Modelling building energy consumption in China under different future scenarios

Guo, Siyue; Yan, Da; Hu, Shan; Zhang, Yang

doi:10.1016/j.energy.2020.119063

Cited by 120 publications

(27 citation statements)

References 21 publications

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“…When study (García et al 2021) is examined, it is seen that the most accurate analysis results are obtained by analysing hourly energy consumption. Similar to this study, there are also studies that want to reduce the energy consumption in shelters and eliminate the disposal of harmful wastes to the environment (Guo et al 2021).…”

Section: Introductionmentioning

confidence: 67%

Enerji Tüketim Tahmini İçin Farklı Regresyon Algoritmalarının Analizi

ÇETİNER¹,

ÇETİNER²

2021

European Journal of Science and Technology

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Due to the increasing population, a great increase is observed in the number of different centers such as art, entertainment, and industry. The number of such centers is increasing day by day. These areas are naturally the centers where energy is needed at a high rate. Energy consumption data in the specified areas are increasing day by day. At this point, it has become a difficult problem to meet energy needs in all areas where people live and need energy, in addition to the mentioned centers. To eliminate this difficult problem, it has become a necessity to both meet the energy consumption and ensure the effective use of energy. It is observed that there is an increase in artificial intelligence supported housing systems consisting of electronic devices in order to minimize energy consumption in shelters and residences. Taking into account the increase in environmental factors such as global warming, greenhouse gas emissions, carbon dioxide, chemical solvents, and radiation, studies on the efficient use of energy should be increased. In line with the stated objectives and purposes, the data of the United States regional communications organization PJM Interconnection LLC (PJM) named Dominion Virginia Power (DOM) have been used. This dataset shows the hourly data consumption in Mega Watts of the Asian region. On this dataset, the energy estimation results of the recently popular XGBoost, LSTM algorithms, classical linear regression and RANSAC algorithms were compared.

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Section: Introductionmentioning

confidence: 67%

Enerji Tüketim Tahmini İçin Farklı Regresyon Algoritmalarının Analizi

ÇETİNER¹,

ÇETİNER²

2021

European Journal of Science and Technology

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“…Besides, the approach can deal with potential instabilities in causal link between EC and HI due to structural breaks. Finally, being different from prior studies ( 17 , 40 , 41 ), some important policy implications are more focused on HIHI market. We advise that the government can strengthen the propaganda of insurance consciousness to the public and offer necessary knowledge for residents to understand the insurance products.…”

Section: Introductionmentioning

confidence: 78%

Energy Consumption and Health Insurance Premiums in China's Provinces: Evidence From Asymmetric Panel Causality Test

Wang

Liu

Lobonţ

et al. 2021

Front. Public Health

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This article employs asymmetric panel causality test to address the causal nexus between energy consumption (EC) and healthcare insurance premiums (IP) for China's different provinces. The empirical results indicate that there exist asymmetric causality runs from positive EC shocks to positive healthcare IPs in Beijing, Hebei, Tianjin, Shanxi, Inner Mongolia, Shaanxi, Gansu, Qinghai, Ningxia, Shandong, Henan, and Anhui. There is no significant link in southern and northeastern provinces mainly because of their industrial structure, high economic development level, strong insurance consciousness, and climate conditions. Therefore, governments should encourage technological innovation and further improve energy efficiency. Meanwhile, we need to optimize EC structure and raise the proportion of renewable energies. The authorities should carry out stricter environmental protection policies and protect people from pollution that comes from fossil fuel burn. The commercial health insurance should be included in the health system and become an important supplement to public health insurance.

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“…At present, research on CPCN in the building sector is mainly focused on developed countries and major economies [90][91][92][93][94], and further cooperation between authors, institutions, and countries is needed to keep the global temperature rise to below 1.5 °C above pre-industrial levels [95]. Take China, for example, the reduction of the ECCE potential of China's building sector has been estimated under various scenarios [7,75,79,96,97].…”

Section: Discussionmentioning

confidence: 99%

Carbon Peak and Carbon Neutrality in the Building Sector: A Bibliometric Review

Sun

et al. 2022

Buildings

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Due to large energy consumption and carbon emissions (ECCE) in the building sector, there is huge potential for carbon emission reduction, and this will strongly influence peak carbon emissions and carbon neutrality in the future. To get a better sense of the current research situation and future trends and to provide a valuable reference and guidance for subsequent research, this study presents a summary of carbon peak and carbon neutrality (CPCN) in buildings using a bibliometric approach. Three areas are addressed in the review through the analysis of 364 articles published from 1990–2021: (1) Which countries, institutions, and individuals have conducted extensive and in-depth research on CPCN in buildings, and what is the status quo of their collaboration and contributions? (2) What subjects and topics have aroused wide interest and enthusiasm among scholars, and what are their time trajectories? (3) What journals and authors have grabbed the attention of many scholars, and what are the research directions related to them? Moreover, we propose future research directions. Filling these gaps will enrich the research body of CPCN and overcome current limitations by developing more methods and exploring other practical applications.

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Modelling building energy consumption in China under different future scenarios

Cited by 120 publications

References 21 publications

Enerji Tüketim Tahmini İçin Farklı Regresyon Algoritmalarının Analizi

Enerji Tüketim Tahmini İçin Farklı Regresyon Algoritmalarının Analizi

Energy Consumption and Health Insurance Premiums in China's Provinces: Evidence From Asymmetric Panel Causality Test

Carbon Peak and Carbon Neutrality in the Building Sector: A Bibliometric Review

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