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Spectrum band for smart grid implementation in Malaysia

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dc.citedby7
dc.contributor.authorHiew Y.K.en_US
dc.contributor.authorAripin N.M.en_US
dc.contributor.authorJayavalan S.en_US
dc.contributor.authorDin N.M.en_US
dc.contributor.authorid56495343900en_US
dc.contributor.authorid35092180800en_US
dc.contributor.authorid55812072300en_US
dc.contributor.authorid9335429400en_US
dc.date.accessioned2023-12-29T07:44:08Z
dc.date.available2023-12-29T07:44:08Z
dc.date.issued2013
dc.description.abstractThe existing electric grid system is facing many challenges: aging infrastructure, growing energy demand, lack of fault-tolerance, lack of diversification of energy supply, emission of carbon dioxide, etc. This encourages the roll out of smart grid system to reinforce the existing grid system. One of the key technologies of smart grid is two-way communication between smart grid components. As smart grid covers a wide range of geographical area, wireless communication outperforms wired communication. However, it is economically not viable to assign a particular band of spectrum for smart grid communication. Besides, the problems encountered in today's spectrum management include scarcity of spectrum, inflexibility of static spectrum assignment, and underutilization of the spectrum. The concept of cognitive radio is an attractive solution for smart grid. By deploying cognitive radio based smart grid, the smart grid component will perform spectrum sensing to look for idle spectrum and opportunistically utilize the idle spectrum. In view of that, the spectrum usage pattern has to be investigated before any justification of a suitable framework for cognitive radio based smart grid is made. In this project, we conducted several spectrum measurements in Malaysia. Antenna and other measurement equipment were set up at Universiti Tenaga Nasional, MIMOS, and Universiti of Malaya to capture 24-hour measurement data. We focused on TV band, GSM band, 3G band, LTE band, ISM band, and WiMAX band. To verify the spectrum usage, the duty cycle (DC) method was used as an indicator of the activeness of the spectrum band. We found that the bands are moderately to heavily underutilize. Based on these spectrum occupancy measurement results, we suggest a feasible cognitive radio based smart grid framework. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7002534
dc.identifier.doi10.1109/SCOReD.2013.7002534
dc.identifier.epage30
dc.identifier.scopus2-s2.0-84921766299
dc.identifier.spage26
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84921766299&doi=10.1109%2fSCOReD.2013.7002534&partnerID=40&md5=d5e80d1c129ae432929981b3afdbdf78
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30043
dc.pagecount4
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceeding - 2013 IEEE Student Conference on Research and Development, SCOReD 2013
dc.subjectcognitive radio
dc.subjectcommunication
dc.subjectsmart grid
dc.subjectspectrum occupancy measurement
dc.subjectAntennas
dc.subjectCarbon dioxide
dc.subjectCognitive radio
dc.subjectCommunication
dc.subjectElectric power transmission networks
dc.subjectFault tolerance
dc.subjectAttractive solutions
dc.subjectMeasurement equipment
dc.subjectSmart grid
dc.subjectSmart Grid Communications
dc.subjectSpectrum measurement
dc.subjectSpectrum occupancies
dc.subjectTwo way communications
dc.subjectWireless communications
dc.subjectSmart power grids
dc.titleSpectrum band for smart grid implementation in Malaysiaen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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