this paper presents a probabilistic optimal power flow (popf) algorithm considering different uncertainties in a smart grid. different uncertainties such as variation of nodal load, change in system configuration, measuring errors, forecasting errors, and etc. can be considered in the proposed algorithm. by increasing the penetration of the renewable energies in power systems, it is more essent...

Modelling of the weak lensing of the CMB will be crucial to obtain correct cosmological parameter constraints from forthcoming precision CMB anisotropy observations. The lensing affects the power spectrum as well as inducing non-Gaussianities. We discuss the simulation of full sky CMB maps in the weak lensing approximation and describe a fast numerical code. The series expansion in the deflecti...

In this paper, a simulation model of a solar cell is defined to allow estimation of the electrical behavior of the cell with respect changes on environmental parameter of temperature and irradiance. Maximum Power Point Trackers (MPPT) play an important role in photovoltaic (PV) power systems because they maximize the power output from a PV system for a given set of conditions, and therefore max...

<span>Parameters evaluation, design, and intelligent control of the solar photovoltaic model are presented in this work. The parameters zeta converters such as a rating an inductor, capacitor, switches for particular load evaluated its values to compare trade existing promoted research proposed area. converter is pulsed through controller-based maximum power point tracking (intelligent-MP...

We display the power Topp-Leone (PTL) distribution with two parameters. The following major features of PTL are investigated: quantile measurements, certain moment’s measures, residual life function, and entropy measure. Maximum likelihood, least squares, Cramer von Mises, weighted squares approaches used to estimate A numerical illustration is prepared compare behavior achieved estimates. Data...

Physics-informed machine learning (PIML) has been emerging as a promising tool for applications with domain knowledge and physical models. To uncover its potentials in power electronics, this article proposes PIML-based parameter estimation method demonstrated by case study of dc–dc Buck converter. A deep neural network the dynamic models converter are seamlessly coupled. It overcomes challenge...

During the last years, different methods for identifying permanent magnet synchronous motor (PMSM) parameters have been developed. Such allow a better characterization of PMSMs, thus enabling control. This article presents novel PMSM parameter estimation method based on differential power factor due to harmonic distortion, which allows identification from data acquisitions representing entire t...

The power-generation capacity of grid-connected photovoltaic (PV) power systems is increasing. As output forecasting required by electricity market participants and utility operators for the stable operation systems, several methods have been proposed using physical statistical approaches various time ranges. A short-term (30 min ahead) method had previously multiple PV motion estimation. This ...