scholarly journals Performance and Energy Trade-Offs for Parallel Applications on Heterogeneous Multi-Processing Systems

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2409
Author(s):  
A. M. Coutinho Demetrios ◽  
Daniele De Sensi ◽  
Arthur Francisco Lorenzon ◽  
Kyriakos Georgiou ◽  
Jose Nunez-Yanez ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Configuration Space ◽  
Energy Savings ◽  
Analytical Models ◽  
Parallel Applications ◽  
Pareto Optimal ◽  
Trade Offs ◽  
Energy Trade ◽  
Optimal Configurations ◽  
Selection Of

This work proposes a methodology to find performance and energy trade-offs for parallel applications running on Heterogeneous Multi-Processing systems with a single instruction-set architecture. These offer flexibility in the form of different core types and voltage and frequency pairings, defining a vast design space to explore. Therefore, for a given application, choosing a configuration that optimizes the performance and energy consumption is not straightforward. Our method proposes novel analytical models for performance and power consumption whose parameters can be fitted using only a few strategically sampled offline measurements. These models are then used to estimate an application’s performance and energy consumption for the whole configuration space. In turn, these offline predictions define the choice of estimated Pareto-optimal configurations of the model, which are used to inform the selection of the configuration that the application should be executed on. The methodology was validated on an ODROID-XU3 board for eight programs from the PARSEC Benchmark, Phoronix Test Suite and Rodinia applications. The generated Pareto-optimal configuration space represented a 99% reduction of the universe of all available configurations. Energy savings of up to 59.77%, 61.38% and 17.7% were observed when compared to the performance, ondemand and powersave Linux governors, respectively, with higher or similar performance.

scholarly journals Construction of Analytical Models for Driving Energy Consumption of Electric Buses through Machine Learning

2020 ◽  
Vol 10 (17) ◽  
pp. 6088
Author(s):  
Kuan-Cheng Lin ◽  
Chuan-Neng Lin ◽  
Josh Jia-Ching Ying
Keyword(s):  
Energy Consumption ◽  
Public Transportation ◽  
Management System ◽  
Energy Savings ◽  
Analytical Models ◽  
Battery Management System ◽  
Battery Management ◽  
Passenger Transport ◽  
Carbon Reduction ◽  
Electric Bus

In recent years, the Taiwan government has been calling for the use of public transportation and has been popularizing pollution-reducing green vehicles. Passenger transport operators are being encouraged to replace traditional buses with electric buses, to increase their use in urban transportation. Reduced energy consumption and operating costs are important operational benefits for passenger transport operators, and driving behavior has a significant impact on fuel consumption. Although many literatures or real-world systems have addressed the issues related to reducing energy consumption with electric buses, these works do not involve the records collected from an on-vehicle battery management system (BMS). Accordingly, the results of analyses of existing works lack in-depth discussions, and therefore the applicability of existing works is insignificant. Therefore, in this study, driving data were collected using a battery management system (BMS), and vehicular power consumption was classified according to energy efficiency. Then, decision trees and random forest were applied to construct energy consumption analytical models. Finally, the driving behaviors that influence energy consumption were investigated. A case study was conducted in which a Taichung passenger transport operator’s electric bus driving data on urban routes were collected to construct energy consumption analytical models. The data consisted of two parts, i.e., vehicle records and route records. On the basis of these records, we considered the practicability and applicability of the analytical models by transforming the unstructured records into raw data. Passenger transport operators and drivers can leverage the obtained eco-driving indicators for different bus routes for energy savings and carbon reduction.

Interpretation and Analysis About Energy Savings in Commercial Green Houses Using Custom-Made Shadenets As Well As Thermal Reflective Screens

2017 ◽  
Author(s):  
Subin MattaraChalill ◽  
Chinnapalaniandi Periasamy ◽  
Pillai Nandakumar ◽  
Ram Karthikeyan
Keyword(s):  
Energy Consumption ◽  
Plant Growth ◽  
Temperature Control ◽  
Large Scale ◽  
Energy Savings ◽  
Microstructural Analysis ◽  
Climatic Conditions ◽  
Operational Cost ◽  
Active Radiation ◽  
Selection Of

