Exploration of Energy Consumption Using the Intel Running Average Power Limit Interface

2019 ◽  
Author(s):  
Joe A. Garcia
Keyword(s):  
Energy Consumption ◽  
Average Power ◽  
Power Limit

A realistic dynamic blower energy consumption model for wastewater applications

2016 ◽  
Vol 74 (7) ◽  
pp. 1561-1576 ◽  
Author(s):  
Y. Amerlinck ◽  
W. De Keyser ◽  
G. Urchegui ◽  
I. Nopens
Keyword(s):  
Energy Consumption ◽  
Dynamic Model ◽  
Wastewater Treatment Plants ◽  
Average Power ◽  
High Energy ◽  
Accurate Prediction ◽  
Process Models ◽  
Average Power Consumption ◽  
Energy Peak ◽  
Plant Optimization

At wastewater treatment plants (WWTPs) aeration is the largest energy consumer. This high energy consumption requires an accurate assessment in view of plant optimization. Despite the ever increasing detail in process models, models for energy production still lack detail to enable a global optimization of WWTPs. A new dynamic model for a more accurate prediction of aeration energy costs in activated sludge systems, equipped with submerged air distributing diffusers (producing coarse or fine bubbles) connected via piping to blowers, has been developed and demonstrated. This paper addresses the model structure, its calibration and application to the WWTP of Mekolalde (Spain). The new model proved to give an accurate prediction of the real energy consumption by the blowers and captures the trends better than the constant average power consumption models currently being used. This enhanced prediction of energy peak demand, which dominates the price setting of energy, illustrates that the dynamic model is preferably used in multi-criteria optimization exercises for minimizing the energy consumption.

Ultra-Wideband Solutions for Last Mile Access Network

2009 ◽  
pp. 1443-1452
Author(s):  
Sabira Khatun ◽  
Rashid A. Saeed ◽  
Nor Kamariah Nordin ◽  
Borhanuddin Mohd Ali
Keyword(s):  
Wireless Communications ◽  
Power Efficiency ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mesh Networks ◽  
Power Level ◽  
Average Power ◽  
Ultra Wideband ◽  
Digital Data ◽  
Higher Power ◽  
Power Limit

Ultra-wideband (UWB) is an alternative wireless communications technology that offers high bandwidth wireless communications without the constraints of spectrum allocation. Fundamentally different from conventional radio frequency communications, UWB relies on a series of narrow, precisely timed pulses to transmit digital data. Transmitters and receivers that use UWB can be much simpler to build than their conventional counterparts, resulting in lower cost and higher power efficiency. Moreover, the inherent properties of UWB emissions allow them to potentially coexist with conventional wireless systems on a noninterfering basis. In April 2002, the Federal Communications Commission (FCC) released UWB emission masks and introduced the concept of coexistence with traditional and protected radio services in the frequency spectrum, which allows the operation of UWB systems mainly in the 3.1 to 10.6 GHz band, limiting the power level emission to -41dBm/MHz. Within the power limit allowed under the current FCC regulations, Ultra-wideband can not only carry huge amounts of data over a shortto- medium distance at very low power (this range can be extended by using ad-hoc or mesh networks), but it also has the ability to carry signals through doors and other obstacles that tend to reflect signals at more limited bandwidths and a higher power (Reed, 2005). At higher power levels, UWB signals can travel to significantly greater ranges. In March 2005, the FCC granted the waiver request, filed by the multiband Orthogonal Frequency Division Multiplexing (OFDM) alliance (MBOA), in which it approved the change in measurement for the all UWB technologies (neutral approach) (Barret, 2005). The FCC’s waiver grants effectively removes the previous transmit power penalties for both frequency-hopping (OFDM) and gated UWB technologies (TH and DS). Hence, they are allowed to transmit at higher power levels and then become idle for some time, as long as they meet the limits for average power density. This new rules allow those technologies to achieve up to four times better performance and double the range.

