Daily Peak Hour Research Articles

Understanding Energy Behavioral Changes Due to COVID-19 in the Residents of Dubai Using Electricity Consumption Data and Their Impacts

The building sector consumes as much as 80% of generated electricity in the UAE; during the COVID-19 pandemic, the energy consumption of two sub-sectors, i.e., commercial (50%) and residential (30%), was significantly impacted. The residential sector was impacted the most due to an increase in the average occupancy during the lockdown period. This increment continued even after the lockdown due to the fear of infection. The COVID-19 pandemic and its lockdown measures can be considered experimental setups, allowing for a better understanding of how users shift their consumption under new conditions. The emergency health measures and new social dynamics shaped the residential sector’s energy behavior and its increase in electricity consumption. This article presents and analyzes the identified issues concerning residential electricity consumers and how their behaviors change based on the electricity consumption data during the COVID-19 period. The Dubai Electricity and Water Authority conducted a voluntary survey to define the profiles of its residential customers. A sample of 439 consumers participated in this survey and four years of smart meter records. The analysis focused on understanding behavioral changes in consumers during the COVID-19 period. At this time, the dwellings were occupied for longer than usual, increasing their domestic energy consumption and altering the daily peak hours for the comparable period before, during, and after the lockdown. This work addressed COVID-19 and the lockdown as an atypical case. The authors used a machine learning model and the consumption data for 2018 to predict the consumption for each year afterward, observing the COVID-19 years (2020 and 2021), and compared them with the so-called typical 2019 predictions. Four years of fifteen-minute resolution data and the detailed profiles of the customers led to a better understanding of the impacts of COVID-19 on residential energy use, irrespective of changes caused by seasonal variations. The findings include the reasons for the changes in consumption and the effects of the pandemic. There was a 12% increase in the annual consumption for the sample residents considered in 2020 (the COVID-19-affected year) as compared to 2019, and the total consumption remained similar with only a 0.2% decrease in 2021. The article also reports that machine learning models created in only one year, 2018, performed better by 10% in prediction compared with the deep learning models due to the limited training data available. The article implies the need for exploring approaches/features that could model the previously unseen COVID-19-like scenarios to improve the performance in case of such an event in the future.

The role of alcohol and cannabis co-use in drinking rate and its impact on consequences.

The impact of alcohol and cannabis co-use on college student drinking and related outcomes is complex. Specific characteristics or patterns of co-use events beyond drinking quantity may be important to the experience of consequences. The present studyused repeated daily surveys to examine the association between co-use (versus use of alcohol only) and drinking rate on negative consequences. The sample included 318 college students (Mage =19.8, 47% female, 76% non-Hispanic White) who were co-users of alcohol and cannabis, recruited from three U.S. college campuses. Participants completed 56 days of data collection (number of drinking days ranged from 1 to 38). Two measures of drinking rate were examined: (1) daily rate (number of drinks divided by number of hours spent drinking per day); and (2) peak hour rate (maximum number of drinks consumed in a single hour) to account for anomalous drinking days of long duration. Generalized linear mixed models examined: (1) associations of co-use with peak hour rate (model 1a) and daily rate (model 1b); (2) associations of peak hour rate (model 2a) and daily rate (model 2b) with experiencing any negative consequence; and (3) interactions of co-use with peak hour rate (model 3a) and daily rate (model 3b) on experiencing a consequence. Co-use was positively associated with peak hour rate but not daily rate. Both peak hour and daily rate positively predicted likelihood of experiencing a negative consequence. The interaction of both peak hour and daily rate by co-use was significant such that the association of rate with experiencing a consequence was stronger on alcohol-only days compared to co-use days. Daily drinking rate and peak hour drinking rate are unique and should be considered when discussing drinking patterns. Both predict negative consequences and may be important aspects of interventions for negative drinking-related outcomes among college students.