Greenhouses are known to be the modern outlook for the agronomical industry in terms of high-end yield especially in the regions where climatic conditions are not stable like in the Middle East, Europe, and United States. Crop optimization is one of the major challenges facing the farmers and the controlled production centers can dictate this difficulty in the upcoming market. Greenhouses are considered as the high -tech production centers which can support the food industry to have a green revolution through the mass production of the vegetables and spices. Properly designed commercial greenhouses can increase the yield by minimizing the operational cost especially in terms of reducing the energy consumption. In order to have a properly designed greenhouse, the selection or up gradation of the shade structures can play a vital role. Conventional greenhouses are made of polycarbonate sheets and in some cases the polyhouses by using simple polyethylene sheets. In this scenario, the main drawbacks were the energy consumption, operational expenses and the effectiveness of the indoor temperature control. Custom designed shades based on the crop requirements can provide high production rate by reducing the energy consumption. The detailed microstructural analysis in conjunction with the photosynthesis demand can provide a better selection of the shade-net or curtains. Greenhouse shade structure can be upgraded using the motorized specially designed nets or by using thermal-reflective screens. This up gradation can provide four stage advantages. In stage one this can decrease the 50% of heat energy and which will save the HVAC operational cost. During the stage, two better temperature control during the day and night will provide a good environment to provide proper PAR (Photosynthetically Active Radiation)[5] for photosynthesis, in the wavelength range of 400 to 700 nanometer. Third and fourth stages are the protection from the frost as well heat stress during the different climatic conditions. In the present market condition, the commercial greenhouses are being built in large scale by neglecting the energy saving options in shade structures. The commercial greenhouses using the upgraded shade structures can save the operational cost by 25 to 30%. Selection of this shade-nets or curtains can be done using the detailed microstructural analysis of the material. Shade-nets/curtains can be controlled manually, mechanically or can be automated in large-scale greenhouses. Flowering dates in the plants can be accelerated using the shading materials and delayed by the use of control treatment, which coincides with the results obtained in the previous studies [1]. This has proven with high land experiments [2]. Greenhouse shade nets are used in order to protect crops and plants from adverse weather conditions, animals and pests, besides providing suitable conditions for plant growth. The essential performance properties required for greenhouse shade nets are the resistance to solar radiation and weathering. The intensity of the Photo Synthetically Active Radiation (PAR) directly influences plant growth. Other nonvisible radiations are ultraviolet (UV), infrared (IR) and far infrared (FIR)[16]. Polypropylene and polyester are more resistant to UV radiation than polyethylene, which is resistant to radiations in the visible region. The use of greenhouse shade nets in outdoor conditions also requires them to be resistant to abrasion[3]. The objective of the present work is to examine the effectiveness of the properly selected shade-net/curtain in commercial greenhouses in terms of high yield energy savings. This study was conducted to compare the traditional polycarbonate sheet with the innovation of properly designed shade curtain made-up from high-density polyethylene (HDPE) fiber reinforced material discover the best shading method for plant growth in an ideal energy conservation scenario. The study was conducted in the two identical greenhouses (planted with lettuce crop) located in Al Khawaneej farm in the Emirate of Dubai in the United Arab Emirates. Yield versus the energy consumption has been observed in a period of time and obtained the reduction in energy consummation of almost 20 to 30 %.

scholarly journals Multi-Criteria Decision-Making Method for Sustainable Energy-Saving Retrofit Façade Solutions

2021 ◽  
Vol 13 (23) ◽  
pp. 13168
Author(s):  
Ziortza Egiluz ◽  
Jesús Cuadrado ◽  
Andoni Kortazar ◽  
Ignacio Marcos
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Savings ◽  
Multi Criteria Decision Making ◽  
Effective Energy ◽  
Economic Basis ◽  
Selection Of

The increasing energy consumption levels of buildings within Europe call for controlled consumption and improvements to energy savings and efficiency and effective energy efficiency regulations. However, many aging and energy-inefficient buildings require energetic retrofitting that can employ various façades solutions and insulation materials. The selection of the most sustainable options in each situation therefore requires a decision-making methodology that can be used to prioritize available retrofit solutions based on economic, functional, environmental and social criteria. In this paper, both the methodology and the economic basis of the retrofitting process are presented. The methodology was validated in a case study, and a sensitivity analysis also demonstrated its validity, robustness and stability

Determining Factor/s of Window Glazing Regarding Reduction in Electrical Energy Consumption

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Arindam Dutta ◽  
Akash Samanta
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Electrical Energy ◽  
Simulation Software ◽  
Tropical Region ◽  
Electrical Energy Consumption ◽  
Heat Gain ◽  
Judicial Selection ◽  
Determining Factor ◽  
Selection Of

