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|
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.title||Intelligent control of PV co-located storage for feeder capacity optimization|
|curtin.department||Department of Electrical and Computer Engineering|