scholarly journals Residential Energy Conservation using Efficient Home Appliances

2020 ◽  
Vol 9 (3) ◽  
pp. 3457-3465
Keyword(s):  
Energy Consumption ◽  
Cost Saving ◽  
Natural Environment ◽  
Energy Demand ◽  
Residential Energy ◽  
Global Energy ◽  
Residential Sector ◽  
Modern House ◽  
Reducing Energy

Significant hike in global energy demand has laid extra pressure on energy generation plants and natural environment as well. Therefore, methods of reducing the global energy demand are being extensively explored worldwide. In this paper, we have discussed ways of reducing energy consumption in Residential sector. We have taken eight major appliances being used in homes and compared them on the basis of annual energy consumed and cost saving by taking suitable assumptions like running hours, seasons of operation, etc. Finally, Case study of a modern house in Aligarh district of UP is studied for analysing the percentage consumption of each appliance being discussed. The results show that appliances like light bulbs, ceiling fans and refrigerators have the highest potential of energy as well as cost saving by improving their efficiency. Further, by switching all the appliances from conventional to the most efficient models resulted in energy and cost saving of about 37% in the house taken for case study.

scholarly journals Residential Energy-Related CO2 Emissions in China’s Less Developed Regions: A Case Study of Jiangxi

2020 ◽  
Vol 12 (5) ◽  
pp. 2000 ◽  
Author(s):  
Yong Yang ◽  
Junsong Jia ◽  
Chundi Chen
Keyword(s):  
Co2 Emissions ◽  
Energy Demand ◽  
Dominant Role ◽  
Energy Structure ◽  
Residential Energy ◽  
Rural Regions ◽  
Residential Sector ◽  
Per Capita ◽  
The Difference

The residential sector is the second-largest consumer of energy in China. However, little attention has been paid to reducing the residential CO2 emissions of China’s less developed or undeveloped regions. Taking Jiangxi as a case study, this paper thus aims at fully analyzing the difference of the residential energy-related CO2 emissions between urban and rural regions based on the Log-Mean Divisia Index (LMDI) and Tapio decoupling model. The main results are showed as follows: (1) Since 2008, residential energy-related CO2 emissions have increased rapidly in both urban and rural Jiangxi. From 2000 to 2017, the residential energy-related CO2 emissions per capita in rural regions rapidly increased and exceeded that in urban regions after 2015. Furthermore, the residential energy structures had become multiple in both urban and rural regions, but rural regions still had room to optimize its energy structure. (2) Over the study period, consumption expenditure per capita played the dominant role in increasing the residential energy-related CO2 emissions in both urban and rural regions, followed by energy demand and energy structure. Energy price had the most important effect on decreasing the urban and rural residential energy-related CO2 emissions, followed by the carbon emission coefficient. However, urbanization increased the urban residential energy-related CO2 emissions but decreased the CO2 emissions in rural regions. Population made marginal and the most stable contribution to increase the residential energy-related CO2 emissions both in urban and rural regions. (3) Overall, the decoupling status showed the weak decoupling (0.1) and expansive negative decoupling (1.21) in urban and rural regions, respectively.

scholarly journals Cooling Degree Models and Future Energy Demand in the Residential Sector. A Seven-Country Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2987
Author(s):  
Raúl Castaño-Rosa ◽  
Roberto Barrella ◽  
Carmen Sánchez-Guevara ◽  
Ricardo Barbosa ◽  
Ioanna Kyprianou ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Demand ◽  
Energy Performance ◽  
Low Energy ◽  
Extreme Weather Events ◽  
Building Stock ◽  
Residential Sector ◽  
Adaptive Thermal Comfort

The intensity and duration of hot weather and the number of extreme weather events, such as heatwaves, are increasing, leading to a growing need for space cooling energy demand. Together with the building stock’s low energy performance, this phenomenon may also increase households’ energy consumption. On the other hand, the low level of ownership of cooling equipment can cause low energy consumption, leading to a lack of indoor thermal comfort and several health-related problems, yet increasing the risk of energy poverty in summer. Understanding future temperature variations and the associated impacts on building cooling demand will allow mitigating future issues related to a warmer climate. In this respect, this paper analyses the effects of change in temperatures in the residential sector cooling demand in 2050 for a case study of nineteen cities across seven countries: Cyprus, Finland, Greece, Israel, Portugal, Slovakia, and Spain, by estimating cooling degree days and hours (CDD and CDH). CDD and CDH are calculated using both fixed and adaptive thermal comfort temperature thresholds for 2020 and 2050, understanding their strengths and weaknesses to assess the effects of warmer temperatures. Results suggest a noticeable average increase in CDD and CDH values, up to double, by using both thresholds for 2050, with a particular interest in northern countries where structural modifications in the building stock and occupants’ behavior should be anticipated. Furthermore, the use of the adaptive thermal comfort threshold shows that the projected temperature increases for 2050 might affect people’s capability to adapt their comfort band (i.e., indoor habitability) as temperatures would be higher than the maximum admissible values for people’s comfort and health.

