Evolutionary algorithms for dynamic optimization of plug-in charging station networks DOI Creative Commons
Manish Kumar,

Errabelli Annapoorna

MATEC Web of Conferences, Год журнала: 2024, Номер 392, С. 01180 - 01180

Опубликована: Янв. 1, 2024

This research explores the integration of predictive analytics and Internet Things (IoT) to transform sustainable urban transportation systems. project intends examine transformational effect IoT on mobility, using empirical data obtained from devices. The includes information vehicle speed, traffic density, air quality index (AQI), meteorological conditions. study use modeling estimate congestion, volume. allows for evaluation prediction accuracy its alignment with actual data. reveals a link between increased density decreased while unfavorable weather conditions correspond congestion. Predictive models demonstrate significant in forecasting congestion quality, accurate volume poses inherent complications. comparison expected real results demonstrates dependability anticipating AQI, hence confirming effectiveness models. interventions led by 25% decrease levels, as well notable 12.7% enhancement despite little 1.4% rise impact highlights efficacy these solutions, showcasing favorable mitigating promoting environmental sustainability. Ultimately, this emphasizes that may have improving enhancing decision-making processes, creating environments via data-driven insights proactive interventions.

Язык: Английский

A four-layer business model for integration of electric vehicle charging stations and hydrogen fuelling stations into modern power systems DOI
Yongfei Wu,

W. Gu,

Shoujun Huang

и другие.

Applied Energy, Год журнала: 2024, Номер 377, С. 124630 - 124630

Опубликована: Окт. 14, 2024

Язык: Английский

Процитировано

7

Optimal Allocation of Fast Charging Stations on Real Power Transmission Network with Penetration of Renewable Energy Plant DOI Creative Commons
Sami M. Alshareef, Ahmed Fathy

World Electric Vehicle Journal, Год журнала: 2024, Номер 15(4), С. 172 - 172

Опубликована: Апрель 20, 2024

Because of their stochastic nature, the high penetration electric vehicles (EVs) places demands on power system that may strain network reliability. Along with increasing voltage deviations, this can also lower quality provided. By placing EV fast charging stations (FCSs) in strategic grid locations, issue be resolved. Thus, work suggests a new methodology incorporating an effective and straightforward Red-Tailed Hawk Algorithm (RTH) to identify optimal locations capacities for FCSs real Aljouf Transmission Network located northern Saudi Arabia. Using fitness function, work’s objective is minimize violations over 24 h period. The merits suggested RTH are its convergence rate ability eschew local solutions. results obtained via contrasted those other approaches such as use Kepler optimization algorithm (KOA), gold rush optimizer (GRO), grey wolf (GWO), spider wasp (SWO). Annual substation demand, solar irradiance, photovoltaic (PV) temperature datasets utilized study describe demand well generation profiles proposed network. A principal component analysis (PCA) employed reduce complexity each dataset prepare them k-means algorithm. Then, clustering used partition into k distinct clusters evaluated using internal external validity indices. values these indices weighted select best number clusters. Moreover, Monte Carlo simulation (MCS) applied probabilistically determine daily profile data set. According results, outperformed others, achieving lowest value 0.134346 pu, while GRO came second place deviation 0.135646 pu. Conversely, KOA was worst method, 0.148358 outcomes attained validate approach’s competency integrating transmission by selecting sizes.

Язык: Английский

Процитировано

4

Impact of time of use program on widely distribution generation interconnection in urban power network DOI
Mohammad Reza Maghami, Jagadeesh Pasupuleti, Senthilarasu Sundaram

и другие.

Journal of Energy Storage, Год журнала: 2024, Номер 101, С. 113789 - 113789

Опубликована: Сен. 25, 2024

Язык: Английский

Процитировано

3

Efficient Management of Electric Vehicle Charging Stations: Balancing user preferences and grid demands with energy storage systems and renewable energy DOI Creative Commons
Anis Ur Rehman, Junwei Lu, Bo Du

и другие.

Applied Energy, Год журнала: 2025, Номер 393, С. 126147 - 126147

Опубликована: Май 20, 2025

Язык: Английский

Процитировано

0

Efficient distribution network based on photovoltaic fed electric vehicle charging station using WSO-RBFNN approach DOI

P. Marish Kumar,

R. Dhilipkumar,

G Geethamahalakshmi

и другие.

Journal of Energy Storage, Год журнала: 2024, Номер 106, С. 114728 - 114728

Опубликована: Дек. 3, 2024

Язык: Английский

Процитировано

3

Photovoltaic-energy storage-integrated charging station retrofitting: A study in Wuhan city DOI
Xinyu Chen,

Xiaotian Geng,

Dong Xie

и другие.

Transportation Research Part D Transport and Environment, Год журнала: 2024, Номер 132, С. 104241 - 104241

Опубликована: Май 17, 2024

Язык: Английский

Процитировано

2

Towards Sustainable Decarbonization: Addressing Challenges in Electric Vehicle Adoption and Infrastructure Development DOI Creative Commons
Nino Adamashvili, Alkis Thrassou

Energies, Год журнала: 2024, Номер 17(21), С. 5443 - 5443

Опубликована: Окт. 31, 2024

The transition to electric vehicles (EVs) plays a pivotal role in achieving decarbonization within the transportation sector. However, widespread adoption of EVs faces multifaceted challenges, particularly concerning infrastructure development. This paper investigates intersection sustainability, decarbonization, and EV adoption, with focus on identifying analyzing challenges associated deployment. Strictly adhering methodological principles process systematic literature reviews, this analyzes research spanning fields engineering, energy, computer science, environmental social sciences, others elucidate barriers hindering ranging from technological limitations regulatory complexities market dynamics. Furthermore, it examines critical infrastructure, encompassing charging networks, grid integration, supportive policies, facilitating uptake maximizing benefits. findings are finally used present implications for theory, practice, policies highlight avenues future research.

Язык: Английский

Процитировано

1

A Systematic Literature Review of Optimal Placement of Fast Charging Station DOI
Jimmy Trio Putra,

M. Isnaeni Bambang Setyonegoro,

Taco Niet

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

A systematic literature review of optimal placement of fast charging station DOI Creative Commons
Jimmy Trio Putra,

M. Isnaeni Bambang Setyonegoro,

Taco Niet

и другие.

e-Prime - Advances in Electrical Engineering Electronics and Energy, Год журнала: 2024, Номер unknown, С. 100818 - 100818

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

0

Evolutionary algorithms for dynamic optimization of plug-in charging station networks DOI Creative Commons
Manish Kumar,

Errabelli Annapoorna

MATEC Web of Conferences, Год журнала: 2024, Номер 392, С. 01180 - 01180

Опубликована: Янв. 1, 2024

This research explores the integration of predictive analytics and Internet Things (IoT) to transform sustainable urban transportation systems. project intends examine transformational effect IoT on mobility, using empirical data obtained from devices. The includes information vehicle speed, traffic density, air quality index (AQI), meteorological conditions. study use modeling estimate congestion, volume. allows for evaluation prediction accuracy its alignment with actual data. reveals a link between increased density decreased while unfavorable weather conditions correspond congestion. Predictive models demonstrate significant in forecasting congestion quality, accurate volume poses inherent complications. comparison expected real results demonstrates dependability anticipating AQI, hence confirming effectiveness models. interventions led by 25% decrease levels, as well notable 12.7% enhancement despite little 1.4% rise impact highlights efficacy these solutions, showcasing favorable mitigating promoting environmental sustainability. Ultimately, this emphasizes that may have improving enhancing decision-making processes, creating environments via data-driven insights proactive interventions.

Язык: Английский

Процитировано

0