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An Approach to Optimize Multi-family Residence HVAC Systems Using Digitalization
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作者 Bilal Faye Osman Ahmed Andrew Rodger 《Management Studies》 2023年第4期185-201,共17页
As mentioned by National Geographic(2017),70%of world’s population is expected to live in large apartment buildings by 2050.Today,buildings in cities generate 30%of world’s greenhouse gas emission or GHG(National Ge... As mentioned by National Geographic(2017),70%of world’s population is expected to live in large apartment buildings by 2050.Today,buildings in cities generate 30%of world’s greenhouse gas emission or GHG(National Geographic,2017).Major urban centers are committed to reducing greenhouse gases by 80%by 2050(IEA,2021).However,achieving such goals in rental properties is not easy.Landlords are hesitant to use high-efficiency technologies because,typically,tenants pay the utilities bill.However,that situation is rapidly changing.For example,New York City like other US cities,is considering a carbon cap on all large buildings(Local Law 97,2019).That means landlords will pay a carbon penalty if the building’s carbon footprint exceeds certain threshold no matter who uses that carbon.The Pacific Northwest National Laboratory(PNNL)has received funds from DOE(US Department of Energy)with the collaboration of a commercial partner to address emerging energy efficiency market opportunity in multi-family or rental housing as discussed above.It has partnered with a large national real estate owner in order to test a novel energy optimization method at a rental property in Tempe,Arizona.By using a seamless-integrated method of acquiring building’s operating data,the optimization approach essentially resets setpoints of different energy consuming equipment such as chillers,boilers,pumps,and fans.Data-driven optimization approach is pragmatic and easily transferrable to other buildings.The authors shall share the problem background,technical approach,and preliminary results. 展开更多
关键词 HVAC optimization IoT DIGITALIZATION multi-family housing commercial buildings
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