scholarly journals Demystifying Energy Consumption Dynamics in Transiently powered Computers

2020 ◽  
Vol 19 (6) ◽  
pp. 1-25
Author(s):  
Saad Ahmed ◽  
Muhammad Nawaz ◽  
Abu Bakar ◽  
Naveed Anwar Bhatti ◽  
Muhammad Hamad Alizai ◽  
...  
2021 ◽  
Vol 16 ◽  
pp. 178-184
Author(s):  
A. A. Vysotskaya ◽  
A. A. Vorontsov ◽  
R. I. Dzerzhinsky

This article examines the overall trend in primary energy consumption from 1635 to 2020 in the United States. Based on the exponential growth model, the annual energy consumption average growth rate and the process characteristic time are determined. The anamorphosis method is used to search for the logistic model parameters. Long-term trends analysis and the corresponding time series fluctuations are carried out. For the fluctuations' analysis, the trend component is preliminarily excluded based on the proportions theory. Near-period values are determined using shift and autocorrelation functions. To predict further energy consumption dynamics, the ARIMA autoregressive model is used, on which basis a local increase in the annual energy consumption level to 97.66 quads Btu is expected by 2025. The US energy consumption dynamics by resource type is considered. A forecast up to 2025 for the primary energy resources consumption shares in their total volume is built on an autoregressive model basis


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2556 ◽  
Author(s):  
Mayra Erazo-Rodas ◽  
Mary Sandoval-Moreno ◽  
Sergio Muñoz-Romero ◽  
Mónica Huerta ◽  
David Rivas-Lalaleo ◽  
...  

Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes.


Author(s):  
Jyoti U. Devkota

<div data-canvas-width="397.374989921387">This study is based on data collected from two sample surveys. They are namely survey of 300 households of national grid energy users and 400 households of biogas users. It was conducted in three different rural settings of Nepal. The responses to questions were classifie d into multiple choice options. This generated categorical data and reduced ambiguity and confusion between interviewer and interviewee. Such data were classified into ordinal scale and modelled. As the dependent variable had more than two categories, polytomous and not dichotomous models are developed and fitted. Ten different hypotheses assessing and measuring the energy consumption dynamics are tested. Values of parameters of these model and odds ratio are used in quantifying the impact of change with respect to energy consumption. The variables considered were namely time spent in the collection of firewood, type of house, amount of firewood saved, time saved, employer and school located within 15 min distance. Such data based studies are very crucial for country like Nepal which lacks a strong backbone of accurate and regularly updated official records. They can be generalized to other counties of Asia and Africa. Such results provide guidelines to policy makers and planners regarding formulation of realistic energy policies for such countries.</div>


Author(s):  
Shahzeen Z. Attari ◽  
Michael L. DeKay ◽  
Cliff I. Davidson ◽  
Wandi Bruine de Bruin

ICCTP 2009 ◽  
2009 ◽  
Author(s):  
Shunquan Huang ◽  
Siqin Yu ◽  
Zhongmin Liu

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.


2019 ◽  
pp. 53-65
Author(s):  
Renata Domingos ◽  
Emeli Guarda ◽  
Elaise Gabriel ◽  
João Sanches

In the last decades, many studies have shown ample evidence that the existence of trees and vegetation around buildings can contribute to reduce the demand for energy by cooling and heating. The use of green areas in the urban environment as an effective strategy in reducing the cooling load of buildings has attracted much attention, though there is a lack of quantitative actions to apply the general idea to a specific building or location. Due to the large-scale construction of high buildings, large amounts of solar radiation are reflected and stored in the canyons of the streets. This causes higher air temperature and surface temperature in city areas compared to the rural environment and, consequently, deteriorates the urban heat island effect. The constant high temperatures lead to more air conditioning demand time, which results in a significant increase in building energy consumption. In general, the shade of the trees reduces the building energy demand for air conditioning, reducing solar radiation on the walls and roofs. The increase of urban green spaces has been extensively accepted as effective in mitigating the effects of heat island and reducing energy use in buildings. However, by influencing temperatures, especially extreme, it is likely that trees also affect human health, an important economic variable of interest. Since human behavior has a major influence on maintaining environmental quality, today's urban problems such as air and water pollution, floods, excessive noise, cause serious damage to the physical and mental health of the population. By minimizing these problems, vegetation (especially trees) is generally known to provide a range of ecosystem services such as rainwater reduction, air pollution mitigation, noise reduction, etc. This study focuses on the functions of temperature regulation, improvement of external thermal comfort and cooling energy reduction, so it aims to evaluate the influence of trees on the energy consumption of a house in the mid-western Brazil, located at latitude 15 ° S, in the center of South America. The methodology adopted was computer simulation, analyzing two scenarios that deal with issues such as the influence of vegetation and tree shade on the energy consumption of a building. In this way, the methodological procedures were divided into three stages: climatic contextualization of the study region; definition of a basic dwelling, of the thermophysical properties; computational simulation for quantification of energy consumption for the four facade orientations. The results show that the façades orientated to north, east and south, without the insertion of arboreal shading, obtained higher values of annual energy consumption. With the adoption of shading, the facades obtained a consumption reduction of around 7,4%. It is concluded that shading vegetation can bring significant climatic contribution to the interior of built environments and, consequently, reduction in energy consumption, promoting improvements in the thermal comfort conditions of users.


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