Intelligent control of PV co-located storage for feeder capacity optimization
| dc.contributor.author | Jayasekara, Manathum Nadeeshani Pushpamala | |
| dc.contributor.supervisor | Prof. Peter J. Wolfs | |
| dc.contributor.supervisor | Prof. Mohammad A. S. Masoum | |
| dc.date.accessioned | 2017-01-30T10:05:38Z | |
| dc.date.available | 2017-01-30T10:05:38Z | |
| dc.date.created | 2015-05-14T07:11:06Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | http://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.language | en | |
| dc.publisher | Curtin University | |
| dc.title | Intelligent control of PV co-located storage for feeder capacity optimization | |
| dc.type | Thesis | |
| dcterms.educationLevel | PhD | |
| curtin.department | Department of Electrical and Computer Engineering | |
| curtin.accessStatus | Open access |