeled on a large-scale parallel processor simulator. A surrogate modeling approach is used to characterize the behavior of the system for the purposes of sensitivity...
Markov models are a well established technique widely used for modeling deterioration processes of the electric power equipment and in reliability analysis. Recently, several papers using Markov and semi-Markov models have been published addressing the issue of the calculation of the remaining life, future failure rates and the probability of failure of power equipment. This paper focuses on one such...
This article is an extension of the work presented earlier, which compared and analyzed the economics of alternative maintenance plans. The proposed model combines genetic algorithms with Monte Carlo simulation to arrive at the most economic investment timing. The approach described earlier was characterized by a very long computing time making it difficult to use. This paper addresses several issues...
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