Abstract Among all building envelops, windows are typically the weakest barrier to heat ingress. The building energy consumption of any conditioned building located in the tropical country is deeply governed by the amount of heat gain inside the building because heating ventilation and air-conditioning (HVAC) system is a major energy consumer. Hence, it can be easily inferred that the energy consumption of a building can be reduced through judicial selection of window glasses. This paper illustrated the importance of thermal transmittance (U-value) and solar heat gain coefficient (SHGC) value of window glazing in detail and also demonstrated the energy savings potential of various types of commercially available windowpanes. The electric energy savings potential of various types of windowpanes such as tinted, reflective, single glazing, and double glazing glasses have been analyzed through eQUEST energy simulation software for a building, situated in the tropical region of India. Building architectural data and all other information regarding HVAC, lighting, etc. have been collected during the energy audit and trained in the eQUEST simulation for further analysis. The calibration of simulation model has been done using actual monthly electricity consumption data of the case building. This study depicts the percentage decrease in electrical energy consumption due to retrofitting of various commercially available window glasses compared with base building. The study also compares the importance of main two determining factor(s) U and SHGC value behind the judicial selection of proper window glazing.

Saving Primary Energy Consumption Through Exergy Analysis of Combine Distillation and Power Plant

2012 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Alhassan Salami Tijani ◽  
Nazri Mohammed ◽  
Werner Witt
Keyword(s):  
Energy Consumption ◽  
Power Plant ◽  
Heat Pump ◽  
Heat Recovery ◽  
Energy Savings ◽  
Primary Energy ◽  
Heat Pumps ◽  
Saturated Steam ◽  
Distillation Unit ◽  
Primary Energy Consumption

Industrial heat pumps are heat-recovery systems that allow the temperature ofwaste-heat stream to be increased to a higher, more efficient temperature. Consequently, heat pumps can improve energy efficiency in industrial processes as well as energy savings when conventional passive-heat recovery is not possible. In this paper, possible ways of saving energy in the chemical industry are considered, the objective is to reduce the primary energy (such as coal) consumption of power plant. Particularly the thermodynamic analyses ofintegrating backpressure turbine ofa power plant with distillation units have been considered. Some practical examples such as conventional distillation unit and heat pump are used as a means of reducing primary energy consumption with tangible indications of energy savings. The heat pump distillation is operated via electrical power from the power plant. The exergy efficiency ofthe primary fuel is calculated for different operating range ofthe heat pump distillation. This is then compared with a conventional distillation unit that depends on saturated steam from a power plant as the source of energy. The results obtained show that heat pump distillation is an economic way to save energy if the temperaturedifference between the overhead and the bottom is small. Based on the result, the energy saved by the application of a heat pump distillation is improved compared to conventional distillation unit.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

scholarly journals Modeling Energy LED Light Consumption Based on an Artificial Intelligent Method Applied to Closed Plant Production System

2021 ◽  
Vol 11 (6) ◽  
pp. 2735
Author(s):  
Ernesto Olvera-Gonzalez ◽  
Martín Montes Rivera ◽  
Nivia Escalante-Garcia ◽  
Eduardo Flores-Gallegos
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Nonlinear Models ◽  
Light Emitting Diode ◽  
Red Light ◽  
Green Light ◽  
Plant Production ◽  
Production Plant ◽  
Light Component ◽  
Gp Model

Artificial lighting is a key factor in Closed Production Plant Systems (CPPS). A significant light-emitting diode (LED) technology attribute is the emission of different wavelengths, called light recipes. Light recipes are typically configured in continuous mode, but can also be configured in pulsed mode to save energy. We propose two nonlinear models, i.e., genetic programing (GP) and feedforward artificial neural networks (FNNs) to predict energy consumption in CPPS. The generated models use the following input variables: intensity, red light component, blue light component, green light component, and white light component; and the following operation modes: continuous and pulsed light including pulsed frequency, and duty cycle as well energy consumption as output. A Spearman's correlation was applied to generate a model with only representative inputs. Two datasets were applied. The first (Test 1), with 5700 samples with similar input ranges, was used to train and evaluate, while the second (Test 2), included 160 total datapoints in different input ranges. The metrics that allowed a quantitative evaluation of the model's performance were MAPE, MSE, MAE, and SEE. Our implemented models achieved an accuracy of 96.1% for the GP model and 98.99% for the FNNs model. The models used in this proposal can be applied or programmed as part of the monitoring system for CPPS which prioritize energy efficiency. The nonlinear models provide a further analysis for energy savings due to the light recipe and operation light mode, i.e., pulsed and continuous on artificial LED lighting systems.

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