scholarly journals Pre-Day Scheduling of Charging Processes in Mobility-on-Demand Systems Considering Electricity Price and Vehicle Utilization Forecasts

2020 ◽  
Author(s):  
Florian Dandl ◽  
Fabian Fehn ◽  
Klaus Bogenberger ◽  
Fritz Busch
Keyword(s):  
Short Interval ◽  
Sustainable Transportation ◽  
Macroscopic Model ◽  
Computational Time ◽  
Exchange Market ◽  
Electricity Prices ◽  
Fleet Size ◽  
On Demand ◽  
Long Time ◽  
Charging Strategy

<div>Electrifying mobility-on-demand (MoD) fleets is</div><div>an important step towards a more sustainable transportation</div><div>system. With increasing fleet size, MoD operators will be</div><div>able to participate in the energy exchange market and will</div><div>have access to time-varying electricity prices. They can benefit from intelligent scheduling of charging processes considering forecasts of electricity prices and vehicle utilization. Considering a long time horizon of, e.g., a day improves scheduling decisions, but electricity prices change in a short interval of 15 minutes; hence, an optimization-based approach needs to overcome challenges regarding computational time. For this reason, we develop a macroscopic model to study the tradeoffs between electricity, battery wear and level-of-service costs. In scenarios with varying fleet size and different numbers of</div><div>charging units, we compare the performance of several reactive and scheduling policies in a simulation framework based on a macroscopic model. Overall, the results of the study show that an MoD provider with 2000 vehicles could save several thousands of euros in daily operational costs by changing from a state of charge reactive charging strategy to one adapting to the price fluctuations of the electricity exchange market.</div>

scholarly journals Pre-Day Scheduling of Charging Processes in Mobility-on-Demand Systems Considering Electricity Price and Vehicle Utilization Forecasts

2020 ◽  
Author(s):  
Florian Dandl ◽  
Fabian Fehn ◽  
Klaus Bogenberger ◽  
Fritz Busch
Keyword(s):  
Short Interval ◽  
Sustainable Transportation ◽  
Macroscopic Model ◽  
Computational Time ◽  
Exchange Market ◽  
Electricity Prices ◽  
Fleet Size ◽  
On Demand ◽  
Long Time ◽  
Charging Strategy

<div>Electrifying mobility-on-demand (MoD) fleets is</div><div>an important step towards a more sustainable transportation</div><div>system. With increasing fleet size, MoD operators will be</div><div>able to participate in the energy exchange market and will</div><div>have access to time-varying electricity prices. They can benefit from intelligent scheduling of charging processes considering forecasts of electricity prices and vehicle utilization. Considering a long time horizon of, e.g., a day improves scheduling decisions, but electricity prices change in a short interval of 15 minutes; hence, an optimization-based approach needs to overcome challenges regarding computational time. For this reason, we develop a macroscopic model to study the tradeoffs between electricity, battery wear and level-of-service costs. In scenarios with varying fleet size and different numbers of</div><div>charging units, we compare the performance of several reactive and scheduling policies in a simulation framework based on a macroscopic model. Overall, the results of the study show that an MoD provider with 2000 vehicles could save several thousands of euros in daily operational costs by changing from a state of charge reactive charging strategy to one adapting to the price fluctuations of the electricity exchange market.</div>

Time Window from Visual Images to Visual Short-Term Memory: Consolidation or Integration?

2004 ◽  
Vol 51 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Yuhong Jiang
Keyword(s):  
Short Term Memory ◽  
Time Window ◽  
Short Interval ◽  
Visual Images ◽  
Short Term ◽  
Temporal Window ◽  
Term Memory ◽  
Visual Short Term Memory ◽  
Probe Task ◽  
Long Time

Abstract. When two dot arrays are briefly presented, separated by a short interval of time, visual short-term memory of the first array is disrupted if the interval between arrays is shorter than 1300-1500 ms ( Brockmole, Wang, & Irwin, 2002 ). Here we investigated whether such a time window was triggered by the necessity to integrate arrays. Using a probe task we removed the need for integration but retained the requirement to represent the images. We found that a long time window was needed for performance to reach asymptote even when integration across images was not required. Furthermore, such window was lengthened if subjects had to remember the locations of the second array, but not if they only conducted a visual search among it. We suggest that a temporal window is required for consolidation of the first array, which is vulnerable to disruption by subsequent images that also need to be memorized.

