Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/70930
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dc.contributor.authorNeo, Sebastian Guang Jin
dc.date.accessioned2017-05-12T04:31:27Z
dc.date.available2017-05-12T04:31:27Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/70930
dc.description.abstractThis report focuses on data analytics for building management system. Data from the smart meters is transmitted and collected in a database so that aggregators and utility companies can keep track and understand power consumption better. Using this system, aggregators will be able to come up with better demand response techniques, benefits and load shifting method that are commonly used in smart grids. Using the system, utility companies will know how much electricity they need to generate in different periods of a day so that there will not be over-generation. As the demand in electricity increases, generation companies try to meet the demands of customers without causing more harm to the environment. They do this by using different approaches to meet the expectations of the consumers more efficiently. This demand response approach makes use of technologies and incentives to encourage consumers to participate in the program by allowing users to keep track of their consumption and to reduce their consumption when the electric tariff is high during peak periods from 7 a.m. to 11.00 p.m. Depending on the program chosen by the consumers, monetary incentives will be rewarded.en_US
dc.format.extent113 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleData analytics for building management system using wireless metering infrastructureen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSo Ping Lamen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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Data Analytics, Smart Meter, Data Retrieval7.52 MBAdobe PDFView/Open

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