Transport accounts for approximately 25% of Green House Gas emissions in Europe, with urban road transport being a major contributor to air pollution. Decarbonizing urban transport is essential, particularly as over 70% of Europeans reside in urban areas. Strengthening public transport, the most sustainable travel option for large populations, is a key strategy. This article focuses on urban tramways, formed by the urban traction electrification systems and electric public transport vehicles. A digital twin approach is proposed to improve the operational activities of tramways, aiming to optimize system design, enhance maintenance, improve reliability, and unlock unused infrastructure potential, such as using the tramway infrastructure for off-peak charging stations. This article presents the methodology adopted to develop the model of the tramway in Turin, Italy. This step is a milestone to implement the tramway digital twin. Moreover, this article presents the validation process of the model, which was carried out through a comparison with both simulated and field measurement data.

The growing demand for digital services has driven the deployment of increasingly large data centers, with in dividual facilities expected to reach gigawatt-scale power requirements in the near future. However, integrating such large loads into existing transmission systems requires careful planning to ensure efficient and timely grid connections while minimizing environmental impacts. In this context, this article introduces a methodology to support the optimal allocation of new data centers within an existing transmission grid. The proposed approach relies on Particle Swarm Optimization and explicitly accounts for the grid's hosting capacity while identifying allocations that remain technically feasible under a predefined set of contingency scenarios. By jointly addressing capacity limits and operational resilience, it enables data center placements that operate within the transmission infrastructure's limits and preserve system security under adverse conditions. A case study based on a real trans mission system with high-capacity data centers already in operation is presented, and the results indicate that the methodology can provide practical decision support for both transmission system planners and data center developers.

The decline in rotational inertia as a consequence of the increasing penetration of inverter-connected generation source may concern the grid security. This requires a significant amount of additional ancillary services. Grid-Forming (GFM) converters are pivotal since they may provide active inertia and damping power. The proposed work assesses the system-level techno-economic benefits of battery storage assets - equipped with GFM converters - delivering a variety of ancillary services under any operational mode. The resulting security-constrained scheduling model simultaneously optimizes energy production, rotational inertia, traditional primary response, inertial and damping response from GFM converters and secondary response. The formulation optimizes system-level requirements to ensure safe rate of changes of frequency, nadirs and quasi-steady state levels, avoiding unnecessary overscheduling of the battery power/energy headroom. Moreover, the model explicitly considers the effect of the energy recovery after delivering secondary response so that its deliverability from batteries is always guaranteed. Numerical simulations, applied to a future low-carbon scenario of the Great Britain system, prove the benefits of the proposed methodology against previous approaches.

Accurately and promptly extracting subsynchronous oscillation (SSO) components from measurements and locating SSO sources are crucial for SSO suppression. Existing transient energy flow (TEF) based SSO location methods suffer from low location accuracy and poor robustness. To cope with the shortcoming of the traditional TEF in SSO source location, This paper proposes a multivariate variational mode decomposition (MVMD) based SSO source location method to locate the SSO source from the measurements. Firstly, the multi-channel measurement matrix of each generator, including voltage and current measurements, is formed. Then, the multi-channel intrinsic mode functions (IMFs) are simultaneously decomposed from the formed multi-channel measurement matrix by using the MVMD approach, enabling the simultaneous decomposition of SSO components from measurements. Furthermore, the IMFs associated with the SSO mode are identified according to the Hilbert transform (HT). Using the identified IMFs, the MVMD-based TEF is calculated and the SSO source is located. Finally, the performance of the proposed method is evaluated using the simulation data of the modified 4-machine 11-bus test system and the field measurements from the Guyuan SSO event in the North China region. The results validate the accuracy and effectiveness of the proposed method in the SSO source location.