Energy Consumption Pattern of Residential Buildings: Case Study of Residential Area in Batu Pahat, Johor

2020 ◽  
Vol 12 (9) ◽  
Author(s):  
Junaidah Jailani ◽  
◽  
Norsyalifa Mohamad ◽  
Muhammad Amirul Omar ◽  
Hauashdh Ali ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Residential Area ◽  
Consumption Pattern ◽  
Air Conditioners ◽  
Residential Sector ◽  
Waste Energy ◽  
Main Factor ◽  
Energy Consumption Pattern

According to the National Energy Balance report released by the Energy Commission of Malaysia in 2016, the residential sector uses 21.6% of the total energy in Malaysia. Residents waste energy through inefficient energy consumption and a lack of awareness. Building occupants are considered the main factor that influences energy consumption in buildings, and to change energy consumption on an overall scale, it is crucial to change individual behaviour. Therefore, this study focused on analysing the energy consumption pattern and the behaviour of consumers towards energy consumption in their homes in the residential area of Batu Pahat, Johor. A self-administrated questionnaire approach was employed in this study. The findings of this study showed that the excessive use of air conditioners was a significant factor in the increasing electricity bills of homeowners as well as the inefficient use of electrical appliances. Also, this study determined the effect of awareness on consumer behaviour. This study recommends ways to help minimise energy consumption in the residential area.

Energy demand projections and relevance of income dynamics in Gauteng’s residential sector

2011 ◽  
Vol 22 (4) ◽  
pp. 31-47 ◽  
Author(s):  
Mamahloko Senatla
Keyword(s):  
Energy Consumption ◽  
Low Income ◽  
Energy Demand ◽  
Electricity Consumption ◽  
Planning System ◽  
Strategy Development ◽  
Computing Power ◽  
Residential Sector ◽  
Energy Modelling ◽  
Main Driver

Energy modelling serves as a crucial tool for informing both energy policy and strategy development. But the modelling process is faced with both sectoral energy data and structural challenges. Among all the sectors, the residential sector usually presents a huge challenge to the modelling profession due to the dynamic nature of the sector. The challenge is brought by the fact that each an every household in a region may have different energy consumption characteristics and the computing power of the available models cannot incorporate all the details of individual household characteristics. Even if there was enough computing power within the models, energy consumption is collected through surveys and as a result only a sample of a region is captured. These challenges have forced energy modellers to categorise households that have similar characteristics. Different researchers choose different methods for categorising the households. Some researchers choose to categorise households by location and climate, others choose housing types while others choose quintiles. Currently, there is no consensus on which categorisation method takes precedence over others. In these myriad ways of categorising households, the determining factor employed in each method is what is assumed to be the driver of energy demand in that particular area of study. Many researchers acknowledge that households’ income, preferences and access to certain fuels determine how households use energy. Although many researchers recognise that income is the main driver of energy demand in the residential sector, there has been no energy modelling study that has tried to categorise households by income in South Africa. This paper chose to categorise households by income because income is taken to be the main driver of energy demand in the urban residential sector. Gauteng province was chosen as a case study area for this paper. The Long-range Energy Alternatives Planning System (LEAP) is used as a tool for such analysis. This paper will further reveal how the dynamics of differing income across the residential sector affects total energy demand in the long run. The households in Gauteng are classified into three income categories – high, middle and low income households. In addition to different income categories, the paper further investigates the energy demand of Gauteng’s residential sector under three economic scenarios with five energy demand scenarios. The three economic scenarios are first economic scenario (ECO1), second economic scenario (ECO2) and third economic scenario (ECO3). The most distinguishing factor between these economic scenarios is the mobility of households from one income band to the next.The model results show that electricity demand will be high in all the three economic scenarios. The reason for such high electrical energy demand in all the economic scenarios compared to other fuels is due to the fact that among all the provinces, Gauteng households have one of the highest electricity consumption profiles. ECO2 showed the highest energy demand in all the five energy demand scenarios. This is due to the fact that the share of high income households in ECO2 was very high, compared to the other two economic scenarios. The favourable energy demand scenarios will be the Energy Efficiency and MEPS scenarios due to their ability to reduce more energy demand than other scenarios in all the three economic scenarios.

Exploration of the Development of Schemes to Achieve a District-Aggregate Energy-Intensity Goal - Taking the 12th Five-Year Period Energy Intensity Goal of Daxing District, Beijing as a Study Case

2014 ◽  
Vol 962-965 ◽  
pp. 1455-1460
Author(s):  
Xiang Qian Li ◽  
Li Juan Yang ◽  
Ling Ling Chen
Keyword(s):  
Energy Consumption ◽  
Gross Domestic Product ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Losses ◽  
Residential Energy ◽  
Initial Value ◽  
Study Case ◽  
Per Capita

The paper explored how to develop schemes to achieve a district’s energy consumption per gross domestic product (ECPGDP) target. It first analysed the available measures regarding the reduction of ECPGDP. These measures include optimising the industrial structure, reducing the energy intensity of different industries, reducing the per capita residential energy consumption, and reducing the energy losses. Next, the procedure and methods of developing schemes to achieve the target ECPGDP were proposed. The procedure contains five steps: determine the target ECPGDP, predicting the initial value of the ECPGDP, analysing the availability of different measures of reducing the ECPGDP, forming the schemes of achieving the target, and summarising the proposed schemes. Finally, the paper considered the 12th Five-Year period ECPGDP target of Daxing District, Beijing as a study case. In the case study, four quantitative schemes to achieve the target ECPGDP were considered.

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.

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