Optimizing energy consumption patterns of smart home based on Sine Cosine Algorithm

This study examines the impact of economic globalization on the patterns of energy consumption for 24 Organisation for Economic Co-operation and Development (OECD) economies from 1995 to 2015. We employ Westerlund cointegration, which shows a long-run association between economic globalization and energy consumption patterns. Furthermore, cross-sectional autoregressive distributed lag models (CS-ARDL) results explain the short-run and long-run relationship between the series. The results further explain that economic globalization reduces oil and coal consumption while accelerating gas consumption in OECD economies. We additionally employ the Eberhardt augmented mean group test to verify consistency with CS-ARDL results. The empirical evidence of this study suggests that OECD economies’ policymakers should prioritize economic globalization in framing policies related to energy consumption. Furthermore, allocating funds for better technology related to high polluting fuels should be one of the crucial considerations arising from this study. Finally, we recommend economic globalization as an important indicator to address the issues related to OECD economics’ environmental and ecological footprints.

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Climate Change as a Driving Force on Urban Energy Consumption Patterns

Encyclopedia of Information Science and Technology, Fourth Edition ◽

10.4018/978-1-5225-2255-3.ch680 ◽

2018 ◽

pp. 7815-7830

Author(s):

Mostafa Jafari ◽

Pete Smith

Keyword(s):

Energy Consumption ◽

Pearson Correlation ◽

Consumption Patterns ◽

Time Slice ◽

Degree Days ◽

Urban Energy ◽

Cooling Degree Days ◽

Energy Consumption Patterns ◽

Annual Total ◽

Heating Degree Days

Heating Degree Days (HDD), in cases where temperatures are below 18°C, and Cooling Degree Days (CDD), in cases where temperatures are above 21°C, were used as energy consumption indices. During the last half century, mean annual temperatures have increased and as a consequence, CDD in the warm season have increased sharply. In the same time slice, HDD, even in the cool and cold season have declined steadily. The number of monthly and annual total HDD (mean= 1556) are much higher than CDD (mean=400) in the case study area and annual total HDD and CDD have a negative correlation (Pearson correlation = - 0.493; p = 0.001). The deceasing rate of HDD is limited and steady (R2= 0.062, p=0.099), but the increasing rate of CDD in the same time slice is sharp (R2=0.427, p=0.813). This shows that energy consumption patterns have increased sharply, and with available projection scenarios, is projected to increase more rapidly, leading to higher energy costs.

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Impact of Urbanization on Energy Consumption Patterns

Energy Services for the Urban Poor in Africa ◽

10.5040/9781350219915.ch-001 ◽

2004 ◽

Author(s):

Stephen Karekezi ◽

Lugard Majoro

Keyword(s):

Energy Consumption ◽

Consumption Patterns ◽

Energy Consumption Patterns ◽

Impact Of Urbanization

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Changing of energy consumption patterns from rural households to urban households in China: An example from Shaanxi Province, China

Renewable and Sustainable Energy Reviews ◽

10.1016/j.rser.2007.03.002 ◽

2008 ◽

Vol 12 (6) ◽

pp. 1667-1680 ◽

Cited By ~ 74

Author(s):

Jing Cai ◽

Zhigang Jiang

Keyword(s):

Energy Consumption ◽

Rural Households ◽

Consumption Patterns ◽

Shaanxi Province ◽

Urban Households ◽

Energy Consumption Patterns

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Analysis of Electric Energy Consumption Patterns: A Case Study of a Real Life Office Building

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.330.158 ◽

2013 ◽

Vol 330 ◽

pp. 158-162 ◽

Cited By ~ 1

Author(s):

Jin Soo Han ◽

Youn Kwae Jeong ◽

Il Woo Lee

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Real Life ◽

Electric Energy ◽

Consumption Patterns ◽

Office Building ◽

Commercial Building ◽

Total Energy Consumption ◽

Electric Energy Consumption ◽

Energy Consumption Patterns

Electric energy consumption shares a great portion of commercial building energy. Electric energy saving is essential to reduce total energy consumption in commercial buildings. To draw energy saving methods, it is necessary to monitor real energy consumption patterns and analyze the results. We monitor the lighting and non-lighting energy consumption of eleven zones in a real working office building every fifteen minutes during eleven months. We observe and analyze the monthly and daily energy consumption patterns of all zones and draw several feasible energy saving methods. Moreover, the lighting and occupancy are monitored simultaneously in detail to investigate the unnecessary energy consumption. It shows the possibility of a great amount of energy saving. Because we analyze the energy consumption patterns in all zones, the drawn energy saving methods are applicable to the current building with some added infrastructure and expandable to other similar office buildings. Our result is expected to contribute to reducing the energy consumption in buildings.

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