Dynamic Modeling of Energy Efficient Crab Walking of Hexapod Robot

2011 ◽  
Vol 110-116 ◽  
pp. 2730-2739 ◽  
Author(s):  
Shibendu Shekhar Roy ◽  
Dilip Kumar Pratihar
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Average Power ◽  
Force Distribution ◽  
Hexapod Robot ◽  
Gait Patterns ◽  
Joint Torques ◽  
Foot Force ◽  
Average Power Consumption

Crab walking is the most general and very important one for omni-directional walking of a hexapod robot. This paper presents a dynamic model for determining energy consumption and energy efficiency of a hexapod robot during its locomotion over flat terrain with a constant crab angle. The model has been derived for statically stable crab-wave gaits by considering a minimization of dissipating energy for optimal foot force distribution. Two approaches, such as minimization of norm of feet forces and minimization of norm of joint torques have been developed. The variations of average power consumption and energy consumption per weight per traveled length with velocity or stroke have been compared for crab walking with tripod and tetrapod gait patterns. Tetrapod gaits are found to be more energy-efficient compared to the tripod gaits.

Average power limit of fiber-laser systems with nearly diffraction-limited beam quality

2016 ◽  
Author(s):  
Hans-Jürgen Otto ◽  
Cesar Jauregui ◽  
Jens Limpert ◽  
Andreas Tünnermann
Keyword(s):  
Fiber Laser ◽  
Beam Quality ◽  
Average Power ◽  
Laser Systems ◽  
Power Limit

scholarly journals Cache optimization cloud scheduling (COCS) algorithm based on last level caches

2019 ◽  
Vol 8 (3) ◽  
pp. 184
Author(s):  
K. Vinod Kumar ◽  
Ranvijay Ranvijay
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Average Power ◽  
Cloud Services ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Cache Optimization ◽  
Dynamic Voltage ◽  
Increasing Demand ◽  
And Storage

<p><span>Recently, the utilization of cloud services like storage, various software, networking resources has extremely enhanced due to widespread demand of these cloud services all over the world. On the other hand, it requires huge amount of storage and resource management to accurately cope up with ever-increasing demand. The high demand of these cloud services can lead to high amount of energy consumption in these cloud centers. Therefore, to eliminate these drawbacks and improve energy consumption and storage enhancement in real time for cloud computing devices, we have presented Cache Optimization Cloud Scheduling (COCS) Algorithm Based on Last Level Caches to ensure high cache memory Optimization and to enhance the processing speed of I/O subsystem in a cloud computing environment which rely upon Dynamic Voltage and Frequency Scaling (DVFS). The proposed COCS technique helps to reduce last level cache failures and the latencies of average memory in cloud computing multi-processor devices. This proposed COCS technique provides an efficient mathematical modelling to minimize energy consumption. We have tested our experiment on Cybershake scientific dataset and the experimental results are compared with different conventional techniques in terms of time taken to accomplish task, power consumed in the VMs and average power required to handle tasks.</span></p>

scholarly journals THE IMPLEMENTATION OF DISAGGREGATION ALGORITHM IN THE ANALYSIS OF ENERGY CONSUMPTION BASED ON THE INTERNET-OF- THINGS TECHNOLOGY

2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Husein H ◽  
Aditya Alviori ◽  
Maman Budiman ◽  
Mitra Djamal
Keyword(s):  
Energy Consumption ◽  
Average Power ◽  
The State ◽  
Android Apps ◽  
Consumption Data ◽  
Cloud Server ◽  
Event Based ◽  
And Control ◽  
Data Frequency ◽  
Internet Of Things Technology

The effort to reduce the mass energy usage without involvement of consumers is not effective. Thereby, creating a pathway for anyone of consumer to be much more involved in the energy-saving effort. The implementation of disaggregation algorithm in the analysis of energy consumption is to recognize when and which appliance has the largest energy consumption and being able to control the state of all appliances from anywhere. In this research, the principle of disaggregation is event-based and low-sampling data frequency. A KWH-meter is used to send power data to the cloud server via MQTT protocol. The cloud server gathers the energy-consumption data, analyses them and then disaggregates them. The output of the disaggregation algorithm would tell the state (on/off), the average power and the percentage of energy consumed by each appliances. The output will then be sent from the cloud server to Android Apps via MQTT protocol. Then the consumer can easily access and control the energy consumption from their smartphone after knowing it through the disaggregation algorithm.

