Optimal On-Load Tap Changer Control for Higher PV Hosting Capacity of Distribution Feeders

Vahid Rasouli Disfani, UC San Diego
January 18, 2017, 11:00am - 12:00pm, EBU-II 479



High Solar Photovoltaic (PV) penetration on distribution systems causes over-voltages near the end of the feeder. Given that voltage regulators are typically not at the end of the feeder, conventional local tap control does not consider the highest feeder voltages limiting the feeder PV hosting capacity. An optimal on-load tap changer (OLTC) control method is proposed using a feeder-wide multi-horizon OLTC control which minimizes the maximum deviation of the voltage profile from 1 p.u. on the entire feeder during the optimization horizon. To reduce maintenance cost of OLTCs, the number of tap operations is also considered in the objective function. In order to reduce the computational cost, linearization techniques are introduced to transform the optimization problem to mixed-integer convex programming. The efficiency of the control algorithm is tested against two real feeders in California. The case studies show that OTC improves the voltage condition such that the PV hosting capacities on the test feeders increase by 40% and 24%. Although OTC increases the number of tap operations on the feeders, the increase does not lead to increased operations and maintenance needs.



Vahid Rasouli Disfani has been a postdoctoral Scholar at University of California San Diego since August 2015. He received a B.S. degree from Amirkabir University of Technology, Iran in 2006 and an M.S. degree from Sharif University of Technology, Iran in 2008, both in Electrical Engineering. He has been awarded full scholarships for his masters and bachelor programs due to his outstanding performance (being among top 0.1%) in Iran nationwide university entrance tests. Immediately after earning his Ph.D. in electrical engineering from University of South Florida in 2015, Vahid joined Dr. Kleissl's Center of Renewable Resources Integration (CRRI) at UCSD as a postdoctoral Research Associate. He has also contributed to several industry projects during his professional career at Iran Grid Management Company and NEC Laboratories America, his Ph.D. program and his two-year postdoctoral experience. He has developed numerous multi-agent algorithms for optimal power flow problem, several model predictive control techniques to control power electronic converters, and optimal voltage control methods to increase PV hosting capacity of distribution systems. His research fields of interest include smart grid, distributed control and optimization, grid integration and market participation of distributed energy resources.

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