Abstract
In order to participate in the electricity market, electric vehicles (EV) need to be aggregated by a market agent, since the current rules do not allow the participation of small loads. The EV aggregator purchases electrical energy for charging its clients, and can offer reserve services. This activity requires forecasting methods for several variables. This paper presents a global view of the relevant variables for an EV aggregation agent participating in the electricity market and discusses the associated forecasting issues. The load forecast problem for direct and indirect control of the EV charging process is discussed. Variables from the market-side, such as reserve price and direction, are also addressed. Existing approaches are reviewed, discussed and tested according to different metrics.

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
A decision-making approach based on multi-criteria techniques can help to make the massive deployment of the microgrid concept a viable solution, potentially leading to proper incentive mechanisms for distribution system operators, microgeneration owners and loads. © 2012 Elsevier Inc.

Abstract
Exploiting the benefit that one can get from large scale integration of microgeneration (mu G) requires the adoption of different control strategies at different distribution network levels. In that sense, MicroGrid (MG) and Multi MicroGrids (MMG) concepts may be seen as a way to facilitate integration of higher levels of mu G into the system. This paper describes new control and management functionalities used to take profit from the presence of microgeneration and active loads under MG and MMG concepts. MultiCriteria Decision Aid (MCDA) techniques are used to capture decision maker's preferences in evaluating the impact of MG and MMG concepts deployment and help selecting the best development strategy.

Abstract
The basic objective of Transmission Expansion Planning (TEP) is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO) meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.

Abstract
This paper describes a Dynamic Model of the electricity sector that can be used to simulate the evolution of some key variables on the long term, namely the evolution of the electricity price, of the demand and of the capacity factors of the technologies in the generation mix. This model can be used in different ways and by several agents, for instance to estimate the impact on the electricity price of the increasing presence of renewable power stations, namely using wind power and PV systems. In several countries these stations are paid feed-in tariffs with a fixed price but in some cases this scheme is under discussion and there are opinions that payments determined by the market price are more adequate and would bring fewer costs to final consumers. Such a change has to be carefully evaluated given that the presence of renewable stations bidding at an infra marginal price will affect the price itself. The model described in this paper can be used in a profitable way both by governmental agencies when preparing or studying alternative remuneration schemes to renewable stations or by promoters themselves to get more insight to the profitability of their investments, namely if the fixed feed-in tariffs in force in several countries are changed.