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Spatial and Temporal Optimization Strategy for Plug-In Electric Vehicle Charging to Mitigate Impacts on Distribution Network

Lili Gong, Wu Cao, Kangli Liu, Jianfeng Zhao, Xiang Li
2018 Energies  
Firstly, the concept of trip chain is introduced to analyze the spatial and temporal distribution of PEVs.  ...  Uncoordinated charging of PEVs will cause a heavy load burden at rush hour and lead to increased power loss and voltage fluctuation.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en11061373 fatcat:kyggt6m7l5eftkjickrthgpjzi

A Survey on PEV Charging Infrastructure: Impact Assessment and Planning

Ahmed Abdalrahman, Weihua Zhuang
2017 Energies  
Optimal planning of PEV charging infrastructure will promote the penetration rate of PEVs and minimize the negative impacts of PEVs on the electric power distribution system and transportation road network  ...  In this paper, we present a comprehensive literature survey on modelling of PEV charging demand, impact assessment approaches and tools, and charging infrastructure planning.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en10101650 fatcat:plmbooqugjdlrbm3w3hhhtxtba

Location Planning of Fast Charging Station considering its Impact on the Power Grid Assets [article]

Daijiafan Mao, Jun Tan, Guangyi Liu, Jiankang Wang
2019 arXiv   pre-print
The location planning of FCS must allow for satisfactory charging service for PEV users as well as mitigate the detrimental effects on power grid caused by uncertainty and impulsiveness of charging demand  ...  Under the ambition of boosting Plug-in Electric Vehicle (PEV) charging speed to a level comparable to the traditional refueling, Fast Charging Station (FCS) has been integrated into power distribution  ...  the number of PEVs traveling on trip chain q, x k is the binary variable that equals 1 if a station is placed at location k and equals 0 otherwise, y q is the binary variable that equals 1 if PEVs on trip  ... 
arXiv:1903.10149v1 fatcat:fsou7nlx6nernmqtfqx2zayweu

Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array

Xiaohua Wu, Xiaosong Hu, Scott Moura, Xiaofeng Yin, Volker Pickert
2016 Journal of Power Sources  
Finally, based on time-varying electricity price, we systematically examine the performance of the proposed control strategy.  ...  This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements, and accommodating the variability of solar power.  ...  Based on real statistical data, Markov Chain models of vehicle trip time and conditional probability of trip length is achieved, as well as predictive models of home load demand and PV power supply.  ... 
doi:10.1016/j.jpowsour.2016.09.157 fatcat:fm4cispkszat5j6hjd34fdmrjy

Estimating panel effects in probabilistic representations of dynamic decision trees using bayesian generalized linear mixture models

Seheon Kim, Soora Rasouli, Harry Timmermans, Dujuan Yang
2018 Transportation Research Part B: Methodological  
Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of  ...  accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the  ...  Instead, Travel distance of a next trip to charging occasion (T6) and Travel time of a trip to the location of charging occasion (T2) newly appeared with modest impacts in Model 5.  ... 
doi:10.1016/j.trb.2018.03.010 fatcat:bowf34u3d5fa5naab4r7cc4lfq

From the top of the organization to the bottom line: Understanding the fleet market for plug-in electric vehicles

Kevin Nesbitt, Jamie Davies
2013 2013 World Electric Vehicle Symposium and Exhibition (EVS27)  
However, the reasons are often based on misconceptions regarding past 3 purchases behavior and misunderstood operational considerations (1).  ...  We also report on the primary concerns expressed 8 by the project participants regarding the purchase and use of PEVs.  ...  The vehicles had regenerative braking, a multi-33 screen human-machine interface (HMI) display, and 6.6 kW of on-board auxiliary 34 power available through several 120V and 220V receptacles (located in  ... 
doi:10.1109/evs.2013.6914995 fatcat:3yxknycxubghtbnymvh5adfefm

A Stochastic Approach to Designing Plug-In Electric Vehicle Charging Controller for Residential Applications

Abdoul Wahab Dante, Sousso Kelouwani, Kodjo Agbossou, Nilson Henao, Jonathan Bouchard, Sayed Saeed Hosseini
2022 IEEE Access  
In addition, it employs a stochastic optimization framework to schedule PEV charging based on the dynamic electricity price and user preference.  ...  Particularly, it takes advantage of a Bayesian forecasting model that is able to efficiently predict charging energy demand according to car owner's behavior.  ...  The charging request was managed based on a Markov chain model of PEV parking status, captured from its historical data.  ... 
doi:10.1109/access.2022.3175817 fatcat:aafcyya5zzaxpfpgovhnpom7we

Optimal fast charging station locations for electric ridesharing service with online vehicle-charging station assignment [article]

Tai-Yu Ma, Simin Xie
2020 arXiv   pre-print
The results show that the proposed online charging policy can effectively reduce the charging delays of the fleet compared to the state-of-the-art methods.  ...  A new online vehicle-charging assignment model is proposed and integrated into the fast charging location problem for dynamic ridesharing services using electric vehicles.  ...  considering trip-chaining behavior.  ... 
arXiv:2008.05949v2 fatcat:26ra4am2r5htrlf26p25unvdh4

Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends

Shafqat Jawad, Junyong Liu
2020 Energies  
, charging loads on the power grid, and high costs.  ...  However, the evaluation of the complex coupled relationship across charging services, transportation, and power networks poses several challenges, including an impact on charging scheduling, traffic congestion  ...  Besides, GIS-based probabilistic models employed to determine the charging load, trip-chain-related travel parameters with the integration of distributed generation, and the cost of electricity have been  ... 
doi:10.3390/en13133371 fatcat:zskjjowzobgvrhnftvhg4kkekm

Sustainability SI: Optimal Prices of Electricity at Public Charging Stations for Plug-in Electric Vehicles

Fang He, Yafeng Yin, Jianhui Wang, Yanni Yang
2013 Networks and Spatial Economics  
This paper explores the use of prices of electricity at public charging stations as an instrument, in couple of road pricing, to better manage both power distribution and urban transportation networks.  ...  With an increasing deployment of plug-in electric vehicles, evaluating and mitigating the impacts of additional electrical loads created by these vehicles on power distribution grids become more important  ...  Acknowledgments This research was partly funded by National Science Foundation (CNS-1239364) and National Natural Science Foundation of China (71228101).  ... 
doi:10.1007/s11067-013-9212-8 fatcat:5nl4cked2bezxd3irss5ipcfjm

Neighbourhood Electric Vehicles in Mature Suburbs

David Magarian, Walter Seimbab
2012 World Electric Vehicle Journal  
This is a Report on the first phase of a demonstration of Neighborhood Electric Vehicles (NEVs) in the South  ...  The usage analysis integrates the following four sources of data: • GPS on each vehicle, which provides comprehensive tracking of distances, routes, destination locations, time of day, and speeds. • Hand  ...  Figure 2 : 2 Access MetricsPercentage of trips taken by distance category The emission reduction analysis is based on 1 This statistic reduces to 15% CO2 reductions when single occupant households are  ... 
doi:10.3390/wevj5030777 fatcat:mdct6c3xnbe6pgu52fwuyuchzy

Public Plug-in Electric Vehicles + Grid Data: Is a New Cyberattack Vector Viable? [article]

Samrat Acharya and Yury Dvorkin and Ramesh Karri
2020 arXiv   pre-print
As a result, information on the charging patterns of PEVs is becoming accessible via smartphone applications, which aggregate real-time availability and historical usage of public PEV charging stations  ...  The study establishes that while such an attack is not possible at the current penetration level of PEVs, it will be practical once the number of PEVs increases.  ...  Similarly, MVAratings of substations are approximated based on the associated generation and load.  ... 
arXiv:1907.08283v2 fatcat:ougwpw4hrbf5zdn7m7woascd6e

Stochastic Modeling of Battery Electric Vehicle Driver Behavior

Jing Dong, Zhenhong Lin
2014 Transportation Research Record  
The approach uses longitudinal travel data and thus allows more realistic analysis of the impact of the charging infrastructure on BEV feasibility.  ...  "Stochastic modeling of battery electric vehicle driver behavior: Impact of charging infrastructure deployment on the feasibility of battery electric vehicles.  ...  Explicit formulation of charging decisions in response to gasoline and 20 electricity prices, location and user-friendliness of chargers, and trip chains is desirable in future 21 research.  ... 
doi:10.3141/2454-08 fatcat:w34r5ipcovac3gvakqp4inoce4

Reinforcement Learning Based EV Charging Management Systems – A review

Heba M. Abdullah, Adel Gastli, Lazhar Ben-Brahim
2021 IEEE Access  
To mitigate global warming and energy shortage, integration of renewable energy generation sources, energy storage systems, and plug-in electric vehicles (PEVs) have been introduced in recent years.  ...  Unlike other machine learning approaches, the RL technique is based on maximizing the cumulative reward.  ...  Stochastic driving behavior was simulated considering only one trip per day for each vehicle.  ... 
doi:10.1109/access.2021.3064354 fatcat:ap66p3hnnng25dp65e6agsjmbq

Exploration of dispatch model integrating wind generators and electric vehicles

A.N.M.M. Haque, A.U.N. Ibn Saif, P.H. Nguyen, S.S. Torbaghan
2016 Applied Energy  
Effects of smart charging on generation cost, CO 2 emissions and total network load are assessed.  ...  Imbalance cost of wind generation is considered in the UC-ED model. Smart charging of EVs is included into the UC-ED problem to mitigate the imbalance cost.  ...  The intermittency and unpredictability of the RES-based generation units together with the stochastic behavior of PEVs have significant impact on two of the most important aspects of system balancing,  ... 
doi:10.1016/j.apenergy.2016.09.078 fatcat:kkdijtbtmfaexozcwdvw4ufiqa
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