How does income level impact residential-building heating energy consumption? Micro-level evidence from household surveys

2021 ◽  
Vol 91 ◽  
pp. 106659
Author(s):  
Tengfei Huo ◽  
Weiguang Cai ◽  
Weishi Zhang ◽  
Jing Wang ◽  
Ya Zhao ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Residential Building ◽  
Income Level ◽  
Household Surveys ◽  
Micro Level ◽  
Heating Energy Consumption

Simulation of Residential Energy Consumption Based on Software of DeST

2013 ◽  
Vol 448-453 ◽  
pp. 1269-1272
Author(s):  
Zhao Chen ◽  
Li Bai ◽  
Feng Li
Keyword(s):  
Energy Consumption ◽  
System Design ◽  
Energy Saving ◽  
Residential Building ◽  
Heating System ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Heating Energy Consumption ◽  
Uneven Heating ◽  
The City

In this paper, the software of DeST was used to simulate the heating energy consumption by the year of a typical energy-saving residential building in the city of Changchun. Comparing the energy consumption of the top and bottom,the middle room and the edges rooms ,we get the reasons for the uneven heating and put forward the corresponding solutions, which provide the reference for heating system design.

scholarly journals The Effect of Fixed External Shading Devices on Daylighting and Thermal Comfort in Residential Building

2021 ◽  
Vol 8 (2) ◽  
pp. 165-180
Author(s):  
Aliakbar Heidari ◽  
◽  
Malihe Taghipour ◽  
Zahra Yarmahmoodi ◽  
◽  
...  
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Residential Building ◽  
Building Energy ◽  
Maximum Energy ◽  
Heating And Cooling ◽  
Hot Climate ◽  
Lighting Energy ◽  
Shading Devices ◽  
Heating Energy Consumption

Building shading devices can improve the thermal comfort in indoor environment, and also reduce cooling and heating energy consumption in dry and hot climate. This study proposes the different kind of window’s fixed shading devices for energy consumption under near-extreme summer and winter conditions by conducting residential building energy simulations in Shiraz climate. Which fixed shading devices optimal configurations that give maximum energy consumption can be used in Shiraz climate. The study was based on modeling-simulation experiments where Ecotect models resented the actual building energy with and without shading devices to reducing heating and cooling load and peak consumption. The results obtained confirmed the accuracy of the model and the suitability of (horizontal, eggcrate and geometrical) of shading devices in reducing the solar gains in summer with reduced blocking of solar radiation in winter. In all cases it has been proven that excessive obstruction may yield an excessive reduction in a range of illuminances between 500 and 2000 lux, increasing lighting energy consumption. At the end results showed that horizontal, geometrical and eggcrate have the best function according to reduce energy and have enough day lighting in the zones in shiraz climate.

scholarly journals Ensemble Prediction Approach Based on Learning to Statistical Model for Efficient Building Energy Consumption Management

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 405
Author(s):  
Anam Nawaz Khan ◽  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Do-Hyeun Kim
Keyword(s):  
Energy Consumption ◽  
Statistical Model ◽  
Residential Buildings ◽  
Residential Building ◽  
Experimental Results ◽  
Consumption Patterns ◽  
Ensemble Prediction ◽  
Short Term ◽  
Term Energy ◽  
Prediction Approach

With the development of modern power systems (smart grid), energy consumption prediction becomes an essential aspect of resource planning and operations. In the last few decades, industrial and commercial buildings have thoroughly been investigated for consumption patterns. However, due to the unavailability of data, the residential buildings could not get much attention. During the last few years, many solutions have been devised for predicting electric consumption; however, it remains a challenging task due to the dynamic nature of residential consumption patterns. Therefore, a more robust solution is required to improve the model performance and achieve a better prediction accuracy. This paper presents an ensemble approach based on learning to a statistical model to predict the short-term energy consumption of a multifamily residential building. Our proposed approach utilizes Long Short-Term Memory (LSTM) and Kalman Filter (KF) to build an ensemble prediction model to predict short term energy demands of multifamily residential buildings. The proposed approach uses real energy data acquired from the multifamily residential building, South Korea. Different statistical measures are used, such as mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and R2 score, to evaluate the performance of the proposed approach and compare it with existing models. The experimental results reveal that the proposed approach predicts accurately and outperforms the existing models. Furthermore, a comparative analysis is performed to evaluate and compare the proposed model with conventional machine learning models. The experimental results show the effectiveness and significance of the proposed approach compared to existing energy prediction models. The proposed approach will support energy management to effectively plan and manage the energy supply and demands of multifamily residential buildings.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals TOPOI RESOURCES: Quantification and Assessment of Global Warming Potential and Land-Uptake of Residential Buildings in Settlement Types along the Urban–Rural Gradient—Opportunities for Sustainable Development

2021 ◽  
Vol 13 (8) ◽  
pp. 4099
Author(s):  
Ann-Kristin Mühlbach ◽  
Olaf Mumm ◽  
Ryan Zeringue ◽  
Oskars Redbergs ◽  
Elisabeth Endres ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Global Warming ◽  
Energy Consumption ◽  
Global Warming Potential ◽  
Residential Buildings ◽  
Residential Building ◽  
Negative Effects ◽  
Building Stock ◽  
Residential Building Stock ◽  
Urban Rural

The METAPOLIS as the polycentric network of urban–rural settlement is undergoing constant transformation and urbanization processes. In particular, the associated imbalance of the shrinkage and growth of different settlement types in relative geographical proximity causes negative effects, such as urban sprawl and the divergence of urban–rural lifestyles with their related resource, land and energy consumption. Implicitly related to these developments, national and global sustainable development goals for the building sector lead to the question of how a region can be assessed without detailed research and surveys to identify critical areas with high potential for sustainable development. In this study, the TOPOI method is used. It classifies settlement units and their interconnections along the urban–rural gradient, in order to quantify and assess the land-uptake and global warming potential driven by residential developments. Applying standard planning parameters in combination with key data from a comprehensive life cycle assessment of the residential building stock, a detailed understanding of different settlement types and their associated resource and energy consumption is achieved.

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