Enhancing the power generation of Rhodopseudomonas palustris-based MFC

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1261-1268
Author(s):  
Shu Otani ◽  
Dang-Trang Nguyen ◽  
Kozo Taguchi
Keyword(s):  
Activated Carbon ◽  
Rhodopseudomonas Palustris ◽  
Ozone Treatment ◽  
Maximum Power Density ◽  
On Demand ◽  
Long Time ◽  
Dry Conditions ◽  
Carbon Sheet ◽  
Uv Ozone

In this study, a portable and disposable paper-based microbial fuel cell (MFC) was fabricated. The MFC was powered by Rhodopseudomonas palustris bacteria (R. palustris). An activated carbon sheet-based anode pre-loaded organic matter (starch) and R. palustris was used. By using starch in the anode, R. palustris-loaded on the anode could be preserved for a long time in dry conditions. The MFC could generate electricity on-demand activated by adding water to the anode. The activated carbon sheet anode was treated by UV-ozone treatment to remove impurities and to improve its hydrophilicity before being loaded with R. palustris. The developed MFC could generate the maximum power density of 0.9 μW/cm2 and could be preserved for long-term usage with little performance degradation (10% after four weeks).

scholarly journals Novel semi-analytical optoelectronic modeling based on homogenization theory for realistic plasmonic polymer solar cells

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zahra Arefinia ◽  
Dip Prakash Samajdar
Keyword(s):  
Solar Cells ◽  
Active Layer ◽  
Analytical Modeling ◽  
High Efficiency ◽  
Polymer Solar Cells ◽  
Scattered Light ◽  
Homogenization Theory ◽  
Computational Time ◽  
Coupled Equations ◽  
Long Time

AbstractNumerical-based simulations of plasmonic polymer solar cells (PSCs) incorporating a disordered array of non-uniform sized plasmonic nanoparticles (NPs) impose a prohibitively long-time and complex computational demand. To surmount this limitation, we present a novel semi-analytical modeling, which dramatically reduces computational time and resource consumption and yet is acceptably accurate. For this purpose, the optical modeling of active layer-incorporated plasmonic metal NPs, which is described by a homogenization theory based on a modified Maxwell–Garnett-Mie theory, is inputted in the electrical modeling based on the coupled equations of Poisson, continuity, and drift–diffusion. Besides, our modeling considers the effects of absorption in the non-active layers, interference induced by electrodes, and scattered light escaping from the PSC. The modeling results satisfactorily reproduce a series of experimental data for photovoltaic parameters of plasmonic PSCs, demonstrating the validity of our modeling approach. According to this, we implement the semi-analytical modeling to propose a new high-efficiency plasmonic PSC based on the PM6:Y6 PSC, having the highest reported power conversion efficiency (PCE) to date. The results show that the incorporation of plasmonic NPs into PM6:Y6 active layer leads to the PCE over 18%.

scholarly journals Reduction of the Risk of Relapse of Symptoms When Using Esophagoprotector in Patients Requiring Temporary Cancellation of Antisecretory Therapy

2021 ◽  
Vol 17 (16) ◽  
pp. 26-30
Author(s):  
Yu.A. Kucheryavy ◽  
◽  
P.R. Movtaeva ◽  
D.N. Andreev ◽  
R.I. Shaburov ◽  
...  
Keyword(s):  
Comparative Study ◽  
Underlying Disease ◽  
On Demand ◽  
Long Time ◽  
Prospective Comparative Study ◽  
Group 2 ◽  
Significant Regression ◽  
Risk Of Relapse ◽  
Group 1

Objective: to evaluate the effectiveness of an esophagoprotector in reducing the risk of recurrent symptoms of gastroesophageal reflux disease (GERD) in patients who requiring temporary cancellation of therapy with proton pump inhibitors (PPIs). Material and methods. For the prospective comparative study there were selectively chose patients who had been taking PPIs for a long time (at least one month) for the underlying disease and who required temporary discontinuation of antisecretory therapy due to objective medical reasons. The study included patients with endoscopically and/or pH-metrically verified GERD, as well as histologically verified Barrett's esophagus. In the process of randomization of patients, two equal groups were formed, depending on the therapy received at the time of PPI withdrawal: group 1 received antacids on demand, group 2 received antacids on demand, as well as the esophagoprotector Alfasoxx at a dose of 10 ml four times a day (after each meal and at night). The follow-up period was two weeks. The patients recorded episodes of heartburn in their personal diaries. Results. The study included 60 patients (28 men and 32 women). The average age of the examined patients was 43.1 ± 5.3 years. By the end of the two-week follow-up period, the frequency of recurrent symptoms in group 1 was 36.7%, while in group 2 it was 13.3%. The use of the esophagoprotector Alfasoxx contributed to the significant regression of the risk of heartburn recurrence (odds ratio 0.2657; 95% confidence interval (CI) 0.07328-0.9637; p = 0.0438) in comparison with the group of patients who received only antacids in the on-demand mode. When analyzing the population of patients who had relapsed symptoms, it was demonstrated that the average number of heartburn episodes in group 1 was 6.18 (95% CI 4,1930-8,1706), and in group 2 – 4.50 (95% CI 0,7121-8,2879). Conclusion. This prospective comparative study demonstrated that the use of the esophagoprotector Alfasoxx helps to reduce the risk of relapse of GERD symptoms in patients requiring temporary cancellation of PPI therapy.

