scholarly journals Numerical Study on Performance Optimization of an Energy-Saving Insulated Window

2021 ◽  
Vol 13 (2) ◽  
pp. 935
Author(s):  
Zhiqiang Wang ◽  
Qi Tian ◽  
Jie Jia
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Performance Optimization ◽  
Numerical Study ◽  
Load Ratio ◽  
Electric Heater ◽  
Optimal Energy ◽  
Key Factor ◽  
Heat Conservation ◽  
Power And Energy

Window energy consumption has become a key factor in designing buildings with optimal energy efficiency. To that end, herein, the use of an energy-saving insulated window (ESIW) is proposed, particularly for winter heat conservation. DeST software was used to evaluate the energy consumption properties of a house with an ESIW-structure window, as well as that of six other window structures currently on the market. The results were subsequently compared. Furthermore, a series of numerical simulations were carried out using Airpak software to investigate the insulation performance of four ESIW models (A, B, C, and D) under different influencing factors. Finally, the response surface method (RSM) was used to obtain the optimal ESIW structure installation conditions and the weight of each factor. The data shows that houses with ESIW-structure windows exhibit a more suitable indoor natural temperature; less heating load, cooling load, and cumulative annual load; and a more feasible price–load ratio than other energy-saving windows. Furthermore, the average temperature gradually decreased in response to decreasing the electric heater power and energy-saving standard, and increasing the heat transfer coefficient (HTC) and window-to-wall ratio (WWR). Thus, as the energy-saving standard (ESS) increases, the importance of the WWR increases in parallel. This study puts forward an HTC prediction formula that is applicable to different conditions. The optimal thermal efficiency conditions consisted of HTC = 1.07 W/m2 × K, WWR = 0.26, and an ESS of 75%. This study demonstrates that the ESIW system has optimal energy-saving properties and broad adaptability and operability, which can be applied in building insulation as a key insulation component.

Study and Analysis of an Electrical Energy Saving Strategies and Gas Emissions Reduction for a Private Hospital Building in Yemen

2021 ◽  
Vol 25 (2) ◽  
pp. 73-96
Author(s):  
عبد الجليل علي العبيدي
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Private Hospital ◽  
High Efficiency ◽  
Load Ratio ◽  
High Energy ◽  
Gas Emissions ◽  
Air Conditioners ◽  
Set Point ◽  
Hospital Building

Hospital buildings consume high energy more than other buildings in the commercial buildings sector as there is a continuous demand for power  supplies. Energy consumption and greenhouse gas emissions can be reduced in the buildings sector by using various energy saving methods. In this study, on-sight visiting for energy audit has been conducted at a private hospital in Sana’a - Yemen to record all data relevant to energy consumption by equipment, machines, and all other mechanical systems. Different energy saving scenarios were using to estimate the potential of energy saving such as using high-efficiency lighting devices, raising the thermostat set point temperature for air conditioners, using high-efficiency motors (HEM) with a different load ratio, and using variable speed motors (VSM). Results indicated that energy consumption for the hospital was 4,061.8 Megawatthourper year whereas energy intensity was 232 kWh/m2. It is found that about 150.32 megawatt-hours of annual energy saving is achieved by using HEM and 689.72 Megawatt-hour per year by raising the set point of air conditioners thermostat to 26 °C. In addition, 1513 megawatt-hours per year of energy can be saved by reducing the VSM speed to 60% whereas95.8 megawatt-hours per year is estimated by adopting 100% load of HEM. The economic study of energy saving strategies was found that the use of HEM is not economically viable, while the use of VSM with large capacity motors is better from economic and environmental points of view. Keywords: Hospital building, energy consumption, Energy index, Energy saving, Emission reduction

scholarly journals Analysis of Windows Element for Energy Saving in a Tropical Residential Buildings in Order to Reduce the Negative Environmental Impacts

2020 ◽  
Vol 9 (1) ◽  
pp. 1-6
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Residential Buildings ◽  
Gain Coefficient ◽  
Energy Performance ◽  
High Energy ◽  
Information Modeling ◽  
Tropical Regions ◽  
Building Information ◽  
Key Factor

In the contemporary milieu of today, sustainability and environmental concerns have become a great subject of debate. Matters related to sustainability are often linked to other crucial concerns like energy consumption. Energy is a key factor in ensuring continuous economic growth and development. One of the highest energy consuming systems in buildings – specifically residential homes in tropical regions – is the air conditioning system. Windows have been identified as the weakest link in the fabric of a building as they serve as thermal holes. Thus, the selection of proper window materials is crucial to reduce energy usage by minimizing the cooling and heating requirements of the building. The aims of this paper are analysis of energy performance for diverse types of window’s glazing with different frames in order to find the most optimized window materials for the tropical residential buildings. The selected case study in this paper is modeled and then simulated by Building Information Modeling (BIM) application, which is appropriate for energy analysis. For simulation, some factors of the window materials were taken into consideration including, four physical properties of the U-factor, solar heat gain coefficient, visible transmittance, and emissivity. The result was shown windows types 02 and 03 were the most optimized of window materials and led to 10% energy saving into the base model and the windows type 05 was high U-factor, results in a greater transfer in internal zones and led to high energy consumption.

scholarly journals Modelling Energy Consumption and Energy-Saving in High-Quality Olive Oil Decanter Centrifuge: Numerical Study and Experimental Validation

