Search Results (23)

This study presents a comprehensive life-cycle assessment of Vehicle-to-Grid (V2G) economic viability, explicitly integrating the costs of both battery cycling degradation and calendar aging. While V2G offers revenue through energy arbitrage, its net profitability is critically dependent on regional electricity price differentials and the associated battery degradation costs. We develop a dynamic cost–benefit model, validated over a 10-year horizon across five diverse regions (Shanghai, Chengdu, the U.S., the U.K., and Australia). The results reveal stark regional disparities: Chengdu (0.65 USD/kWh peak–valley gap) and Australia (0.53 USD/kWh) achieve substantial net revenues of up to USD 25,000 per vehicle, whereas Shanghai’s narrow price differential (0.03 USD/kWh) renders V2G unprofitable. Sensitivity analysis quantifies critical break-even price differentials, varying by EV model and annual mileage (e.g., 0.12 USD/kWh minimum for Tesla Model Y). Crucially, calendar aging emerged as the dominant degradation cost (67% at 10,000 km/year), indicating significant battery underutilization potential. Policy insights emphasize the necessity of targeted interventions, such as Chengdu’s discharge incentives (0.69 USD/kWh), to bridge profitability gaps. This research provides actionable guidance for policymakers, grid operators, and EV owners by quantifying the trade-offs between V2G revenue and battery longevity, enabling optimized deployment strategies. Full article

As electric vehicle (EV) adoption grows, efficient and accessible charging infrastructure is essential. This paper introduces a modular simulation environment to evaluate charging point configurations and operational strategies. The simulation incorporates detailed models of electrical consumers and user behaviour, leveraging real-world data to simulate charging scenarios. A rule-based control strategy is applied to assess six configurations for a supermarket parking lot charging point. Key findings include the highest profit being achieved with two fast chargers. In scenarios with a 50 kW grid connection limit, combining fast chargers with stationary battery storage proves effective. Conversely, mobile charging robots generate lower revenue, though grid peak limitations have minimal impact. The study highlights the potential of the simulation environment to optimise charging layouts, refine operational strategies, and develop energy management algorithms. This work demonstrates the utility of the simulation framework for analyzing diverse charging solutions, offering insights into cost efficiency and user satisfaction. The results emphasise the importance of tailored strategies to balance grid constraints, profitability, and user needs, paving the way for intelligent EV charging infrastructure development. Full article

In response to the challenges of imbalanced economic efficiency of charging stations caused by disorderly charging of large-scale electric vehicles (EVs), rising electricity expenditure of users, and increased risk of stable operation of the power grid, this study designs a user-side vehicle pile resource interaction strategy considering source load clustering to enhance the economy and safety of electric vehicle energy management. Firstly, by constructing a dynamic traffic flow distribution network coupling architecture, a bidirectional interaction model between charging facilities and transportation/power systems is established to analyze the dynamic correlation between charging demand and road network status. Next, an EV charging and discharging electricity price response model is established to quantify the load regulation potential under different scenarios. Secondly, by combining urban transportation big data and prediction networks, high-precision inference of the spatiotemporal distribution of charging loads can be achieved. Then, a multidimensional optimization objective function covering operator revenue, user economy, and grid power quality is constructed, and a collaborative decision-making model is established. Finally, the IEEE69 node system is validated through joint simulation with actual urban areas, and the non-dominated sorting genetic algorithm II (NSGA-II) based on reference points is used for the solution. The results show that the optimization strategy proposed by NSGA-II can increase the operating revenue of charging stations by 33.43% while reducing user energy costs and grid voltage deviations by 18.9% and 68.89%, respectively. Full article

With the increasing prevalence of electric vehicles (EVs), optimizing their scheduling for grid peak-shaving has become a focal point of research. This study develops a multi-time-scale optimization model for EV clusters to participate in peak shaving, integrating a comprehensive evaluation and feedback mechanism. The innovation of this paper lies in the addition of an evaluation and feedback loop to the multi-time-scale scheduling optimization method for EVs participating in peak shaving, which fully utilizes the scheduling potential of EV clusters and mitigates the impact of uncertainties associated with EV clusters. The multi-time-scale approach mitigates response errors stemming from EV uncertainties. A feedback loop enables the grid to adaptively adjust scheduling commands to match real-time conditions. Simulations on the IEEE 33-node system demonstrate that the proposed model effectively optimizes EV load profiles, reducing the peak-to-valley difference rate from 41.74% to 35.19%. It also enhances response accuracy to peak-shaving instructions and upgrades the peak-shaving evaluation from a C rating to a B rating, ultimately increasing the revenue for aggregators participating in peak shaving. Full article

