Abstract
This paper presents a comparative study between two non-causal algorithms for the energy management problem of electric vehicles, endowed with batteries and supercapacitors(SCs). Toward that goal, an optimization-based energy problem is formulated, which targets the minimization of the source's energy losses throughout a given driving cycle. This problem is solved, firstly, with the help of a fast (but locally optimal) non-linear programming solver; and, secondly, with a slow, but globally optimal, dynamic programming (DP) approach. Simulation results will demonstrate that, despite the different theoretical properties associated with these two solver approaches, both generate similar solutions. In the second part of the work, we will develop a filter-based energy management algorithm, i.e., employ batteries to provide the low-frequency content of the power demand, while SCs cover the high-frequency demand. Our approach builds on the idea of adapting the filter's time constant throughout the vehicle's journey, using, for that purpose, a fuzzy logic algorithm and the information of the state of the vehicle. In comparison with the traditional fixed time-constant approach, the simulation results show that under some conditions the adaptive time-constant algorithm has the potential to reduce the energy losses of the sources by up to 62%. © 2013 IEEE.

Abstract

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. © Springer International Publishing Switzerland 2014.

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
The power systems operation in the smart grid context increases significantly the complexity of their management. New approaches for ancillary services procurement are essential to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. These approaches should include market mechanisms which allow the participation of small and medium distributed energy resources players in a competitive market environment. In this paper, an energy and ancillary services joint market model used by an aggregator is proposed, considering bids of several types of distributed energy resources. In order to improve economic efficiency in the market, ancillary services cascading market mechanism is also considered in the model. The proposed model is included in MASCEM - a multi-agent system electricity market simulator. A case study considering a distribution network with high penetration of distributed energy resources is presented.