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Impact of household transitions on domestic energy consumption and its applicability to urban energy planning 被引量:3
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作者 Benachir MEDJDOUB Moulay Larbi CHALAL 《Frontiers of Engineering Management》 2017年第2期171-183,共13页
The household sector consumes roughly 30% of Earth's energy resources and emits approximately 17% of its carbon dioxide. As such, developing appropriate policies to reduce the CO_2 emissions, which are associated ... The household sector consumes roughly 30% of Earth's energy resources and emits approximately 17% of its carbon dioxide. As such, developing appropriate policies to reduce the CO_2 emissions, which are associated with the world's rapidly growing urban population, is a high priority. This, in turn, will enable the creation of cities that respect the natural environment and the well-being of future generations. However, most of the existing expertise focuses on enhancing the thermal quality of buildings through building physics while few studies address the social and behavioral aspects. In fact, focusing on these aspects should be more prominent, as they cause between 4% and 30% of variation in domestic energy consumption.Premised on that, the aim of this study was to investigate the effect in the context of the UK of household transitions on household energy consumption patterns. To achieve this, we applied statistical procedures(e.g., logistic regression) to official panel survey data comprising more than 5500 households in the UK tracked annually over the course of 18 years. This helped in predicting future transition patterns for different household types for the next 10 to 15 years. Furthermore, it enabled us to study the relationship between the predicted patterns and the household energy usage for both gas and electricity. The findings indicate that the life cycle transitions of a household significantly influence its domestic energy usage. However, this effect is mostly positive in direction and weak in magnitude. Finally, we present our developed urban energy model "Evo Energy" to demonstrate the importance of incorporating such a concept in energy forecasting for effective sustainable energy decision-making. 展开更多
关键词 urban energy planning household transitions smart cities energy forecasting household projection serious gaming
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Big Data to support sustainable urban energy planning:The EvoEnergy project 被引量:1
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作者 Moulay Larbi CHALAL Benachir MEDJDOUB +1 位作者 Nacer BEZAI Raid SHRAHILY 《Frontiers of Engineering Management》 2020年第2期287-300,共14页
Energy sustainability is a complex problem that needs to be tackled holistically by equally addressing other aspects such as socio-economic to meet the strict CO emission targets.This paper builds upon our previous wo... Energy sustainability is a complex problem that needs to be tackled holistically by equally addressing other aspects such as socio-economic to meet the strict CO emission targets.This paper builds upon our previous work on the effect of household transition on residential energy consumption where we developed a 3D urban energy prediction system(EvoEnergy)using the old UK panel data survey,namely,the British household panel data survey(BHPS).In particular,the aim of the present study is to examine the validity and reliability of EvoEnergy under the new UK household longitudinal study(UKHLS)launched in 2009.To achieve this aim,the household transition and energy prediction modules of EvoEnergy have been tested under both data sets using various statistical techniques such as Chow test.The analysis of the results advised that EvoEnergy remains a reliable prediction system and had a good prediction accuracy(MAPE;5%)when compared to actual energy performance certificate data.From this premise,we recommend researchers,who are working on data-driven energy consumption forecasting,to consider merging the BHPS and UKHLS data sets.This will,in turn,enable them to capture the bigger picture of different energy phenomena such as fuel poverty;consequently,anticipate problems with policy prior to their occurrence.Finally,the paper concludes by discussing two scenarios of EvoEnergy development in relation to energy policy and decision-making. 展开更多
关键词 urban energy planning sustainable planning Big Data household transition energy prediction
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