Forecasting the Building Energy Consumption in China Using Grey Model
The consumption of energy is receiving increasing attention and the building energy consumption is an important component of this. However, buildings in China, a developing country, consume large amounts of energy, and the accurate prediction of building energy consumption is particularly important...
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| Veröffentlicht in: | Environmental Processes 2020-09, Vol.7 (3), p.1009-1022 |
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| container_title | Environmental Processes |
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| creator | Dun, Meng Wu, Lifeng |
| description | The consumption of energy is receiving increasing attention and the building energy consumption is an important component of this. However, buildings in China, a developing country, consume large amounts of energy, and the accurate prediction of building energy consumption is particularly important for its reduction. The buildings causing energy consumption are divided into three types (i.e., rural, public and urban buildings). Using data from the period 2001–2016, the grey model was applied to predict the building energy consumption, the building area and the building energy consumption per unit area of the three building types in 2017–2020. According to the forecasting results, the energy consumption per unit area of rural buildings, public buildings and the total building energy consumption per unit area will show an increasing trend at varying degrees in 2017–2020. This indicates that the existing problems of building energy consumption have not been effectively solved. Based on the forecasting results, the problems of the building energy consumption are summarized and solutions are proposed. |
| doi_str_mv | 10.1007/s40710-020-00438-3 |
| format | Article |
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However, buildings in China, a developing country, consume large amounts of energy, and the accurate prediction of building energy consumption is particularly important for its reduction. The buildings causing energy consumption are divided into three types (i.e., rural, public and urban buildings). Using data from the period 2001–2016, the grey model was applied to predict the building energy consumption, the building area and the building energy consumption per unit area of the three building types in 2017–2020. According to the forecasting results, the energy consumption per unit area of rural buildings, public buildings and the total building energy consumption per unit area will show an increasing trend at varying degrees in 2017–2020. This indicates that the existing problems of building energy consumption have not been effectively solved. Based on the forecasting results, the problems of the building energy consumption are summarized and solutions are proposed.</description><identifier>ISSN: 2198-7491</identifier><identifier>EISSN: 2198-7505</identifier><identifier>DOI: 10.1007/s40710-020-00438-3</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Analysis ; Architecture and energy conservation ; Buildings ; Developing countries ; Earth and Environmental Science ; Earth Sciences ; Energy consumption ; Energy industry ; Energy management ; Environmental Management ; Environmental Science and Engineering ; Forecasting ; Forecasts and trends ; LDCs ; Mathematical models ; Public buildings ; Rural areas ; Short Communication ; Waste Management/Waste Technology ; Water Quality/Water Pollution</subject><ispartof>Environmental Processes, 2020-09, Vol.7 (3), p.1009-1022</ispartof><rights>Springer Nature Switzerland AG 2020</rights><rights>COPYRIGHT 2020 Springer</rights><rights>Springer Nature Switzerland AG 2020.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c421t-eb8a4a2a83b65b453ccbda77b827115776c2db287cfca8160a9aad330123fde33</citedby><cites>FETCH-LOGICAL-c421t-eb8a4a2a83b65b453ccbda77b827115776c2db287cfca8160a9aad330123fde33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40710-020-00438-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40710-020-00438-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Dun, Meng</creatorcontrib><creatorcontrib>Wu, Lifeng</creatorcontrib><title>Forecasting the Building Energy Consumption in China Using Grey Model</title><title>Environmental Processes</title><addtitle>Environ. 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This indicates that the existing problems of building energy consumption have not been effectively solved. Based on the forecasting results, the problems of the building energy consumption are summarized and solutions are proposed.