scholarly journals Optimization Strategies for Dockless Bike Sharing Systems via two Algorithms of Closed Queuing Networks

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 345 ◽  
Author(s):  
Rui-Na Fan ◽  
Fan-Qi Ma ◽  
Quan-Lin Li
Keyword(s):  
Mean Value ◽  
Sustainable Transportation ◽  
Queuing Network ◽  
Value Analysis ◽  
Fleet Size ◽  
Closed Queuing Networks ◽  
Mean Value Analysis ◽  
Bike Sharing ◽  
The Mean ◽  
First Time

The dockless bike sharing system (DBSS) has been globally adopted as a sustainable transportation system. Due to the robustness and tractability of the closed queuing network (CQN), it is a well-behaved method to model DBSSs. In this paper, we view DBSSs as CQNs and use the mean value analysis (MVA) algorithm to calculate a small size DBSS and the flow equivalent server (FES) algorithm to calculate the larger size DBSS. This is the first time that the FES algorithm is used to study the DBSS, by which the CQN can be divided into different subnetworks. A parking region and its downlink roads are viewed as a subnetwork, so the computation of CQN is reduced greatly. Based on the computation results of the two algorithms, we propose two optimization functions for determining the optimal fleet size and repositioning flow, respectively. At last, we provide numerical experiments to verify the two algorithms and illustrate the optimal fleet size and repositioning flow. This computation framework can also be used to analyze other on-demand transportation networks.

scholarly journals Learning to Fail in Aphasia: An Investigation of Error Learning in Naming

2013 ◽  
Vol 56 (4) ◽  
pp. 1287-1297 ◽  
Author(s):  
Erica L. Middleton ◽  
Myrna F. Schwartz
Keyword(s):  
Short Interval ◽  
Proper Noun ◽  
Time Condition ◽  
Retrieval Strategies ◽  
Post Test ◽  
Long Time ◽  
Error Learning ◽  
Short Time ◽  
Neurologically Intact ◽  
Tip Of The Tongue

Purpose To determine whether the naming impairment in aphasia is influenced by error learning and whether error learning is related to type of retrieval strategy. Method Nine participants with aphasia and 10 neurologically intact controls named familiar proper noun concepts. When experiencing tip-of-the-tongue naming failure (TOT) in an initial TOT-elicitation phase, participants were instructed to adopt phonological or semantic self-cued retrieval strategies. In the error learning manipulation, items evoking TOT states during TOT elicitation were randomly assigned to a short or long time condition in which participants were encouraged to continue to try to retrieve the name for either 20 s (short interval) or 60 s (long). The incidence of TOT on the same items was measured on a post-test after 48 hr. Error learning was defined as a higher rate of recurrent TOTs (TOT at both TOT elicitation and post-test) for items assigned to the long (versus short) time condition. Results In the phonological condition, participants with aphasia showed error learning, whereas controls showed a pattern opposite to error learning. There was no evidence for error learning in the semantic condition for either group. Conclusion Error learning is operative in aphasia but is dependent on the type of strategy used during naming failure.

Research on Optimization Model and Generation Coal-Saving Effect of Tiered Pricing of Household Electricity Structures

2013 ◽  
Vol 389 ◽  
pp. 126-130
Author(s):  
Hui Juan Zhang ◽  
Zhong Fu Tan ◽  
Hui Xu ◽  
He Yin
Keyword(s):  
Optimization Model ◽  
Electricity Consumption ◽  
On Demand ◽  
Tiered Pricing ◽  
Long Time ◽  
Resources Conservation ◽  
Saving Effect ◽  
Cross Subsidization ◽  
Demand Side Response

For a long time, there is serious cross-subsidization among the power sales prices in China, and tiered pricing of household electricity is a new price measure for power consumption equity, resources utilization rationality and then achieving resources conservation and environmental protection. Based on demand side response theory, the optimization model of tiered pricing of household electricity with objective function of minimum household electricity consumption was built, and the coal-saving effect of tiered pricing was studied. The results of case study indicate that energy and coal saving effect of tiered pricing is remarkable.

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