Sustainable Energy, Grids and Networks

Open access Sep 2026

Design and Optimization of Smart-Grid-Connected Microgrids for EV Charging Stations Integrating Net Energy Metering and Demand Response

The widespread adoption of EVs is expected to intensify peak demand, stress distribution networks, and increase carbon emissions if traditional grid-based charging models continue. Therefore, this study proposes a smart-grid-connected microgrid (MG) architecture for EV charging stations (EVCSs) that integrates renewables and energy storage, while incorporating incentive-based response (iDR) and net energy metering schemes into a single optimization framework. To maintain the quality of EV charging services, optimize grid interactions and MG reliability, and explore the socioeconomic impact of establishing such infrastructures, a comprehensive 4E optimization framework incorporating energy, environmental, employment, and economic metrics is developed. The suggested framework is applied to an urban case study in Riyadh, including realistic load profiles, tariff structures, EV charging behavior, network outage scenarios, NEM conditions, and an assumed iDR incentive scenario. A grid-dependent BES/Conv/Grid configuration optimized without iDR is adopted as the common reference for consistently evaluating all system configurations. Compared with this common reference, the results show that while renewable hybridization improves performance, the assumed iDR scenario provides further economic and operational benefits. The optimal iDR-enabled configuration achieves an 87.5% reduction in TNPC and a standard HOMER Grid LCOE of $0.0287/kWh, corresponding to a 67% reduction relative to the common grid-dependent reference. When electricity exports are excluded from the LCOE normalization, the corresponding load-serving LCOE is approximately $0.0372/kWh, which remains approximately 57.3% lower than the reference value of $0.0872/kWh. In addition, the optimal MG generates $63,128 in revenue/year through participation in iDR events without degrading EV charging service performance relative to the non-iDR scenario. Employment analysis indicates that the optimal system supports approximately 49 job-years of direct project-associated employment over the 25-year project lifetime through infrastructure deployment, operation, and maintenance, while ecologically, it limits annual grid-related CO2 emissions to approximately 280.18 tons, representing about an 84.7% reduction relative to the reference scenario. These findings confirm that coordinated demand-side flexibility and intelligent storage dispatch can partially substitute for infrastructure oversizing, enabling cost-effective, low-carbon, and investor-attractive EVCS-based MGs aligned with sustainability targets.

Unknown authors · World Electric Vehicle Journ... · 0 citations

Open access Sep 2026

Cost-effective and emission-aware dispatch strategy for a smart EV charging parking lot

The growing adoption of electric vehicles (EVs) necessitates intelligent charging strategies to alleviate grid congestion and control rising operational costs. This study introduces an IoT-enabled centralized energy management framework for a PV-BESS-EV integrated smart parking system, leveraging real-time data on carbon emissions, grid pricing, and solar irradiance. A key innovation is its bi-objective optimization model, which simultaneously minimizes both cost and carbon footprint, setting it apart from traditional single-objective approaches. The study evaluates teaching-learning-based optimization (TLBO) and particle swarm optimization (PSO) for addressing the system’s nonlinear challenges. Results indicate that TLBO offers faster convergence and greater robustness, leading to improved load flattening, enhanced PV utilization, and stable battery energy storage system (BESS) state of charge (SoC). Overall, the framework provides a scalable solution that effectively balances economic and environmental objectives for modern grid-integrated EV charging systems.

O. K. Rajesh, N. Shanmugasundaram, V. Rajendran · International Journal of Pow... · 0 citations

Open access Jul 2026

A new smart charging strategy for electric vehicles in energy communities

The aim of this study is to evaluate the energy and economic benefits of different Electric Vehicles (EV) charging strategies within Renewable Energy Communities (REC) in Italy. The electrification process for mobility purposes will lead to increased and concentrated electricity demand that may lead to network congestion and other issues. Distributed self-consumption combined with RECs and optimal control of EVs’ charging profiles may reduce the network stress and improve the economic benefits of stakeholders. A simulated case study is used to explore three cases in which 20 EVs (domestic and commercial): (i) are charged independently using a “standard” charging strategy, (ii) join a REC with other users and there aren’t modifications of EV charging profiles, (iii) implement smart charging strategies to integrate with the REC via real-time control infrastructure. In this last case, EV charging power is controlled by a remote controller that monitors the production and consumption of all REC members and controls the EV charge to maximize energy sharing while respecting infrastructure and users’ constraints (e.g., guarantees of minimum SOC, EV maximum charging power, etc.). The developed algorithm firstly simulates all EV trips in a year starting from probability distributions for different parameters, recreating their location and availability for charging on a 15min timestep granularity; secondly, it computes the REC energy flows and assigns the charging power to all vehicles, based on the charging logic which changes across the cases. In conclusion, the paper shows how the EV smart charging and load shift can generate additional value in the form of incentives (+50%) to the REC, without creating disruptions in terms of mobility.

