scholarly journals Analysis to energy consumption characteristics and influencing factors of terminal building based on airport operating data

2021 ◽  
Vol 44 ◽  
pp. 101034
Author(s):  
Gu Xianliang ◽  
Xie Jingchao ◽  
Luo Zhiwen ◽  
Liu Jiaping
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Operating Data

scholarly journals Influencing Factors of Commercial Energy Consumption Intention of Rural Residents: Evidence from Rural Chengdu

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1010
Author(s):  
Aichun Jiang ◽  
Qian Zhong ◽  
Yan Wang ◽  
Yibin Ao ◽  
Chuan Chen
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Rural Areas ◽  
Structural Equation ◽  
Equation Modeling ◽  
Main Body ◽  
Rural Residents ◽  
Rural Construction ◽  
Commercial Energy ◽  
New Rural Construction

With rapid rural urbanization and new rural construction, the commercial energy consumption of rural residents shows a trend of rapid growth, and China’s rural areas are also faced with environmental challenges brought by the increase of commercial energy consumption. China’s commercial energy consumption behavior of rural residents has also undergone tremendous changes. However, scholars have neglected the research on rural residents’ commercial energy consumption intention from a micro perspective. Therefore, this study takes the 5 villages in Chengdu out of the 100 representative villages in the Sichuan province as examples. From the perspective of the head of a family of permanent rural residents, extended planned behavior theory, exploratory factor analysis, and structural equation modeling are used to explore the influencing factors of rural resident commercial energy consumption intention and their relationship. Findings show that subjective norm, perceived behavioral control (PBC), and habit significantly affect residents’ behavioral intention. Habits significantly influence subjective norms and PBC. Therefore, in the new rural construction, rural residents are the main body and participants of energy consumption. Local government departments should plan reasonably according to the needs and characteristics of residents, constantly improve commercial energy infrastructure, improve service level, and further strengthen farmers’ attitude and satisfaction toward commercial energy. Moreover, they should increase the publicity and education of commercial energy, advocate green housing, and promote energy saving consumption reduction, and sustainable development in new rural areas.

The Influencing Factors Analysis of Implementing Green Supply Chain Based on the Investigation Data in Shandong Province of China

2013 ◽  
Vol 671-674 ◽  
pp. 3049-3054
Author(s):  
Cao Qian ◽  
Xi Jian Quan ◽  
Yu Yan Wang
Keyword(s):  
Factor Analysis ◽  
Supply Chain ◽  
Energy Consumption ◽  
Product Design ◽  
Influencing Factors ◽  
Shandong Province ◽  
Raw Material ◽  
Green Supply Chain ◽  
Manufacturing Enterprises ◽  
Factors Analysis

On the basis of investigation and research, we firstly determined factors that impact manufacturing enterprises to implement green supply chain. Then, based on data of Parts of manufacturing enterprises in Shandong Province implementing green supply chain, the influencing factors of manufacturing enterprises implementing green supply chain is analyzed by factor analysis. The conclusion show that the influencing factors mainly concentrates in seven aspects that is raw material purchase, the enterprise internal management, the worn recycling, the product design, the enterprise prestige, the enterprise energy consumption, the reject processes.

scholarly journals Building energy consumption prediction and energy control of large-scale shopping malls based on a noncentralized self-adaptive energy management control system

2020 ◽  
pp. 014459872092073
Author(s):  
Bao Peng ◽  
Hui-Min Zou ◽  
Peng-Fei Bai ◽  
Yu-Yang Feng
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Air Conditioning ◽  
Large Scale ◽  
Commercial Buildings ◽  
Shopping Malls ◽  
Consumption Values ◽  
Central Air Conditioning ◽  
Energy Consumption Prediction ◽  
Consumption Prediction

Central air conditioning is the main energy-consuming equipment in modern large-scale commercial buildings. Its energy consumption generally accounts for more than 60% of the electricity load of an entire building, and there is a rising trend. Focusing on reducing central air conditioning energy consumption is a first priority to achieve energy savings in modern large-scale commercial buildings. To study the main influencing factors of central air conditioning energy consumption in large shopping malls, in-depth collection and analysis of energy consumption data of Shenzhen Tian-hong shopping mall were considered, and the impact of factors such as the basic composition of central air conditioning, time, and Shenzhen weather on the energy consumption of shopping malls was considered. The most representative Buji Rainbow store of the Rainbow Group is used as the research object. The influencing factors of central air conditioning on its energy consumption are divided into air conditioning pumps, host 1–1, host 1–2, host 2–1, and host 2–2. The power consumption of the freezer and the eight impact indicators of time and weather in Shenzhen were constructed using Pearson correlation coefficients and a long short-term memory neural network method to construct a regression model of the energy consumption prediction of the mall building. The average relative deviation between the predicted energy consumption values and the measured energy consumption values is less than 10%, which indicates that the main influencing factors selected in this paper can better explain the energy consumption of the mall, and the obtained energy consumption prediction model has high accuracy.

Analysis of energy consumption in the production of hot mix asphalt (batch mix plant)

2016 ◽  
Vol 43 (12) ◽  
pp. 1044-1051 ◽  
Author(s):  
Ivica Androjić ◽  
Zlata Dolaček Alduk
Keyword(s):  
Energy Consumption ◽  
Influencing Factors ◽  
Hot Mix Asphalt ◽  
Asphalt Mixture ◽  
Production Capacity ◽  
Daily Production ◽  
Mineral Mixture ◽  
The Republic ◽  
Production Period ◽  
Mixture Samples

This paper describes tests in which influencing factors that affect energy consumption in the rotary drum were monitored. The monitored influencing factors are moisture, delays in daily production, hourly production capacity, and temperature of produced hot mix asphalt (HMA). The tests include the production of 88 079 t of HMA of continuous and discontinuous gradation on a cyclic asphalt plant in the Republic of Croatia. In 2014, 182 production terms were monitored (155 observed), whereas the moisture content was tested using the same number of input mineral mixture samples. The temperature of the produced asphalt mixture was measured using approximately 67 753 samples during the entire production period. Delays in work and hourly production capacity were measured during production by recording the duration of working time and delays. The final result of this study is the creation of a regression model of the correlation between energy consumption and temperature of the asphalt mixture and the hourly capacity and moisture in the mineral aggregate.

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