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1
Mello, Carlos, Marília Saraiva, Diego Menor, and Ricardo Nishihara. "A Comparative Study of Objective Video Quality Assessment Metrics." JUCS - Journal of Universal Computer Science 23, no. (5) (2017): 505–27. https://doi.org/10.3217/jucs-023-05-0505.
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This paper presents a comparison of several video quality metrics, analysing their performance against different types of distortions. Usually, comparisons are made considering a full dataset with few different degradations. We are presenting here a comparison using three very different datasets (VQEG Phase I, LIVE VQA and ReTRIeVED) and a fourth dataset which was generated in a mobile phone network simulator. This was done to check if the video quality metrics can correctly measure the degradations created by variations in the network, very close to real scenarios. The analysis was done with 13 full reference metrics (including Opticom's PEVQ commercial tool) and two no-reference metrics. We have concluded that NTIA's VQM achieved the best results, in most of the cases. It is an open source algorithm that outperformed most of the other techniques, including the licensed PEVQ.
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Uhl, T., and H. S. Jürgensen. "The new, parametrised IPTV Model for Determining the Quality in the IPTV Service." Bulletin of the Polish Academy of Sciences Technical Sciences 63, no. 2 (2015): 495–500. http://dx.doi.org/10.1515/bpasts-2015-0057.
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Abstract This paper describes a new measurement method for determining the quality of the IPTV (Television over IP) service. This method uses the latest IPTV Model and is one of a number of parameter-based measuring techniques (offline operation, i.e. without intrusive measurement). It delivers results that come very close to those of the corresponding Perceptual Evaluation of Video Quality (PEVQ) curves. The method is quickly and easily implemented - one of the great advantages of using this method to measure QoS
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Uhl, T., and S. Paulsen. "The new, parameterised VT model for determining quality in the video-telephony service." Bulletin of the Polish Academy of Sciences Technical Sciences 62, no. 3 (2014): 431–37. http://dx.doi.org/10.2478/bpasts-2014-0045.
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Abstract This paper describes a new method for measuring and appraising the quality of the video stream in the video-telephony service in IP environments (VToIP). The method uses the so-called VS Model and belongs to the group of parameter-based measurement techniques (offline operation, i.e. without active measurement). It delivers results that come extremely close to those contained in the corresponding Perceptual Evaluation of Video Quality (PEVQ) curves. The method is quick and easy to use - a convincing argument for using this new QoS measuring method.
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Xu, Wei-Jian, Cai-Dan Zhao, Hua-Pei Chiang, Lianfen Huang, and Yueh-Min Huang. "The RR-PEVQ algorithm research based on active area detection for big data applications." Multimedia Tools and Applications 74, no. 10 (2014): 3507–20. http://dx.doi.org/10.1007/s11042-014-1903-8.
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Hoppe, Christian, Robert Manzke, Marcus Rompf, and Tadeus Uhl. "Quantifying the Suitability of Reference Signals for the Video Streaming Analysis for IPTV." Journal of Telecommunications and Information Technology, no. 1 (March 30, 2016): 29–36. http://dx.doi.org/10.26636/jtit.2016.1.701.
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IP networks are indispensable nowadays and they are some of the most efficient platforms. The constantly growing number of users and new services in these networks – the largest being the Internet – require a satisfactory quality of service from any application they use. So, determining the QoS in real-time services is particularly important. This work shows how to quantify the suitability of reference signals for analyzing the quality of video streaming in IPTV. The assessment relies on two different algorithms: PEVQ and VQuad-HD. Three different reference signals – two real ones and an artificial one – are used in this study, and a numerical measurement system is used, which simulates mean network impairments. These measurements provide valuable information for determining the QoS of actual IPTV services in practice.
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Gavrilov, Sergey, Anatoly Karalkin, Nadezhda Mishakina, Oksana Efremova, and Anastasia Grishenkova. "Relationships of Pelvic Vein Diameter and Reflux with Clinical Manifestations of Pelvic Venous Disorder." Diagnostics 12, no. 1 (2022): 145. http://dx.doi.org/10.3390/diagnostics12010145.
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The causes of chronic pelvic pain (CPP) in patients with pelvic venous disorder (PeVD) are not completely understood. Various authors consider dilation of pelvic veins (PeVs) and pelvic venous reflux (PVR) as the main mechanisms underlying symptomatic forms of PeVD. The aim of this study was to assess relationships of pelvic vein dilation and PVR with clinical manifestations of PeVD. This non-randomized comparative cohort study included 80 female patients with PeVD who were allocated into two groups with symptomatic (n = 42) and asymptomatic (n = 38) forms of the disease. All patients underwent duplex scanning and single-photon emission computed tomography (SPECT) of PeVs with in vivo labeled red blood cells (RBCs). The PeV diameters, the presence, duration and pattern of PVR in the pelvic veins, as well as the coefficient of pelvic venous congestion (CPVC) were assessed. Two groups did not differ significantly in pelvic vein diameters (gonadal veins (GVs): 7.7 ± 1.3 vs. 8.5 ± 0.5 mm; parametrial veins (PVs): 9.8 ± 0.9 vs. 9.5 ± 0.9 mm; and uterine veins (UVs): 5.6 ± 0.2 vs. 5.5 ± 0.6 mm). Despite this, CPVC was significantly higher in symptomatic versus asymptomatic patients (1.9 ± 0.4 vs. 0.7 ± 0.2, respectively; p = 0.008). Symptomatic patients had type II or III PVR, while asymptomatic patients had type I PVR. The reflux duration was found to be significantly greater in symptomatic versus asymptomatic patients (median and interquartile range: 4.0 [3.0; 5.0] vs. 1.0 [0; 2.0] s for GVs, p = 0.008; 4.0 [3.0; 5.0] vs. 1.1 [1.0; 2.0] s for PVs, p = 0.007; and 2.0 [2.0; 3.0] vs. 1.0 [1.0; 2.0] s for UVs, p = 0.04). Linear correlation analysis revealed a strong positive relationship (Pearson’s r = 0.78; p = 0.007) of CPP with the PVR duration but not with vein diameter. The grade of PeV dilation may not be a determining factor in CPP development in patients with PeVD. The presence and duration of reflux in the pelvic veins were found to be predictors of the development of symptomatic PeVD.
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Egbue, Ona, Suzanna Long, and Seong Dae Kim. "Resource Availability and Implications for the Development of Plug-In Electric Vehicles." Sustainability 14, no. 3 (2022): 1665. http://dx.doi.org/10.3390/su14031665.
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Plug-in electric vehicles (PEVs) have immense potential for reducing greenhouse gas emissions and dependence on fossil fuels, and for smart grid applications. Although a great deal of research is focused on technological limitations that affect PEV battery performance targets, a major and arguably equal concern is the constraint imposed by the finite availability of elements or resources used in the manufacture of PEV batteries. Availability of resources, such as lithium, for batteries is critical to the future of PEVs and is, therefore, a topic that needs attention. This study addresses the issues related to lithium availability and sustainability, particularly supply and demand related to PEVs and the impact on future PEV growth. In this paper, a detailed review of the research on lithium availability for PEV batteries is presented, key challenges are pinpointed and future impacts on PEV technology are outlined.
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Deilami, Sara. "Online Coordination of Plug-In Electric Vehicles Considering Grid Congestion and Smart Grid Power Quality." Energies 11, no. 9 (2018): 2187. http://dx.doi.org/10.3390/en11092187.
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This paper first introduces the impacts of battery charger and nonlinear load harmonics on smart grids considering random plug-in of electric vehicles (PEVs) without any coordination. Then, a new centralized nonlinear online maximum sensitivity selection-based charging algorithm (NOL-MSSCA) is proposed for coordinating PEVs that minimizes the costs associated with generation and losses considering network and bus total harmonic distortion (THD). The aim is to first attend the high priority customers and charge their vehicles as quickly as possible while postponing the service to medium and low priority consumers to the off-peak hours, considering network, battery and power quality constraints and harmonics. The vehicles were randomly plugged at different locations during a period of 24 h. The proposed PEV coordination is based on the maximum sensitivity selection (MSS), which is the sensitivity of losses (including fundamental and harmonic losses) with respect to the PEV location (PEV bus). The proposed algorithm uses the decoupled harmonic power flow (DHPF) to model the nonlinear loads (including the PEV chargers) as current harmonic sources and computes the harmonic power losses, harmonic voltages and THD of the smart grid. The MSS vectors are easily determined using the entries of the Jacobian matrix of the DHPF program, which includes the spectrums of all injected harmonics by nonlinear electric vehicle (EV) chargers and nonlinear industrial loads. The sensitivity of the objective function (fundamental and harmonic power losses) to the PEVs were then used to schedule PEVs accordingly. The algorithm successfully controls the network THDv level within the standard limit of 5% for low and moderate PEV penetrations by delaying PEV charging activities. For high PEV penetrations, the installation of passive power filters (PPFs) is suggested to reduce the THDv and manage to fully charge the PEVs. Detailed simulations considering random and coordinated charging were performed on the modified IEEE 23 kV distribution system with 22 low voltage residential networks populated with PEVs that have nonlinear battery chargers. Simulation results are provided without/with filters for different penetration levels of PEVs.
