Voltage security problems became a matter of concern over the last three decades because of the systems complexity. This is about to worsen as the penetration of renewable sources grows. Different operating scenarios must be addressed because of the intermittent nature of some sources. This study discusses this problem by proposing a neuro-fuzzy methodology to determine the load margin when the intermittency of the sources is taken into account. Load margin is obtained by the continuation method enhanced by the Constrained Reactive Implicit Coupling (CRIC) method, so its computational effort is reduced. Monte Carlo simulation is employed to generate the bunch of data considered by the neuro-fuzzy and the results are obtained in two ways. First, a sample IEEE 34-bus system is employed, so the results may be reproduced. Then, a modified Brazilian real system with 115 buses is considered.
This paper describes the dynamics of the level, slope and curvature of the Brazilian nominal yield curve using only observable macroeconomic indicators. The model is able to explain 94.5% of the variation in the yield curve. We find that the main drivers of the level factor is the Brazil risk premium (5-year CDS spread) and the unemployment rate. In turn, the slope steepens with increases either in the SELIC rate or in the spot exchange rate, and flattens with increases in unemployment rate and commodity returns. Lastly, the curvature increases with the unemployment, inflation and SELIC rates, but decreases with changes in the exchange rate.
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