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The rise of electric vehicles (EVs) is unstoppable due to factors such as the decreasing cost of batteries and various policy decisions. These vehicles need to be charged and will therefore cause congestion in local distribution grids in…
Electric road systems (ERS) are roads that allow compatible vehicles to be powered by grid electricity while in transit, reducing the need for stopping to recharge electric batteries. We investigate how this technology can affect routing…
Due to the ongoing electrification of transport in combination with limited power grid capacities, efficient ways to schedule the charging of electric vehicles (EVs) are needed for the operation of, for example, large parking lots. Common…
The operation of the power grid is becoming more stressed, due to the addition of new large loads represented by Electric Vehicles (EVs) and a more intermittent supply due to the incorporation of renewable sources. As a consequence, the…
Transit agencies that operate battery-electric buses must carefully manage fast-charging infrastructure to extend daily bus range without degrading on-time performance. To support this need, we propose a mixed-integer linear programming…
Adoption of battery energy storage systems for behind-the-meters application offers valuable benefits for demand charge management as well as increasing PV-utilization. The key point is that while the benefit/cost ratio for a single…
Edge intelligence is an emerging paradigm for real-time training and inference at the wireless edge, thus enabling mission-critical applications. Accordingly, base stations (BSs) and edge servers (ESs) need to be densely deployed, leading…
With the recent advances in mobile energy storage technologies, electric vehicles (EVs) have become a crucial part of smart grids. When EVs participate in the demand response program, the charging cost can be significantly reduced by taking…
Maintaining grid stability amid widespread electric vehicle (EV) adoption is vital for sustainable transportation. Traditional optimization methods and Reinforcement Learning (RL) approaches often struggle with the high dimensionality and…
The increasing number of Electric Vehicles (EVs) have led to rising energy demands which aggregates the burden on grid supply. A few solutions have been proposed to reduce grid load, for example, using storage systems for storing surplus…
Electric vehicle (EV) charging patterns are highly uncertain in both location, time, and duration particularly in association with the predicted high demand for electric mobility in the future. An EV can be charged at home, at charging…
In this paper, we attempt to optimally schedule the charging of long-range battery electric vehicles (BEVs) along highway networks, in order to minimize aggregate costs to the overall system consisting of utilities or electricity providers,…
Electric vehicles (EVs) and particularly plug-in hybrid electric vehicles (PHEVs) are foreseen to become popular in the near future. Not only are they much more environmentally friendly than conventional internal combustion engine (ICE)…
Battery energy storage systems (BESS) play an increasingly vital role in integrating renewable generation into power grids due to their ability to dynamically balance supply. Grid-tied batteries typically employ power converters, where…
This paper introduces an Electric Vehicle Charging Station (EVCS) model that incorporates real-world constraints, such as slot power limitations, contract threshold overruns penalties, or early disconnections of electric vehicles (EVs). We…
Electric vehicles (EVs) are finally making their way onto the roads, but the challenges concerning long charging times and impact on congestion of the power distribution grid are still not resolved. Proposed solutions depend on heavy…
The growing penetration of electric vehicles (EVs) significantly changes typical load curves in smart grids. With the development of fast charging technology, the volatility of EV charging demand is increasing, which requires additional…
In recent years, the development of Artificial Intelligence (AI) has shown tremendous potential in diverse areas. Among them, reinforcement learning (RL) has proven to be an effective solution for learning intelligent control strategies. As…
Battery Energy Storage Systems (BESS) can mitigate effects of intermittent energy production from renewable energy sources and play a critical role in peak shaving and demand charge management. To optimally size the BESS from an economic…
The most commonly used model for battery energy storage systems (BESSs) in optimal BESS allocation problems is a constant-efficiency model. However, the charging and discharging efficiencies of BESSs vary non-linearly as functions of their…