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Bhim Singh - One of the best experts on this subject based on the ideXlab platform.
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Improved power quality Charging Scheme for heavy-duty vehicle battery swapping stations
IET Power Electronics, 2019Co-Authors: Ujjwal Kumar Kalla, Rakhi Suthar, Bhim SinghAbstract:This study, presents a generalised multi-pulse converter (MPC)-based improved power quality Charging Scheme for heavy-duty vehicle battery swapping stations. The proposed control is a generalised control, which is used to develop an MPC-based Charging Scheme for any pulse number such as 2-pulse, 6-pulse, 12-pulse, 18-pulse and 24-pulse Charging Schemes for heavy-duty vehicle battery swapping stations. The 2-pulse, 6-pulse and 12-pulse Charging Schemes are implemented in the laboratory using proposed generalised control. This proposed Scheme operates on fundamental switching frequency, therefore, it significantly reduces the switching losses, electromagnetic interference, radio frequency interference levels in heavy-duty vehicle battery swapping stations. Moreover, the sliding mode controller has been introduced in the current control loop of the proposed battery charger which removes all the possibilities of the occurring of undershoot and overshoot in the battery Charging, that significantly improves the life of the battery banks. Test results of all these developed Schemes are presented in this study for validating the proposed Scheme.
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Single Sensor-Based MPPT of Partially Shaded PV System for Battery Charging by Using Cauchy and Gaussian Sine Cosine Optimization
IEEE Transactions on Energy Conversion, 2017Co-Authors: Nishant Kumar, Bhim Singh, Ikhlaq Hussain, Bijaya Ketan PanigrahiAbstract:This paper introduces a battery Charging Scheme from a solar photovoltaic (SPV) by using a single sensor-based maximum power point tracking (MPPT) strategy. Here, for quick and efficient tracking, a novel hybrid “Cauchy and Gaussian sine cosine optimization” (CGSCO) algorithm is proposed for MPPT, which is based on only a single current sensor. The main objective of the CGSCO algorithm is, maximum extraction of the power from SPV panel and efficiently Charging the battery through maximizing the Charging current of the battery. Due to the single sensor, the cost of the Charging Scheme is very low, as well as the algorithm complexity and computational burden are very less, so it can be easily implemented on the low-cost microcontroller. In this paper, a single current sensor-based battery Charging Scheme by CGSCO algorithm is tested on MATLAB simulator and verified on a developed hardware of the SPV system. The panel condition, with and without shaded as well as dynamic environmental condition (variable temperature and insolation), is considered during simulation as well as on hardware implementation. Moreover, the tracking ability is compared with the most recent state of the art techniques (Grey wolf optimization and Lagrange interpolation particle swarm optimization (LIPSO)) as well as compared with “CGSCO with the conventional dual (voltage and current) sensor-based MPPT Scheme.” The efficient battery Charging with quick MPPT by CGSCO algorithm w.r.t. all state of the art techniques as well as dual sensor-based MPPT Scheme, in steady-state as well as in dynamic conditions meets the motive of the work.
Ning Zhang - One of the best experts on this subject based on the ideXlab platform.
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a novel Charging Scheme for electric vehicles with smart communities in vehicular networks
IEEE Transactions on Vehicular Technology, 2019Co-Authors: Yuntao Wang, Tingting Yang, Ning ZhangAbstract:In a smart community (SC) with renewable energy sources (RES), flexible Charging service can be provisioned to electric vehicles (EVs), where EVs can choose clean energy, traditional energy, or the mixture of them on demand in the vehicular networks. Considering the existence of various entities in the SC and the limited generation capacity of RES, it becomes of significance yet very challenging to optimally schedule the Charging service for EVs with different consumption preferences. In this paper, we propose a Charging Scheme for EVs in a SC integrated with RES using a game theoretical approach. First, a three-party energy network is proposed to model the interactions among the main grid, EVs, and aggregators in the smart grid. Second, the trust model is presented to improve the safety of energy trading by evaluating the reliability of aggregators based on direct trust and indirect trust. Third, based on the four-stage Stackelberg game, the optimal strategies of three energy entities are analyzed. The Stackelberg equilibrium can be obtained by the proposed accelerated gradient descent based iteration algorithm. Furthermore, a weighted max–min fairness based energy allocation algorithm is proposed to allocate the limited renewable energy for EVs in a fair and efficient manner. Finally, extensive simulations are carried out to evaluate and demonstrate the effectiveness of the proposed Scheme through comparison with conventional Schemes.