The effects of infill patterns and infill percentages on energy consumption in fused filament fabrication using CFR-PEEK

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Rashidul Hassan ◽  
Hyun Woo Jeon ◽  
Gayeon Kim ◽  
Kijung Park
Keyword(s):  
Energy Consumption ◽  
Average Power ◽  
Energy Performance ◽  
Fused Filament Fabrication ◽  
Content Type ◽  
Practical Applications ◽  
Ether Ether Ketone ◽  
Poly Ether Ether Ketone ◽  
Full Factorial Experimental Design ◽  
Full Factorial

Purpose This study aims to identify the effects of infill patterns and infill percentages on the energy consumption (EC) of fused filament fabrication (FFF). With increasing attention on carbon-fiber-reinforced–poly-ether-ether-ketone (CFR-PEEK) for practical applications in FFF, infill pattern and infill percentage for FFF can be properly controlled to achieve better energy performance of CFR-PEEK outputs. However, the effects of infill parameters on EC for FFF using CFR-PEEK have not been clearly addressed yet. Design/methodology/approach Using a full factorial experimental design, six types of infill patterns (rectilinear, grid, triangular, wiggle, fast honeycomb and full honeycomb) and four different infill percentages (25%, 50%, 75% and 100%) were considered for a design of experiments with three replicates. Then, analysis of variance, Tukey test and regression analysis were performed to investigate both the effects of infill pattern and infill percentage on energy performance during FFF. Findings EC is characterized to be high for the wiggle and triangular patterns and low for the rectilinear pattern during both the printing stage and the entire process. The wiggle pattern results in the greatest increase in EC, whereas the rectilinear pattern leads to the least increase in EC. Although EC during the FFF process increases as the infill percentage increases, the average power demand during the printing stage decreases. Originality/value Both the main and interaction effects of infill pattern and infill percentage are investigated to estimate EC and power during the different process stages of FFF.

Energy Aware Better Implementation of Load Balancing in Cloud Computing

2020 ◽  
Vol 13 ◽  
Author(s):  
Alekhya Orugonda ◽  
V. Kiran Kumar
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Power Consumption ◽  
Virtual Machines ◽  
Average Power ◽  
Power Saving ◽  
System Level ◽  
Energy Aware ◽  
Physical Machine ◽  
Average Power Consumption

Background: It is important to minimize bandwidth that improves battery life, system reliability and other environmental concerns and energy optimization.It also do everything within their power to reduce the amount of data that flows through their pipes.To increase resource exertion, task consolidation is an effective technique, greatly enabled by virtualization technologies, which facilitate the concurrent execution of several tasks and, in turn, reduce energy consumption. : MaxUtil, which aims to maximize resource exertion, and Energy Conscious Task Consolidation which explicitly takes into account both active and idle energy consumption. Method: In this paper an Energy Aware Cloud Load Balancing Technique (EACLBT) is proposed for the performance improvement in terms of energy and run time. It predicts load of host after VM allocation and if according to prediction host become overloaded than VM will be created on different host. So it minimize the number of migrations due to host overloading conditions. This proposed technique results in minimize bandwidth and energy utilization. Results: The result shows that the energy efficient method has been proposed for monitor energy exhaustion and support static and dynamic system level optimization.The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving.Besides minimization in bandwidth along with energy exertion, reduction in the number of executed instructions is also achieved. Conclusion: This paper comprehensively describes the EACLBT (Energy Aware Cloud Load Balancing Technique) to deploy the virtual machines for power saving purpose. The average power consumption is used as performance metrics and the result of PALB is used as baseline. The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving. It shown that on average an idle server consumes approximately 70% of the power consumed by the server running at the full CPU speed.The performance holds better for Common sub utterance elimination. So, we can say the proposed Energy Aware Cloud Load Balancing Technique (EACLBT) is effective in bandwidth minimization and reduction of energy exertion.

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