The Ecological Strategies of Residential Buildings in Qinba Mountain Villages

2013 ◽  
Vol 368-370 ◽  
pp. 470-473
Author(s):  
Juan Xu ◽  
Jia Ping Liu
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Environmental Pollution ◽  
Residential Buildings ◽  
Standard Of Living ◽  
Living Standard ◽  
Ecological Strategies ◽  
Residential Energy ◽  
Level Of Economic Development ◽  
Mountain Villages

In recent years, a large number of new residential buildings of villages have a large number of problems which is the traditional residential energy consumption, and local environmental pollution. We Urgently need to explore the appropriate strategies about the level of economic development of the local eco-building technologies in Qinba mountain villages. It is want to improve villagers' living standard of living, to make residential buildings comfortable, healthy, energy-saving, and try to find a environmental protection of the local ecological road.

scholarly journals Regional Disparities and Transformation of Energy Consumption in China Based on a Hybrid Input-Output Analysis

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5287
Author(s):  
Yuehui Xia ◽  
Ting Zhang ◽  
Miaomiao Yu ◽  
Lingying Pan
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Rapid Development ◽  
Input Output ◽  
Output Analysis ◽  
Four Dimensions ◽  
Low Energy Consumption ◽  
Level Of Economic Development ◽  
Radar Map ◽  
Consumption Control

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings.

scholarly journals Dilution effect of the building area on energy intensity in urban residential buildings

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Jingxin Gao ◽  
Xiaoyang Zhong ◽  
Weiguang Cai ◽  
Hong Ren ◽  
Tengfei Huo ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Intensity ◽  
Energy Savings ◽  
Residential Buildings ◽  
Dilution Effect ◽  
Building Energy ◽  
Residential Energy ◽  
Stirpat Model ◽  
Building Area ◽  
Consumption Energy

Abstract Urban residential buildings make large contributions to energy consumption. Energy consumption per square meter is most widely used to measure energy efficiency in urban residential buildings. This study aims to explore whether it is an appropriate indicator. An extended STIRPAT model was used based on the survey data from 867 households. Here we present that building area per household has a dilution effect on energy consumption per square meter. Neglecting this dilution effect leads to a significant overestimation of the effectiveness of building energy savings standards. Further analysis suggests that the peak of energy consumption per square meter in China’s urban residential buildings occurred in 2012 when accounting for the dilution effect, which is 11 years later than it would have occurred without considering the dilution effect. Overall, overlooking the dilution effect may lead to misleading judgments of crucial energy-saving policy tools, as well as the ongoing trend of residential energy consumption in China.

Forecasting of Energy Consumption of Beijing's Residential Sector Based on System Dynamics Model

2013 ◽  
Vol 869-870 ◽  
pp. 537-540
Author(s):  
Hui Xie ◽  
Li Feng Wang ◽  
Wei Liang
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
System Dynamics ◽  
Feedback System ◽  
Living Standard ◽  
System Dynamics Model ◽  
Residential Energy ◽  
Dynamics Model ◽  
Residential Sector ◽  
Complete Dependence

Beijing is a major municipality/province of energy consumption, but poor in energy resources. The inherent and complete dependence on importing energy makes energy security extremely difficult, which draws more attention to the energy conservation in Beijing. With the improvement of people's living standard, the proportion of the residential energy consumption continuously increased. Residential energy saving became the key field of energy conservation and environmental protection. A great many factors of which the relations are complex affect the energy conservation. By introducing System Dynamics analysis, which has a unique advantage of analyzing the multiple and complex feedback system, this paper aims to analyze energy consumption of Beijings residential sector and finally comes to some suggestions towards governments policies.

scholarly journals A Novel Power-Driven Grey Model with Whale Optimization Algorithm and Its Application in Forecasting the Residential Energy Consumption in China

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-22 ◽  
Author(s):  
Peng Zhang ◽  
Xin Ma ◽  
Kun She
Keyword(s):  
Energy Consumption ◽  
Optimization Algorithm ◽  
Nonlinear Parameter ◽  
Whale Optimization Algorithm ◽  
Grey Model ◽  
Living Standard ◽  
Grey Prediction ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Whale Optimization