As the share of electric vehicles (EVs) continues to rise, the distribution grid faces the risk of overload. In Germany, the reform of § 14a Energiewirtschaftsgesetz (German Energy Industry Act, EnWG) was introduced to address this problem. The reform has changed the revenue potential of smart chargeable uni and bidirectional EVs (smart EVs). The reform introduces variable grid fee tariffs for smart EVs, but also possible emergency power reduction measures to relieve grid overload situations. While variable grid fee tariffs can increase revenues, power reduction measures can lead to revenue losses. This work investigates the dual impact of these factors by implementing variable grid fee tariffs and the option of power reduction signals in a flexibility marketing model. Our findings indicate that smart EVs can generate significant additional revenues through variable grid fee tariffs in 2035. Conversely, the impact of emergency power signals on these revenues and the EV load profile is marginal. As a result, the effect of power reduction measures on the German load profile is also negligible. Full article

During the planning and construction of electric vehicle charging stations (EVCSs), consideration of the long-term operating revenue loss for investors is often lacking. To address this issue, this study proposes an EVCS planning method that takes into account the potential loss of long-term operating revenues associated with charging facilities. First, the method combines the Bass model with electric vehicle (EV) user travel characteristics to generate a charging load dataset. Then, the cost of profit loss—which represents the EVCS utilization rate—is incorporated into the construction of the objective function. Additionally, a parallel computing method is introduced into the solution algorithm to generate the EVCS planning scheme. Finally, the cost-to-profit ratio of the EVCSs is used as a filtering condition to obtain the optimal EVCS planning scheme. The results show that the EVCS planning scheme considering the profit loss reduces the annual comprehensive cost by 24.25% and 16.93%, and increases the net profit by 22.14% and 24.49%, respectively, when compared to the traditional planning scheme under high and low oil prices. In particular, the charging station strategy proposed in this study has the best effect in the case of high oil prices. Full article

Electric vehicles (EVs) have seen significant advancements and mainstream adoption, prompting in-depth analysis of their economic, technical, and environmental impacts. Economically, while EVs offer lower operational costs than internal combustion engine vehicles, challenges remain, particularly for urban users reliant on public charging stations and the potential implementation of new road taxes to offset declining fuel tax revenues. Technically, electric motors in EVs have fewer moving parts, but battery management and cybersecurity complexities pose new risks. Transitioning from Nickel-Manganese-Cobalt (NMC) to Lithium-Iron-Phosphate (LFP) batteries reflects efforts to enhance thermal stability and mitigate fire hazards. Environmentally, lithium extraction for batteries has profound ecological impacts, including for water consumption and pollution. Battery production and the carbon footprint of the entire lifecycle remain pressing concerns, with battery recycling and second-life applications as crucial mitigation strategies. Smart integration of EVs with the energy infrastructure introduces challenges like grid stability and opportunities, such as smart, intelligent, innovative charging solutions and vehicle-to-grid (V2G) technology. Future research should develop economic models to forecast long-term impacts, advance battery technology, enhance cybersecurity, and conduct comprehensive environmental assessments to optimise the benefits of electromobility, addressing the multidimensional challenges and opportunities presented by EVs. Full article

This study explores the obstacles to electric vehicle (EV) adoption in Indonesia, focusing on technological, environmental, economic, and regulatory factors. Despite government initiatives, such as the Presidential Regulation 55 of 2019, intended to encourage the adoption of EVs and mitigate air pollution, the EV market share in Indonesia remains low, at 1.47%. The main challenges include inadequate charging infrastructure, limited public revenue, and financial constraints. This research highlights the need for improved government policies, incentives for producers, and increased public awareness to encourage EV adoption. Factors influencing consumer decisions include operational costs, environmental concerns, and the availability of charging stations. Key findings suggest that electric motorcycle users have a lower understanding of technology than electric car users, with particular attention to initial costs, maintenance costs, and the accessibility of charging infrastructure. This study recommends that manufacturers and policymakers consider the different preferences of electric car and motorcycle users in their EV adoption promotion strategies. The study seeks to elucidate the determinants affecting EV adoption in Indonesia and propose potential solutions to accelerate the transition to electric mobility. Full article