Operational grid and environmental impacts for a V2G-enabled electric school bus fleet using DC fast chargers

As states replace diesel school buses with electric ones, utilities will want to control charging schedules to capture potential benefits on the grid and avoid all buses charging at the same time, adding a large electric load. Vehicle-to-grid (V2G) services can provide more grid stability and reduced carbon dioxide emissions than simple controlled charging systems, yet the grid impacts of V2G school buses have not been modeled using realistic school bus schedules. This paper develops a methodology for simulating the effect of managed charging of electric school buses on peak shaving in the state of North Carolina using V2G interactions and DC fast chargers to determine potential emissions reductions by minimizing peak load periods. The V2G-Sim model is used to manage fleet-wide charging, while minimizing peak generation of electricity on the grid and flattening the load curve under different battery capacities, charger power ratings, and fleet sizes. Historic annual peak hours are examined to determine the feasibility of reducing generation capacity, and the daily peak hours are examined to determine the potential peak shaving and subsequent avoided emissions. The results demonstrate that at full electric school bus replacement, 14,000 V2G buses can aggregate and shift 2.6 GWh in North Carolina, avoiding up to 1,130 t of carbon dioxide emissions per day, assuming decreased dependence on natural gas peaker plants. An additional 1,500 t of CO2 can be avoided by replacing diesel-powered buses compared to the 320,000 t total daily CO2 emissions from all activities in North Carolina. Additional emissions are avoided by the replacement of diesel buses with electric buses. The largest greenhouse gas emission benefit is the replacement of diesel with electric school buses, and the ability to shave peak loads is maximized on weekend days in the winter. The model can be used by researchers, the utility, and states as these entities evaluate the environmental and operational grid benefits of a V2G school bus program.

Advances in pedestrian travel monitoring: Temporal patterns and spatial characteristics using pedestrian push-button data from Utah traffic signals

In this study, we advanced pedestrian travel monitoring using a novel data source: pedestrian push-button presses obtained from archived traffic signal controller logs at more than 1,500 signalized intersections in Utah over one year. The purposes of this study were to: (1) quantify pedestrian activity patterns; (2) create factor groups and expansion/adjustment factors from these temporal patterns; and (3) explore relationships between patterns and spatial characteristics. Using empirical clustering, we classified signals into five groups, based on normalized hourly/weekly counts (each hour’s proportion of weekly totals, or the inverse of the expansion factors), and three clusters with similar monthly adjustment factors. We also used multinomial logit models to identify spatial characteristics (land use, built environment, socio-economic characteristics, and climatic regions) associated with different temporal patterns. For example, we found that signals near schools were much more likely to have bimodal daily peak hours and lower pedestrian activity during out-of-school months. Despite these good results, our hourly/weekday patterns differed less than in past research, highlighting the limits of existing infrastructure for capturing all kinds of activity patterns. Nevertheless, we demonstrated that signals with push-button data are a useful supplement to existing permanent counters within a broader pedestrian traffic monitoring program.

Characterization of Penetration Strength of GSM Signals (900 MHz) and their attenuation within some selected Buildings at the University of Ibadan

The diverse challenges been encountered by GSM subscribers within some locations at the University of Ibadan through their usual transits within and outside of buildings, before been able to receive uninterrupted flow of GSM communication due to signal fade and call drop, motivated the need to attempt to characterize signal strength penetration in buildings. This characterization would assist in determining the link budget required for a better Quality of Service (QoS) in this community. However, signal strength path measurement from GSM transmitter (i.e. base station) to the receiver is amongst the parameters required in estimating signal attenuation. Thus, in order to be able to estimate the magnitude of signal penetrations into buildings at the University of Ibadan, the factory fitted signal strength software installed on an android phone was utilized in obtaining the signal strengths of the four major GSM service providers (940MHz, 950MHz, 955MHz and 960MHz) operating in this vicinity. These measurements were taken for three weeks during the daily peak hours of communication (09Hr, 12Hr, 15Hr, and 18Hr) within every three minutes interval, at eight selected buildings (isolated and non-isolated) due to their closeness to GSM base stations. Analysis of data showed that the signal strengths at corridors of both isolated and non-isolated buildings are stronger than those indoors. Moreover, the signal attenuation used in depicting signal fade further showed that the attenuation increased at indoors more than corridors. This increment in indoor attenuations could be due to resistance against signals by the materials utilized in the construction of these buildings. In essence, the base station’s transmission power for this community should be increased by the various GSM network service providers in order to overcome attenuation problem. Likewise, the determined penetration attenuation allowance value of 15dB could be utilized in designing their link budget for a better QoS.

