Abstract
An aggregator agent for electric vehicles is a commercial middleman between a system operator and plug-in electrical vehicles (EV). For the system operator 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. In this paper, the integration of these concepts in an electricity market environment is discussed through proposing a framework for the information characterization (and availability) between aggregator, system operators and clients. A specific market (the Iberian Market - MIBEL) is discussed. In the sequence, the different degrees of availability of the relevant information are identified and characterized, including the variables that are necessary to forecast.

Abstract
An electric vehicle (EV) aggregation agent, as a commercial middleman between electricity market and EV owners, participates with bids for purchasing electrical energy and selling secondary reserve. This paper presents an optimization approach to support the aggregation agent participating in the day-ahead and secondary reserve sessions, and identifies the input variables that need to be forecasted or estimated. Results are presented for two years (2009 and 2010) of the Iberian market, and considering perfect and naive forecast for all variables of the problem.

Abstract
This paper reports results and an evaluation methodology from two new decision-aid tools that were demonstrated at a Transmission System Operator (REN, Portugal) during several months in the framework of the E. U. project Anemos. plus. The first tool is a probabilistic method intended to support the definition of the operating reserve requirements. The second is a fuzzy power flow tool that identifies possible congestion situations and voltage violations in the transmission network. Both tools use as input probabilistic wind power predictions.

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 integration of large shares of wind generation in power systems requires the development of new algorithms and forecasting tools for making decisions in the operational domain taking into account wind generation forecast uncertainties. One of these decisions regards operating reserve requirements to meet load and wind variations. The aim of this paper is therefore to address this issue from a risk evaluation perspective, 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 described in this paper is intended to support the Transmission System Operator (TSO) in defining on-line 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. A case-study based on the Portuguese power system demonstrates the usefulness and efficiency of the tool.

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.