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a secure Charging Scheme for electric vehicles with smart communities in energy blockchain
IEEE Internet of Things Journal, 2019Co-Authors: Yuntao Wang, Minrui Fei, Yuchu Tian, Ning ZhangAbstract:The smart community (SC), as an important part of the Internet of Energy (IoE), can facilitate integration of distributed renewable energy sources and electric vehicles (EVs) in the smart grid. However, due to the potential security and privacy issues caused by untrusted and opaque energy markets, it becomes a great challenge to optimally schedule the Charging behaviors of EVs with distinct energy consumption preferences in SC. In this paper, we propose a contract-based energy blockchain for secure EV Charging in SC. First, a permissioned energy blockchain system is introduced to implement secure Charging services for EVs with the execution of smart contracts. Second, a reputation-based delegated Byzantine fault tolerance consensus algorithm is proposed to efficiently achieve the consensus in the permissioned blockchain. Third, based on the contract theory, the optimal contracts are analyzed and designed to satisfy EVs’ individual needs for energy sources while maximizing the operator’s utility. Furthermore, a novel energy allocation mechanism is proposed to allocate the limited renewable energy for EVs. Finally, extensive numerical results are carried out to evaluate and demonstrate the effectiveness and efficiency of the proposed Scheme through comparison with other conventional Schemes.
Paul Wilkinson - One of the best experts on this subject based on the ideXlab platform.
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the impact of the congestion Charging Scheme on air quality in london part 2 analysis of the oxidative potential of particulate matter
Research report (Health Effects Institute), 2011Co-Authors: Frank J. Kelly, Ben Armstrong, Richard Atkinson, Sean Beevers, Dick Derwent, David C. Green, Ian Mudway, Benjamin Barratt, Ross H Anderson, Paul WilkinsonAbstract:There is growing scientific consensus that the ability of inhaled particulate matter (PM*) to elicit oxidative stress both at the air-lung interface and systemically might underpin many of the acute and chronic respiratory and cardiovascular responses observed in exposed populations. In the current study (which is part two of a two-part HEI study of a congestion Charging Scheme [CCS] introduced in London, United Kingdom, in 2003), we tested the hypothesis that the reduction in vehicle numbers and changes in traffic composition resulting from the introduction of the CCS would result in decreased concentrations of traffic-specific emissions, both from vehicle exhaust and other sources (brake wear and tire wear), and an associated reduction in the oxidative potential of PM with an aerodynamic diameter < or = 10 microm (PM10). To test this hypothesis, we obtained, extracted, and analyzed tapered element oscillating microbalance (TEOM) PM10 filters from six monitoring sites within, bordering, or outside the area of the congestion Charging zone (CCZ) for the 3 years before and after the introduction of the Scheme. In addition, from January 2005, TEOM PM10 filters were obtained from an additional 10 sites outside the zone in order to perform the first-ever assessment of within-city spatial variability in the oxidative potential of PM10. Although London's PM10 was found to have remarkably high oxidative potential, it varied markedly between the studied sites, with evidence of increased potential at roadside locations compared with urban background locations. This difference appeared to reflect increased concentrations of copper (Cu), barium (Ba), and bioavailable iron (Fe) in PM10 collected at the roadside sites. PM10's oxidative potential after the introduction of the CCS did not change at the one urban background site within the zone. Yet compositional changes in PM10 were noted at the same site, including significant decreases in Cu and zinc (Zn) content, probably reflecting brake and tire wear (compared with increases in these metals at all sites outside the zone in the 3 years since the Scheme's introduction). This pattern of results is consistent with observations of increased vehicle use throughout London in recent years and decreases in the number of vehicles entering the zone since the Scheme's introduction.