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Khobaragade, Tejaswita, and K. T. Chaturvedi. "Enhanced Economic Load Dispatch by Teaching–Learning-Based Optimization (TLBO) on Thermal Units: A Comparative Study with Different Plug-in Electric Vehicle (PEV) Charging Strategies." Energies 16, no. 19 (2023): 6933. http://dx.doi.org/10.3390/en16196933.
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This research paper presents an enhanced economic load dispatch (ELD) approach using the Teaching–Learning-Based Optimization (TLBO) algorithm for 10 thermal units, examining the impact of Plug-in Electric Vehicles (PEVs) in different charging scenarios. The TLBO algorithm was utilized to optimize the ELD problem, considering the complexities associated with thermal units. The integration of PEVs in the load dispatch optimization was investigated, and different charging profiles and probability distributions were defined for PEVs in various scenarios, including overall charging profile, off-peak charging, peak charging, and stochastic charging. These tables allow for the modeling and analysis of PEV charging behavior and power requirements within the power system. By incorporating PEVs, additional controllable resources were introduced, enabling more effective load management and grid stability. The comparative analysis showcases the advantages of the TLBO-based ELD model with PEVs, demonstrating the potential of coordinated dispatch strategies leveraging PEV storage and controllability. This paper emphasizes the importance of integrating PEVs into the load dispatch optimization process, utilizing the TLBO algorithm, to achieve economic and reliable power system operation while considering different PEV charging scenarios.
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Desai, Ranjit R., Roger B. Chen, and William Armington. "A Pattern Analysis of Daily Electric Vehicle Charging Profiles: Operational Efficiency and Environmental Impacts." Journal of Advanced Transportation 2018 (2018): 1–15. http://dx.doi.org/10.1155/2018/6930932.
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Plug-in Electric Vehicles (PEVs) are considered one solution to reducing GHG emissions from private transport. Additionally, PEV adopters often have free access to public charging facilities. Through a pattern analysis, this study identifies five distinct clusters of daily PEV charging profiles observed at the public charging stations. Empirically observed patterns indicate a significant amount of operational inefficiency, where 54% of the total parking duration PEVs do not consume electricity, preventing other users from charging. This study identifies the opportunity cost in terms of GHG emissions savings if gasoline vehicles are replaced with potential PEV adopters. The time spent in parking without charging by current PEV users can be used by these potential PEV users to charge their PEVs and replace the use of gasoline. The results suggest that reducing inefficient station use leads to significant reductions in emissions. Overall, there is significant variability in outcomes depending on the specific cluster membership.
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Mansour-Saatloo, Amin, Arash Moradzadeh, Behnam Mohammadi-Ivatloo, Ali Ahmadian, and Ali Elkamel. "Machine Learning Based PEVs Load Extraction and Analysis." Electronics 9, no. 7 (2020): 1150. http://dx.doi.org/10.3390/electronics9071150.
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Transformation of the energy sector due to the appearance of plug-in electric vehicles (PEVs) has faced the researchers with challenges in recent years. The foremost challenge is uncertain behavior of a PEV that hinders operators determining a deterministic load profile. Load forecasting of PEVs is so crucial in both operating and planning of the energy systems. PEV load demand mainly depends on traveling behavior of them. This paper tries to present an accurate model to forecast PEVs’ traveling behavior in order to extract the PEV load profile. The presented model is based on machine-learning techniques; namely, a generalized regression neural network (GRNN) that correlates between PEVs’ arrival/departure times and traveling behavior is considered in the model. The results show the ability of the GRNN to communicate between arrival/departure times of PEVs and the distance traveled by them with a correlation coefficient (R) of 99.49% for training and 98.99% for tests. Therefore, the trained and saved GRNN model is ready to forecast PEVs’ trip length based on training and testing with historical data. Finally, the results indicate the importance of implementing more accurate methods to predict PEVs to gain the significant advantages in the importance of electrical energy in vehicles in the years to come.
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Hujacova, A., T. Brozova, T. Mosko, M. Kostelanska, Z. Stranak, and Karel Holada. "Platelet Extracellular Vesicles in Cord Blood of Term and Preterm Newborns Assayed by Flow Cytometry: the Effect of Delay in Sample Preparation and of Sample Freezing." Folia Biologica 66, no. 5-6 (2020): 204–11. http://dx.doi.org/10.14712/fb2020066050204.
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Plasma levels of circulating platelet extracellular vesicles (PEVs) are an emerging marker of platelet activation, thrombosis, inflammation, and endothelial dysfunction. Analysis of PEVs in cord blood of preterm newborns may reflect the underlying pathology and possibly serve as a new diagnostic and prognostic tool. However, collection, preparation and analysis of cord blood samples in clinical settings is a logistically complex process. We have studied the effect of delay in sample preparation and sample freezing on the PEV analysis by flow cytometry. PEVs in the cord blood plasma were identified after double labelling with monoclonal antibodies CD36+CD41 or CD41+CD62. Both, the delay and the freezing significantly affected the count and often also fluorescence of the detected PEVs. Additionally, our pilot study utilizing fresh cord blood samples of term and preterm newborns demonstrated significantly decreased CD36 and CD62 PEV fluorescence in preterm newborns. Our data highlight the importance of pre-analytical steps in the analysis of cord blood PEVs and suggest that not only the count, but also the level of PEV fluorescence may have possible diagnostic potential.
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Fu, Haiming, Yinghua Han, Jinkuan Wang, and Qiang Zhao. "A Novel Optimization of Plug-In Electric Vehicles Charging and Discharging Behaviors in Electrical Distribution Grid." Journal of Electrical and Computer Engineering 2018 (August 30, 2018): 1–9. http://dx.doi.org/10.1155/2018/5091084.
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In most countries, the problems of energy and environment are becoming worse. To deal with the environmental impacts and the dependence on fossil energy, many solutions were proposed. Plug-in electric vehicles (PEVs) is one of the best technique among these solutions. However, the large number of PEVs connected to the power grid simultaneously might increase power fluctuation or even cause the electricity shortage and thus affecting the typical use of the basic load. To cope with this issue and inspire PEV users coordinating with scheduling results, an algorithm was proposed to ensure the power transmission safety of branches and maximize the economic benefits. Considering the cost of both PEV owners and the power grid, a two-phase model of optimizing PEVs charging and discharging behaviors was built. According to the traveling purpose of PEV owners and the current electricity price, in the first phase, a novel model which defines each PEV’s charging or discharging status was established. The number of PEVs’ charging and discharging in each charging station can be obtained. Considering the constraints on the power transportation of branch, in the second phase, we built a mathematical model to maximize the benefit of both power grid and PEV owners. The genetic algorithm was used to optimize the charging and discharging power of PEVs. Simulation results show that the optimization method proposed in this paper has a better performance on the daily power curve compared with the uncoordinated PEVs charging.
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Weng, Shengxuan, Yanman Li, and Xiaohua Ding. "Resilient Distributed Coordination of Plug-In Electric Vehicles Charging under Cyber-Attack." Electronics 9, no. 5 (2020): 770. http://dx.doi.org/10.3390/electronics9050770.
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The coordinated scheduling of plug-in electric vehicle (PEV) charging should be constructed in distributed architecture due to the growing population of PEVs. Since the information and communication technology makes the adversary more permeable, the distributed PEV charging coordination is vulnerable to cyber-attack which may degrade the performance of scheduling and even cause the failure of scheduler task. Considering the tradeoff between system-wide economic efficiency, distribution level limitations and PEV battery degration, this paper investigates the resilient distributed coordination of PEV charging to resist cyber-attack, where the steps of detection, isolation, updating and recovery are designed synthetically. Under the proposed scheduling scheme, the misbehaving PEVs suffering from cyber-attack are gradually marginalized and finally isolated, and the remaining well-behaving PEVs obtain their own optimal charging strategy to minimize the total system cost in distributed architecture. The simulation results verify the effectiveness of theoretical method.
