Bruna Costa Tavares

Abstract
This chapter presents key insights for the planning and operation of distribution power grids integrating high shares of renewable generation and charging capacity for electric vehicles (EVs). Case studies are presented to illustrate the impact of expected trends for vehicle electrification in the operation and future expansion of distribution power grids. The potential of innovative approaches is also exploited. The smart-transformer concept based on solid-state-transformer architectures as well as hybrid AC/DC distribution grids is qualitatively evaluated as a suitable solution for the massive integration of EV charging.

Abstract
Taking advantage of the flexibility of Distributed Energy Resources (DER) can help improve distribution network efficiency, reliability and resilience. EUniversal project aims to facilitate the use of flexibility services and interlink active system management of distribution system operators with electricity markets. congestion management and voltage control have been identified has the most relevant needs, within different operation timeframes, namely: from day, weeks and years ahead. This paper considers long-term flexibility services to support maintenance actions, increasing the periods where is technically possible to perform maintenance actions maintaining security of operation. The methodology developed to schedule planned maintenance actions based on forecasted network profiles, maintenance costs, network reconfiguration capability and flexibility contracted in long-term flexible markets will be presented. © The Institution of Engineering and Technology 2023.

Abstract
Recent advances in electric vehicle (EV) charging capability have seen a wide growth in the consumer market, which will continue to increase in future years with favourable policy incentives. However, the uncontrolled connection and charging of EV may have an adverse effect on three-phase distribution grids operation. This paper presents the impact of EV integration in a real LV Portuguese urban network. It analyses the network loading, energy losses, and voltage imbalances, under different scenarios of EV charging location and phase connection. The DIgSILENT Power Factory software is used in the voltage imbalance studies. Preliminary results show that the voltage drop in the analysed network is significantly affected by the location of the EV. Furthermore, as expected, the unbalanced EV loading leads to an increase of voltage unbalance between phases which is more pronounced when higher levels of EV are considered. © 2021 The Institution of Engineering and Technology.

Abstract
The increasing integration of Distributed Energy Resources (DER) in electricity networks has required an improvement in the network management procedures. While the operation paradigm is evolving and adapting to the new network features, the planning approach is rather inefficient as network assets are usually oversized to meet the worst-case scenario. In this regard, this paper presents an innovative methodology that integrates the potential flexibility of DER into the planning process, in an attempt to bridge the gap between current network operation approaches and the planning methods. It includes an analysis of future scenarios, providing different reinforcement plans considering the realistic network operation for those scenarios. The proposed optimal design of the reinforcement plans has two complementary processes: First to optimize flexible resources in their owner's perspective and second to reschedule the flexible resources' operation when the DSO needs to solve technical problems. The model has been tested in a typical Portuguese medium voltage network using future scenarios of DER integration from ENTSO-E. The results conclude that the proposed methodology leads to cost-effective solutions, which provide a better use of flexible resources, deferring high capital investments in network reinforcement.

Abstract
In this article, we present a holistic framework for the integration of electric vehicles (EVs) in electric power systems. Their charging management and control methodologies must be optimized to minimize the negative impact of the charging process on the grid and maximize the benefits that charging controllability may bring to their owners, energy retailers, and system operators. We have assessed the performance of these methods initially through steady-state computational simulations, and then we validated them in a microgrid (MG) laboratory environment.