Areas of Expertise (8)
Electric Power Engineering
Modeling and Simulation of Cyber-Physical Systems
Power Systems, Power Grid
Real-Time Hardware-in-the-Loop Simulation, CHIL, PHIL
Synchrophasor Measurements, PMU, Synchrophasor Technologies
VTOL, Electrified Aircraft, Electrified Transportation
Luigi Vanfretti (senior member, IEEE; member, Modelica Association) leads ALSETLab on research in energy systems, electrical power systems, and aircraft electrification. His research includes cyber-physical system (CPS) modeling, simulation, stability, and control in energy systems, power grids, and electrified transportation.
In addition, Vanfretti researches development and data analytics in synchrophasor technologies. He is interested in the application of software technologies, signal processing, system identification, and machine learning for design and operation analytics for CPS.
Vanfretti has been a professor since 2022 and was previously an associate professor. Vanfretti also earned his master’s and doctoral degrees in electric power engineering from Rensselaer Polytechnic Institute.
Vanfretti has held temporary posts in prestigious international institutions, as well. In 2022, he was a visiting professor at both the Laboratoire Ampère of the École Centrale de Lyon and the SuperGrid Institute in Lyon, France. In 2019, he was a visiting faculty at the King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Prior to emigrating to join RPI as a faculty member, Vanfretti was an assistant professor, tenured associate professor, and docent with the KTH Royal Institute of Technology in Stockholm, Sweden, where he led the SmarTS Lab. He was also employed as Special Advisor in Strategy and Public Affairs and Special Advisor in Strategy and International Collaboration in the Research and Development Department of Statnett SF, the Norwegian transmission system operator. Prior to his employment with Statnett SF, he was a Scientific Advisor, reporting to the Vice President of the Research and Development Division, during 2011 to 2013.
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 (7)
Collaboration between RPI’s ECSE and Dominion Energy Led to Best Conference Paper in 2022 IEEE PES General Meeting
Rensselaer Polytechnic Institute | School of Engineering News online
2022 IEEE Power and Energy Society selects a collaborative paper co-authored by Prof. Luigi Vanfretti and Dominion Energy as one of the Best Conference Papers
The Power of Modelica: An Interview With Professor Luigi Vanfretti
In this interview, we ask Professor Luigi Vanfretti what has helped him succeed in learning Modelica, and how impactful Modelica has been within his research and discipline at Rensselear Polytechnic Institute. Learn how Professor Vanfretti harnessed the power of Modelica with Modelon technology.
Stewart's wanted to build upstate's biggest electric car charging network. Here's why it didn't happen
The Business Journals online
[No Abstract Available]
Electrical and Systems Engineers To Support NASA-Funded Research on Electric Aircraft
Rensselaer News online
“A plane has multiple systems inside of it,” said Luigi Vanfretti, associate professor of electrical, computer, and systems engineering. “You need to have a way to understand the interaction of the systems and, in an integrated way, you need to optimize them together.”
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.
American power grid ill-equipped for electric car wave
[No Abstract Available]
Experimental Quantification of Hardware Requirements for FPGA-Based Reconfigurable PMUsIEEE Access
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.
Measurement-based Network Clustering for Active Distribution SystemsIEEE Transactions on Smart Grid
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.
Coalesced Gas Turbine and Power System Modeling and Simulation using ModelicaProceedings of The American Modelica Conference 2018
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.