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With more electric vehicles introduced in society, there is a need for the further implementation of charging infrastructure. Innovation in electromobility may result in new charging and discharging strategies, including concepts such as smart charging and vehicle-to-grid. This article provides an overview of vehicle charging and discharging innovations with a cable connection. A MATLAB/Simulink model is developed to show the difference between an electric vehicle with and without the vehicle-to-grid capabilities for electricity grid prices estimated for Sweden for three different electric vehicle user profiles and four different electric vehicle models. The result includes the state-of-charge values and price estimations for the different vehicles charged with or without a bidirectional power flow to and from the electric grid. The results show that there is a greater difference in state-of-charge values over the day investigated for the electric vehicles with vehicle-to-grid capabilities than for vehicles without vehicle-to-grid capabilities. The results indicate potential economic revenues from using vehicle-to-grid if there is a significant variation in electricity prices during different hours. Therefore, the vehicle owner can potentially receive money from selling electricity to the grid while also supporting the electric grid. The study provides insights into utilizing vehicle-to-grid in society and taking steps towards its implementation.

The decarbonization of the power generation and transport sector encourage the analysis of connection of distributed energy resources (DER), such as electric vehicles (EVs), to the electrical system, as well as the evaluation of their impact on smart cities. A better understanding of the negative impacts on the power systems will lead to propose mitigation measures and eventually revolutionize the way distributed generation works. This paper aims at modelling and evaluating the impact of EVs on a real distribution network. The energy system chosen operates at 60 Hz, 34.5 kV (medium voltage) and 0.208 kV (low voltage) and it is simulated using PSCAD/EMTDC. To reproduce realistic user consumption profiles, dynamic load profiles based on EV owners behaviour have been simulated. The vehicle-to-grid (V2G) technology is modelled to mitigate the impacts of high penetration of EVs by supporting the network from undervoltage. The results show the importance of active management in modern power systems, especially considering the increase in DER penetration expected for the coming years. This work shows the benefits of implementing V2G technology while highlighting the challenges involved in a real case. This paper aims at modelling and evaluating the impact of EVs on a real distribution network. The V2G technology is modelled to mitigate the impacts of high penetration of EVs by supporting the network from undervoltage. This work shows the benefits of implementing V2G technology while highlighting the challenges involved in a real case.image

Flexibility has increasingly gained attention within the field of electrification and energy transition where a common objective is to reduce the electricity consumption peaks. However, flexibility can increase the risk of grid congestion depending on where and when and it is used, thus an overall system perspective needs to be considered to ensure an effective energy transition. This paper presents a framework to assess electricity users' contributions to grid load peaks by splitting electricity consumption data into subsets based on time and temperature. The data in each subset is separately correlated with the grid load using three correlation measures to assess how the user's consumption changes at the same time as typical grid peak loads occur. The framework is implemented on four different types of business activities at Uppsala municipality in Sweden, which is a large public entity, to explore their behaviors and assess their grid peak load contributions. The results of this study conclude that all four activities generally contribute to the grid peak loads, but that differences exist. These differences are not visible without splitting the data, and not doing so can lead to unrepresentative conclusions. The presented framework can identify activities that contribute the most to unfavorable grid peaks, providing a tool for decision-makers to enable an accelerated energy transition.

This study investigates the potential implementation of a microgrid at Dansmästaren, a multifunctional building in Uppsala, Sweden, comprising a supermarket, residential apartments, and a parking garage. This paper analyzes the load profiles of the various components within Dansmästaren and the Uppsala grid to identify overlapping peak demand periods that increase overall facility power consumption and contribute to grid congestion. Focus is given to the three days with the highest peak loads; the worst day for Uppsala’s distribution grid, the highest peak for the entire building, and the highest peak for the parking garage, representing the most challenging scenarios for the microgrid. The study explores how integrating smart charging capabilities for electric vehicles in the parking garage can provide flexibility to shift loads and mitigate peak demands during these worst-case days. A flexibility index quantifies the extent to which the parking garage’s smart charging capabilities can support the building’s energy needs and reduce grid strain during peak demands. The study demonstrates a high potential for demand-side flexibility in Dansmästaren, as reflected by the Time Flexibility Index values of 0.77, 0.79, and 0.72. These results underscore the effectiveness of smart charging strategies in reducing peak loads and enhancing grid stability. The findings suggest that more advanced approaches could further improve building sustainability, especially in light of Sweden’s growing adoption of electric vehicles. This study encourages innovative urban solutions and provides a foundation for future research.