Along with the improvement of Chinese people’s living standard, the proportion of residential energy consumption in total energy consumption is rapidly increasing in China year by year. Accurately forecasting the residential energy consumption is conducive to making energy programming and supply plan for the administrative departments or energy companies. By improving the grey action quantity of traditional grey model with an exponential time term, a novel power-driven grey model is proposed to forecast energy consumption as reference data for decision makers. The nonlinear parameter of power-driven grey action quantity is a crucial factor to influence the prediction precision. To promote the prediction accuracy of the power-driven grey model, whale optimization algorithm is adopted to seek for the optimal value of the nonlinear parameter. Two validations on real-world datasets are conducted, and the results indicate that the power-driven grey model has significant advantages on the aspect of prediction performance compared with the other seven classical grey prediction methods. Finally, the power-driven grey model is applied in forecasting the total residential energy and the thermal energy consumption of China.

scholarly journals Factors for Bioeconomy Development in EU Countries with Different Overall Levels of Economic Development

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3182
Author(s):  
Andrzej Czyżewski ◽  
Andrzej Grzyb ◽  
Anna Matuszczak ◽  
Mariola Michałowska
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Agricultural Production ◽  
National Income ◽  
Developed Countries ◽  
Renewable Energy Consumption ◽  
Eu Countries ◽  
Level Of Economic Development ◽  
High Share ◽  
Different Levels

The aim of this article is to indicate the rationale for the development of the bioeconomy in selected EU countries depending on their overall level of economic development. The research was based on four highly developed countries, i.e., Germany, France, Finland and Denmark, and four medium-developed countries, i.e., Poland, Hungary, Czech Republic, and Slovakia for the period 2001–2018. Renewable energy consumption, biomass and agricultural production were analysed as determinants of the bioeconomy development. The question was also answered whether differences in terms of measures determining the level of bioeconomy development between countries with different levels of economic development during the studied period are decreasing or increasing, using sigma (σ)-convergence coefficients. It is shown that the development of the bioeconomy of the studied countries is related to their level of economic development. In the middle economically developed countries, real opportunities for the development of the bioeconomy are noted, through a high share of agriculture in national income; and in highly developed countries—high spending on research and development and the growth of eco-innovation, which contributes to maintaining a development advantage between these groups of countries.

PRIORITIZING OCCUPANTS UNDERSTANDING LEVEL ON RESIDENTIAL BUILDING ENERGY CONSUMPTION

2015 ◽  
Vol 77 (16) ◽  
Author(s):  
Jibrin Hassan Suleiman ◽  
Ali Keyvanfar ◽  
Rosli Mohamad Zin ◽  
Saeed Balubaid ◽  
Shaiful Amri Mansur
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Energy Use ◽  
Negative Impact ◽  
Residential Buildings ◽  
Residential Building ◽  
Building Energy ◽  
Living Standard ◽  
Survey Form ◽  
Home Appliance

The building sector is widely known for its greenhouse gas and carbon emission which is very significant to the global warming as observed in recent years. Many research works highlighted that buildings has a negative impact on the society as it consumes up to 80% of the total energy used during operation stage. In Malaysia, electricity energy consumption in buildings is 63,354GWh out of the total 116,353GWh of total energy consumed in the country in the year 2012. This paper consider the understanding level of the residential owners in their building energy usage at their various residential buildings. Energy use by household varies widely, this is due to the living standard of a country, type of buildings and climate condition of the region. The study is based on the tips and guides to energy efficiency at home of the Sustainable Energy Development Authority (SEDA) Malaysia. Data was collected through a questionnaire survey form and was analyzed using regression analysis, the results indicates that the occupants have little or no proper understanding of Air-condition, Home appliance and Lighting appliances.

scholarly journals A Study on Household Sector Energy Consumption of Rural and Urban Areas in Virudhunagar District of Tamil Nadu

2019 ◽  
Vol 8 (1) ◽  
pp. 21-31
Author(s):  
K Ramabose ◽  
S Ganesan
Keyword(s):  
Energy Consumption ◽  
Urban Areas ◽  
Tamil Nadu ◽  
Standard Of Living ◽  
Living Standard ◽  
Human Beings ◽  
Basic Requirement ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Universal Measure