Statistical Analysis of Electrical and Non-Electrical Parameters of Photovoltaic Modules in Controlled Tracking Systems

The paper presents statistical analysis of measurement results of electrical parameters for photovoltaic modules installed in stationary and dual-axis configurations. The parameters which were taken into account included: coefficient of variation, skewness and standard deviation. Also a correlation was determined between independent variables such as insolation, sunshine duration, cloudiness, ambient temperature and atmospheric pressure, and the dependent variable in the form of the daily electricity from photovoltaic conversion. In order to determine the repeatability of electricity waveforms occurring between summer months as well as between summer and winter months, the non-parametric U Mann-Whitney test was used. In order to analyse the repeatability of daily peak hours in which the highest value of the hourly electricity production is observed, the non-parametric Kruskal-Wallis test was used. The tested systems were connected to the power grid and operated independently. Test stands consisting of polycrystalline photovoltaic modules, single-phase on-grid inverters, irradiance sensors and a temperature recorder, were located on the building rooftop of the Faculty of Control Robotics and Electrical Engineering of the Poznan University of Technology in Poland (Central Poland, 52°24.4152′N, 16°55.7958′E) at the height of 30 metres above the ground level. A significant increase in the production of electricity using the PV module spatial positioning system was demonstrated in relation to modules based on the year-round modified design.

Pumped Hydroelectric Energy Storage as a Facilitator of Renewable Energy in Liberalized Electricity Market

Besides many benefits deriving from the energy transition process, it is not uncommon for modern power systems to be faced with difficulties in their operation. The issues are dominantly related to the non-dispatchable nature of renewable energy sources (RES) and the mismatching between electricity generation and load demand. As a consequence of a constant peak load growth, this problem is particularly pronounced during the daily peak hours. Therefore, it is of great importance to conduct all necessary activities within the system in order to preserve the system stability and continuity of operation. Energy storage systems have been recognized as a major facilitator of renewable energy, by providing additional operational flexibility. Since pumped hydroelectric energy storage (PHES) accounts for almost 97% of the world’s storage capacity, in this paper, we have investigated the benefits of using pumped-storage hydropower in modern power systems characterized by high penetration of RES and the liberalized electricity market. A novel operation algorithm has been developed which finds the balance between providing additional flexibility by alleviating the peak load and obtaining financial revenue to justify the high investment costs associated with PHES. The algorithm has been tested for the daily and monthly operation of the Tonstad PHES in the dynamic environment of the Norwegian power system.

Characteristics of patients visiting emergency department by different ways of transportation

Objective To explore the characteristics of patients visiting emergency department by different ways of transportation. Methods The medical information of 23 039 patients visiting emergency department from January 2017 to December 2017 was obtained through the Hospital Information System (HIS). There were 20 856 patients visiting emergency arranged by themselves (self-visiting group), and 2 183 patients sent by ambulance (ambulance group). The characteristics of two groups were compared. Results The proportion of young patients in the self-visit group was the highest (45.97%, 9 587/20 856), and the proportion of elderly patients in the ambulance group was the highest (40.04%, 874/2 183). Throughout the year, the number of patients who came to the hospital by themselves was the highest in the summer, that by ambulance was the highest in the winter, while that was the lowest in spring for both groups. There was no significant fluctuation in the number of patients who came to the hospital during the week. In the self-visited group, the daily peak hours were 18:00-02:00 at night and the ambulance group were 10:00-18:00. The number of visits for top 5 system diseases were trauma, digestive system, other diseases, respiratory system and urinary system diseases in self-visiting group; and were nervous system, trauma, digestive system, respiratory system and circulatory system diseases in ambulance group. The hospitalization rates of self-visiting group and ambulance group were 14.41% (3 006/20 856) and 76.64% (1 564/2 183), respectively. Conclusion The emergency patients with different visiting modes have different characteristics. The information would be useful for rationally allocate emergency resources, optimize the treatment process, improve the emergency capacity and ensure the safety of patients. Key words: Emergency service, hospital; Epidemiology; Epidemics; Ambulances; Hospitalization

