Abstract
This paper highlights findings of the European Commission funded project called MERGE (Mobile Energy Resources in Grids of Electricity). MERGE is a collaborative research project that includes utilities, regulators, commercial organisations and universities with interests in the power generation, automotive, electronic commerce and hybrid and electric vehicle sectors across the entire European Union (EU). This major two-year research initiative began in January 2010. The MERGE project mission is to evaluate the impacts that electric vehicles (EV) will have on the European Union (EU) electric power systems with regards to planning, operation and market functioning. The focus is placed on EV and SmartGrid/MicroGrid simultaneous deployment, together with renewable energy increase, leading to CO2 emission reduction through the identification of enabling technologies and advanced control approaches. In this paper indicative results from the impact of the additional EV load will have in the daily and yearly system load diagrams and in the operation of the transmission and distribution networks of five European countries (Greece, UK, Spain, Portugal, and Germany) in 2020 are presented. General conclusions are drawn.

Abstract
This paper presents and evaluates a method of generating partial bitstreams at run-time for dynamic reconfiguration of sections of an FPGA. The method is intended for use in adaptive embedded systems that employ run-time reconfiguration to achieve high flexibility and performance. The proposed approach combines partial bitstreams of coarse-grained components to produce a new partial bitstream implementing a given circuit netlist. Topological sorting of the netlist is used to determine the initial positions of individual components, whose placement is then improved by simulated annealing. Connection routing is done by a breadth-first search of the reconfigurable area based on a simplified resource model of the reconfigurable fabric. The desired partial bitstream is constructed by merging together the default bitstream of the reconfigurable area, the relocated partial bitstreams of the components, and the configurations of the switch matrices used for routing. The approach is embodied in a code library that applications can use to create new bitstreams at run-time. For the members of a set of 29 benchmarks (both synthetic and application-derived) having between five and 41 components, the complete process of bitstream generation takes between 8 s and 35 s when running on an embedded PowerPC 405 microprocessor clocked at 300 MHz.

Abstract
The foreseeable increase in the use of electric vehicles (EV) led to the discussion on intermediate entities that could help manage a great number of EV. An aggregation agent for electric vehicles is a commercial middleman between a system operator (SO) and plug-in EV. From the SO perspective, the aggregator is seen as a large source of generation or load, which could provide ancillary services such as spinning and regulating reserve. Generally, these services will be provided in the day-ahead and intraday electricity markets. In addition, the aggregator also participates in the electricity market with supply and demand energy bids. This paper provides a comprehensive bibliographic survey on the aggregator role in the power system operation and electricity market. The scope of the survey covers 59 references divided in journal, conference proceedings, thesis, research papers, and technical reports published after 1994. These papers are put into several technical categories: electricity market and EV technical and economic issues; aggregation agent concept, role and business model; algorithms for EV management as a load/resource. Copyright (C) 2011 John Wiley & Sons, Ltd.

Abstract
This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Abstract
This paper, presents on the coordination of power system expansion planning including sustainable generation expansion planning (GEP) and transmission network expansion planning (TEP). For this purpose, a game theory based model is proposed to determine the dominant strategy of each investor entities in the generation and transmission sectors. In this model, all power producers compete with each other at the same level for maintaining the energy and reserve services. At this stage, after determining the Cournot equilibrium, the suggestions accepted in previous stage are evaluated in the transmission planning stage. Here, according to the existing units and the units proposed in the previous stage, transmission network expansion planning takes place based on cost, social welfare and reliability indices by independent system operator. Thereafter transmission expansion planning results announced, the accepted unit and not accepted units can offer their new strategies to the market. This iterative process continues until the dominant strategy of each entity is satisfied and the final equilibrium is obtained. To solve this game and finding its Nash equilibrium, the mixed integer non-linear programming (MINLP) optimization is used by all decision makers for optimizing their desirable strategies to invest in the power market. A conceptual test system is proposed to show the ability of the model. Simulation results verify the feasibility and capability of the proposed modeling of the long-term expansion planning. © Indian Society for Education and Environment (iSee).

Abstract
This paper presents an overview of the current state-of-the-art in mobile data stream mining. This area of mobile data stream mining is significant for a number of new application domains such as mobile crowd sensing and mobile activity recognition. The paper presents the strategies and techniques for adaptation that are essential in order to perform real-time, continuous data mining on mobile devices. We present an overview of the algorithms research in this area. Finally, we discuss the key toolkits, systems and applications of mobile data stream mining. © 2012 IEEE.