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dc.contributor.authorJayasekara, Manathum Nadeeshani Pushpamala
dc.contributor.supervisorProf. Peter J. Wolfs
dc.contributor.supervisorProf. Mohammad A. S. Masoum
dc.date.accessioned2017-01-30T10:05:38Z
dc.date.available2017-01-30T10:05:38Z
dc.date.created2015-05-14T07:11:06Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/20.500.11937/1415
dc.description.abstract

Battery energy storage is identified as a strong enabler and a core element of the next generation grid. However, at present the widespread deployment of storage is constrained by the concerns that surround the techno-economic viability. This thesis addresses this issue through optimal integration of storage to improve the efficiency of the electricity grid. A holistic approach to optimal integration includes the development of methodologies for optimal siting, sizing and dispatch coordination of storage.

dc.languageen
dc.publisherCurtin University
dc.titleIntelligent control of PV co-located storage for feeder capacity optimization
dc.typeThesis
dcterms.educationLevelPh.D.
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusOpen access


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