The effect of paid parking and bicycle subsidies on employees’ parking demand

Employers usually offer free parking to employees, which may lead to welfare losses. Using exogenous variation in daily peak-hour parking tariffs, monthly subscription fees and bicycle subsidies faced by hospital employees, we demonstrate that employees’ parking demand is reduced by about 5 percent for every euro per-day tariff increase, and that it is reduced by about 2 percent for every euro subscription fee increase. The introduction of higher parking prices particularly reduced demand during peak hours. We offer compelling evidence that bicycle subsidies reduce parking demand. Hospitals that offer free parking to employees, but then introduce a parking tariff equal to marginal parking costs, induce modest yearly welfare gains of € 60 per parking space, about 8 percent of parking resource costs. This is slightly less than previously found in the literature.

Analysis of Internet Traffic Using Average Daily Peak Hour (ADPH)

In this era, Internet for education is one of the basic need; for students, teachers, lecturers, and staff. The increasing of internet needs cause the increasing of data traffic than before. In this research, traffic volumes of the Internet is analyzed using the ADPH (Average Daily Peak Hour) technique. ADPH is one of teletraffic techniques to calculate traffic volumes based on its busy hours. Previously, this technique is used in telephony systems. In this research, ADPH is tried to be used for calculating data traffic volumes.

A stage-based estimator of daily egg production

Abstract Snapper (Chrysophrys auratus) in South Australia spawn over a wide range of daily times and hatch in ∼1.5 d. Traditional estimates of daily egg production (i) divide sampled eggs into daily age cohorts, e.g. days 1 and 2, (ii) compute cohort ages by assuming that all spawning occurs at a fixed daily peak hour, and (iii) link the estimation of spawning egg density with egg mortality rate by regressing cohort egg densities against cohort age. We propose a method for estimating daily egg production, the number of eggs spawned per unit area per day (P0), without these assumptions. We use a range of estimates of snapper egg mortality rate obtained from prior studies to backcorrect for egg mortality to the age 0 spawning egg density for each stage of eggs individually rather than aggregating into daily cohorts. P0 is estimated as a mean of sample tow densities rather than as a regression intercept. This stage-based P0 estimator avoids errors associated with assuming a fixed daily spawning hour and classifying eggs into day 1 or 2. It requires no regressions of sampled daily cohort egg densities against age, which often provide imprecise estimates of mortality rates. Simulation testing showed 1–2% accuracy for this estimator of P0. The uncertainty of assuming egg mortality rates is moderated by the insensitivity of estimates of P0 to the input value of egg mortality rate.

Evaluation of Collision Potential at Four- Legged Unsignalized Intersection Using Traffic Conflict Technique

The counting of traffic conflict allows the estimation of accident potential at a particular location such as at-grade intersection. The objective of this paper is to examine the evasive action of driver occurs with some frequency at Shao intersection which may result in potential accident. This paper applied traffic conflict techniques to evaluate collision potential at unsignalized intersection located at Shao. The morning and evening peak traffic flow was captured using a video camera for seven days and then analyzed by playing back the video on daily basis. The 100 sample size of observed conflict was based on 95% confidence level, 5% permitted error and the proportion of the vehicles that were involved in a specific conflict for the observed traffic flow. The conflicts identified were compared with volume counts at minor approach. The daily peak hour approach traffic volumes were found to have a close relationship with the percentage values of conflict on the two minor approaches. It also showed that rear end collision accounted for more than 70 percent of traffic conflicts and it correlated well with the traffic volumes on WB and EB approaches.

