In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power injected by wind farms. The method proposed is based on the generation of correlated series of power values, which can be used in a MonteCarlo simulation, to obtain the probability d...

Starting from an agent-based interpretation of the well-known Bass innovation diffusion model, we perform a Montecarlo analysis of the performance of a method of simulated moment (MSM) estimator. We show that nonlinearities of the moments lead to a small bias in the estimates in small populations, although our estimates are consistent and converge to the true values as population size increases...

This paper proposes a Monte Carlo based statistical simulation technique in place of the difficult mathematical analysis to obtain an estimate of the error probability of a log-normal Raleigh faded channel in a digital wireless communication network taking into account the users random positions and the modulation type. The results obtained are consistent with those in the literature. Index Ter...

The objective of this paper is to develop the method for selection of the optimal structure of simultaneous equation system from the given model set in the condition of the limited sample of observations. The identification purpose is the model selection with the best predictive possibility. The information criteria for selecting the best model of nonlinear simultaneous equation system from the...

The Montecarlo method is used to computer simulate a random distribution of molecular lengths generated by inducing T4 DNA fragmentation through the decay of 32P atoms introduced in the molecule. Taking into account the experimental conditions we find that the value of alpha for alkali sucrose gradients is 0.46 +/- 0.02 and does not depend on the running time. Our findings also prove that the c...

We propose a new global optimization method (Simulated Tempering) for simulating effectively a system with a rough free energy landscape (i.e. many coexisting states) at finite non-zero temperature. This method is related to simulated annealing, but here the temperature becomes a dynamic variable, and the system is always kept at equilibrium. We analyze the method on the Random Field Ising Mode...

The montecarlo method, which is quite commonly used to solve maximum entropy problems in statistical physics, can actually be used to solve inverse problems in a much wider context. The probability distribution which maximizes entropy can be calculated analytically by introducing Lagrange parameters. The problem of xing these lagrangean parameters is circumvented by introduction of a microcanon...

En el presente artículo se presenta estudio de la estimación demanda una estación carga vehículos eléctricos basado en uso simulación Montecarlo. La modelación del sistema eléctrico lo realiza a través software PowerFactory, por otra parte, para desarrollo las simulaciones Montecarlo y procesamiento información, Python. El análisis general está enfocado determinar impacto integración red eléctr...

This paper proposes a method of estimating and simulating a maximum entropy distribution given moment conditions based on MonteCarlo approach. The method provides an simple alternative to conventional calculation methods of maximum entropy densities which involve complex numerical integration and are subject to occasional failure. We first show that maximum entropy density on a random sample co...