Contingency analysis plays an important role in assessing the static security of a network. Its purpose is to check whether system can operate safely when some elements are out service. In real-time application, computational time required perform calculation paramount for operators take immediate actions prevent cascading outages. Therefore, numerical performance contingency main focus this cu...

<p>Distributed generations (DG), specially including renewable sources such as wind and sun are offering several opportunities for the currently in existence distribution networks becoming one of keys treatment its problems. Knowing effects each kind DG on is a primordial task because impacts differ from to another. In this paper, we have analyzed compared two kinds DG, which provides rea...

Power-flow (PF) solution is a basic and powerful tool in power system analysis. Distribution networks (DNs), compared to transmission systems, have many fundamental distinctions that cause the conventional PF to be ineffective on these networks. This paper presents a new fast and efficient PF method which provides all different models of Distributed Generations (DGs) and their operational modes...

The paper presents an algorithm of adaptation by successive mesh regeneration and its application to the potential nonlinear flow problems. The Newton-Raphson method is applied to the solution of nonlinear problem. The Kutta-Zhukovsky condition is implemented by the penalty function method. The adaptation algorithm is based on the modification of mesh size function depending on the error indica...

A nite element formulation to deal with the friction contact problem between an elastic body and a rigid foundation is presented. An augmented Lagrangian method, which incorporates two Lagrange multipliers and a slack variable in the constraint equation, is developed. In this method, the solution is achieved through a Newton-Raphson monolithic iterative strategy and leads to simple implementati...

We present a scalable and robust Bayesian method for demand forecasting in the context of a large e-commerce platform, paying special attention to intermittent and bursty target statistics. Inference is approximated by the Newton-Raphson algorithm, reduced to linear-time Kalman smoothing, which allows us to operate on several orders of magnitude larger problems than previous related work. In a ...