Areas of Expertise (9)
Stability and Control
Modeling and Simulation
Real-Time Hardware-in-the-Loop Simulation
Luigi Vanfretti (SMIEEE’14) obtained the M.Sc. and Ph.D. degrees in electric power engineering at Rensselaer Polytechnic Institute, Troy, NY, USA, in 2007 and 2009, respectively.
He was with KTH Royal Institute of Technology, Stockholm, Sweden, as Assistant 2010-2013), and Associate Professor (Tenured) and Docent (2013-2017/August); where he lead the SmarTS Lab and research group.
He also worked at Statnett SF, the Norwegian electric power transmission system operator, as consultant (2011 - 2012), and Special Advisor in R&D (2013 - 2016).
He joined Rensselaer Polytechnic Institute in August 2017, to continue to develop his research at ALSETLab, his laboratory at ECSE.
His research interests are in the area of synchrophasor technology applications; and cyber-physical power system modeling, simulation, stability and control.
Rensselaer Polytechnic Institute: Ph.D., Electric Power Engineering 2009
Rensselaer Polytechnic Institute: M.Sc, Electric Power Engineering 2007
Major: Electric Power. Minor: Control Systems.
Universidad de San Carlos de Guatemala: Electric Power Engineering, Electrical Engineering Degree 2005
Media Appearances (2)
NASA Funds Aviation Research on a New Fuel Concept
Researchers at the University of Illinois are leading a newly funded project from NASA to develop a novel approach for all-electric aircraft.
NYPA AND RENSSELAER LAB COLLABORATION TO RESEARCH CLEANER GRID TECHNOLOGIES
Inter-lab collaboration between the New York Power Authority (NYPA) and Rensselaer Polytechnic Institute is paving the way for a greener and more resilient power grid – and attracting interest from businesses and government in the process.
Prottay M Adhikari, Hossein Hooshyar, Luigi Vanfretti
2019 Phasor Measurement Units (PMUs) are becoming intrinsic components of modern power systems. The synchrophasor estimation algorithms in PMUs pose stringent computational demands, which makes the application of Field Programmable Gate Arrays (FPGA) highly attractive. Previous works reported the implementation of PMU algorithms on specific FPGA-targets using a particular PMU design. This paper explores the implementation of different PMU designs on multiple FPGA targets using Xilinx and NI software and hardware infrastructures and toolsets. In this process, a metric has been formulated to predict FPGA-target hardware requirements. The metric allows predicting if an FPGA-target meets the needs to deploy a given PMU design resulting in significant engineering design time savings. Since the compilation/synthesis on FPGAs is a time-consuming job, this metric can reduce the implementation time for FPGA-based PMUs drastically and can help in determining if additional functionalities can be added.
Mehdi Monadi, Hossein Hooshyar, Luigi Vanfretti, Farhan Mahmood, Jose Ignacio Candela, Pedro Rodriguez
2019 This paper presents a Network Clustering (NC) method for active distribution networks (ADNs). Following the outage of a section of an ADN, the method identifies and forms an optimum cluster of microgrids within the section. The optimum cluster is determined from a set of candidate microgrid clusters by estimating the following metrics: total power loss, voltage deviations and minimum load shedding. To compute these metrics, equivalent circuits of the clusters are estimated using measured data provided by Phasor Measurement Units (PMUs). Hence, the proposed NC method determines the optimum microgrid cluster without requiring information about the network’s topology and its components. The proposed method is tested by simulating a study network in a real-time simulator coupled to physical PMUs and a prototype algorithm implementation, also executing in real-time.
Miguel Aguilera, Luigi Vanfretti, Tetiana Bogodorova, Francisco Gómez
2019 This work reports how the multi-domain physical modeling and simulation Modelica language has been employed to create a benchmark power grid and gas turbine model within the ITEA3 OpenCPS project. The modeling approach is not only shown to be useful to test the functionalities of the OpenCPS toolchains, but it also could give rise to potential applications in power system domain studies where the widely-accepted turbinegovernor models are not rich enough to represent the multi-domain system dynamics.