Abstract
This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the Robot@Factory which is a new robotic competition presented in Lisbon 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that is well-behaved. The sensor information is continuously updated in time and space through the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, a particle filter based on Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high. Meaning that the map-matching is unreliable and robot is lost. The experiments conducted in this paper prove the ability and accuracy of the presented technique to localize small mobile robots for this competition. Therefore, extensive results show that the proposed method have an interesting localization capability for robots equipped with a limited amount of sensors.

Abstract
This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results. © 2013, Springer Science+Business Media Dordrecht.

Abstract
Nowadays, wind energy has an important role in the challenges of clean energy supply. It is the fastest growing energy source with a increasing annual rate of 20%. This scenario motivate the development of an optimization design tool to find optimal layout for wind farms. This paper proposes a mathematical model to find the best electrical interconnection configuration of the wind farm turbines and the substation. The goal is to minimize the installation costs, that include cable cost and cable installation costs, considering technical constraints. This problem corresponds to a capacitated minimum spanning tree with additional constraints. The methodology proposed is applied in a real case study and the results are compared with the ground solution.

Abstract
Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players' benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Abstract
The smart grids represent a new and attracting challenge for various research areas. The inclusion of information technologies across the entire electrical grid creates new capacities, with impact on the environment, science and technology, economy and lifestyle. Creation of a smart grid provides utilities and their customers a significant improvement in power reliability and services. This paper presents an overview of smart grid technologies focusing on its characteristics, benefits and challenges. Moreover, this paper reviews the reliability impacts of the major smart grid resources such as renewables, demand response and storage. The main differences between a traditional grid and a smart grid, the trends in the evolution of power distribution systems and the highlights of smart grid segments and applications are also presented. Smart Grids represent one of the great challenges at the global level. Under the effect of political and societal pressure due to climate change and pollution concerns, and enabled by availability of new technologies, the electrical power systems are undergoing reconsideration. Including the technology of information in the whole electric grid creates new capabilities with strong impact in the environment, science and technology, but also in the economy and life in general. The term "smart grid" describes the evolution of the electrical grids and reflects a change of paradigm in the electric market organization and management. Some changes are already on the way to be implemented, such as a growth of the renewable fraction of the generating power, some other are envisioned, such as the fully flexible energy routing or the consumer driven distribution. From a global perspective, implementing smart grids at a large scale will definitely improve the services that supply electrical energy in the future. In recent years, electrical grids have been faced with an increasing concentration of distortion loads that generate distortion, causing both current and voltage harmonic distortions. The impact of these loads increases as their power approaches the power capacity of the grid.

Abstract
This work addresses the problem of computing the time evolution of the probability density function (pdf) of the state in a nonlinear neuromuscular blockade (NMB) model, assuming that the source of uncertainty is the knowledge about one parameter. The NMB state is enlarged with the parameter, that verifies an equation given by its derivative being zero and has an initial condition described by a known pdf. By treating the resulting enlarged state-space model as a stochastic differential equation, the pdf of the state verifies a special case of the Fokker-Planck equation in which the second derivative terms vanish. This partial differential equation is solved with a numerical method based on Trotter’s formula for semigroup decomposition. The method is illustrated with results for a reduced complexity NMB model. A comparison of the predicted state pdf with clinical data for real patients is provided.