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Kaku, Yoshihiro, Akinori Sarai, and Yosuke Murakami. "Genetic reclassification of porcine enteroviruses." Journal of General Virology 82, no. 2 (2001): 417–24. http://dx.doi.org/10.1099/0022-1317-82-2-417.
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The genetic diversity of porcine teschoviruses (PTVs; previously named porcine enterovirus 1) and most serotypes of porcine enteroviruses (PEVs) was studied. Following the determination of the major portion of the genomic sequence of PTV reference strain Talfan, the nucleotide and derived amino acid sequences of the RNA-dependent RNA polymerase (RdRp) region, the capsid VP2 region and the 3′ non-translated region (3′-NTR) were compared among PTVs and PEVs and with other picornaviruses. The sequences were obtained by RT–PCR and 3′-RACE with primers based on the sequences of Talfan and available PEV strains. Phylogenetic analysis of RdRp/VP2 and analysis of the predicted RNA secondary structure of the 3′-NTR indicated that PEVs should be reclassified genetically into at least three groups, one that should be assigned to PTVs and two PEV subspecies represented by strain PEV-8 V13 and strain PEV-9 UKG410/73.
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Moon, Jong Hui, Han Na Gwon, Gi Ryong Jo, Woo Yeong Choi, and Kyung Soo Kook. "Stochastic Modeling Method of Plug-in Electric Vehicle Charging Demand for Korean Transmission System Planning." Energies 13, no. 17 (2020): 4404. http://dx.doi.org/10.3390/en13174404.
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The number of plug-in electric vehicles (PEVs) has rapidly increased owing to the government’s active promotion policy worldwide. Consequently, in the near future, their charging demand is expected to grow enough for consideration in the planning process of the transmission system. This study proposes a stochastic method for modeling the PEV charging demand, of which the time and amount are uncertain. In the proposed method, the distribution of PEVs is estimated by the substations based on the number of electricity customers, PEV expansion target, and statistics of existing vehicles. An individual PEV charging profile is modeled using the statistics of internal combustion engine (ICE) vehicles driving and by aggregating the PEV charging profiles per 154 kV substation, the charging demand of PEVs is determined for consideration as part of the total electricity demand in the planning process of transmission systems. The effectiveness of the proposed method is verified through case studies in the Korean power system. It was found that the PEV charging demand has considerable potential as the additional peak demand in the transmission system planning because the charging time could be concentrated in the evening peak time.
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Chen, Dapeng, Zhaoxia Jing, and Huijuan Tan. "Optimal Bidding/Offering Strategy for EV Aggregators under a Novel Business Model." Energies 12, no. 7 (2019): 1384. http://dx.doi.org/10.3390/en12071384.
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Realizing the full potential of plug-in electric vehicle (PEVs) in power systems requires the development of business models for PEV owners and electric vehicle aggregators (EVAs). Most business models neglect the significant economic potential of PEV demand response. This paper addresses this challenge by proposing a novel business model to optimize the charging energy of PEVs for maximizing the owners’ profits. The proposed business model aims to overcome the opportunity cost neglect for PEV owners, whose charging energy and charging profiles are optimized with full consideration of the demand curves and market conditions. Lagrangian relaxation technology is used for the relaxation of the constraint of satisfying the charging demand, and as a result, the optimization potential becomes greater. The bidding/offering strategy is formulated as a two-stage stochastic optimization problem, considering the different market prices and initial and target state of energy (SOE) of the PEVs. By case studies and analyses, we demonstrate that the proposed business model can effectively overcome the opportunity cost neglect and increase the PEV owners’ profits. Furthermore, we demonstrate that the proposed business model is incentive-compatible. The PEV owners will be attracted by the proposed business model.
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Germanà, Roberto, Francesco Liberati, Emanuele De Santis, Alessandro Giuseppi, Francesco Delli Priscoli, and Alessandro Di Giorgio. "Optimal Control of Plug-In Electric Vehicles Charging for Composition of Frequency Regulation Services." Energies 14, no. 23 (2021): 7879. http://dx.doi.org/10.3390/en14237879.
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This paper presents a novel control system for the participation of plug-in electric vehicles (PEVs) in the provisioning of ancillary services for frequency regulation, in a way that is transparent to the driver and harmonized with the smart charging service requirements. Given a power-frequency droop curve, which specifies how the set of PEVs collectively participate to the provisioning of the frequency regulation service (we call this curve a “global” droop curve), we propose an algorithm to compute “local” droop curves (one for each PEV), which are optimized according to the current status of the PEV and the current progress of the smart recharging session. Once aggregated, the local droop curves match the global one (so that the PEVs contribute as expected to the provisioning of the ancillary service). One innovative aspect of the proposed algorithm is that it is specifically designed to be interoperable with the algorithms that control the PEV recharging process; hence, it is transparent to the PEV drivers. Simulation results are presented to validate the proposed solution.
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Nazari, Fatemeh, Abolfazl (Kouros) Mohammadian, and Thomas Stephens. "Dynamic Household Vehicle Decision Modeling Considering Plug-In Electric Vehicles." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 49 (2018): 91–100. http://dx.doi.org/10.1177/0361198118796925.
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Plug-in electric vehicles (PEVs) offer alternatives to traditional vehicles that rely on petroleum-based fuels. While PEV customers can enjoy significant reductions in fuel costs, they incur a larger capital cost than users of traditional vehicles because PEV technology is still maturing. Therefore, consumers adopting PEVs face a trade-off between fuel cost savings with environmental benefits and extra capital cost. It is thus crucial for policy makers and PEV manufacturers to understand people’s vehicle decision-making process while considering their socio-economic and travel pattern characteristics as well as the built-environment factors. This paper presents a connected, two-stage, dynamic model of PEV adoption and vehicle-transaction decision-making. Two connected nested logit (NL) models are estimated. The upper level is a two-level NL model to predict choice of vehicle type between four fuel types: gasoline, diesel, hybrid gasoline–electric, and PEV. The lower level is an NL model of vehicle-transaction choice which accommodates four transaction decisions of buy, trade, dispose, and do nothing, while accounting for the log-sum from the vehicle-type choice model, and is estimated using two waves of a panel data set. We find that households with higher levels of income and education are more likely to adopt a PEV. We also found that primarily decision makers take into account the accessibility to charging stations as a critical factor in choosing PEVs.
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Sridhar, Mr Vakeel, and Mr S. Radha Krishna Reddy. "Effective Utilization of Available PEV Battery Capacity for Mitigation of Solar PV Impact and Grid Support with Integrated V2G Functionality." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (2023): 753–64. http://dx.doi.org/10.22214/ijraset.2023.49504.
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Abstract: Utilizing battery storage devices in plug-in electric vehicles (PEVs) for grid support using vehicle-to-grid (V2G) concept is gaining popularity. With appropriate control strategies, the PEV batteries and associated power electronics can exploited for solar photovoltaic (PV) impact mitigation and grid support. However, as the PEV batteries have limited capacity and the capacity usage is also constrained by transportation requirements, an intelligent strategy is necessary for an effective utilization of the available capacity for V2G applications. In this paper, a strategy for an effective utilization of PEV battery capacity for solar PV impact mitigation and grid support is proposed. A controllable charging/ discharging pattern is developed to optimize the use of the limited PEV battery capacity to mitigate PV impacts, such as voltage rise during midday or to support the evening load peak. To ensure an effective utilization of the available PEV battery capacity when used for travel (which is the main usage of the PEVs) or when interventions in the charging operation is caused by passing clouds, a strategy for dynamic adjustments in PEV charging/discharging rates is proposed. The effectiveness of the proposed strategy is tested using a real distribution system in Australia based on practical PV and PEV data.
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Qian, Kun, Zhichao Hou, Jie Liang, Ruixue Liu, and Dengke Sun. "Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis." Applied Sciences 11, no. 10 (2021): 4385. http://dx.doi.org/10.3390/app11104385.
