Abstract
Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multi-objective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.

Abstract
It is foreseeable that electricity retailers for electrical mobility will be market agents. These retailers are electric vehicle (EV) aggregation agents, which operate as a commercial middleman between electricity market and EV owners. Furthermore, with the foreseen evolution of the smart-grid concept, these agents will be able to control the EV charging rates and offer several ancillary services. This paper formulates an optimization problem for the EV aggregation agent participation in the day-ahead and secondary reserve market sessions. Forecasting issues are also discussed. The methodology was tested for two years (2009 and 2010) of the Iberian market, considering perfect and naïve forecast for all variables of the problem. © 2011 IEEE.

Abstract
In power systems with a large integration of wind power, setting the adequate operating reserve levels is one of the main concerns of system operators (SO). The integration of large shares of wind generation in power systems led to the development of new forecasting methodologies, including probabilistic forecasting tools, but management tools able to use those forecasts to help making operational decisions are still needed. In this paper, a risk evaluation perspective is used, showing that it is possible to describe the consequences of each possible reserve level through a set of risk indices useful for decision making. The new reserve management tool (RMT) described in the paper is intended to support the SO in defining the operating reserve needs for the daily and intraday markets. Decision strategies like setting an acceptable risk level or finding a compromise between economic issues and the risk of loss of load are explored. An illustrative example based on the Portuguese power system demonstrates the usefulness and efficiency of the tool.

Abstract
This paper presents a Multicriteria Decision Aid methodology for planning energy storage and sustainable mobility, in an isolated system. The objective of this research is to enhance the sustainability of the analyzed case study (São Miguel Island), by comparing a set of alternatives for energy storage and sustainable mobility. The alternatives characterization and evaluation is made through the calculation of meaningful attributes, namely: carbon emissions, overall costs and reliability. An analysis of the most interesting alternatives is also performed. © 2011 IEEE.

Abstract
Due to the high penetration of renewable energy into the energy matrix of today's power networks, the design of generating systems based only on static reserve assessment does not seem to be enough to guarantee the security of power system operation. From the wind power integration perspective, this energy source imposes additional requirements, mainly due to the inherent unpredictable characteristic of the wind. Besides the uncertainties in load and generating unit availabilities, the operating reserve needs also to deal with the fluctuation characteristic of the wind power. Therefore, more flexibility of the conventional generators (hydro and thermal) is required to provide system support services. This paper discusses a new methodology based on chronological Monte Carlo simulation to evaluate the operating reserve requirements of generating systems with large amounts of renewable energy sources, in particular, wind power.

Abstract
In response to the soaring energy crisis and the related pollution problems worldwide, it is essential to apply new technologies that use renewable energy sources in both an efficient and environmentally friendly manner. In this way, biomass offers one of the largest potential among renewable energy sources. The aim of this work is to demonstrate a novel fuzzy-based methodology for selecting hybrid energy systems fuelled by biogas. Fuzzy multi-rules and fuzzy multi-sets are used to evaluate the main operational characteristics of five types of renewable sources fuelled by biogas. The possibility of using the methodology for energy storage system evaluation is also assessed. The construction of the fuzzy multirules and fuzzy multi-sets is based on the following methods: Mamdani (fuzzification process), Max-Min (inference process), and Center of Gravity (defuzzification process). Several criteria are used: costs, efficiency, cogeneration, life-cycle, technical maturity, power application range, and environmental impacts. The methodology considers three different settings with two different constraints: costs and environment. One of the most relevant aspects presented by this work is about the previous classification of the criteria. It was created according to the different relevance observed among the attributes. The purpose of the proposed arrangement is to facilitate the understanding of the methodology and to increase the possibility of incorporating the decision makers' preferences on the decision-aid process. These aspects are essential to strengthen the final decision. © Springer-Verlag Berlin Heidelberg 2011.