Evaluation of Collision Potential at Four- Legged Unsignalized Intersection Using Traffic Conflict Technique

The counting of traffic conflict allows the estimation of accident potential at a particular location such as at-grade intersection. The objective of this paper is to examine the evasive action of driver occurs with some frequency at Shao intersection which may result in potential accident. This paper applied traffic conflict techniques to evaluate collision potential at unsignalized intersection located at Shao. The morning and evening peak traffic flow was captured using a video camera for seven days and then analyzed by playing back the video on daily basis. The 100 sample size of observed conflict was based on 95% confidence level, 5% permitted error and the proportion of the vehicles that were involved in a specific conflict for the observed traffic flow. The conflicts identified were compared with volume counts at minor approach. The daily peak hour approach traffic volumes were found to have a close relationship with the percentage values of conflict on the two minor approaches. It also showed that rear end collision accounted for more than 70 percent of traffic conflicts and it correlated well with the traffic volumes on WB and EB approaches.

Nonlinearity and chaos in wireless network traffic

The natural complexity of wireless mobile network traffic dynamics has been assessed in this article by tracing the presence of nonlinearity and chaos in the profile of daily peak hour call arrival and daily call drop of a sub-urban local mobile switching centre. The tools like Recurrence Plot and Recurrence Quantification Analysis (RQA) has been used to reveal the probable presence of non-stationarity, nonlinearity and chaosity in the network traffic. Information Entropy (IE) and 0–1 test have been employed to provide the quantitative support to the findings. Both the daily peak hour call arrival profile and the daily call drop profile exhibit non-stationarity, determinism and nonlinearity with the former one being more regular while the later one is chaotic.

Statistical analysis of the electric energy production from photovoltaic conversion using mobile and fixed constructions

The paper presents the most representative – from the three-year measurement time period – characteristics of daily and monthly electricity production from a photovoltaic conversion using modules installed in a fixed and 2-axis tracking construction. Results are presented for selected summer, autumn, spring and winter days. Analyzed measuring stand is located on the roof of the Faculty of Electrical Engineering Poznan University of Technology building. The basic parameters of the statistical analysis like mean value, standard deviation, skewness, kurtosis, median, range, or coefficient of variation were used. It was found that the asymmetry factor can be useful in the analysis of the daily electricity production from a photovoltaic conversion. In order to determine the repeatability of monthly electricity production, occurring between the summer, and summer and winter months, a non-parametric Mann-Whitney U test was used as a statistical solution. In order to analyze the repeatability of daily peak hours, describing the largest value of the hourly electricity production, a non-parametric Kruskal-Wallis test was applied as an extension of the Mann-Whitney U test. Based on the analysis of the electric energy distribution from a prepared monitoring system it was found that traditional forecasting methods of the electricity production from a photovoltaic conversion, like multiple regression models, should not be the preferred methods of the analysis.

Is our everyday comfort for sale? Preferences for demand management on the electricity market

In a European perspective, the electricity markets have been experiencing major changes via deregulation, new technologies and changes in the production mix. Together with the daily and seasonal peak hours on the demand side, the changing markets put pressure on increased flexibility to handle and sustain balance in the grid systems. This paper focuses on the demand side and analyzes preferences related to demand management of Swedish households' energy use. In a web-based choice experiment respondents were faced with three hypothetical electricity contracts. The choices of preferred contracts revealed preferences for attributes related to external control of heating, household electricity and information dissemination (integrity). The results show that people put a substantial value on not being controlled, illustrated by compensations up to thousands of SEK for accepting a contract characterized by external control of energy use in various dimensions. In addition, the results show that household composition, age, gender and income play a role for the perceived discomfort from the external control and information dissemination.

Determination and Application of Standard K Factors for Bicycle Traffic

This research is concerned with the calculation and application of the design hour factor, also known as the K factor, for bicycle traffic. Two variations of the K factor were developed. The first variation was referred to as Kp/d and was calculated as the ratio between the peak hour volume and the total daily volume. The second variation was referred to as Kp/AADB and was computed as the ratio of the daily peak hour volume to the annual average daily bicycle volume (AADB). An application was presented on how to use the developed K factors to calculate the AADB, and the estimation accuracy of using the two variations of the K factor was assessed. Five groups of the K factors were calculated according to different criteria. The results showed that the Kp/d factors classified by groups of similar links, weekdays and weekends, and year led to the best results where the average estimation error of the daily bicycle volume was about 16.6%. Furthermore, the use of the best set of K p/d factors along with daily and monthly adjustment factors for the estimation of the AADB value led to an average estimation error of 28.3%. Conversely, the set of Kp/AADB factors classified by weekdays and weekends, month, and year led to the lowest estimation error with an average of 28.9%. The paper provides insights on the selection of data collection days and months, which could improve the design of data collection programs of bicycle traffic.

