This user guide describes the rationale behind, and the modus operandi of a Unix script-driven package for evolutionary searching of optimal Support Vector Machine model parameters as computed by the libsvm package, leading to support vector machine models of maximal predictive power and...

This study presents the auxiliary damping control with the reactive power loop on the rotor-side converter of doubly-fed induction generator (DFIG)-based wind farms to depress the sub-synchronous resonance oscillations in nearby turbogenerators. These generators are connected to a series...

This paper presents development of an optimal control strategy for a hybrid photovoltaic/battery energy storage (PV/BES) system. The fluctuations at the DC bus voltage due to voltage sag were mitigated by using charge/discharge capability of the BES through the DC/DC buck/boost converter....

Accurate power generation forecasting provides the basis of decision making for electric power industry development plans, energy conservation and environmental protection. Since the power generation time series are rarely purely linear or nonlinear, no single forecasting model can identify the...

Volatility forecasting is an important process required to measure variability in equity prices, risk management, and several other financial activities. Generalized autoregressive conditional heteroscedastic methods <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$(\textit{GARCH})$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mo stretchy="false">(</mo> <mi mathvariant="italic">GARCH</mi> <mo stretchy="false">)</mo> </mrow> </math> </EquationSource> </InlineEquation> have been used to forecast volatility...</equationsource></equationsource></inlineequation>