Smart Electrified Traction Systems (SETS) ma: play a pivotal role towards the decarbonization of the transpor sector and the integration of renewable energy sources. For thi reason, the paper proposes an up-to-date state of the art revier of the main configurations, operational schemes and flexibl assets forming these networks. Also, the intrinsic flexibility 0 these tractions systems calls for the optimal management of th assets in order to minimize the operational costs. This pape also reviews the main formulations of customized optimal powe flow problems, which incorporate the intrinsic features of thes networks. The critical analysis focuses on the reformulation techniques or algorithms adopted to overcome non-linear an non-convex constraints, typical of optimal power flow problems

The urgent need to decarbonize our cities places the transport sector—responsible for a significant share of greenhouse gas emissions—at the center of global sustainability efforts. Achieving this goal requires not only the electrification of public transport systems but also ensuring their efficiency and effectiveness to encourage widespread adoption over private vehicles. A promising strategy to modernize such systems is the implementation of a Digital Twin (DT), a virtual counterpart of the infrastructure that integrates real-time field data from strategically deployed sensors. This work focuses on trambased urban transport systems, where one of the most critical parameters for DT applications is the traction current absorbed by each vehicle. However, the deployment of dedicated onboard current sensors is often constrained by economic and timerelated limitations. To address this, we propose a transitional solution: a data-driven model capable of estimating tram current consumption using only GPS-based vehicle position data. Specifically, this paper presents a hybrid neural network architecture combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models. The network processes speed and acceleration profiles derived from open-access GPS data, eliminating the need for onboard instrumentation. The model was trained and validated with data from a targeted field measurement campaign, achieving a Mean Absolute Error (MAE) of 61.3 A and a Root Mean Square Error (RMSE) of 95.6 A. Given that the maximum absorbed current exceeds 900 A, these error values indicate that the model's predictive performance is within an acceptable range. This methodology provides a robust, low-cost solution for enabling early-stage DT development in Urban Traction Electrification Systems (UTES), supporting simulation and planning in the ongoing digital transformation of public transport.

The surge in Electric Vehicle (EV) adoption marks a crucial shift towards sustainable transportation solutions driven by environmental concerns. EVs offer various advantages, including reduced emissions, enhanced energy efficiency, and quieter operation. However, the EVs are also affected by faults and crashes, requiring personnel to repair them. Currently, no International, American, or European Standard is dedicated to work activities on EVs. This paper addresses the regulatory gap by examining the properties of the EVs, the risk sources, and the available standards related to generic electrical installations, or EV emergency scenarios. The study proposes suggestions for workshop setup, organizational procedures, and operational protocols to ensure safety during EV maintenance activities. Moreover, the processes of evaluating and managing the electric risks are presented for a real case study, in which technicians replace cells in a battery pack of an electric bus.

Digital Twin (DT) technology has emerged as a valuable tool for researchers and engineers, enabling them to optimize performance and enhance system efficiency. This paper presents a comprehensive Systematic Literature Review (SLR) following the PRISMA framework to explore current applications of DT technology in the power generation sector while highlighting key advancements. A new framework is developed to categorize DTs in terms of time-scale horizons and applications, focusing on power plant types (emissive vs. non-emissive), operational behaviors (including condition monitoring, predictive maintenance, fault detection, power generation prediction, and optimization), and specific components (e.g., power transformers). The time-scale is subdivided into a six-level structure to precisely indicate the speed and time range at which it is used. More importantly, each category in the application is further subcategorized into a three-level framework: component-level (i.e., fundamental physical properties and operational characteristics), system-level (i.e., interaction of subsystems and optimization), and service-level (i.e., value-adding service outputs). This classification can be utilized by various parties, such as stakeholders, engineers, scientists, and policymakers, to gain both a general and detailed understanding of potential research and operational gaps. Addressing these gaps could improve asset longevity and reduce energy consumption and emissions.