Federico Aleotti, Antonino Rollo, P. Marcolin et al. · Engineering power · 0 citations

Review Open access Aug 2026

Electric Vehicles for Sustainable Transportation: Technologies, Charging Strategies, and Grid Integration

Electric vehicles are rapidly reshaping global transportation, emerging as a central pillar of efforts to cut greenhouse gas emissions and end dependence on fossil fuels. This review provides a critical and integrative synthesis of recent advances in electric vehicle technologies, focusing on three interconnected domains: battery innovations, charging strategies, and grid integration. Progress in high-energy-density lithium-ion chemistries, emerging solid-state and sodium-ion batteries, and advanced battery management systems is examined with respect to their implications for driving range, safety, and lifecycle sustainability. Charging infrastructure developments, including fast and ultra-fast charging, wireless charging, and battery-swapping networks, are evaluated in terms of technical feasibility, grid impact, and user adoption. The evolving role of EVs in enhancing energy system flexibility is further analyzed through vehicle-to-grid (V2G) and smart grid interactions, with emphasis on control algorithms, grid stability, and renewable energy integration. By critically analyzing recent literature, this review identifies key technological, infrastructural, and system-level challenges, as well as emerging research directions that require coordinated optimization across domains. The insights presented aim to guide future research, technology development, and policy design toward the realization of a resilient, efficient, and scalable electric mobility ecosystem.

Sachin Kumar Sharma, Lokesh Kumar Sharma, Saša Milojević et al. · Energies · 0 citations

Open access Aug 2026

Decarbonising Transport, Energising the Grid: A Study of Electric Vehicle–Grid Interactions in New Zealand

The transport sector contributes nearly 20% of New Zealand’s total greenhouse gas emissions, making it crucial for interventions to meet the 2050 net-zero target. Transitioning to electric vehicles (EVs) presents a sustainable solution but poses challenges in electricity distribution due to unpredictable EV charging behaviours. This research addresses these challenges by developing three mathematical models that optimise EV charging patterns, manage power flow along distribution lines and incorporate battery storage systems. Using the Tāmaki area as a case study, the models analyse total energy demand and optimal battery storage size, revealing that a 3.49 MWh battery system could mitigate the projected 2040 peak daily grid energy demand of 541.5 MWh and avoid costly power line upgrades. The study also introduces a vehicle-to-grid (V2G) integration model, showcasing its potential to reduce grid dependence and improve energy utilisation. The findings provide critical insights for Auckland’s electricity distribution companies, supporting strategic asset upgrades and offering evidence-based guidance for government policies on EV adoption. In summary, this research provides innovative solutions for optimising EV charging infrastructure, benefiting utility companies and policymakers by informing data-driven decisions. The comprehensive approach, which includes power flow, battery storage, and V2G technology, presents a scalable framework for international cities facing similar challenges, promoting global sustainable transport solutions towards achieving international climate targets and sustainable urban development.

A. Sreenivasan, R. Majhi, M. Sheng et al. · Energies · 0 citations

Jul 2026

Energy Management of Integrated Electric Vehicle Charging and Hydrogen Refueling Station With Mobile Charging Unit

The increased charging demand of electric vehicles (EVs) and fuel cell EVs has created an additional burden on the fossil fuel‐based electric grid. The article proposes a hybrid energy system (HES)‐based integrated EV charging and hydrogen refueling stations with mobility‐assisted storage flexibility, that is, a mobile charging unit (MCU). As the system has multiple sources and services, a priority‐based energy management framework is designed to maximize use of renewable energy sources (RES). To achieve techno‐economic benefits, a lexicographic optimization with slack‐based demand modeling is introduced to coordinate renewable generation, hydrogen production, grid interaction, and MCU scheduling under realistic operational constraints. Results demonstrate that the proposed system significantly improves RES utilization up to 95% and reduces grid dependency up to 86.53%. Multiobjective optimization enhances economic performance by 19.33% and customer satisfaction by 95% in all seasons. The proposed system provides a significant annual profitability and sustainability for multienergy charging infrastructure.

Kiran Nathgosavi, V. Kalkhambkar, Pratyasa Bhui · Energy Storage · 0 citations