As the global transition away from fossil fuels accelerates, energy systems across the globe face a significant challenge. Given the high energy consumption of electric vehicle chargers, effective control is imperative to prevent local grid overload and congestion. In Uppsala, Sweden, a newly built parking garage includes 30 electric vehicle chargers, 62 kW solar energy production, and a 60 kW/137 kWh battery energy storage system. This paper presents a control algorithm that uses a negative correlation scheme, adjusted to the local grid load, to effectively manage the battery energy storage. To improve the performance of the algorithm, a genetic optimization method is applied to find the best feasible daily load profile for the parking garage. The results indicate that peak load and energy consumption during grid high-load hours can be significantly reduced. This also results in an 9.5−12.8% reduction in electricity distribution fees at current prices as well as a peak load reduction of up to 50 %. Increasing the battery capacity and charging/discharging power in the scenarios analysed within the study will improve the algorithm’s ability to achieve a satisfactory negative correlation between the load demand of the facility and the local grid. The proposed control algorithm lowers the facility’s impact on the local grid during high-load peak hours by utilizing the battery energy storage system at the parking garage. Moreover, it decreases the distribution fees of the facility by lowering the load peaks and shifting the electricity consumption to the morning and night.

With more electric vehicles introduced in society, there is a need for further implementation of charging infrastructure. Innovation in electromobility may result in new charging and discharging strategies, including novel concepts such as smart charging, vehicle-to-grid and vehicle-to-everything. Access to charging infrastructure and novel ideas on charging or discharging may contribute to driving the transition towards e-mobility. This article aims to provide an overview of vehicle charging and discharging innovations with a cable connection, including an example of a MATLAB/Simulink model of vehicle-to-grid dynamics.

The need for a more flexible usage of power is increasing due to the electrification of new sectors in society combined with larger amounts of integrated intermittent electricity production in the power system. Among other cities, Uppsala in Sweden is undergoing an accelerated transition of its vehicle fleet from fossil combustion engines to electrical vehicles. To meet the requirements of the transforming mobility infrastructure, Uppsala municipality has, in collaboration with Uppsala University, built a full-scale commercial electrical vehicle parking garage equipped with a battery storage and photovoltaic system. This paper presents the current hardware topology of the parking garage, a neural network for day-ahead predictions of the parking garage’s load profile, and a simulation model in MATLAB using rule-based peak shaving control. The created neural network was trained on data from 2021 and its performance was evaluated using data from 2022. The performance of the rule-based peak shaving control was evaluated using the predicted load demand and photovoltaic data collected for the parking garage. The aim of this paper is to test a prediction model and peak shaving strategy that could be implemented in practice on-site at the parking garage. The created neural network has a linear regression index of 0.61, which proved to yield a satisfying result when used in the rule-based peak shaving control with the parking garage’s 60 kW/137 kWh battery system. The peak shaving model was able to reduce the highest load demand peak of 117 kW by 38.6% using the forecast of a neural network.

The electrification of the transport sector is of crucial importance for a successful transition to a fossil-free society. However, the electricity grid constitutes a bottleneck. This article provides a case study based on a real-world parking garage with a smart grid infrastructure, called Dansmästaren. The analysis shows how renewable energy sources, energy storage technologies, and smart charging of electric vehicles can smooth out the load curve of the parking garage and relieve the electric grid during peak hours. Dansmästaren is located in Uppsala, Sweden, and equipped with 60 charging points for electric vehicles, a PV system, and a battery storage system. The study utilizes an energy flow model to show the potential of a realistically dimensioned smart energy system, that can benefit the parking facility in itself and the local distribution grid in a city, Uppsala, with grid capacity challenges. The results suggest that the parking garage demand on the local grid can be significantly lowered by smarter control of its relatively small battery energy storage. Moreover, further smart control strategies can decrease demand up to 60% during high load hours while still guaranteeing fully charged vehicles at departure in near future scenarios. The study also shows that peak shaving strategies can lower the maximum peaks by up to 79%. A better understanding of the potential of public infrastructures for electric vehicle charging helps to increase knowledge on how they can contribute to more sustainable cities and a fossil-free society.

The distribution grid in Uppsala, Sweden, has during the last years experienced an increasing number of hours with congestion, and as the city and number of EVs are growing new solutions are needed to not worsen this problem. Uppsala Municipality is planning a series of so-called “mobility houses” which will act as a hub for transportation while, at the same time, supporting the transition to a fossil-free energy system. Dansmästaren – the first mobility house in Uppsala – was built in 2020 and this paper describes its parking garage's main energy system parts, giving a brief introduction and analysis of each and their potential effect on Dansmästaren's grid impact. Dansmästaren has the potential to control its load on the grid, but it is essential to collect more data and analyze when flexibility is of most importance. Future studies suggest analyzing Dansmästaren's systems in more detail and developing a more advanced energy management system.

To obtain a maximum power output and minimized capital and operational costs, the layout of wave energyparks needs to be optimally designed. An economical model for large-scale wave energy systems is built andmerged into an evolutionary optimization routine for arrays of point-absorbing energy converters. The modelincludes all the parameters that affect the total system revenue such as electrical cable lengths, distance fromgrid connection point, number of substations and hydrodynamic interaction among the devices, with the goal tofind the optimal layout which minimizes the levelized cost of electricity. Converters inside the park are groupedin clusters via a k-means clustering algorithm, which allows to minimize the intra-array cable length under theinput of real wave climates. The results show that the hydrodynamical interaction has a large impact on theoptimal design of wave energy parks, and that the length of the intra-array cable does not play a significant rolein the economical layout optimization routine for the studied wave energy park system.