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The interior sound quality (SQ) of pure electric vehicles (PEVs) has become an important consideration for users purchasing vehicles. At present, it is insufficient to take the sound pressure level as the interior acoustics design index of PEVs. Transfer path analysis (TPA) and transfer path synthesis (TPS) that take the SQ of interior noise as the improvement target remains in the preliminary exploration stage. In this paper, objective psychoacoustic parameters of SQ were taken as evaluation indexes of interior PEV noise. A virtual interior SQ synthesis model was designed on the basis of TPA and TPS, which combines experimentation and simulation. The SQ synthesis model demonstrates each noise component contribution in a PEV by new SQ separation technology. First, the interior noise transfer path and noise source of the PEV were determined in a synthesis analysis method of the interior PEV noise. Second, on the basis of the composition mechanism of interior noise and the basic principle of TPA, the excitation signal and transfer function of each interior noise path in the PEV were tested. On the basis of TPS, the interior SQ synthesis model of PEV was then established. Finally, the accuracy of the prediction model was verified in simulation and experimental comparison studies on the psychoacoustic objective parameters of SQ. The SQ objective parameter value of each transfer path was quantified by using contribution analysis. The results are expected to improve the comfort of the interior acoustic environment and enhance the competitiveness of vehicle products. They also provide an effective reference and new ideas for the development of interior SQ in PEVs.
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Willis, Cory M., Alexandra M. Nicaise, Antoine Menoret, et al. "Extracellular vesicle fibrinogen induces encephalitogenic CD8+ T cells in a mouse model of multiple sclerosis." Proceedings of the National Academy of Sciences 116, no. 21 (2019): 10488–93. http://dx.doi.org/10.1073/pnas.1816911116.
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Extracellular vesicles (EVs) are emerging as potent mediators of intercellular communication with roles in inflammation and disease. In this study, we examined the role of EVs from blood plasma (pEVs) in an experimental autoimmune encephalomyelitis mouse model of central nervous system demyelination. We determined that pEVs induced a spontaneous relapsing−remitting disease phenotype in MOG35–55-immunized C57BL/6 mice. This modified disease phenotype was found to be driven by CD8+ T cells and required fibrinogen in pEVs. Analysis of pEVs from relapsing−remitting multiple sclerosis patients also identified fibrinogen as a significant portion of pEV cargo. Together, these data suggest that fibrinogen in pEVs contributes to the perpetuation of neuroinflammation and relapses in disease.
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Kang, Ti, Huaqing Li, and Lifeng Zheng. "Aggregative Game for Distributed Charging Strategy of PEVs in a Smart Charging Station." Axioms 12, no. 2 (2023): 186. http://dx.doi.org/10.3390/axioms12020186.
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This paper proposes a charging strategy for plug-in electric vehicles (PEVs) in a smart charging station (SCS) that considers load constraints and time anxieties. Due to the rapidly growing load demand of PEVs and the load capacity investments in infrastructure, PEV charging needs to be subject to overload limits, beyond which failures can occur. The time anxiety is presented to address some of the uncertainties that may arise while charging PEVs. Under an aggregative game framework, this paper constructs a price-driven charging model to minimize costs by choosing the optimal charging strategy. Meanwhile, since the driver information is an aggregated item in the PEV cost function, the drivers’ privacy can be protected. Then, a distributed reflected forward–backward (RFB) splitting method is developed to search for the generalized Nash equilibria (GNE) of the game. The convergence of the proposed algorithm and the effectiveness of the charging strategy are verified by the detailed simulation and results.
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Zeinali, Mehdi, Nuh Erdogan, Islam Safak Bayram, and John S. Thompson. "Impact of Communication System Characteristics on Electric Vehicle Grid Integration: A Large-Scale Practical Assessment of the UK’s Cellular Network for the Internet of Energy." Electricity 4, no. 4 (2023): 309–19. http://dx.doi.org/10.3390/electricity4040018.
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The ever-increasing number of plug-in electric vehicles (PEVs) requires appropriate electric vehicle grid integration (EVGI) for charging coordination to maintain grid stability and enhance PEV user convenience. As such, the widespread adoption of electric mobility can be successful. EVGI is facilitated through charging stations and empowers PEV users to manage their charging demand by using smart charging solutions. This makes PEV grids assets that provide flexibility to the power grid. The Internet of Things (IoT) feature can make smooth EVGI possible through a supporting communication infrastructure. In this regard, the selection of an appropriate communication protocol is essential for the successful implementation of EVGI. This study assesses the efficacy of the UK’s 4G network with TCP and 4G UDP protocols for potential EVGI operations. For this, an EVGI emulation test bed is developed, featuring three charging parking lots with the capacity to accommodate up to 64 PEVs. The network’s performance is assessed in terms of data packet loss (e.g., the data-exchange capability between EVGI entities) and latency metrics. The findings reveal that while 4G TCP often outperforms 4G UDP, both achieve latencies of less than 1 s with confidence intervals of 90% or greater for single PEV cases. However, it is observed that the high penetration of PEVs introduces a pronounced latency due to queuing delays in the network including routers and the base station servers, highlighting the challenges associated with maintaining efficient EVGI coordination, which in turn affects the efficient use of grid assets.
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Suyono, Hadi, Mir Toufikur Rahman, Hazlie Mokhlis, Mohamadariff Othman, Hazlee Azil Illias, and Hasmaini Mohamad. "Optimal Scheduling of Plug-in Electric Vehicle Charging Including Time-of-Use Tariff to Minimize Cost and System Stress." Energies 12, no. 8 (2019): 1500. http://dx.doi.org/10.3390/en12081500.
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Technological advancement, environmental concerns, and social factors have made plug-in electric vehicles (PEVs) popular and attractive vehicles. Such a trend has caused major impacts to electrical distribution systems in terms of efficiency, stability, and reliability. Moreover, excessive power loss, severe voltage deviation, transformer overload, and system blackouts will happen if PEV charging activities are not coordinated well. This paper presents an optimal charging coordination method for a random arrival of PEVs in a residential distribution network with minimum power loss and voltage deviation. The method also incorporates capacitor switching and on-load tap changer adjustment for further improvement of the voltage profile. The meta-heuristic methods, binary particle swarm optimization (BPSO) and binary grey wolf optimization (BGWO), are employed in this paper. The proposed method considers a time-of-use (ToU) electricity tariff such that PEV users will get more benefits. The random PEV arrival is considered based on the driving pattern of four different regions. To demonstrate the effectiveness of the proposed method, comprehensive analysis is conducted using a modified of IEEE 31 bus system with three different PEV penetrations. The results indicate a promising outcome in terms of cost and the distribution system stress minimization.
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Jayasri, Nemala, V. S. Anusuya Devi, Preeti Tewari, Sorabh Lakhanpal, Tamam Ali Abd Ulabbas Abedi, and Kapil Bodha. "Adaptive Control Strategy for Real-Time Regulation of PEV Charging in Response to Fluctuating Renewable Energy Supply." E3S Web of Conferences 616 (2025): 01006. https://doi.org/10.1051/e3sconf/202561601006.
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This study is concerned with the coordinated charging pattern of plugin electric vehicles (PEVs) by using a simulation and control framework. The first of these is to develop a novel control technique based on a grid structure to manage the charging power of PEVs in reaction to fluctuating renewable energy sources. The grid is assumed to control and communicate instantly and directly through a common control signal the electricity used for PEV charging. Based on the principle of market-based demand modeling, the subsequent theoretical formulation involves a system of partial differential equations for concurrent PEV charging. It is then applied to future real world driving data and compared to a PEV Monte Carlo model. Moreover, the principles of SM control are introduced to synthesize the robust output feedback controller for the system without state error. The fluctuating PEV count is addressed by focusing on the sole observable output: the instantaneous mismatch of supply and demand of renewable electricity by customers. The performance of the controller is evaluated in the present research based on a real wind power state trajectory through numerical simulations of the system.
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Anderson, Tessa. "Electric vehicles in Danish Municipalities: An Understanding of Motivations, Barriers, and the Future of Sustainable Mobility." Vehicles 1, no. 1 (2019): 57–68. http://dx.doi.org/10.3390/vehicles1010004.
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This paper explores the procurement, use, and experience of plug-in electric vehicles (PEVs) in Danish municipalities in relation to the notion of early adopters and socio-technical theory. Denmark has been one of the most ambitious countries in terms of electric vehicle adoption and use. This study used a combination of in-depth surveys and interviews with all 61 Danish municipalities on their fleet PEV experience and use. By building on the literature, the paper offers a deeper understanding of decision-making pathways for the procurement of PEVs. PEVs were found to be most suited to certain departments and the acceptance and uptake of PEVs was found to be complex and not straightforward.
