The Japanese Electricity System 15 months After March 11th 2011

The Great East Japan earthquake and tsunami on March 11th 2011 caused mass destruction, significant loss-of-life and a large displacement of people. It also placed significant strain of Japan's electricity-generating infrastructure. There was a significant reduction in capacity due to the damage in thermal generation and gradual closure of Japan's nuclear power plants; the ability for load-balancing across the Japanese grid was compromised due to limited interconnections between the different utilities that comprise the Japanese electricity system. This paper looks at the first fifteen months following the earthquake and tsunami: outlining the supply reduction and consequent attempts to manage the demand. In turn it highlights the foibles of Japan's vertically-integrated monopolistic structures and the evolution of governmental and utilities response that went from decisions made 'on-the-fly' to a more developed policy for peak-demand electricity savings. The findings from this paper should serve as a useful set of examples to aid decision makers in contingency planning for disruptive large-scale reduction in electricity-generating capacity

Uncertainty propagation and sensitivity analysis in ray-tracing simulations

Up to now, ray-tracing simulations are commonly used with a deterministic approach. Given the input parameters, the ray-tracing algorithm computes a value for the electric field. In this paper, we present a method that aims at computing the mean and standard deviation of the electric field. More precisely, we aim to obtain the probabilistic content of the electric field value and direction. We assume that this uncertainty results from input random variables which we consider uniformly distributed. Since ray-tracing computations have a high computational cost, we use spectral methods in order to optimize the number of simulations. We consider 2D electromagnetic propagation for the multi-path components, which can interact with the environment through four processes: transmission, single reflection, double reflection and diffraction. These are modelled using adequate coeffcients. In order to calculate the polynomial chaos expansion coeffcients, we use the projection method and Gauss-Legendre quadratures. These coeffcients can then be used to determine the Sobol indices of input parameters. This is done in order to neglect variables in practical computation of the uncertainties.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Application of polynomial chaos expansions for uncertainty estimation in angle-of-arrival based localization

Invited talkinfo:eu-repo/semantics/nonPublishe