The word “Energy” is derived from the Greek word ‘energeia’, which means ‘in work’. It is the power or capacity to do work. Energy has become an important and one of the basic infrastructures for human development and economic growth of a country. Energy is the universal measure of all kinds of work and its consumption has been increasing worldwide. It has become a basic requirement of today’s life. In fact, it is the backbone of present day civilization. Thus, with an increase in the living standard of human beings, the energy consumption is also accelerated. There is a strong correlation between standard of living and energy consumption. Any physical activity in this world, whether carried out by human beings or by nature, is caused due to the flow of energy in one form or the other? Energy is required to do any kind of work. The work output depends on the energy input. The capacity to do work depends upon the amount of energy one can control and utilise.

scholarly journals A brief analysis of the development of green building technology in Shanxi—take residential buildings as an example

2018 ◽  
Vol 53 ◽  
pp. 03019
Author(s):  
Meng Jinlan ◽  
Gao Yubo
Keyword(s):  
Energy Consumption ◽  
Environmental Factors ◽  
Environmental Pollution ◽  
Residential Buildings ◽  
Green Building ◽  
The State ◽  
Building Technology ◽  
Energy Consumption Analysis ◽  
Resource Shortage

Facing the two problems of environmental pollution and resource shortage, human realizes the harm brought by the economic deformity development to nature, and green building arises at the historic moment. In order to promote the application of green building technology in the market, this paper first understand the state of development of green building in domestic, and then combine the environmental factors and energy consumption analysis in Shanxi area, take residential buildings as the object, and analyze the development and application of green building technology briefly in Shanxi area.

scholarly journals Artificial Neural Network-Based Residential Energy Consumption Prediction Models Considering Residential Building Information and User Features in South Korea

2019 ◽  
Vol 12 (1) ◽  
pp. 109 ◽  
Author(s):  
Mansu Kim ◽  
Sungwon Jung ◽  
Joo-won Kang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Regression Analysis ◽  
Energy Consumption ◽  
Prediction Models ◽  
Residential Buildings ◽  
Residential Energy ◽  
Artificial Neural ◽  
Energy Consumption Prediction ◽  
Consumption Prediction

When researching the energy consumption of residential buildings, it is becoming increasingly important to consider how residents use energy. With the advancement of computing power and data analysis techniques, it is now possible to analyze user information using big data techniques. Here, we endeavored to integrate user information with the physical characteristics of residential buildings to analyze how these elements impact energy consumption. Regression analysis was conducted to accurately identify the impact of each element on energy consumption. It was found that six elements were influential in all seasons: the number of exterior walls, housing direction, housing area, number of years occupied, number of household members, and the occupation of the household head. The elements that had an impact in each period were then derived. Based on the results of the regression analysis, input variables for the training of an artificial neural network (ANN) model were selected for each period, and residential energy consumption prediction models were implemented based on actual consumption. The elements identified as those affecting energy consumption, through regression analysis, can be used for implementing prediction models with advanced forms. This study is significant in that we derived influential elements from an integrative perspective.

scholarly journals Evaluating the Age-Energy Consumption Profile in Residential Buildings

2018 ◽  
Author(s):  
Hossein Estiri ◽  
Emilio Zagheni
Keyword(s):  
Energy Consumption ◽  
Life Course ◽  
Energy Demand ◽  
Population Aging ◽  
Residential Buildings ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Residential Energy Consumption Survey ◽  
The Life Course ◽  
Consumption Profile

Age is an important proxy for many life course trajectories. The relationship between energy consumption and age is complex and understudied. We evaluated the existence and determinants of an age-energy consumption profile in the U.S. residential sector, using microdata from four waves of the Residential Energy Consumption Survey (RECS) in 1987, 1990, 2005, and 2009. We constructed pseudo cohorts from Bayesian generalized linear model estimates to draw micro-profiles for energy consumption across the life course. Overall, we found that residential energy consumption increases over the life course. Much of the increase in energy consumption is due to housing size. Variations in the age-energy consumption micro-profiles can be described by concave and convex functions. In contrast to previous research that suggested that population aging would reduce energy demand, our results indicate that changing population age structure could amplify residential energy demand.

Sign in / Sign up

Export Citation Format

Share Document