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Islam, Junaid Bin Fakhrul, Mir Toufikur Rahman, Shameem Ahmad, et al. "Multi-Objective-Based Charging and Discharging Coordination of Plug-in Electric Vehicle Integrating Capacitor and OLTC." Energies 16, no. 5 (2023): 2172. http://dx.doi.org/10.3390/en16052172.
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The integration of plug-in electric vehicles (PEVs) in residential distribution networks demands a significant amount of electrical load where random and uncoordinated charging affects the quality and performance of the distribution network. Random and uncoordinated charging may increase the peak demand and can increase stress on critical network assets such as line, transformer, and switching devices. Moreover, the charging of PEVs in a low network reduces the voltage of the system below the lower limit. On the other hand, using PEVs as storage in the V2G mode can improve the network condition. Therefore, it is critical to properly manage the charging and discharging operation of PEVs. This paper proposes a multi-objective-based charging and discharging coordination of PEVs with the operation of the capacitor and on-load tap changer (OLTC). With the proposed strategy, the distribution network is operated safely, and charging is ensured for all PEVs connected to the network. The main consideration of this research is to reduce the daily power loss, operational cost, and voltage deviation of the system. The metaheuristic optimization binary firefly algorithm (BFA) has been applied to coordinate PEV charging and discharging as well as capacitor and OLTC operation in the system. A modified IEEE 31 bus 23 kV distribution system is used to implement the proposed strategy. From the obtained results, it is found that the combined PEV charging and discharging coordination with capacitor and OLTC operation reduces the power loss and cost by 34.16% and 12.68%, respectively, with respect to uncoordinated charging and enhances the voltage condition of the network.
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Konstantinidis, George, Emmanuel Karapidakis, and Alexandros Paspatis. "Mitigating the Impact of an Official PEV Charger Deployment Plan on an Urban Grid." Energies 15, no. 4 (2022): 1321. http://dx.doi.org/10.3390/en15041321.
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Plug-in electric vehicles (PEVs) are rapidly increasing all over the world as electromobility is being promoted to reduce the greenhouse gas (GHG) emissions. PEVs locally produce zero emissions and they are more efficient in contrast to internal combustion engine vehicles. On the other hand, the impact of the uncoordinated charging of PEVs is expected to create new challenges for the established distribution grid. This article initially evaluates the impact of uncoordinated charging on the voltage regulation and transformer loading in the city of Heraklion, Greece. Then, a coordinated charging strategy is proposed to deal with the issue of transformer capacity violation by PEVs. Two cases were considered when the transformer overloading from PEV charging was taken into consideration: (a) keeping the transformer below its nominal capacity limit and (b) keeping the transformer below 90% of its nominal capacity limit. This was achieved by distributing the available capacity (nominal capacity minus the residential loads) of the transformer to the PEV chargers in a way that the aforementioned limits were satisfied. Real-world data of the distribution grid and the hourly power consumption of the city were used to validate the proposed method. Results show that possible transformer capacity violation can be tackled by the proposed coordinated charging, without exceeding the voltage regulation limits.
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Lugo-Gavidia, Leslie Marisol, Dylan Burger, Janis M. Nolde, Vance B. Matthews, and Markus P. Schlaich. "Evaluation of Circulating Platelet Extracellular Vesicles and Hypertension Mediated Organ Damage." International Journal of Molecular Sciences 23, no. 23 (2022): 15150. http://dx.doi.org/10.3390/ijms232315150.
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Elevated circulating platelet-derived extracellular vesicles (pEVs) have been associated with arterial hypertension. The role of hypertension-mediated organ damage (HMOD) to induce EV release is still unknown. We studied the micro- and macro-vascular changes (retinal vascular density and pulse wave velocity), endothelial function (flow-mediated vasodilation of brachial artery and finger plethysmography), and assessed the psychosocial status (anxiety and depression) in hypertensive patients to determine their relationship with EV release. Pulse wave velocity showed a significant positive correlation with pEVs (r = 0.33; p = 0.01). Systolic blood pressure (SBP) negatively correlated with retinal vascularity. The superficial retinal vascular plexus density in the whole image showed a significant negative correlation with 24 h SBP (r = −0.38, p < 0.01), day-SBP (r = −0.35, p = 0.01), and night-SBP (r = −0.27, p = 0.04). pEVs did not show significant associations with microvascular damage (retinal vascular density), endothelial function (flow-mediated vasodilation of brachial artery and finger plethysmography), or psychosocial status (anxiety and depression). Our results indicate that the pEV levels were associated with macrovascular damage measured by PWV, whereas no significant association between pEVs and microvascular damage, endothelial function, or emotional status could be detected. The potential utility of pEV in clinical practice in the context of HMOD may be limited to macrovascular changes.
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Chaudhary, Preeti Kumari, Sanggu Kim, and Soochong Kim. "Shedding Light on the Cell Biology of Platelet-Derived Extracellular Vesicles and Their Biomedical Applications." Life 13, no. 6 (2023): 1403. http://dx.doi.org/10.3390/life13061403.
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EVs are membranous subcellular structures originating from various cells, including platelets which consist of biomolecules that can modify the target cell’s pathophysiological functions including inflammation, cell communication, coagulation, and metastasis. EVs, which are known to allow the transmission of a wide range of molecules between cells, are gaining popularity in the fields of subcellular treatment, regenerative medicine, and drug delivery. PEVs are the most abundant EVs in circulation, being produced by platelet activation, and are considered to have a significant role in coagulation. PEV cargo is extremely diverse, containing lipids, proteins, nucleic acids, and organelles depending on the condition that induced their release and can regulate a wide range of biological activities. PEVs, unlike platelets, can overcome tissue barriers, allowing platelet-derived contents to be transferred to target cells and organs that platelets cannot reach. Their isolation, characterization, and therapeutic efficacy, on the other hand, are poorly understood. This review summarizes the technical elements of PEV isolation and characterization methods as well as the pathophysiological role of PEVs, including therapeutic potential and translational possibility in diverse disciplines.
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Baharin, Nurliyana, Mohamad Fani Sulaima, Nofri Yenita Dahlan, and Hazlie Mokhlis. "Evaluation of the time-of-use tariff responsiveness for plug-in electric vehicle home charging in Malaysia." International Journal of Advances in Applied Sciences 13, no. 4 (2024): 769. http://dx.doi.org/10.11591/ijaas.v13.i4.pp769-776.
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Plug-in electric vehicles (PEVS) have become increasingly popular as a viable transportation option as owners can charge them at home. This will add much energy to the house if the users charge their PEVs at home. The PEV charging load will lead to extra energy demand on the distribution network, and the users will need to pay more for electricity if they use the current domestic tariff in Malaysia. This research aims to analyze the PEV charging costs using time-of-use (ToU) tariffs with different time segmentations and price elasticity. The effect of four residential load profile patterns has also been investigated in Malaysia as a case study. Four PEV charging scenarios were created, and the charging times were set according to Malaysian driving styles, with charging times starting at 6 PM, 10 PM, and 9 AM. The PEV and electric vehicle supply equipment (EVSE) are set to be homogeneous, and the EV was assumed to have a minimum state-of-charge of 20%. The main contribution of this paper is the selection of the ToU tariff segmentation, where the structure of the smallest time segmentation gave the lowest electricity bill per month compared to the Tenaga Malaysia Berhad (TNB) domestic tariff.
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Nurliyana, Baharin, Fani Sulaima Mohamad, Yenita Dahlan Nofri, and Mokhlis Hazlie. "Evaluation of the time-of-use tariff responsiveness for plug-in electric vehicle home charging in Malaysia." International Journal of Advances in Applied Sciences 13, no. 4 (2024): 769–76. https://doi.org/10.11591/ijaas.v13.i4.pp769-776.
Full textAbstract:
Plug-in electric vehicles (PEVS) have become increasingly popular as a viable transportation option as owners can charge them at home. This will add much energy to the house if the users charge their PEVs at home. The PEV charging load will lead to extra energy demand on the distribution network, and the users will need to pay more for electricity if they use the current domestic tariff in Malaysia. This research aims to analyze the PEV charging costs using time-of-use (ToU) tariffs with different time segmentations and price elasticity. The effect of four residential load profile patterns has also been investigated in Malaysia as a case study. Four PEV charging scenarios were created, and the charging times were set according to Malaysian driving styles, with charging times starting at 6 PM, 10 PM, and 9 AM. The PEV and electric vehicle supply equipment (EVSE) are set to be homogeneous, and the EV was assumed to have a minimum state-of charge of 20%. The main contribution of this paper is the selection of the ToU tariff segmentation, where the structure of the smallest time segmentation gave the lowest electricity bill per month compared to the Tenaga Malaysia Berhad (TNB) domestic tariff.
