Abstract
In this paper we describe the models and the simulations that were conducted in order to access the impact of feed-in subsidized generation in the market price in Portugal in the context of the Iberian Electricity Market. In Portugal and Spain feed-in generation (namely wind power) has a large share both in terms of installed capacity and generated energy and the presence of this energy in the hourly balance originates the reduction of the market price and of the number of hours during which traditional generation (namely coal and CCGT stations) are scheduled. This paper aims at evaluating this impact both in the short term (using the real market curves) and in the long term (using a long term generation expansion planning model). The paper includes results for the Iberian power system currently having a total installed capacity above 120 GW and a total demand of 310 TWh by the end of 2013. © 2014 IEEE.

Abstract
In this paper we describe the models and the simulations that were conducted in order to access the impact of feed-in subsidized generation in the market price in Portugal in the context of the Iberian Electricity Market. In Portugal and Spain feed-in generation (namely wind power) has a large share both in terms of installed capacity and generated energy and the presence of this energy in the hourly balance originates the reduction of the market price and of the number of hours during which traditional generation (namely coal and CCGT stations) are scheduled. This paper aims at evaluating this impact both in the short term (using the real market curves) and in the long term (using a long term generation expansion planning model). The paper includes results for the Iberian power system currently having a total installed capacity above 120 GW and a total demand of 310 TWh by the end of 2013.

Abstract
With the advent of restructuring, generation companies have to plan the operation of their stations in order to maximize their profits. This is very relevant for companies having a large share of hydro stations, and even more if these stations have pumping capacity. This paper describes a model to plan the operation of a set of hydro stations eventually installed in cascade and admitting that some of them are pumping stations. Once a first set of operation orders is obtained using a Genetic Algorithm, their generation/load values are included in the expected market selling/buying curves and the hourly prices are updated. These prices are then used to refine the operation orders originating an iterative process so that hydro stations are price makers. The paper includes results for a hydro system in order to illustrate the application of the developed approach.

Abstract
A fully operational multiterminal dc (MTDC) grid will play a strategic role for mainland ac systems interconnection and to integrate offshore wind farms. The importance of such infrastructure requires its compliance with fault ride through (FRT) capability in case of mainland ac faults. In order to provide FRT capability in MTDC grids, communication-free advanced control functionalities exploiting a set of local control rules at the converter stations and wind turbines are identified. The proposed control functionalities are responsible for mitigating the dc voltage rise effect resulting from the reduction of active power injection into onshore ac systems during grid faults. The proposed strategies envision a fast control of the wind turbine active power output as a function of the dc grid voltage rise and constitute alternative options in order to avoid the use of classical solutions based on the installation of chopper resistors in the MTDC grid. The feasibility and robustness of the proposed strategies are demonstrated and discussed in the paper under different circumstances.

Abstract
This paper presents a holistic framework for electric vehicles integration in electric power systems together with their charging management and control methodologies that allow minimizing the negative impacts in the grid of the charging process and maximize the benefits that charging controllability may bring to their owners, energy retailers and system operators. The performance of these management and control methods will be assessed through steady state computational simulations and then validated in a microgrid laboratory environment.

Abstract
The uncertainties related to when and where Plug-in Electric Vehicles (PEVs) will charge in the future requires the development of stochastic based approaches to identify the corresponding load scenarios. Such tools can be used to enhance existing system operators planning techniques, allowing them to obtain additional knowledge on the impacts of a new type of load, so far unknown or negligible to the power systems, the PEVs battery charging. This chapter presents a tool developed to evaluate the steady state impacts of integrating PEVs in distribution networks. It incorporates several PEV models, allowing estimating their charging impacts in a given network, during a predefined period, when different charging strategies are adopted (non-controlled charging, multiple tariff policies and controlled charging). It uses a stochastic model to simulate PEVs movement in a geographic region and a Monte Carlo method to create different scenarios of PEVs charging. It allows calculating the maximum number of PEVs that can be safely integrated in a given network and the changes provoked by PEVs in the load diagrams, voltage profiles, lines loading and energy losses. Additionally, the tool can also be used to quantify the critical mass (percentage) of PEV owners that need to adhere to controlled charging schemes in order to enable the safe operation of distribution networks. © Springer Science+Business Media Singapore 2015.