Distributed generation, such as photovoltaics (PVs), and electrification of heating and transportation with heat pumps (HPs) and electric vehicles (EVs) will play a major role in the energy transition. However, these low-carbon technologies (LCTs) do not come without side effects such as voltage violations, power loss increase, component overloading, higher energy consumption, power peaks, and power quality issues, e.g., harmonics and phase unbalance. This work constitutes a review analysis and summary of all the important findings concerning the various grid impact issues that can appear due to the grid integration of these 3 LCTs. The work also encapsulates various research characteristics such as grid topology, seasons, simultaneous operation under various LCT combinations, penetration levels, etc. Moreover, it incorporates a qualitative analysis of the impact level of the most investigated grid issues and quantitative comparisons between the different grid types and LCTs. It has been shown that the combined integration of PVs-EVs and PVs-HPs can result in mitigation effects without extra solutions. Moreover, voltage deviations and unbalance affect more the rural grids while component overloading is more hazardous for suburban grids. Finally, proposed mitigation solutions, such as energy storage, smart charging, etc., are correlated with their respective grid impact issues.

This paper proposes a shared multi-stakeholder PV system for traction substations and nearby residential loads to reduce the need for storage, AC grid exchange, and curtailment. The residential stakeholders offer both the base electrical load and the solar panels installation space needed by the traction stakeholder, who brings the peak load and investments to the former. Two case studies were conducted for one year in the city of Arnhem, The cy=Netherlands, using comprehensive and verified simulation models: A high-traffic and a low-traffic substation. The results showed a positive, synergetic benefit in reducing the PV system's excess energy and size requirement for any type of traction substations connected to any number of households. In one detailed example, the multi-stakeholder system suggested in this paper is shown to reduce curtailment by up to 80% in moments of zero-traction load. Generally, the direct load coverage of a PV system is increased by as much as 7 absolute percentage points to the single-stakeholder system when looking at energy-neutral system sizes. This multi-stakeholders system offers then an increase in the techno-economic feasibility of PV system integration in urban loads.

Power control of flexible loads will play a significant role in energy transition. This work has developed a mixed-integer linear power control (MILP) model that manages electric vehicle (EV) chargers, heat pumps (HPs), and PV rooftops. The power control was tested with and without vehicle-to-grid (V2G) capabilities in different grid types, namely residential, commercial, and mixed grids. Moreover, the effect of different seasons and charger efficiencies was investigated. It was shown that grid characteristics such as EV parking times and building occupations can affect significantly the power control, e.g. the amount of imported and V2G power. Moreover, while V2G power is rarely used due to current V2G round-trip efficiency, future efficiency improvement can lead to a significant increase in V2G use. Finally, the seasonal effect had also a significant impact with Summer being characterized by higher exported and lower imported energy due to the high and prolonged PV power availability.

The rising demand for electric vehicles (EVs) in the face of limited grid capacity encourages the development and implementation of smart charging (SC) algorithms. Experimental validation plays a pivotal role in advancing this field. This article formulates a hierarchical mixed integer programming EV SC algorithm designed for low voltage (LV) distribution grid applications. A flexible receding horizon scheme is introduced in response to system uncertainties. It also considers the practical constraints in protocols, such as IEC/ISO 15118 and IEC 61851-1. The proposed algorithm is verified and assessed in a power hardware-in-the-loop testbed that incorporates models of real LV distribution grids. Furthermore, the algorithm's capabilities are examined through eight scenarios, out of which four focus on the uncertainties of the input data and two address the engagement of extra grid capacity restrictions. The results demonstrate that the SC algorithm adequately lowers the EV charging cost while fulfilling the charging demand, and substantially reduces the peak power as well as the overloading duration, even when faced with input data uncertainty. The additional grid restrictions in place are proven to improve peak demand reduction and overloading mitigation further. Finally, the limitations and potentials of the developed algorithm are scrutinized.

Electric aircraft is a promising alternative to conventional fuel-based aircraft, offering reduced greenhouse gas emissions and enhanced operational efficiency. To ensure seamless operations and optimize energy management, accurate electric aircraft charging demand prediction becomes imperative. This paper presents a study on forecasting the charging demand for future small, short-range electric aircraft. First, battery sizes are determined for various types of small all-electric aircraft and electric vertical takeoff and landing aircraft. Utilizing the electrical circuit model for lithium-ion batteries, this study derives the charging power curve of electric aircraft under the constant current constant voltage charging strategy. Subsequently, charging demand prediction is conducted using the flight schedule of a selected airport, allowing for a realistic assessment of the power requirements for charging electric aircraft. Finally, case studies exploring charging demand under different scenarios are conducted. The results highlight the substantial power demand associated with the charging process, emphasizing the essential infrastructure needs and potential approaches for managing charging power in electric flight.

