Electrification of mobility is paving the way in decreasing emissions from the transport sector; nevertheless, to achieve a more sustainable and inclusive transport system, effective and long-term planning of electric vehicles charging infrastructure will be crucial. Developing an infrastructure that supports the substitution of the internal combustion engine and societal needs is no easy feat; different modes of transport and networks require specific analyses to match the requirements of the users and the capabilities of the power grid. In order to outline best practices and guidelines for a cost-effective and holistic charging infrastructure planning process, the authors have evaluated all the aspects and factors along the charging infrastructure planning cycle, analysing different methodological approaches from scientific literature over the last few years. The review starts with target identification (including transport networks, modes of transport, charging technologies implemented, and candidate sites), second, the data acquisition process (detailing data types sources and data processing), and finally, modelling, allocation, and sizing methodologies. The investigation results in a decision support tool to plan high-power charging infrastructure for electric vehicles, taking into account the interests of all the stakeholders involved in the infrastructure investment and the mobility value chain (distributed system operators, final users, and service providers).

In smart grids the bidirectional exchange of large amounts of data will create a keen interdependence between electric system and communication, automation and control systems. In order to assess the performance of communication technologies for smart grid applications and find the most appropriate, co-simulation tools are crucial to simulate the behavior of both physical and cyber systems simultaneously, and properly consider their mutual interaction in planning and operation studies. This article aims at evaluating some wireless and wired communication technologies for smart grid implementation. The analysis performed shows that wireless technologies are potentially suitable for smart grid applications, while a combination of mixed wireless and wired technologies may introduce latencies that cannot match with mission critical functions, such as network protection.

Information and Communication Technologies (ICT), Wide Area Measurement Systems (WAMS) and state estimation represent the key-tools for achieving a reliable and accurate knowledge of the power grid, and represent the foundation of an information-based operation of Smart Grids. Nevertheless, ICT brings new potential vulnerabilities within the power grid operation, that need to be evaluated. The strong interdependence between power system and ICT systems requires new methodologies for modeling the smart grid as a Cyber Physical System (CPS), and finally analyzing the impact of ICT failures on the power grid operation. This paper proposes a novel methodological approach that combines Stochastic Activity Networks (SAN) modeling and numerical computation for dependability analysis of a 5G-based WAMS. Internal influences such as component failures and external influences such as rain effect are considered, and the impact of these failures are assessed over the WAMS capability to provide reliable data for performing an accurate power network state estimation. Different state estimation approaches (traditional SCADA and PMU-based algorithms) and weather conditions are compared in terms of mean states estimation error and safety. The results highlight that 5G based WAMS result in a close-to-ideal behavior which enforces the prospect of a future adoption for smart grid monitoring applications.

In Smart Grids the flow of electricity and information is strictly interrelated with the management and control of the electricity supply system. ICT is not only an extension or a modernization of the power system equipment, but a fundamental requirement for supporting the distribution network monitoring, operation and control. To enable monitoring and control of the Smart Grid and accommodate the large realtime data flow between controlled equipment and the distribution management system it is necessary the deployment of advanced sensors and measurement systems along with the communication network infrastructure. In this paper two different strategies for power network monitoring and control are compared: an LTE-based centralized management approach and a 5G-based distributed management approach. The two types of communications systems are compared considering their performances during fault management in a Smart Grid scenario.

Transition towards a smart grid requires network modernization based on the deployment of information and communication technologies for managing network operation and coordinating distributed energy resources in distribution systems. The success of the most advanced smart grid functionalities depends on the availability and quality of communication systems. Amongst the most demanding functionalities, those related to fault isolation, location and system restoration (FLISR) to obtain a self-healing smart grid are critical and require low latency communication systems, particularly in case of application to weakly-meshed operated networks. Simulation tools capable of capturing the interaction between communication and electrical systems are of outmost utility to check proper functioning of FLISR under different utilization conditions, to assess the expected improvements of Quality of Service, and to define minimum requirements of the communication system. In this context, this paper investigates the use of public mobile telecommunication system 4G Long Term Evolution (LTE) for FLISR applications in both radially and weakly-meshed medium voltage (MV) distribution networks. This study makes use of a co-simulation software platform capable to consider power system dynamics. The results demonstrate that LTE can be used as communication medium for advanced fault location, extinction, and network reconfiguration in distribution networks. Furthermore, this paper shows that the reduction of performances with mobile background usage does not affect the system and does not cause delays higher than 100 ms, which is the maximum allowable for power system protections.