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The impact of the congestion Charging Scheme on air quality in London. Part 1. Emissions modeling and analysis of air pollution measurements.
Research report (Health Effects Institute), 2011Co-Authors: Frank J. Kelly, H R Anderson, Ben Armstrong, Richard Atkinson, Ben Barratt, Sean Beevers, Dick Derwent, David C. Green, Ian Mudway, Paul WilkinsonAbstract:On February 17, 2003, a congestion Charging Scheme (CCS*) was introduced in central London along with a program of traffic management measures. The Scheme operated Monday through Friday, 7 AM to 6 PM. This program resulted in an 18% reduction in traffic volume and a 30% reduction in traffic congestion in the first year (2003). We developed methods to evaluate the possible effects of the Scheme on air quality: We used a temporal-spatial design in which modeled and measured air quality data from roadside and background monitoring stations were used to compare time periods before (2001-2002) and after (2003-2004) the CCS was introduced and to compare the spatial area of the congestion Charging zone (CCZ) with the rest of London. In the first part of this project, we modeled changes in concentrations of oxides of nitrogen (NOx), nitrogen dioxide (NO2), and PM10 (particles with a mass median aerodynamic diameter < or = 10 microm) across the CCZ and in Greater London under different traffic and emission scenarios for the periods before and after CCS introduction. Comparing model results within and outside the zone suggested that introducing the CCS would be associated with a net 0.8-microg/m3 decrease in the mean concentration of PM10 and a net 1.7-ppb decrease in the mean concentration of NOx within the CCZ. In contrast, a net 0.3-ppb increase in the mean concentration of NO2 was predicted within the zone; this was partly explained by an expected increase in primary NO2 emissions due to the introduction of particle traps on diesel buses (one part of the improvements in public transport associated with the CCS). In the second part of the project, we established a CCS Study Database from measurements obtained from the London Air Quality Network (LAQN) for air pollution monitors sited to measure roadside and urban background concentrations. Fully ratified (validated) 15-minute mean carbon monoxide (CO), nitric oxide (NO), NO2, NOx, PM10, and PM2.5 data from each chosen monitoring site for the period from February 17, 2001, to February 16, 2005, were transferred from the LAQN database. In the third part of our project, these data were used to compare geometric means for the 2 years before and the 2 years after the CCS was introduced. Temporal changes within the CCZ were compared with changes, over the same period, at similarly sited (roadside or background) monitors in a control area 8 km distant from the center of the CCZ. The analysis was confined to measurements obtained during the hours and days on which the Scheme was in operation and focused on pollutants derived from vehicles (NO, NO2, NOx, PM10, and CO). This set of analyses was based on the limited data available from within the CCZ. When compared with data from outside the zone, we did not find evidence of temporal changes in roadside measurements of NOx, NO, and NO2, nor in urban background concentrations of NOx. (The latter result, however, concealed divergent trends in NO, which fell, and NO2, which rose.) Although based upon fewer stations, there was evidence that background concentrations of PM10 and CO fell within the CCZ compared with outside the zone. We also analyzed the trends in background concentrations for all London monitoring stations; as distance from the center of the CCZ increased, we found some evidence of an increasing gradation in NO and PM10 concentrations before versus after the intervention. This suggests a possible intermediate effect on air quality in the area immediately surrounding the CCZ. Although London is relatively well served with air quality monitoring stations, our study was restricted by the availability of only a few monitoring sites within the CCZ, and only one of those was at a roadside location. The results derived from this single roadside site are not likely to be an adequate basis for evaluating this complex urban traffic management Scheme. Our primary approach to assessing the impact of the CCS was to analyze the changes in geometric mean pollutant concentrations in the 2 years before and 2 years after the CCS was introduced and to compare changes at monitoring stations within the CCZ with those in a distant control area (8 km from the CCZ center) unlikely to be influenced by the CCS. We saw this as the most robust analytical approach with which to examine the CCS Study Database, but in the fourth part of the project we did consider three other approaches: ethane as an indicator of pollution dispersion; the cumulative