This paper presents the study and development of a high-performance voltage transducer for the accurate monitoring and control of traction voltage in tramway systems. The proposed transducer offers a more effective alternative to the Hall-effect sensors currently adopted, which suffer from some drawbacks such as limited frequency bandwidth and unsuitability for outdoor applications. The research activity is carried out in different steps. Initially, the typical characteristics of the voltage signals to be monitored, such as amplitude dynamics and spectral content, are analyzed. Attention is then focused on the environmental conditions in which the monitoring voltage transducer must operate. These preliminary analyses allowed for the definition of the key design constraints for the sensor under study. The article describes the implementation of the voltage transducer, with particular focus on the transducer typology, components selection, and insulation techniques, tailored to the identified design constraints. Preliminary results from laboratory experimental tests are presented and discussed, demonstrating the voltage transducer's high performance, with amplitude linearity within tens of ppm from 50 V to 1 kV and a frequency response error lower than 0.15% up to 2 kHz.

Regenerative braking of trains is a crucial method of harnessing energy, significantly improving the overall efficiency of DC networks by repurposing energy during acceleration or returning it to the grid. Various strategies have been developed to optimize this process, including on-board and off-board energy storage systems using a third rail, as well as systems designed to return energy to the overhead line via pantographs. This paper focuses on a detailed analysis using a 40kWh Electric Vehicle (EV) charger to evaluate the regenerative braking energy produced by trams operating at the Caio Mario Park Tram Station in Torino, Italy. The station serves as a vital connection point for two primary zones, where multiple trams operate at varying intervals. An AC-DC 12-pulse rectifier is installed upstream of the DC bus-bar, converting the 22kV three-phase AC power into 600V DC to match the operational voltage of the tram system. This DC bus-bar not only supplies power to both zones, but also supports EV chargers. The energy recovered from the trams during braking can be channeled directly into the EV charger for vehicle recharging or routed back to the grid’s auxiliary systems through a DC-AC converter, enhancing the overall energy management of the network. Current probes are strategically installed to monitor the energy flow between the two regions and the EV charger, providing detailed measurements of the energy delivered and reclaimed. The data collected by these probes are subsequently processed using Matlab/Simulink for a comprehensive analysis. This approach allows for an in-depth examination of the energy-transfer dynamics, efficiency of energy recovery, and the potential impact on the DC grid’s performance. The findings offer valuable information on optimizing regenerative energy utilization, contributing to a more sustainable and efficient tram network.

The accelerating adoption of electric vehicles and their integration into smart grids through Vehicle-to-Everything technologies present novel opportunities for enhancing energy efficiency and grid stability. This study explores the potential of leveraging electric vehicles within building energy systems, employing a digital twin model for comprehensive analysis and optimization. By simulating various scenarios, including standard and cloud-impacted photovoltaic production and different energy pricing strategies, the research assesses the operational and eco-nomic impacts of utilizing a V2G-enabled car park. The proposed formulation is cast as mixed-integer linear programming, tested through a digital twin approach, demonstrates improvements in energy management and cost efficiency. The findings suggest that, under certain conditions, the bidirectional energy flow capabilities of electric vehicles can effectively substitute for traditional stationary storage systems, offering a dual benefit of vehicle charging and grid support.

The rapid adoption of Electric Vehicles requires advancements in Electric Vehicle Supply Equipment to accommodate the demand for enhanced performance. Commercial chargers now enable vehicles to inject power into the grid. However, the operation of the chargers introduces also distortions, in particular when multiple chargers operate simultaneously at the same node. This paper investigates the interaction between two different DC charging stations: one unidirectional and the other bidirectional. Then the analysis is extended to the harmonic interaction between the chargers. The results demonstrate the significant influence of the charger operation on grid power quality and highlight the importance of managing harmonic distortion.