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2592 ◽  
Author(s):  
Antonia Tamborrino ◽  
Claudio Perone ◽  
Filippo Catalano ◽  
Giacomo Squeo ◽  
Francesco Caponio ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Olive Oil ◽  
Energy Saving ◽  
Numerical Study ◽  
Fluid Dynamic ◽  
Operating Conditions ◽  
Screw Conveyor ◽  
Physical Constraints ◽  
Machine Systems ◽  
Decanter Centrifuge

In this study, an energy consumption model of a decanter centrifuge was proposed, in particular for a technologically evolved machine equipped with an electromechanical recovery system. This model should be suitably coupled with an auto-adaptive controlling technique used to accurately manage the olive oil process. To achieve this goal, a solid physical and theoretical basis that simple to implement is required. To date there have only been limited scientific studies modelling energy consumption applied to the machines used in olive oil extraction processes. Therefore, the model was developed using fluid dynamic analysis and physical constraints to give it a solid basis. It was then simplified sufficiently for future implementation in automatic machine systems. The empirical model was validated through power measurements conducted in two harvesting seasons under varying operating conditions. The model estimates the power absorbed by the bowl and that produced and recovered by the screw, with high accuracy in each harvesting season. When considering the two harvesting seasons as a single season, the prediction accuracy remains considerable, despite a marginal increase in errors (correlation coefficient greater than 0.90). Finally, the model indicates that the screw conveyor speed is the most important parameter to achieve the desired energy recovery level, while the differential speed, which is a process parameter, has only a negligible impact on energy saving.

The Research of Measuring Approach and Energy Efficiency for Hadoop Periodic Jobs

2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Estimate ◽  
Cloud Platform ◽  
Periodic Tasks ◽  
Current Consumption ◽  
Reduce Energy Consumption

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.

Design and Implementation of Low Energy Wireless Network Nodes based on Hardware Compression Acceleration

2019 ◽  
Vol 12 ◽  
Author(s):  
Hui Yang ◽  
Anand Nayyar
Keyword(s):  
Energy Consumption ◽  
Data Compression ◽  
Energy Saving ◽  
Optimization Design ◽  
Hardware Acceleration ◽  
Transmission Efficiency ◽  
General Purpose ◽  
Storage Space ◽  
General Purpose Processor ◽  
Compression Time

: In the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. processing. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, The effect of energy saving can also be obtained by improving the hardware structure of node. In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor.On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

scholarly journals Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 81
Author(s):  
Rongjiang Ma ◽  
Shen Yang ◽  
Xianlin Wang ◽  
Xi-Cheng Wang ◽  
Ming Shan ◽  
...  
Keyword(s):  
Data Mining ◽  
Energy Consumption ◽  
Energy Saving ◽  
Air Conditioning ◽  
Storage System ◽  
Operation Mode ◽  
Systematic Method ◽  
Potential Analysis ◽  
Energy Saving Potential ◽  
Air Conditioning Systems

Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method through observation, test, and identification (OTI) has several drawbacks such as time consumption and narrow focus. To overcome these problems, this study proposed a systematic method for energy-saving diagnosis in air-conditioning systems based on data mining. The method mainly includes seven steps: (1) data collection, (2) data preprocessing, (3) recognition of variable-speed equipment, (4) recognition of system operation mode, (5) regression analysis of energy consumption data, (6) constraints analysis of system running, and (7) energy-saving potential analysis. A case study with a complicated air-conditioning system coupled with an ice storage system demonstrated the effectiveness of the proposed method. Compared with the traditional OTI method, the data-mining-based method can provide a more comprehensive analysis of energy-saving potential with less time cost, although it strongly relies on data quality in all steps and lacks flexibility for diagnosing specific equipment for energy-saving potential analysis. The results can deepen the understanding of the operating data characteristics of air-conditioning systems.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

scholarly journals Energy Saving Strategies and On-Site Power Generation in a University Building from a Tropical Climate

2021 ◽  
Vol 11 (2) ◽  
pp. 542
Author(s):  
Jaqueline Litardo ◽  
Massimo Palme ◽  
Rubén Hidalgo-León ◽  
Fernando Amoroso ◽  
Guillermo Soriano
Keyword(s):  
Power Generation ◽  
Energy Consumption ◽  
Energy Saving ◽  
Building Energy ◽  
Tropical Climate ◽  
Power Converter ◽  
Photovoltaic System ◽  
Base Line ◽  
Building Energy Consumption ◽  
Cooling Loads

This paper compares the potential for building energy saving of various passive and active strategies and on-site power generation through a grid-connected solar photovoltaic system (SPVS). The case study is a student welfare unit from a university campus located in the tropical climate (Aw) of Guayaquil, Ecuador. The proposed approach aims to identify the most effective energy saving strategy for building retrofit in this climate. For this purpose, we modeled the base line of the building and proposed energy saving scenarios that were evaluated independently. All building simulations were done in OpenStudio-EnergyPlus, while the on-site power generation was carried out using the Homer PRO software. Results indicated that the incorporation of daylighting controls accounted for the highest energy savings of around 20% and 14% in total building energy consumption, and cooling loads, respectively. Also, this strategy provided a reduction of about 35% and 43% in total building energy consumption, and cooling loads, respectively, when combined with triple low-e coating glazing and active measures. On the other hand, the total annual electric energy delivered by the SPVS (output power converter) was 66,590 kWh, from where 48,497 kWh was supplied to the building while the remaining electricity was injected into the grid.

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