scholarly journals Energy saving performance optimization and regional adaptability of prefabricated buildings with PCM in different climates

2021 ◽  
pp. 101164
Author(s):  
Jiaojiao Jia ◽  
Bo Liu ◽  
Lingyong Ma ◽  
Hui Wang ◽  
Dong Li ◽  
...  
Keyword(s):  
Energy Saving ◽  
Performance Optimization ◽  
Different Climates

Optimisation of Thermochromic Thin Films on Glass; Design of Intelligent Windows

2010 ◽  
Vol 75 ◽  
pp. 79-90 ◽  
Author(s):  
Manfredi Saeli ◽  
Clara Piccirillo ◽  
Ivan P. Parkin ◽  
Russell Binions ◽  
Ian Ridley
Keyword(s):  
Thin Films ◽  
Energy Consumption ◽  
Visible Light ◽  
Energy Saving ◽  
Building Simulation ◽  
Heating Season ◽  
Reduce Energy Consumption ◽  
Saving Effect ◽  
Different Climates

Theoretically thermochromic glazing has the potential to reduce energy consumption in buildings by allowing visible light for day lighting, reducing unwanted solar gain during the cooling season, while allowing useful solar gain in the heating season. In this study building simulation is used to predict the savings made by novel thermochromic glazing coatings compared to standard products, for locations with different climates. The results suggest that thermochromic glazing can have a significant energy saving effect compared to current approaches.

scholarly journals Energy-Efficiency Improvement and Processing Performance Optimization of Forging Hydraulic Presses Based on an Energy-Saving Buffer System

2020 ◽  
Vol 10 (17) ◽  
pp. 6020
Author(s):  
Xiaopeng Yan ◽  
Baijin Chen
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Power Unit ◽  
Performance Optimization ◽  
Cooling System ◽  
Hydraulic Press ◽  
Buffer System ◽  
Hydraulic Actuator ◽  
Increase Energy Efficiency ◽  
Energy Efficiency Improvement

This paper proposes an energy-saving system based on a prefill system and a buffer system to improve the energy efficiency and the processing performance of hydraulic presses. Saving energy by integrating such systems into the cooling system of a hydraulic press has not been previously reported. A prefill system, powered by the power unit of the cooling system, is used to supply power simultaneously with the traditional power unit during the pressurization stage, thus reducing the usage of pumps and installed power of the hydraulic press. In contrast to the traditional prefill system, the proposed energy-saving system is controlled by a servo valve to adjust flow according to the load profile. In addition, a buffer system is employed to the cooling system to absorb the hydraulic shock generated at the unloading stage, store those shares of hydraulic energy as a recovery accumulator, and then release this energy to power the prefill system and the hydraulic actuator in the subsequent productive process. Finally, through a series of comparative experiments, it was preliminarily validated that the proposed system could reduce the installed power and pressure shock by up to 22.85% and 41%, respectively, increase energy efficiency by up to 26.71%, and provide the same processing characteristics and properties as the traditional hydraulic press.

scholarly journals Optimal Switching and Load Distribution Strategy for Energy Minimization and Performance Optimization of Cloud Data Center

2021 ◽  
Author(s):  
Poobalan A ◽  
◽  
Sangeetha S ◽  
Shanthakumar P ◽  
◽  
...  
Keyword(s):  
Energy Saving ◽  
Performance Optimization ◽  
Data Center ◽  
Load Distribution ◽  
Data Centers ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Power Load ◽  
Cloud Data Centers ◽  
Manta Ray

Cloud computing is a promising computing technology utilized in every stage of the business. The cloud offers different services to cloud users from anytime to anywhere, and it is attained with different parameters, like load optimization, resource optimization. Due to the increase in data center, energy consumption has become a major issue in green data centers. The majority of data centers are function using peak load with huge scales. Thus, it is essential for carrying out energy saving in cloud data centers. This paper designed an energy-saving method using fat tree. The proposed techniques optimize the load at different zones of data center and user in the cloud platform. Here, the distribution of load in cloud data centers is performed using Taylor-based Manta Ray Foraging Optimization (Taylor-MRFO), which is an integration of Manta Ray Foraging Optimization (MRFO) and Taylor series. The method utilized different objectives that involve power, load, latency, and bandwidth. With the load distribution, the switching of cloud data center to the desired mode is performed using Actor critic neural network (ACNN). Thus, the dual strategy leads to performance optimization in cloud infrastructure and also in consolidating parallel workload in data centers more effectively. The proposed Taylor-MRFO+ACNN outperformed other methods with minimal energy of 0.553, minimal load of 0.363, and minimal fitness of 0.437, respectively.

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.

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

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