Electric aircraft technology has gained considerable attention and is rapidly developing to mitigate the environmental impact of air transportation and move toward more sustainable modes. Nevertheless, the unique characteristics of electric aircraft pose significant challenges for the charging infrastructure, which must be effectively addressed to facilitate the growth of electric aircraft. This article provides a comprehensive review of the latest developments and future trends in electric aviation, which covers electric aircraft, battery technology, and electric aircraft charging systems. This article also surveys the possible charging system architectures that can be employed for electric aircraft charging. Various power electronic converter topologies that are suitable for future electric aircraft dc fast chargers are presented. This article concludes by identifying future challenges in the path toward charging electric aircraft and discusses potential solutions to these challenges.

The large Electric Vehicle (EV) fleet penetrations can provoke several grid impact issues if no EV smart-charging is implemented. However, many EV smart-charging works assume an accurate prediction of input data, such as the EV driving patterns, which are highly uncertain. This paper addresses the impact and potential management of several uncertainties related to EV smart charging, such as photovoltaic (PV) generation, load demand, arrival state-of-charge (SOC), requested energy, and arrival and departure time of the EVs. The application of different levels of uncertainty budgets is proposed to account for the gradual impact of every uncertainty on smart charging performance. Moreover, potential uncertainty management is investigated with the use of robust optimization (RO) in predictive receding-horizon EV smart charging under the worst-case uncertainty level, and the ''price of robustness"is calculated. The results show that the EV driving uncertainties are more hazardous for the provided charging energy. In contrast, PV generation and load demand uncertainties have a significant impact mostly on the charging cost. Moreover, the price of robustness is very low for EV charging under every uncertainty case.

In the presence of a catenary infrastructure, the transition from fossil fuel-based bus fleets to electric-powered ones can be facilitated through conventional trolleybuses or In-Motion-Charging trolleybuses, offering environmentally friendly and cost-effective solutions. However, grid congestion at traction substations (TSs) can limit this transition as the grid operator is incapable or unwilling to provide more capacity. As grid connection contracts are typically tallied and billed in periods of 15 minutes, stationary energy storage devices can prove useful in short-term buffering of the power demand. Consequently, more electrification projects can be rolled out under the same, or minimally extended grid contract. In this aim, this paper looks at validating energy storage as a means of enabling bus fleet electrification. It presents a power management strategy that controls the power exchange between the energy storage system (ESS) within the TS, specifically to manage the 15-minute average power. This strategy also serves as a tool for sizing the ESS with the minimum capacity required for the application. A case study for the city of Bologna, Italy, has been considered to validate the proposed approach. The findings indicate that billing contract power can be reduced by up to 41.7% when a storage device actuates in high-energy-demand substations. Furthermore, different types of Lithium-ion cells, including their second-life versions, are compared to determine the most beneficial options under limited cost and volume constraints. Recommendations are drawn on the exact scenarios where each type of cell is most beneficial.

The development of lithium-ion batteries has experienced massive progress in recent years. Battery aging models are employed in advanced battery management systems to optimize the use of the battery and prolong its lifetime. However, Li-ion battery cells often experience fluctuations in battery capacity and performance during cycling, which makes capacity prediction more difficult. Moreover, the reason for the capacity regeneration phenomenon occurring after resting periods is not clear yet, as well as the influence of cycling conditions on capacity regeneration. A relationship between this phenomenon to cycling state of charge (SoC) ranges and current rates was investigated in this paper on a battery cell with Lithium Nickel Manganese Cobalt Oxide positive electrode. Experimental results show that the capacity increase is a consequence of decreased internal impedance after the resting period. The experiments also showed that a significant power drop and subsequent power regeneration after a resting period occurs only for specific SoC ranges, and applying a resting period after battery cycling can mitigate this power fading process. The semi-empirical model of battery degradation including capacity regeneration is proposed in this paper based on physical processes inside of the cell retaining low computational requirements. The acquired results can be utilized in battery management systems for more accurate state of health estimation and to prolong battery lifetime.

