Abstract
This paper presents a model predictive control (MPC) framework for battery energy storage systems (BESS) management considering models for battery degradation, system efficiency and V-I characteristics. The optimization framework has been tested for microgrids with different renewable generation and load mix considering several operation strategies. A comparison for one-year simulations between the proposed model and a naïve BESS model, show an increase in computation times that still allows the application of the framework for real-time control. Furthermore, a trade-off between financial revenue and reduced BESS degradation was evaluated for the yearly simulation, considering the degradation model proposed. Results show that a conservative BESS usage strategy can have a high impact on the asset's lifetime and on the expected system revenues, depending on factors such as the objective function and the degradation threshold considered.

Abstract
EUniversal project aims to facilitate the use of flexibility services and interlink distribution system's active management with electricity markets. Implementing market-based flexibility services implies a change in distribution network monitoring and control towards a more predictive approach. However, integrating cost-effective monitoring and control tools for the LV network is still quite challenging. Within the project, a set of operation and planning tools have been developed for a coordinated quantification and activation of flexibility in HV, MV and LV distribution networks. The paper presents the tools developed for the Portuguese pilot and shows preliminary results obtained when considering network operation scenarios characterized by large scale integration of DER and EV.

Abstract
This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer's individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers' energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer's new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

Abstract
This paper provides a general overview of the initial developments in the REIVE project (Smart Grids with Electric Vehicles). The main focus of the project is on smart grid infrastructures for large scale integration of EV and micro-generation units. It is a natural evolution of the InovGrid project promoted by the EDP Distribuição - the Portuguese Distribution Network Operator - and allows the development of seminal concepts and enabling technological developments within the Smart Grid paradigm. This paper presents the management and control architecture developed to allow electric vehicle integration in smart grid operation. Additionally, it presents the major impacts in distribution grids of the simultaneous deployment of electric vehicles, micro-generation and smart grid technologies.

Abstract
This paper describes the main results of the MERGE project relative to Electric Vehicle (EV) charging strategies and the impacts of EV integration on the steady-state grid operation. MERGE is a €4.5m, collaborative research project supported by the European Commission's Seventh Framework Programme (FP7). The consortium 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). One of the MERGE project missions is to evaluate the impacts that EV will have on EU electric power systems, exploring EV and SmartGrid/MicroGrid simultaneous deployment, together with renewable energy increase, to achieve CO 2 emission reduction through the identification of enabling technologies and advanced control approaches. The work presented proposes three charging strategies, dumb charging, multiple price tariffs and smart charging, and uses EV integration scenarios of adherence to these charging schemes. The resulting scenarios are tested using an algorithm coded with Python and using PSS/E, created within the MERGE framework to study EU grids steady-state behaviour. Additionally, the critical mass of EV adherence to smart charging schemes that brings positive impacts to the distribution grids operation was also evaluated.

Abstract
This work presents an approach to the flexibility of energy consumption in Renewable Energy Communities (RECs). A two-stage model for quantifying the flexibility provided by the domestic energy resources operation and its negotiation in a market platform is proposed. In stage 1, the optimal consumption of each prosumer is determined, as well as the respective technical flexibility of their resources, namely the maximum and minimum resource operation limits. In stage 2, this technical flexibility is offered in a local flexibility-only market structure, in which both the DSO and the prosumers can present their flexibility needs and requirements. The flexibility selling and buying bids of the prosumers participating in the market are priced based on their base tariff, which is the energy cost of the prosumers corresponding to their optimal schedule of the first stage when no flexibility is provided. Therefore, providing flexibility is an incentive to reduce their energy bill or increase their utility, encouraging their participation in the local flexibility market.