The electrification of mobility has introduced considerable challenges to distribution networks due to varying demand patterns in both time and location. This underscores the need for adaptable tools to support strategic investments, grid reinforcement, and infrastructure deployment. In this context, the present study employs real-world datasets to propose a comprehensive spatial–temporal energy model that integrates a traffic model and geo-referenced data to realistically evaluate the flexibility potential embedded in the light-duty transportation sector for a given study region. The methodology involves assessing traffic patterns, evaluating the grid impact of EV charging processes, and extending the analysis to flexibility services, particularly in providing primary and tertiary reserves. The analysis is geographically confined to the Lombardy region in Italy, relying on a national survey of 8.2 million trips on a typical day. Given a target EV penetration equal to 2.5%, corresponding to approximately 200,000 EVs in the region, flexibility bands for both services are calculated and economically evaluated. Within the modeled framework, power-intensive services demonstrated significant economic value, constituting over 80% of the entire potential revenues. Considering European markets, the average marginal benefit for each EV owner is in the order of 10 € per year, but revenues could be higher for sub-classes of users better fitting the network needs. Full article

The potential of renewable energy sources to lower greenhouse gas emissions and lessen our reliance on fossil fuels has accelerated their integration globally, and especially that of solar photovoltaic (PV) systems. Malaysia has shown great progress in the adoption of photovoltaic systems thanks to its plentiful solar resources. On the other hand, energy storage systems (ESSs) are becoming more and more necessary in order to guarantee grid stability and fully realize the benefits of PV systems. This study attempts to assess the current condition of PV installations in Malaysia with an emphasis on their economic feasibility, regulatory compliance, technological capabilities, and compatibility with various energy storage technologies. Malaysian photovoltaic (PV) systems’ readiness to integrate energy storage systems (ESSs) using second-life electric vehicle batteries (SLEVBs) is examined in this article. Integrating PV systems with SLEVBs in residential ESSs shows economic viability, with a 15-year payback and 25% return on investment (ROI). Therefore, for every 1 MW of installed PV capacity, with ESS integration it is estimated to reduce approximately 3504 metric tons of CO₂ emissions annually in Malaysia. The homeowner benefits from large electricity bill savings, net metering revenue, and various incentives or financing alternatives that make the project financially attractive despite the extended payback time. Energy storage solutions are needed to improve grid stability, energy usage, and solar power generation in Malaysia as renewable energy adoption increases. Reusing retired EV batteries for stationary storage could solve environmental and economic issues. This study examines the feasibility, regulatory frameworks, and economic viability of combining second-life EV batteries with PV installations in Malaysia. Full article

This paper proposes a multi-objective optimization framework for safe, reliable, and economic integration of electric vehicles (EVs) and renewable distributed generators (DGs) in distribution micro-grids. EV and DG coordination optimization with the use of vehicle-to-grid (V2G) technology along with system reconfiguration optimization is developed to provide collective revenues and address integrational complications that may occur by additional system loading due to EV charging and EV-DG energy exchanges. A Genetic Algorithm (GA) optimizes the EV charging/discharging in synergies with renewable DGs to maximize benefits that can be captured by their collaborative participation in electricity market and through renewable energy arbitrage. The developed EV charging/discharging optimization is implemented in a real 134-bus distribution network and is evaluated for its potential operational implications, namely, increased system losses. A system reconfiguration is then proposed to reduce the system losses by optimizing the flow of power through switching on/off the connections within the micro-grid and/or with other distribution systems. Simulation results demonstrate the efficiency of the proposed method in not only providing collective revenues, but also in enhancing the system operation by reducing the losses of the distribution grid. The collective benefits proposed by the developed optimization and validated by the simulation results facilitate transitioning to clean and eco-friendly sources of energy for generation and transportation, which in turn leads to more sustainable development of societies and communities. Full article

Promoting the accelerated adoption of electric vehicles (EVs) in the United States (US) is one of the main strategies for reducing risk related to climate change. However, the lack of public charging stations (EVCSs) in the US has been identified as a grave obstacle to EV market penetration. The US Federal Government is providing extensive financial incentives to promote EVCSs. This allows diverse businesses to offer EV charging as an ancillary service, without the risks associated with traditional fuel facilities. Locations offering these novel services will reduce their financial operational risks, increase customer traffic and receive additional revenue. However, selecting unsuitable equipment for particular business segments and locations creates a severe risk of underuse and disrepair, leading to the potential failure of these new projects. Furthermore, these unsuccessful EVCSs exacerbate consumer reluctance to EV adoption and foster social opposition to this new technology. This study provides stakeholders with a framework for the optimal placement of EVCSs to maximize their successful deployment and incentivize continuous growth in the EV market. It identifies risk factors related to the placement and operation of EVCSs, aiding in optimal equipment selection for each location. Results from this study highlight EVCS location trends based on location and type of business, with the potential for some retrofitting projects. This framework provides relevant geospatial results for business owners, policy makers, consumers and other stakeholders in the adequacy of new charging infrastructure. Full article