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Eustes, Alicia S., and Sanjana Dayal. "The Role of Platelet-Derived Extracellular Vesicles in Immune-Mediated Thrombosis." International Journal of Molecular Sciences 23, no. 14 (2022): 7837. http://dx.doi.org/10.3390/ijms23147837.
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Platelet-derived extracellular vesicles (PEVs) play important roles in hemostasis and thrombosis. There are three major types of PEVs described based on their size and characteristics, but newer types may continue to emerge owing to the ongoing improvement in the methodologies and terms used to define various types of EVs. As the literature on EVs is growing, there are continuing attempts to standardize protocols for EV isolation and reach consensus in the field. This review provides information on mechanisms of PEV production, characteristics, cellular interaction, and their pathological role, especially in autoimmune and infectious diseases. We also highlight the mechanisms through which PEVs can activate parent cells in a feedback loop.
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Wang, Ying, Zhile Yang, Monjur Mourshed, Yuanjun Guo, Qin Niu, and Xiaodong Zhu. "Demand side management of plug-in electric vehicles and coordinated unit commitment: A novel parallel competitive swarm optimization method." Energy Conversion and Management 196 (June 28, 2019): 935–49. https://doi.org/10.1016/j.enconman.2019.06.012.
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Decreasing initial costs, the increased availability of charging infrastructure and favorable policy measures have resulted in the recent surge in plug-in electric vehicle (PEV) ownerships. PEV adoption increases electricity consumption from the grid that could either exacerbate electricity supply shortages or smooth demand curves. The optimal coordination and commitment of power generation units while ensuring wider access of PEVs to the grid are, therefore, important to reduce the cost and environmental pollution from thermal power generation systems, and to transition to a smarter grid. However, flexible demand side management (DSM) considering the stochastic charging behavior of PEVs adds new challenges to the complex power system optimization, and makes existing mathematical approaches ineffective. In this research, a novel parallel competitive swarm optimization algorithm is developed for solving large-scale unit commitment (UC) problems with mixed-integer variables and multiple constraints – typically found in PEV integrated grids. The parallel optimization framework combines binary and real-valued competitive swarm optimizers for solving the UC problem and demand side management of PEVs simultaneously. Numerical case studies have been conducted with multiple scales of unit numbers and various demand side management strategies of plug-in electric vehicles. The results show superior performance of proposed parallel competitive swarm optimization based method in successfully solving the proposed complex optimization problem. The flexible demand side management strategies of plug-in electric vehicles have shown large potentials in bringing considerable economic benefit.
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Panichtanakom, Supipat, and Kusumal Chalermyanont. "Electric Energy Management for Plug-in Electric Vehicles Charging in the Distribution System by a dual cascade scheduling algorithm." International journal of electrical and computer engineering systems 13, no. 1 (2022): 63–75. http://dx.doi.org/10.32985/ijeces.13.1.7.
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This paper presents an algorithm for plug-in electric vehicles (PEVs) charging in the three-phase distribution system for residential houses. It aims to prevent violent voltage level deviation and increasing losses on the three-phase distribution system due to uncontrolled charging and allocate power to each plug-in electric vehicle. The algorithm is comprised of two processes. The first process is power limitation and limited power of load imbalance by if-else rules, while the second process is power allocation to each PEV by the dual cascade scheduling algorithm which is the integration of tasking scheduling algorithms. A 100 kVA distribution transformer and 30 houses are defined in the simulation situation. Also, the available PEVs in single-phase, two-phase, and three-phase systems are assigned for verification of the proposed algorithm. Root-mean-square deviation (RMSD) referred to the satisfaction of PEV owners, total PEVs charged energy, and the average percentage of achieved charging time, as the result indicators. The results show the proposed algorithm can provide good results without rejected PEVs charging. Furthermore, this paper also displays the analysis of voltage level, percentage of voltage unbalance factor, and loss in the distribution system. In the future, coordination with home appliances to gain a high load margin or electric energy cost control will be improved in the proposed algorithm
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Memon, Zeeshan Anjum, Dalila Mat Said, Mohammad Yusri Hassan, Hafiz Mudassir Munir, Faisal Alsaif, and Sager Alsulamy. "Effective Deterministic Methodology for Enhanced Distribution Network Performance and Plug-in Electric Vehicles." Sustainability 15, no. 9 (2023): 7078. http://dx.doi.org/10.3390/su15097078.
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The rapid depletion of fossil fuel motivates researchers and policymakers to switch from the internal combustion engine (ICE) to plug-in electric vehicles (PEVs). However, the electric power distribution networks are congested, which lowers the accommodation of PEVs and produces higher power losses. Therefore, the study proposes an effective deterministic methodology to maximize the accommodation of PEVs and percentage power loss reduction (%PLR) in radial distribution networks (RDNs). In the first stage, the PEVs are allocated to the best bus, which is chosen based on the loading capacity to power loss index (LCPLI), and the accommodation profile of PEVs is developed based on varying states of charge (SoC) and battery capacities (BCs). In the second stage, the power losses are minimized in PEV integrated networks with the allocation of DG units using a recently developed parallel-operated arithmetic optimization algorithm salp swarm algorithm (AOASSA). In the third stage, the charging and discharging ratios of PEVs are optimized analytically to minimize power losses after planning PEVs and DGs. The outcomes reveal that bus-2 is the most optimal bus for accommodation of PEVs, as it has the highest level of LCPLI, which is 9.81 in the 33-bus system and 28.24 in the 69-bus system. The optimal bus can safely accommodate the largest number of electric vehicles, with a capacity of 31,988 units in the 33-bus system and 92,519 units in the 69-bus system. Additionally, the parallel-operated AOASSA mechanism leads to a reduction in power losses of at least 0.09% and 0.25% compared with other algorithms that have been previously applied to the 33-bus and 69-bus systems, respectively. Moreover, with an optimal charging and discharging ratio of PEVs in the IEEE-33-bus radial distribution network (RDN), the %PLR further improved by 3.08%, 4.19%, and 2.29% in the presence of the optimal allocation of one, two and three DG units, respectively. In the IEEE-69-bus RDN, the %PLR further improved by 0.09%, 0.09%, and 0.08% with optimal charge and discharge ratios in the presence of one, two, and three DG units, respectively. The proposed study intends to help the local power distribution companies to maximize accommodation of PEV units and minimize power losses in RDNs.
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Kazatsker, Marina Marks, Adi Sharabi-Nov, Hamutal Meiri, Rami Sammour, and Marei Sammar. "Augmented Placental Protein 13 in Placental-Associated Extracellular Vesicles in Term and Preterm Preeclampsia Is Further Elevated by Corticosteroids." International Journal of Molecular Sciences 24, no. 15 (2023): 12051. http://dx.doi.org/10.3390/ijms241512051.
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Placental protein 13 (PP13) is a regulatory protein involved in remodeling the vascular system of the pregnancy and extending the immune tolerance of the mother to the growing fetus. PP13 is localized on the surface of the syncytiotrophoblast. An ex vivo placental model shows that the PP13 is released via placental-associated extracellular vesicles (PEVs) to the maternal uterine vein. This exploratory study aimed to determine PEV-associated PP13 in the maternal circulation as compared to the known soluble fraction since each has a specific communication pathway. Patients admitted to Bnai Zion Medical Center for delivery were recruited, and included 19 preeclampsia (PE) patients (7 preterm PE gestational age < 37 weeks’ gestation), 16 preterm delivery (PTD, delivery at GA < 37 weeks’ gestation), and 15 matched term delivery controls. Treatment by corticosteroids (Celestone), which is often given to patients with suspected preterm PE and PTD, was recorded. The PEV proteome was purified from the patients’ plasma by size exclusion chromatography (SEC) to separate the soluble and PEV-associated PP13. The total level of PP13 (soluble and PEV-associated) was determined using mild detergent that depleted the PEV proteome. PP13 fractions were determined by ELISA with PP13 specific antibodies. ELISA with alkaline phosphatase (PLAP)- and cluster differentiation 63 (CD63)-specific antibodies served to verify the placental origin of the PEVs. SPSS was used for statistical analysis. The patients’ medical, pregnancy, and delivery records in all groups were similar except, as expected, that a larger number of PE and PTD patients had smaller babies who were delivered earlier, and the PE patients had hypertension and proteinuria. The SEC analysis detected the presence of PP13 in the cargo of the PEVs and on their surface, in addition to the known soluble fraction. The median soluble PP13 was not significantly different across the PE, PTD, and term delivery control groups. However, after depleting the PEV of their proteome, the total PP13 (soluble and PEV-associated) was augmented in the cases of preterm PE, reaching 2153 pg/mL [IQR 1866–2838] but not in cases of PTD reaching 1576 pg/mL [1011–2014] or term delivery groups reaching 964 pg/mL [875–1636]), p < 0.01. On the surface of the circulating PEV from PTD patients, there was a decrease in PP13. Corticosteroid treatment was accompanied by a massive depletion of PP13 from the PEV, especially in preterm PE patients. This exploratory study is, thus, the first to determine PEV-associated PP13 in maternal circulation, providing a quantitative determination of the soluble and the PEV-associated fractions, and it shows that the latter is the larger. We found an increase in the amount of PP13 carried via the PEV-associated pathway in PE and PTD patients compared to term delivery cases, which was further augmented when the patients were treated with corticosteroids, especially in preterm PE. The signal conveyed by this novel communication pathway warrants further research to investigate these two differential pathways for the liberation of PP13.
