Oxygen Enrichment in Combustion Processes: Comparative Experimental Results From Several Application Fields

1991 ◽  
Vol 113 (2) ◽  
pp. 122-126
Author(s):  
M. De Lucia
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Copper Alloys ◽  
Ceramic Materials ◽  
Oxygen Enrichment ◽  
Experimental Results ◽  
Ferrous Metals ◽  
Definition Of ◽  
Application Fields ◽  
Combustion Processes

The effects of using oxygen to partially or wholly replace fuel air in small-size melting furnaces were studied over a range of application fields. Following definition of the useful parameters, testing was conducted on furnaces for melting glass, ferrous metals (pigiron), nonferrous metals (copper alloys), and ceramic materials. In all cases, oxygen-enrichment was found to provide significant energy savings, as well as notable advantages in terms of both plant output and energy consumption.

scholarly journals Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2166 ◽  
Author(s):  
Aniela Kaminska ◽  
Andrzej Ożadowicz
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Savings ◽  
Residential Buildings ◽  
Experimental Tests ◽  
Experimental Results ◽  
Automation System ◽  
Building Automation ◽  
Total Energy Consumption ◽  
Lighting Control

Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well.

Assessment of Different Natural Ventilation Strategies for an Educational Building on the Warm-Humid Climate of Guayaquil, Ecuador

2015 ◽  
Author(s):  
R. David Beltrán ◽  
Juan Kastillo ◽  
Isabel Miño-Rodríguez ◽  
Carlos Naranjo-Mendoza ◽  
Carlos Ávila
Keyword(s):  
Energy Consumption ◽  
Natural Ventilation ◽  
Energy Savings ◽  
Main Concern ◽  
Humid Climate ◽  
The Real ◽  
Ventilation Strategies ◽  
Definition Of ◽  
The Impact ◽  
Real State

Natural ventilation has been studied as an effective strategy in order to reduce energy consumption without compromising occupant’s hygrothermal comfort in warm-humid climates. However, the main concern about the current state of art in the use of Building Energy Simulation (BES) as an approach to natural ventilation is the definition of input data which usually do not represent the real state of the buildings in the studied region. Within this context, the main contribution of this research is to propose a methodology through which the real state of buildings can be evaluated. By this analysis, valid input parameters was found to exploit the capabilities of BES and CFD simulations to fulfill the main objective of this study, which is to assess the impact of natural ventilation strategies in the energy consumption of HVAC systems and occupants hygrothermal comfort. Four natural ventilation strategies were evaluated: single sided ventilation, cross ventilation, solar chimney and double façade. The results show that the exclusive use of natural ventilation is ineffective to ensure hygrothermal comfort in a building with high thermal loads in a warm-humid climate like Guayaquil. However, by using a hybrid system (natural ventilation/dehumidification and cooling) cooling energy consumption can be reduced in up to 10.6% without compromising occupant’s hygrothermal comfort. Due to the promising results regarding energy savings, further research will aim to evaluate the impact of other passive strategies in energy consumption.

GENERATION AND PROPERTIES OF INFRARED RADIATION

2019 ◽  
Vol 6 (2) ◽  
pp. 101-137
Author(s):  
RUSTAM KHAKIMOVICH RAKHIMOV
Keyword(s):  
Electromagnetic Radiation ◽  
Infrared Radiation ◽  
Radiation Spectrum ◽  
Laws Of Nature ◽  
Primary Source ◽  
Ceramic Materials ◽  
Experimental Results ◽  
Ir Radiation ◽  
Scattering Of Light

The article presents the main basic laws of nature and modern theories of the nature of electromagnetic radiation, its generation, characteristics, and laws of reflection, absorption and scattering of light. The principle of transformation of the radiation spectrum of the primary source using the developed ceramic materials are shown, as well as experimental results of the interaction of IR radiation with matter and various mechanisms of influence on various objects and processes are described.

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.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

scholarly journals Ensemble Prediction Approach Based on Learning to Statistical Model for Efficient Building Energy Consumption Management

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 405
Author(s):  
Anam Nawaz Khan ◽  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Do-Hyeun Kim
Keyword(s):  
Energy Consumption ◽  
Statistical Model ◽  
Residential Buildings ◽  
Residential Building ◽  
Experimental Results ◽  
Consumption Patterns ◽  
Ensemble Prediction ◽  
Short Term ◽  
Term Energy ◽  
Prediction Approach

With the development of modern power systems (smart grid), energy consumption prediction becomes an essential aspect of resource planning and operations. In the last few decades, industrial and commercial buildings have thoroughly been investigated for consumption patterns. However, due to the unavailability of data, the residential buildings could not get much attention. During the last few years, many solutions have been devised for predicting electric consumption; however, it remains a challenging task due to the dynamic nature of residential consumption patterns. Therefore, a more robust solution is required to improve the model performance and achieve a better prediction accuracy. This paper presents an ensemble approach based on learning to a statistical model to predict the short-term energy consumption of a multifamily residential building. Our proposed approach utilizes Long Short-Term Memory (LSTM) and Kalman Filter (KF) to build an ensemble prediction model to predict short term energy demands of multifamily residential buildings. The proposed approach uses real energy data acquired from the multifamily residential building, South Korea. Different statistical measures are used, such as mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and R2 score, to evaluate the performance of the proposed approach and compare it with existing models. The experimental results reveal that the proposed approach predicts accurately and outperforms the existing models. Furthermore, a comparative analysis is performed to evaluate and compare the proposed model with conventional machine learning models. The experimental results show the effectiveness and significance of the proposed approach compared to existing energy prediction models. The proposed approach will support energy management to effectively plan and manage the energy supply and demands of multifamily residential buildings.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals On the Optimization of Electrical Water Heaters: Modelling Simulations and Experimentation

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3912
Author(s):  
Wassim Salameh ◽  
Jalal Faraj ◽  
Elias Harika ◽  
Rabih Murr ◽  
Mahmoud Khaled
Keyword(s):  
Experimental Study ◽  
Energy Consumption ◽  
Parametric Study ◽  
Thermal Model ◽  
Energy Savings ◽  
Input Power ◽  
Energy Crisis ◽  
Water Heaters ◽  
World Energy ◽  
Electrical Components

In the context of a world energy crisis, the only solution to control the situation is in the management of energy. One of the most important management keys is the optimization of electrical components. This article presents a complete numerical and experimental study aiming for the optimization of electrical water heaters for household use. The optimization conceives the minimization of energy consumption simultaneously with the minimization of time to heat water. Firstly, a thermal model well adapted for the case of heaters is constructed and validated experimentally and then a parametric study is conducted covering all the input power, the volume and the external area of the heater. Results are promising, showing significant energy savings are possible with an optimum setting of these parameters, thus presenting a firm tool for the optimization of heaters.

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