The adoption of electric vehicles (EVs) is increasing due to governmental policies focused on curbing climate change. EV batteries are retired when they are no longer suitable for energy-intensive EV operations. A large number of EV batteries are expected to be retired in the next 5–10 years. These retired batteries have 70–80% average capacity left. Second-life use of these battery packs has the potential to address the increasing energy storage system (ESS) demand for the grid and also to create a circular economy for EV batteries. The needs of modern grids for frequency regulation, power smoothing, and peak shaving can be met using retired batteries. Moreover, these batteries can also be employed for revenue generation for energy arbitrage (EA). While there are articles reviewing the general applications of retired batteries, this paper presents a comprehensive review of the research work on applications of the second-life batteries (SLBs) specific to the power grid and SLB degradation. The power electronics interface and battery management systems for the SLB are also thoroughly reviewed. Full article

The overutilization of electric vehicles (EVs) has the potential to result in significant challenges regarding the reliability, contingency, and standby capabilities of traditional power systems. The utilization of renewable energy distributed generator (REDG) presents a potential solution to address these issues. By incorporating REDG, the reliance of EV charging power on conventional energy sources can be diminished, resulting in significant reductions in transmission losses and enhanced capacity within the traditional power system. The effective management of the REDG necessitates intelligent coordination between the available generation capacity of the REDG and the charging and discharging power of EVs. Furthermore, the utilization of EVs as a means of energy storage is facilitated through the integration of vehicle-to-grid (V2G) technology. Despite the importance of the V2G technology for EV owners and electric utility, it still has a slow progress due to the distrust of the revenue model that can encourage the EV owners and the electric utility as well to participate in V2G programs. This study presents a new wear model that aims to precisely assess the wear cost of EV batteries, resulting from their involvement in V2G activities. The proposed model seeks to provide EV owners with a precise understanding of the potential revenue they might obtain from participating in V2G programs, hence encouraging their active engagement in such initiatives. Various EV battery wear models are employed and compared. Additionally, this study introduces a novel method for optimal charging scheduling, which aims to effectively manage the charging and discharging patterns of EVs by utilizing a day-ahead pricing technique. This study presents a novel approach, namely, the gradual reduction of swarm size with the grey wolf optimization (GRSS-GWO) algorithm, for determining the optimal hourly charging/discharging power with short convergence time and the highest accuracy based on maximizing the profit of EV owners. Full article

With the development of the electric vehicle industry, the number of batteries that are retired from vehicles is increasing rapidly, which raises critical environmental and waste issues. Second-life batteries recycled from automobiles have eighty percent of the capacity, which is a potential solution for the electricity grid application. To utilize the second-life batteries efficiently, an accurate estimation of their performance becomes a crucial portion of the optimization of cost-effectiveness. Nonetheless, few works focus on the modeling of the applications of second-life batteries. In this work, a general methodology is presented for the performance modeling and degradation prediction of second-life batteries applied in electric grid systems. The proposed method couples an electrochemical model of the battery performance, a state of health estimation method, and a revenue maximization algorithm for the application in the electric grid. The degradation of the battery is predicted under distinct charging and discharging rates. The results show that the degradation of the batteries can be slowed down, which is achieved by connecting numbers of batteries together in parallel to provide the same amount of required power. Many works aim for optimization of the operation of fresh Battery Energy Storage Systems (BESS). However, few works focus on the second-life battery applications. In this work, we present a trade-off between the revenue of the second-life battery and the service life while utilizing the battery for distinct operational strategies, i.e., arbitrage and peak shaving against Michigan’s DTE electricity utility’s Dynamic Peak Pricing (DPP) and Time of Use (TOU) tariffs. Results from case studies show that arbitrage against the TOU tariff in summer is the best choice due to its longer battery service life under the same power requirement. With the number of retired batteries set to increase over the next 10 years, this will give insight to the retired battery owners/procurers on how to increase the profitability, while making a circular economy of EV batteries more sustainable. Full article