</description><subject>Analysis</subject><subject>Architecture and energy conservation</subject><subject>Buildings</subject><subject>Developing countries</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Energy consumption</subject><subject>Energy industry</subject><subject>Energy management</subject><subject>Environmental Management</subject><subject>Environmental Science and Engineering</subject><subject>Forecasting</subject><subject>Forecasts and trends</subject><subject>LDCs</subject><subject>Mathematical models</subject><subject>Public buildings</subject><subject>Rural areas</subject><subject>Short Communication</subject><subject>Waste Management/Waste Technology</subject><subject>Water Quality/Water Pollution</subject><issn>2198-7491</issn><issn>2198-7505</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9UD1PwzAQtRBIVKV_gCkSc8rZTuJkLFFbkIpY6Gw5jpO6Su1iJ0P_PU4DYkOn-9R7d6eH0COGJQZgzz4BhiEGEhwSmsf0Bs0ILvKYpZDe_tZJge_RwvsjABCcAKHFDK031ikpfK9NG_UHFb0MuqvHZm2Uay9RaY0fTudeWxNpE5UHbUS09yNi69Qlere16h7QXSM6rxY_eY72m_Vn-RrvPrZv5WoXy4TgPlZVLhJBRE6rLK2SlEpZ1YKxKicM45SxTJK6IjmTjRQ5zkAUQtSUAia0qRWlc_Q07T07-zUo3_OjHZwJJzlJKKTXEFDLCdWKTnFtGts7IYPV6qSlNarRYb5ikKUkIwQCgUwE6az3TjX87PRJuAvHwEeJ-SQxDxLzq8R8_IVOJB_AplXu75d_WN_1v3zi</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Dun, Meng</creator><creator>Wu, Lifeng</creator><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IAO</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>20200901</creationdate><title>Forecasting the Building Energy Consumption in China Using Grey Model</title><author>Dun, Meng ; Wu, Lifeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c421t-eb8a4a2a83b65b453ccbda77b827115776c2db287cfca8160a9aad330123fde33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analysis</topic><topic>Architecture and energy conservation</topic><topic>Buildings</topic><topic>Developing countries</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Energy consumption</topic><topic>Energy industry</topic><topic>Energy management</topic><topic>Environmental Management</topic><topic>Environmental Science and Engineering</topic><topic>Forecasting</topic><topic>Forecasts and trends</topic><topic>LDCs</topic><topic>Mathematical models</topic><topic>Public buildings</topic><topic>Rural areas</topic><topic>Short Communication</topic><topic>Waste Management/Waste Technology</topic><topic>Water Quality/Water Pollution</topic><toplevel>online_resources</toplevel><creatorcontrib>Dun, Meng</creatorcontrib><creatorcontrib>Wu, Lifeng</creatorcontrib><collection>CrossRef</collection><collection>Gale Academic OneFile</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>Environmental Processes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dun, Meng</au><au>Wu, Lifeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Forecasting the Building Energy Consumption in China Using Grey Model</atitle><jtitle>Environmental Processes</jtitle><stitle>Environ. Process</stitle><date>2020-09-01</date><risdate>2020</risdate><volume>7</volume><issue>3</issue><spage>1009</spage><epage>1022</epage><pages>1009-1022</pages><issn>2198-7491</issn><eissn>2198-7505</eissn><abstract>The consumption of energy is receiving increasing attention and the building energy consumption is an important component of this. However, buildings in China, a developing country, consume large amounts of energy, and the accurate prediction of building energy consumption is particularly important for its reduction. The buildings causing energy consumption are divided into three types (i.e., rural, public and urban buildings). Using data from the period 2001–2016, the grey model was applied to predict the building energy consumption, the building area and the building energy consumption per unit area of the three building types in 2017–2020. 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| subjects | Analysis Architecture and energy conservation Buildings Developing countries Earth and Environmental Science Earth Sciences Energy consumption Energy industry Energy management Environmental Management Environmental Science and Engineering Forecasting Forecasts and trends LDCs Mathematical models Public buildings Rural areas Short Communication Waste Management/Waste Technology Water Quality/Water Pollution |
| title | Forecasting the Building Energy Consumption in China Using Grey Model |
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