sum (CUSUM) statistical technique; and bivariate polar plots for local emissions. All three were subsequently judged as requiring further development outside of the scope of this study. However, despite their investigative nature, each technique provided useful information supporting the main analyses. The first method used ethane as a dispersion indicator to remove the inherent variability in air pollutant concentrations caused by changes in meteorology and atmospheric dispersion. The technique had the potential to ascertain more accurately the likely impacts of the CCS on London's air quality. Although this novel method appeared promising over short time periods, a number of concerns arose about whether the spatial and temporal variability of ethane over longer time periods would be representative of meteorologic conditions alone. The major strength of CUSUM, the second method, is that it can be used to identify the approximate timing of changes that may have been caused by the CCS. This ability is weakened, however, by the effects of serial correlation (the correlation of data among measurements in successive time intervals) within air pollution data that is caused by seasonality and long-term meteorologic trends. The secure interpretation of CUSUM requires that the technique be adapted to take proper account of the underlying correlation between measurements without the use of smoothing functions that would obscure a stepped change in concentrations. Although CUSUM was not able to provide a quantitative estimation of changes in pollution levels arising from the introduction of the CCS, the strong signals that were identified were considered in the context of other results from the study. The third method, bivariate polar plots, proved useful. The plots revealed important characteristics of the data from the only roadside monitoring site within the CCZ and highlighted the importance of considering prevailing weather conditions when positioning a roadside monitor. The technique would benefit from further development, however, in transforming the qualitative assessment of change into a quantitative assessment and including an estimate of uncertainty. Research is ongoing to develop this method in air-quality time-series studies. Overall, using a range of measurement and modeling approaches, we found evidence of small changes in air quality after introduction of the CCS. These include small decreases in PM10, NO, and CO. The possibility that some of these effects might reflect more general changes in London's air quality is suggested by the findings of somewhat similar changes in geometric means for weekends, when the CCS was not operating. However, since some evidence suggests that the CCS also had an impact on traffic volume on weekends, the CCS remains as one possible explanation for the observed pattern of changes in pollutant concentrations. In addition, the CCS was just one of a number of traffic and emission reduction Schemes introduced in London over the 4-year study period; if the other measures had an impact in central London, they might partly explain our findings. Although not the aim of this study, it is important to consider how the trends we observed might be translated into health effects. For example, given that London already has NO2 concentrations in excess of the permitted limit value, we do not know what the effects of an increase in NO2 created by diesel-exhaust after-treatment for particles might mean for health. Further, although it is not likely that NO affects health, the decrease in NO concentrations is likely associated with an increase in ozone concentrations (a pollutant associated with health effects), as has been seen in recent years in London. These and other similar issues require further investigation. Although the CCS is a relatively simple traffic management Scheme in the middle of a major urban environment, analyzing its possible impact on air quality was found to be far from straightforward. Using a range of modeling and monitoring approaches to address the impact of the Scheme revealed that each technique has its own advantages and limitations. The placement of monitoring sites and the availably of traffic count data were also identified as key issues. The most compelling lesson we take away from this study is that such work is impossible to undertake without a coherent multi-disciplinary team of skilled researchers. In conclusion, our study suggests that the introduction of the CCS in 2003 was associated with small temporal changes in air pollutant concentrations in central London compared with outer areas. However, attributing the cause of these changes to the CCS alone is not appropriate because the Scheme was introduced at a time when other traffic and emissions interventions, which might have had a more concentrated effect in central London, were also being implemented.