The intrinsic complexity of smart grids requires computer-aided power system analysis to evaluate novel monitoring and control strategies and innovative devices. Due to the enormous computational requirements and the necessary Hardware-In-the-Loop (HIL) and Power Hardware-In-the-Loop (PHIL) applications, real-time power system simulation plays a fundamental role in this context. However, performing real-time simulations in a monolithic way, i.e. exploiting a single Digital Real-Time Simulator (DRTS) rack, could result in the inability to create reliable and accurate digital twins of increasingly complex power systems such as smart grids. This paper proposes a digital real-time power system co-simulation to link different DRTS and scale up the viable Power System Under Test (PSUT). It exploits Aurora 8B/10B to manage the data exchange and a Distributed Transmission Line Model (DTLM) to split the PSUT into the two real-time simulation environments. Furthermore, the DTLM permits the absorption of the communication latency, which normally occurs in real-time co-simulation, into the propagation model of a transmission line. With the presented setup, a time step duration of $50 \mu \mathrm{s}$ proves to be stable and accurate when running a co-simulated Electro-Magnetic Transients (EMT) analysis of a power grid scenario by interconnecting two commercial DRTS (i.e. OPAL-RT) with comparable results compared to the monolithic simulation, extending the scalability of future real-time smart grid simulations.

Recently, there has been a significant interest in the integration of engineering systems into digital formats. This trend has attracted considerable attention because of the numerous advantages it offers in terms of enhancing system performance and reducing costs. Within digitalization techniques, one approach that has gained prominence is the utilization of Digital Twins (DTs). DTs have emerged as a promising method for improving performance, reducing maintenance and operation expenses, and ensuring the safety of associated systems. This research provides an in-depth analysis of the key concepts and characteristics of existing studies on DTs applied in diverse energy systems areas. This study also illustrates the wide range of application areas where DT technology can be employed in power systems such as battery management systems, power monitoring systems, microgrid management, fault detection, and demand forecasting. Furthermore, the research aims to provide insights into future research directions that can facilitate the practical implementation of DTs in various domains.

Smart Grid integration plays a crucial role in transitioning towards a climate-neutral future by enabling advanced monitoring, management, and control of renewable energy sources, energy systems, and networks. However, several barriers related to technological, economic, regulatory, and social aspects hinder the integration of these innovative resources and strategies into current power systems due to the inherent complexity of heterogeneous technologies, entities, and actors. For example, interoperability issues, cybersecurity concerns and data management are relevant to the integration and digitalization of smart grids. To address these challenges, this paper proposes a hybrid multi-model co-simulation infrastructure to simulate innovative Smart Grid scenarios. The infrastructure enables the interconnection of heterogeneous software simulators with real-time hardware simulators within a shared and distributed co-simulation environment, facilitating Hardware-In-the-Loop (HIL) applications through a semi-automated scenario configuration procedure. The proposed infrastructure’s capabilities and performance are assessed through a smart grid scenario, focusing on implementing a distribution voltage regulation service provided by distributed resources installed on a building premise. Specifically, the scenario includes a physical smart meter device interconnected in HIL with the simulated building energy management system to test the integrated functionality and interoperability for the ancillary service. The scenario results demonstrate the facilitated scenario design process, and the promising performance and low co-simulation latencies of the co-simulation infrastructure when coupling software and hardware simulators with HIL applications. Overall, the infrastructure has the potential to assist researchers, system operators, and energy stakeholders in evaluating Smart Grid scenarios and designing, developing, and testing new systems, technologies, and business models.

Cold ironing represents an effective solution to remove air-polluting emissions from ports. The high voltage shore connection (HVSC) system is the key enabling facility that allows providing power from the shore-side electrical system to the ship. The design of the shore connection needs a comprehensive assessment of the fault currents in different operating scenarios. International standards require the neutral point of the shore connection transformer to be equipped with a neutral grounding resistor. Its value has to be defined to guarantee the safety and protection of equipment and personnel in the case of single phase-to-ground faults. Moreover, three-phase short circuits need to be considered to size equipment and protection devices. A crucial role is played by the frequency converter control system, required to adapt the mains frequency to the frequency of the ship. In this work, a complete electromagnetic dynamic model of the HVSC has been developed, including a frequency converter, a shore-side transformer, connection medium voltage (MV) cables, and a power system of the ship, to analyze in detail the behavior of the system in the case of single phase-to-ground fault and three-phase short circuit, taking into account relevant standards and best practices.

