Intelligent control of PV co-located storage for feeder capacity optimization
Institution: | Curtin University of Technology |
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Department: | Electrical and Computer Engineering |
Year: | 2015 |
Record ID: | 1073092 |
Full text PDF: | http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=226050&local_base=gen01-era02 |
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.