Abstract
Demand aggregators are new market players that represent a group of consumers in the electricity market. This paper proposes an aggregator model responsible for gathering residential and commercial consumers, which has the role of managing their flexible consumption in the day-ahead electricity market. A methodology to optimize the aggregator's bids is also presented. It optimizes the scheduling of the flexible loads taking simultaneously into account the consumers' preferences and temporal trajectories of forecasted outdoor temperatures and electricity prices. The proposed methodology was tested using a case study with 200 residential and commercial consumers from the Iberian market.

Abstract
This paper proposes a novel method to characterize the availability of household loads to participate in demand response programmes, as well as detailed mathematical models to characterize households loads. The availability of the households results from the flexibility of their controllable loads to increase/reduce consumption. This flexibility is calculated taking into account the comfort levels predefined by the customers and the technical restrictions of the controllable loads. The proposed method was evaluated through a management algorithm developed to perform demand control actions in quasi-real-time, according to the objectives of the distribution system operator or energy aggregator and the availability of the household loads. A scenario with a single household located in a semi-urban area is used to illustrate the application of the algorithm and validate the proposed method.

Abstract
In the Smart Grid environment, it is expected that Home Energy Management Systems (HEMS) should be capable of managing appliances inside the house, in order to provide reserve services. This paper aims at estimating the flexibility of a Portuguese typical residential load diagram. For this purpose, a bottom-up approach is used, i.e., the aggregated flexible load demand is determined taking into account the availability of each appliance to be controlled by the HEMS. The comfort requirements of the consumers are also incorporated in the flexibility calculations by integrating realistic load models into HEMS.

Abstract
The impact of large-scale Electric Vehicles (EVs) deployment in electric power systems is a current issue under study by the scientific community. The integration of this type of electric component requires robust planning solutions to mitigate possible consequences from such integration. This paper explores the quantification of the amount of renewable sources, namely wind and hydro power, which can be safely integrated into power systems in a scenario of a mass integration of EVs. The increase of renewable power in the generation portfolio is analyzed under the framework of generating system adequacy assessment considering several EVs deployment scenarios and an adequate charging strategy. The analysis is carried for the planning configurations of the Portuguese and Spanish generating systems and the results are focused on the potential benefits of EV integration in terms of hydro and wind power usage.

Abstract
This paper proposes a novel Energy Aggregator model responsible for managing the flexibility of low voltage customers in order to reduce electricity costs. The flexibility of the customers is represented by the availability of their controllable loads to reduce/ increase power consumption. The flexible loads are managed according to the customers' preferences and the technical limitations of the flexible loads. The Energy Aggregator model developed includes an algorithm designed to manage customers' flexibility in quasi-real-time, with the objective of minimizing the deviations from the energy bought by the aggregator in the market. A scenario with 30 households located in a semi-urban area is used to illustrate the application of the algorithm and validate the proposed approach.

Abstract
This work proposes an innovative method based on autoencoders to perform state estimation in distribution grids, which has as main advantage the fact of being independent of the network parameters and topology. The method was tested in a real low voltage grid (incorporating smart grid features), under different scenarios of smart meter deployment. Simulations were performed in order to understand the necessary requirements for an accurate distribution grid state estimator and to evaluate the performance of a state estimator based on autoencoders.