The need for decarbonizing the entire energy system calls for new operational approaches in different sectors, currently (almost) fully dominated by fossil fuels, such as the transports. In particular, the decarbonization of the light-duty passenger transport, based on the implementation of Battery Electric Vehicles, may have a twofold benefit, because of (i) the reduction of local and global direct emissions, and (ii) the role that the Battery Electric Vehicles can have in supporting the operation of the power system in case of large share of non-dispatchable renewable energy sources. This paper aims to investigate, through a Power Hardware-In-the-Loop laboratory setup, the impacts of the Vehicle-to-Grid and Grid-to-Vehicle paradigms on a Low Voltage grid portion serving as grid infrastructure a car parking. The results show that the Low Voltage grid losses, if not taken into account, can cause a wrong evaluation of the expected impact on the grid of the Battery Electric Vehicles. Furthermore, the harmonics of current injected into the grid by several chargers could compromise the perceived power quality. Both the analyzed aspects must be hence carefully considered for properly evaluating pros and cons that the installation of several chargers may have on the grid side. The main contributions refer to the calculation of losses and to the evaluation of the power quality aspects through a Power Hardware-In-the-Loop configuration, enabling to take into account the interaction between charging stations and power grid. & COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Managing a large share of non-dispatchable renewable energy sources requires new approaches, which have to be integrated with existing and well-established control systems currently used to guarantee power system operation. In this context, the number of energy communities is expected to increase, and hence their effective integration is fundamental. This paper aims at assessing the role and impact of energy communities on the operation of a transition power system, still having a share of active traditional power plants. Simulation models and real hardware have been included in the experiment, based on a live real-time co-simulation. The results highlight both the significant contribution that the methodology (i.e., geographically-distributed real-time co-simulation) can give in informing and driving energy transition policies and the important role that energy communities may have in supporting the transition towards completely de-carbonized power systems.

Real Time Simulation is a powerful tool to study the dynamics of power systems, in particular when combined with Power Hardware-In-the-Loop. However, obtaining a stable test setup for Power Hardware-In-the-Loop is not trivial, as system stability is influenced by several factors. In this paper the stability of a Power Hardware-In-the-Loop test setup is studied. The focus is on evaluating the hardware used and the interaction of the tested hardware in the virtual environment. The methodology used to analyze the stability of the test setup, including the measurement of the dynamic response of the system and the evaluation of the hardware components, is presented. The results of the study demonstrate the effectiveness of the proposed method in achieving a stable test setup for Power Hardware-In-the-Loop simulations. The findings of this research can be used to improve the reliability of Power Hardware-In-the-Loop simulations for power systems and provide a better understanding of the behavior of the tested hardware in a virtual environment. Furthermore, the paper highlights the importance of evaluating the hardware components' responses (in particular that of the power amplifier) and their interactions in Power Hardware-In-the-Loop simulations in order to achieve a stable test setup.

Electromagnetic transients (EMT) is the most accurate, but computationally expensive method of analyzing power system phenomena. Thereby, interconnecting several real-time simulators can unlock scalability and system coverage, but leads to a number of new challenges, mainly in time synchronization, numerical stability, and accuracy quantification. This study presents such a cosimulation, based on digital real-time simulators (DRTS), connected via Aurora 8B/10B protocol. Such a setup allows to analyze complex and hybrid system-of-systems whose resulting numerical phenomena and artifacts have been poorly investigated and understood so far. We experimentally investigate the impact of IEEE 1588 precision time protocol synchronization assessing both time and frequency domains. The analysis of the experimental results is encouraging and show that numerical stability can be maintained even with complex system setups. Growing shares of inverter-based renewable power generation require larger and interconnected EMT system studies. This work helps to understand the phenomena connected to such DRTS advanced cosimulation setups.