Perbandingan Perhitungan Trafik Jam Sibuk CDMA 2000 1x pada BTS Inner City dan BTS Outer City dengan Mempergunakan Metode ADPH, TCBH, FDMH dan FDMP

<p class="Abstract">Cellular communication system is a wireless communication system where the subscriber can move within a wide network coverage. Code Division Multiple Access (CDMA) is a multiuser access technology that is each user uses a unique code contained in the access channel in the system. Calculation and determination of peak hours can be done by several methods such as: Average Daily Peak Hour (ADPH), Time Consistent Busy Hour (TCBH), Fixed Daily Measurement Hour (FDMH), Fixed Daily Measurement Period (FDMP). The effectiveness of the channel should be determined by occupancy both at inner city territory and outer city territory location. Using design Erlang (Erl) for supply channel at Base Transceiver Station (BTS) that provided, BTS has a design Erlang of 369,83 Erl at inner city and it has a design Erlang of 241,8 Erl at outer city. Peak hour on the inner city occurred at 12:00 to 15:00, whereas the outer city of peak hour occurred at 18:00 to 21:00. Effectiveness value that determined by operator are : <20% = low occupancy (not effective), 21% to 69% = normal occupancy (effective), and > 70% = high occupancy (very effective). In this case occupancy values ​​obtained in each method is between 21% to 69% which means effective.</p>

Space–Time Dynamics of Crime in Transport Nodes

This article assesses space–time variations of crime rates in underground stations. Drawing on assumptions from time geography, routine activity principles, and defensible space theory, the study investigates daily, weekly, and seasonal variations of crime at underground stations in the Swedish capital, Stockholm. Data from extensive field work at the stations was combined with crime records and passenger flow to test whether stations’ environmental attributes affect crime at different times. Geographical information systems, spatial statistic techniques, and modeling underpin the methodology used in the study. Findings show that crimes tend to happen more often in the evening, at night, on holidays, and on weekends. There is also evidence of seasonal variations of crime. In the winter, stations with social disturbance and signs of deterioration show high levels of crime, whereas in the summer, offenses are concentrated in stations nearby alcohol selling outlets. Stations with hiding spots are often targeted for crime during daily peak hours, whereas during holidays, crowded stations and those with alcohol selling outlets attract more criminal activities. Results suggest that the role of the stations’ environment on crime causation varies over time—an important fact for safety interventions.

Perbandingan Perhitungan Trafik Jam Sibuk CDMA 2000 1x pada BTS Inner City dan BTS Outer City dengan Mempergunakan Metode ADPH, TCBH, FDMH dan FDMP

Cellular communication system is a wireless communication system where the subscriber can move within a wide network coverage. Code Division Multiple Access (CDMA) is a multiuser access technology that is each user uses a unique code contained in the access channel in the system. Calculation and determination of peak hours can be done by several methods such as: Average Daily Peak Hour (ADPH), Time Consistent Busy Hour (TCBH), Fixed Daily Measurement Hour (FDMH), Fixed Daily Measurement Period (FDMP). The effectiveness of the channel should be determined by occupancy both at inner city territory and outer city territory location. Using design Erlang (Erl) for supply channel at Base Transceiver Station (BTS) that provided, BTS has a design Erlang of 369,83 Erl at inner city and it has a design Erlang of 241,8 Erl at outer city. Peak hour on the inner city occurred at 12:00 to 15:00, whereas the outer city of peak hour occurred at 18:00 to 21:00. Effectiveness value that determined by operator are : <20% = low occupancy (not effective), 21% to 69% = normal occupancy (effective), and > 70% = high occupancy (very effective). In this case occupancy values obtained in each method is between 21% to 69% which means effective