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Xu, Shaolun, Zheng Yan, Xiaobo Zhao, Liang Zhang, Donghan Feng, and Xiaoyuan Xu. "Decentralized Charging of Plug-In Electric Vehicles Using Lagrange Relaxation Method at the Residential Transformer Level." International Journal of Emerging Electric Power Systems 17, no. 3 (2016): 267–76. http://dx.doi.org/10.1515/ijeeps-2015-0148.
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Abstract The expected rise of plug-in electric vehicles (PEVs) will lead to a significant additional demand on low voltage distribution systems, and PEVs can challenge power quality and reliability of power systems if their charging is not coordinated. The PEV aggregator, acting as an intermedium between customers and the grid operator, can solve the charging management problem effectively. In this study, a decentralized scheduling scheme of aggregators for PEV charging based on Lagrange Relaxation method is proposed. At the same time, a centralized model of aggregators is also formulated in the same situation in order to make comparisons with the proposed scheme. The two charging models are both aimed at maximizing the charging profit of PEV aggregators considering constraints including users’ electricity demand, charging time, available capacity of distribution transformers, etc. A number of charging scenarios are simulated to evaluate the proposed method. The economic benefits, computational complexity and efficiency are compared and analyzed between the centralized charging and the decentralized charging. Simulation results verify that the decentralized charging strategy based on Lagrange Relaxation method gains charging profit close to the centralized charging yet is more efficient and realizable than the centralized charging.
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Coria, Gustavo E., Angel M. Sanchez, Ameena S. Al-Sumaiti, Guiseppe A. Rattá, Sergio R. Rivera, and Andrés A. Romero. "A Framework for Determining a Prediction-Of-Use Tariff Aimed at Coordinating Aggregators of Plug-In Electric Vehicles." Energies 12, no. 23 (2019): 4487. http://dx.doi.org/10.3390/en12234487.
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The objective of this article is to propose a framework for defining a day-ahead prediction-of-use tariff (POU) that promotes aggregators of the plug-in electric vehicles (PEVs) to operate as closely as possible to an optimal charging curve previously calculated by the distribution system operator (DSO). The DSO calculates this optimal charging curve to flatten the load curve of the distribution transformers as much as possible by coordinating the daily recharging of PEVs. The objective is to establish the optimal power profile of the PEV aggregators needed to flatten the power curve supplied by the transformer, so that PEV customers’ needs can be met throughout the day. The proposed framework is applied in a case study accounting for uncertainties associated with charging through Monte Carlo simulation, in order to find the POU tariff. The results demonstrate that applying the POU tariff determines the transformer’s minimum power limit necessary to meet all PEV users’ needs. Additionally, the day-ahead POU tariff does not generate new demand peaks, since it does not concentrate the energy supply of flexible loads in pre-established time bands. Finally, simulation reflects the significant effect of the PEV charging on the distribution system in terms of enhancing the voltage profile, maximizing the transformer life, and reducing the power/energy losses.
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Kongjeen, Yuttana, Krischonme Bhumkittipich, and Nadarajah Mithulananthan. "Optimal DG Sizing and Location in Modern Power Grids using PEVs Load Demand Probability." ECTI Transactions on Electrical Engineering, Electronics, and Communications 17, no. 1 (2019): 51–59. http://dx.doi.org/10.37936/ecti-eec.2019171.215410.
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The integration of plug-in electric vehicles (PEVs) to the conventional distribution system has had a major impact upon consumption of energy in the past year. This paper presents optimal distributed generator (DG) sizing and location in the power system using PEVs load demand probability. The MATLAB m-file scripts and OpenDSS were applied to solve the proposed study by varying the percentage penetration level of PEVs. A genetic algorithm optimization technique was used to find the best solution of DG installation. The simulation results showed thatthe PEVs were directly connected to the power grid with 100 PEVs (13.84%), 200 PEVs (27.68%) and 500 PEVs (69.19%), respectively. It was found that the DG sizing also varied with 1.773 MW, 1.663 MW and 1.996 MW, respectively. While the position of the DG also changes according to the sizing of DG. The position of DG was installed at bus No.738, bus No.741 and bus No.711, respectively. Therefore, the optimal DG placement helped to improve and reduce the total line loss and total energy demand from the power grid. The grid increased the power system stability and reduced the impact from the large scale of PEV penetration.
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Sai Kalyan, Ch Naga, Pasala Gopi, Govind Singh Jethi, K. Harinath Reddy, and Mohit Bajaj. "Water Cycle Algorithm Tuned Cascade Controller for the Frequency Control of a Nonlinear Hydrothermal Power System with PEV Integration." E3S Web of Conferences 564 (2024): 06002. http://dx.doi.org/10.1051/e3sconf/202456406002.
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In this paper, a new cascade (C) fractional order (FO) proportional-integral-derivative (PID) and proportional-integral (PI) (CFOPID-PI) controller is designed based on the optimization technique of the water cycle algorithm (WCA) for the frequency regulation of plug-in electric vehicles (PEVs) integrated dual area non-linear hydrothermal (DANLHT) system. The PEVs integrated DANLHT system has two areas: thermal, hydro, and PEVs integration, and the system dynamic analysis is initiated for the step load disturbance (SLD) of 10% in area 1. However, the performance efficacy of the proposed CFOPID-PI controller is demonstrated by the performances of other reported controllers in the literature. Further, the impact of considering the PEV integration on the performance of the DANLHT system is showcased. Furthermore, the high-voltage direct current (HVDC) line is enacted as the tie-line with the PEVs integrated DANLHT system to obtain an improvement in system dynamical behavior. Simulation analysis revealed an enhancement in system performance with the deployment of the HVDC line as the tie-line with the PEVs integrated DANLHT system.
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Subba Rami Reddy, Chagam, Badathala Venkata Prasanth, and Balapanur Mouli Chandra. "Active power management of grid-connected PV-PEV using a Hybrid GRFO-ITSA technique." Science and Technology for Energy Transition 78 (2023): 7. http://dx.doi.org/10.2516/stet/2023001.
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In this manuscript proposed a hybrid Garra Rufa Fish Optimization (GRFO) and Improved Tunicate Swarm Algorithm (ITSA) for improving the power quality of the integrated Photovoltaic (PV) and Plug-in Electric Vehicle (PEV) in Smart Grid (SG) system. The GRFO-ITSA approach is hybrid wrapper of GRFO and ITSA. Commonly it is named as GRFO-ITSA approach. The grid-connected PV-PEV, active power management is performed by the proposed approach. The proposed GRFO approach is used to determine the individual harmonic components and to reduce the recompense currents applied to PVs via PEV converters. The load flow control is performed by ITSA approach, which controls the power among the PVs, and PEVs. Additionally, it satisfies the power demand, and voltage variation. The proposed approach is also to analyze the mutual properties of PVs as well as PEVs on the feeder and transmitting loads, voltage outlines, harmonic alterations of an urban electric power distribution system. Also, the performance of the GRFO-ITSA is implemented on MATLAB site as well as associated with several existing approaches. The GRFO-ITSA have improved the power quality and compensate the harmonics and reactive power of the system. The optimal outcome is obtained by GRFO-ITSA with less computation time.
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Gąsecka, Aleksandra, Sylwester Rogula, Ceren Eyileten, et al. "Role of P2Y Receptors in Platelet Extracellular Vesicle Release." International Journal of Molecular Sciences 21, no. 17 (2020): 6065. http://dx.doi.org/10.3390/ijms21176065.