The aviation industry, responsible for over 2% of energy-related CO₂ emissions in 2022, aims for Net Zero Emissions by 2050. Despite electric aircraft's environmental benefits and improved operational efficiency, the current battery technology limits their range and size. Based on the optimal system voltage and power profile of the reference all-electric aircraft, this paper presents the design of a hybrid reconfigurable battery pack. The design incorporates a combination of high-specific-energy (263 W h kg^-1 at cell level) and high-specific-power (1800 W kg^-1 at cell level) battery types and its performance is compared with that of a fixed configuration battery pack comprising a single battery type. Simulation results suggest a potential 900 kg (18% lighter than fixed configuration) weight savings with reconfigurable pack, translating into enhanced payload, energy savings, or range extension for 9 PAX Eviation Alice electric aircraft at just 0.4% more energy capacity loss in 500 cycles.

Solar PV systems have so far been the source of choice for the sustainable supply of urban electric transport networks—like trams and trolleybus grids. However, no consensus exists yet on the placement or sizing of PV systems at the traction substations, and no method is available for easy estimation of the PV system utilization performance. The latter is crucial for understanding the need for storage, grid exchange, or even power curtailment, and has therefore a direct impact on the technical and financial feasibility of the project. This paper looks at 11 Key Performance Indicators (KPI) that are available to trolleybus operators, in two PV case studies on Arnhem (NL) and Gdynia (PL), using verified and validated bus, grid, and PV models. Through one KPI, namely the here-defined Energy Traffic KPI, a strong trend (R²=0.93) is described that can now allow stakeholders a quick estimation of the PV potential using a simple third-degree polynomial instead of resorting to the complex grid, bus, and PV modelling. A simple placement and sizing method is also presented derived from this KPI, in a way as to increase the technical and economical feasibility of an installed PV system. Despite all efforts, stakeholders are still warned of an intrinsic, upper-performance plateau that exists in transport grids, at around 38% direct PV utilization, caused by the unavoidable mismatch between PV generation and vehicle timetables and schedules. Stakeholders are urged to implement more smart grid loads as a base load to increase the feasibility of their investments in renewables, and to transform the transportation systems thereby to multi-functional grids that can assist the main city grid.

Low Carbon Technologies (LCTs), such as Photovoltaics (PVs), Electric Vehicles (EVs), and Heat Pumps (HPs), are expected to cause a huge electric load in future distribution grids. This paper investigates the grid impact in terms of over-loading and nodal voltage deviations in different distribution grids due to increasing LCT penetrations. The major objectives are the identification of the most severe LCT, grid impact issue, seasonal effect, and vulnerable distributional area, considering the physical models of the LCTs. It is concluded that Winter is the most hazardous for the future grid impact, characterized by nearly 3 times higher over-loading and 2.5 times higher voltage deviations during high HP penetrations, while suburban areas are the most vulnerable. Moreover, while HPs seem to have, in general, a greater impact compared to EVs, EVs cause more prolonged violations. While this work follows a bottom-up approach, using detailed physical models, aggregated national data has also been acquired, which is often used by top-down approaches. Different grid impact issues have been compared for the two approaches in terms of magnitude and duration. While bottom-up approaches generate more pessimistic results regarding the magnitude of the violations, results about the duration of the violations can be contradictory.

The decarbonization of urban bus fleets can be made by their electrification as in-motion-charging (IMC) buses which can run as trolleybuses or in battery mode. The benefit is that IMC buses can use the existing trolleygrid infrastructure where their route overlaps with it to charge the battery and operate in battery mode outside of it. Presently, the IMC battery charging power is set conservatively to the minimum of all the spare capacities of the traction substations (SSs) found along the bus route. This can render most electrification projects techno/economically infeasible as not enough energy is picked up for the battery-mode operation and long charging times at bus terminals are required. This article proposes then an adaptive charging approach that uses the locally available spare capacity under any traction SS, taking into account the limitations of the maximum SS power and the minimum line voltage. The method is proven here both theoretically and in a case study over one full year of operation of four electrified diesel/compressed natural gas (CNG) bus lines in Arnhem, The Netherlands, using comprehensive and verified trolleybus and trolleygrid models. The proposed adaptive charging method, as opposed to the present conservative method (here, Regular Charging), is shown to make one bus electrification project completely feasible and reduce the extra terminal charging time for the other lines by up to 64%.

An important aspect of the energy transition is the expected grid impact due to the abrupt increase of distributed electric generation and electric load demand. A part of this impact is going to be inflicted by the electrification of heating with heat pumps (HPs). Therefore, it is essential that the future power consumption of electric heating is estimated. This work develops a power estimation model without the use of heating demand data, needing only weather data and building heat pump specifications. Moreover, it is characterized as a risk-averse estimation since it uses no optimal control and utilizes the heat pump output capacity curves giving simultaneous priority to the customers' thermal comfort. Finally, it also estimates the power savings of electric heating due to future buildings' new insulation and energy label norms, revealing their importance.