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the impact of the congestion Charging Scheme on ambient air pollution concentrations in london
Atmospheric Environment, 2009Co-Authors: Richard Atkinson, H R Anderson, Ben Armstrong, Sean Beevers, David C. Green, Ian Mudway, Benjamin Barratt, R G Derwent, Paul WilkinsonAbstract:Abstract On 17th February 2003, a congestion Charging Scheme (CCS), operating Monday–Friday, 07:00–18:00, was introduced in central London along with a programme of traffic management measures. We investigated the potential impact of the introduction of the CCS on measured pollutant concentrations (oxides of nitrogen (NOX, NO and NO2), particles with a median diameter less than 10 microns (PM10), carbon monoxide (CO) and ozone (O3)) measured at roadside and background monitoring sites across Greater London. Temporal changes in pollution concentrations within the congestion Charging zone were compared to changes, over the same time period, at monitors unlikely to be affected by the CCS (the control zone) and in the boundary zone between the two. Similar analyses were done for CCS hours during weekends (when the CCS was not operating). Based on the single roadside monitor with the CCS Zone, it was not possible to identify any relative changes in pollution concentrations associated with the introduction of the Scheme. However, using background monitors, there was good evidence for a decrease in NO and increases in NO2 and O3 relative to the control zone. There was little change in background concentrations of NOX. There was also evidence of relative reductions in PM10 and CO. Similar changes were observed during the same hours in weekends when the Scheme was not operating. The causal attribution of these changes to the CCS per se is not appropriate since the Scheme was introduced concurrently with other traffic and emissions interventions which might have had a more concentrated effect in central London. This study provides important pointers for study design and data requirements for the evaluation of similar Schemes in terms of air quality. It also shows that results may be unexpected and that the overall effect on toxicity may not be entirely favourable.
Fitri Maya Puspita - One of the best experts on this subject based on the ideXlab platform.
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mathematical model of improved reverse Charging of wireless internet pricing Scheme in servicing multiple qos
Journal of Engineering and Scientific Research, 2020Co-Authors: Fitri Maya Puspita, D R Nur, A L Tanjung, J Silaen, Weny Herlina, Yunita YunitaAbstract:This paper seeks to utilize the improved model of reverse Charging Scheme. Reverse Charging basically is defined as a capability of stored network that replaces the network used when the network is suddenly shut down. In this paper, Charging back on 3G and 4G network that is user automated platform, will change the access of 4G to 3G and on the contrary when platform conduct thehosting. This research was solved as a problem Mixed Integer Nonlinear Programming (MINLP) by LINGO 13.0. An optimal pricing Scheme is applied to a local data server, including digilib traffic and mail traffic. The improved model of Reverse Charging is modified into 4 cases and formed by setting the base price (?) and service level (?). Based on the analysis that has been done, the results of this study indicate that the reverse Charging model can be utilized Internet Service Provider (ISP) to maximize profits and provide quality services for the user if compared to previous model without reverse Charging Scheme
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mathematical model of improved reverse Charging of wireless internet pricing Scheme in servicing multiple qos
Journal of Engineering and Scientific Research, 2020Co-Authors: Fitri Maya Puspita, D R Nur, A L Tanjung, J Silaen, Weny Herlina, Yunita YunitaAbstract:This paper seeks to utilize the improved model of reverse Charging Scheme. Reverse Charging basically is defined as a capability of stored network that replaces the network used when the network is suddenly shut down. In this paper, Charging back on 3G and 4G network that is user automated platform, will change the access of 4G to 3G and on the contrary when platform conduct the hosting. This research was solved as a problem Mixed Integer Nonlinear Programming (MINLP) by LINGO 13.0. An optimal pricing Scheme is applied to a local data server, including digilib traffic and mail traffic. The improved model of Reverse Charging is modified into 4 cases and formed by setting the base price (α) and service level (β). Based on the analysis that has been done, the results of this study indicate that the reverse Charging model can be utilized Internet Service Provider (ISP) to maximize profits and provide quality services for the user if compared to previous model without reverse Charging Scheme . Keywords: improved model of revere Charging Scheme, MINLP, ISP, QoS, pricing Scheme
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improved models of internet Charging Scheme of single bottleneck link in multi qos networks
Journal of Applied Sciences, 2013Co-Authors: Fitri Maya Puspita, Kamaruzzaman Seman, Bachok M. Taib, Zurina ShafiiAbstract:This paper will seek new proposed pricing plans to develop new pricing Scheme that serve both customers and maximize the supplier profit as nowadays Internet Service Providers (ISPs) deal with high demand to promote good quality information but only a few pricing plans involve QoS networks. We are going to solve multi bottleneck links in multi QoS Network Scheme as an optimization model by comparing two models in multi QoS networks by taking into consideration decision whether to set up base price to be fixed to recover the cost or to be varied to compete in the market and quality premium to be fixed to enable user to choose classes according to their preferences and budget or to be varied to enable ISP to promote certain service. The results were obtained by aid of LINGO 13.0 software application. The results show that our two modified models slightly yield better solution rather than in original problem but with advantages that ISP has options to choose which of two models to be adopted depending on ISP goals in achieving the profit maximization.