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Platelet extracellular vesicles (PEVs) are potential new biomarkers of platelet activation which may allow us to predict and/or diagnose developing coronary thrombosis before myocardial necrosis occurs. The P2Y1 and P2Y12 receptors play a key role in platelet activation and aggregation. Whereas the P2Y1 antagonists are at the preclinical stage, at present, the P2Y12 antagonists are the most effective treatment strategy to prevent stent thrombosis after percutaneous coronary intervention. Despite an increasing number of publications on PEVs, the mechanisms underlying their formation, including the role of purinergic receptors in this process, remain an active research field. Here, we outline the clinical relevance of PEVs in cardiovascular disease, summarize the role and downstream signalling of P2Y receptors in platelet activation, and discuss the available evidence regarding their role in PEV formation.
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Jabalameli, Nasim, Xianging Su, and Sara Deilami. "An Online Coordinated Charging/Discharging Strategy of Plug-in Electric Vehicles in Unbalanced Active Distribution Networks with Ancillary Reactive Service in the Energy Market." Energies 12, no. 7 (2019): 1350. http://dx.doi.org/10.3390/en12071350.
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The global acceptance and off-grid charging of plug-in electric vehicles (PEVs) are expected to grow tremendously in the next few years. Uncoordinated PEV charging can cause serious grid issues such as overloading of transformers and unacceptable voltage drops. Single-phase residential charging can also initiate or contribute to voltage unbalance conditions in the distribution networks. A potential solution and key challenge for PEV integration is shifting of the charging activities to off-peak periods. This paper proposes a new PEV coordination approach based on genetic algorithm (GA) optimization to perform online centralized charging and discharging considering transformer loading and node voltage magnitude and unbalance profiles. It allows PEV as source of active and reactive power to participate in energy market based on different prices during a day, without any degradation. Finally, the impacts of uncoordinated and the proposed GA coordinated PEV charging/discharging strategy are simulated for a real unbalanced Western Australian distribution network in the Perth solar city over 24 h.
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Dakanalis, Michail, and Fotios D. Kanellos. "Efficient Model for Accurate Assessment of Frequency Support by Large Populations of Plug-in Electric Vehicles." Inventions 6, no. 4 (2021): 89. http://dx.doi.org/10.3390/inventions6040089.
Full textAbstract:
In recent years, plug-in electric vehicles (PEVs) have gained immense popularity and are on a trajectory of constant growth. As a result, power systems are confronted with new issues and challenges, threatening their safety and reliability. PEVs are currently treated as simple loads due to their low penetration. However, as their numbers are growing, PEVs could potentially be exploited as distributed energy storage devices providing ancillary services to the network. Batteries used in PEVs are developed to deliver instantaneously active power, making them an excellent solution for system frequency support. This paper proposes a detailed dynamic model that is able to simulate frequency support capability from a large number of PEVs, using an innovative aggregate battery model that takes into account the most significant constraints at PEV and aggregate battery levels. The cost optimization algorithm, which is the most time-consuming process of the problem, is executed only at the aggregate battery level, thereby reducing the computational requirements of the model without compromising the obtained accuracy. The proposed method is applied to the power system of Crete exploiting detailed statistical data of EV mobility. It is proven that PEVs can effectively support power system frequency fluctuations without any significant deviation from their optimal operation.
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Ahmed, Asad, Osman Hasan, Falah Awwad, Nabil Bastaki, and Syed Rafay Hasan. "Formal Asymptotic Analysis of Online Scheduling Algorithms for Plug-In Electric Vehicles’ Charging." Energies 12, no. 1 (2018): 19. http://dx.doi.org/10.3390/en12010019.
Full textAbstract:
A large-scale integration of plug-in electric vehicles (PEVs) into the power grid system has necessitated the design of online scheduling algorithms to accommodate the after-effects of this new type of load, i.e., PEVs, on the overall efficiency of the power system. In online settings, the low computational complexity of the corresponding scheduling algorithms is of paramount importance for the reliable, secure, and efficient operation of the grid system. Generally, the computational complexity of an algorithm is computed using asymptotic analysis. Traditionally, the analysis is performed using the paper-pencil proof method, which is error-prone and thus not suitable for analyzing the mission-critical online scheduling algorithms for PEV charging. To overcome these issues, this paper presents a formal asymptotic analysis approach for online scheduling algorithms for PEV charging using higher-order-logic theorem proving, which is a sound computer-based verification approach. For illustration purposes, we present the complexity analysis of two state-of-the-art online algorithms: the Online cooRdinated CHARging Decision (ORCHARD) algorithm and online Expected Load Flattening (ELF) algorithm.
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Żmigrodzka, Magdalena, Olga Witkowska-Piłaszewicz, Rafał Pingwara, and Anna Winnicka. "Platelet Extracellular Vesicles Are Taken up by Canine T Lymphocytes but Do Not Play a Role in Their Proliferation, Differentiation and Cytokine Production In Vitro." International Journal of Molecular Sciences 23, no. 10 (2022): 5504. http://dx.doi.org/10.3390/ijms23105504.
Full textAbstract:
Eukaryotic and prokaryotic cells in physiological and pathological conditions form membrane-bound extracellular vesicles, known as EVs. The ability of these submicron structures to transfer their cargoes (miRNA, DNA, protein, cytokines, receptors, etc.) into recipient cells is described. Recent data revealed that platelet-derived extracellular vesicles (PEVs) crosstalk promotes cancer growth and metastasis formation. Moreover, they exert immunosuppressive activities on phagocytes. This EV subpopulation is the most abundant amongst all types in circulation. According to the authors’ best knowledge, there is no information regarding the impact of PEVs on canine lymphocytes. The aim of this study was to evaluate the influence of PEVs on lymphocyte proliferation, phenotype and cytokine production in vitro. In the study, it was demonstrated (i) that PEVs interact differently with lymphocyte subsets and are preferentially associated with T-lymphocytes PBMC, while (ii) they are rarely detected in association with B-lymphocytes, and there is evidence that (iii) PEV uptake is observed after 7 h of co-culturing with lymphocytes. In addition, obtained data support the notion that PEVs do not influence in vitro lymphocyte proliferation, differentiation and cytokine production in a canine model.
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Tsakalidis, Anastasios, Andreea Julea, and Christian Thiel. "The Role of Infrastructure for Electric Passenger Car Uptake in Europe." Energies 12, no. 22 (2019): 4348. http://dx.doi.org/10.3390/en12224348.
Full textAbstract:
Plug-in electric vehicles (PEV) can be a main lever towards a decarbonised road transport system. The PEV market uptake needs to be nurtured by appropriate support measures for users, for technological advances related to the vehicle and its components, and for all relevant recharging infrastructure deployment. This paper focuses on the role of PEV recharging infrastructure for electric passenger car uptake in Europe. It examines the status of road transport electrification, relevant policies, incentives and national plans. We find that the status and plans of PEV and recharging infrastructure and the corresponding support measures vary significantly between countries. The PEV share in the various analysed countries ranged in 2017 from 0.01% to 5.49% and is estimated to reach values between 0.05% and 12.71% in 2020. The corresponding ratio of PEV per one publicly accessible recharging point ranged between 1 and 60 and is estimated to vary between 3 and 161 in 2020. Diverging plans could lead to market fragmentation in the European Union (EU) and impede the EU-wide circulation of PEVs. The appropriate level of recharging infrastructure should be determined to both support PEV deployment and to prevent sunk investments. Different country experiences vis-à-vis PEV and infrastructure support could be useful to identify best practices.
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Chung, Ching-Yen, Joshua Chynoweth, Chi-Cheng Chu, and Rajit Gadh. "Master-Slave Control Scheme in Electric Vehicle Smart Charging Infrastructure." Scientific World Journal 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/462312.
Full textAbstract:
WINSmartEV is a software based plug-in electric vehicle (PEV) monitoring, control, and management system. It not only incorporates intelligence at every level so that charge scheduling can avoid grid bottlenecks, but it also multiplies the number of PEVs that can be plugged into a single circuit. This paper proposes, designs, and executes many upgrades to WINSmartEV. These upgrades include new hardware that makes the level 1 and level 2 chargers faster, more robust, and more scalable. It includes algorithms that provide a more optimal charge scheduling for the level 2 (EVSE) and an enhanced vehicle monitoring/identification module (VMM) system that can automatically identify PEVs and authorize charging.