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Amin received the B.Sc. and M.Sc. degrees in electrical engineering from the University of Tabriz, Iran, in 2010 and 2013, respectively. He is currently pursuing the Ph.D. degree with Queensland University of Technology, Brisbane, QLD, Australia. He has more than six years of industrial experience in transmission and distribution networks. His research interests are solar energy estimation, power system state estimation, smart grid control, load shedding (LS), frequency Control (FC), system Reliability evaluation and uncertainty Analysis.
Principal Supervisor: Dr Ghavameddin Nourbakhsh
Associate Supervisor: Adj/Prof Gerard Ledwich Dr Ali Arefi (External Supervisor)
PhD Overview
Power System State Estimation (PSSE) has been used extensively and applied in transmission system planning, control and operation. With the emerging active distribution networks (DNs), monitoring of voltage and line power flow beyond the distribution substations is becoming important. However, current installation of monitoring devices such as Phasor Measurement Units (PMUs) in DNs is not practical solution due to a significant cost and infrastructure investment requirements. Therefore, a fast and accurate estimating methodology for DNs with low number of monitoring devices would be a very cost-effective alternative.
One of the advantages of the Distribution System State Estimation (DSSE) is to estimate DNs state variables using a limited measurement devices at certain locations. Using DSSE in active distribution systems is a challenging task due to demand and supply uncertainties. Furthermore, large-scale integration of the Distributed Energy Resources (DERs) in low voltage (LV) grids and the weather uncertainty would add to the complexity of the estimation modelling and evaluation processes. In addition, market price responsive demands and supplies, including batteries and Electric Vehicles (EVs) can also make the problem much more challenging. Consequently, adequately proper DSSE method should be developed to cater for the noted aims and objectives, including protection, optimization, and control techniques applying to LV DNs.