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An Improved Optimization Model of Internet Charging Scheme in Multi Service Networks
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2012Co-Authors: Fitri Maya Puspita, Kamaruzzaman Seman, Bachok M. Taib, Zurina ShafiiAbstract:This article will analyze new improved Charging Scheme with base price, quality premium and QoS networks involved. Sain and Herpers [5] already attempted to obtain revenue maximization by creating Charging Scheme of internet. The plan is attempted to solve multi service networks Scheme as an optimization model to obtain revenue maximization using our improved model based on Byun and Chatterjee [2] and Sain and Herpers [5]. The results show that improved model can be solved optimally using optimization tool LINGO to achieve better revenue maximization. Better results are obtained in all cases rather than in [5]. The advantage of our new model is that ISP also can set up their base price and quality premium based on ISP preferences. For some cases for getting revenue maximization, we do not offer one service and just utilize some of the services.
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an improved optimization model of internet Charging Scheme in multi service networks
Indonesian Journal of Electrical Engineering and Computer Science, 2012Co-Authors: Fitri Maya Puspita, Kamaruzzaman Seman, Bachok M. Taib, Zurina ShafiiAbstract:This paper will analyze new improved Charging Scheme with base price, quality premium and QoS networks involved. Sain and Herpers [5] already attempted to obtain revenue maximization by creating Charging Scheme of internet. The plan is attempted to solve multiple service networks Scheme as an optimization model to obtain revenue maximization using our improved model based on [2] and [5]. The results show that improved model can be solved optimally using optimization tool to achieve better revenue maximization. DOI: http://dx.doi.org/10.11591/telkomnika.v10i3.623
Hoi Yan Lam - One of the best experts on this subject based on the ideXlab platform.
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A Charging-Scheme decision model for electric vehicle battery swapping station using varied population evolutionary algorithms
Applied Soft Computing Journal, 2017Co-Authors: Hao Wu, Grantham Kwok Hung Pang, Kwang-leong Choy, Hoi Yan LamAbstract:This paper proposes a new battery swapping station (BSS) model to determine the optimized Charging Scheme for each incoming Electric Vehicle (EV) battery. The objective is to maximize the BSS's battery stock level and minimize the average Charging damage with the use of different types of chargers. An integrated objective function is defined for the multi-objective optimization problem. The genetic algorithm (GA), differential evolution (DE) algorithm and three versions of particle swarm optimization (PSO) algorithms have been implemented to solve the problem, and the results show that GA and DE perform better than the PSO algorithms, but the computational time of GA and DE are longer than using PSO. Hence, the varied population genetic algorithm (VPGA) and varied population differential evolution (VPDE) algorithm are proposed to determine the optimal solution and reduce the computational time of typical evolutionary algorithms. The simulation results show that the performances of the proposed algorithms are comparable with the typical GA and DE, but the computational times of the VPGA and VPDE are significantly shorter. A 24-h simulation study is carried out to examine the feasibility of the model.