Farid Khazaeli Moghadam
About
My theoretical and experimental research receives funding from Norwegian Research Council in the project CONWIND: Research on smart operation control technologies for offshore wind farms (grant no. 304229), and the project ONLINEPROP: Torsional vibration measurements for online monitoring of ship propulsion system (grant no. 331655). Below I discuss in more detail my research highlights
- The power demand of the future wind farms can change quickly to improve the grid support feature. The power command of individual turbines should vary in such a way to account for turbulent fluctuations of wind. The latter will influence unevenly the fatigue damage of the power train system of different turbines in different places of the farm. Different approaches for improving the wind farm power tracking control are investigated which are able to accommodate the power train system damage in addition to minimizing the wind farm reference power tracking error. Computationally efficient load calculation techniques for a variety of power train system components, performing probabilistic analysis for defining an overall degradation index and employing surrogate models to encompase life in different operating conditions for control tuning are the keys.
- Modelling the future decentralized power systems and analyzing the dynamic interactions between the power grid and the power train system of wind turbines by taking into account the internal dynamics of electric generator, electronic converter and gear transmission system. The influence of grid forming control strategies in wind turbines' electronic converters on the power system local- and intra-area oscillations are investigated. The consequences on power train system degradation and power quality of the power system are studied. Different active and passive solutions are proposed to improve the overall performance.
- Experimentally testing the possibility of using torsional vibrations in electromechanical systems with torsional dynamics to estimate the system dynamic properties (natural frequency, damping, mode shape), excitation frequencies (components defect frequencies and external excitation frequencies), equivalent model parameters (stiffness and inertia of the components). The latter feeds the algorithms which able to offer more accurate and faster fault diagnosis and prognosis by using the near real-time digital twin model of system.
Education
- Ph.D. in Engineering (Aug. 2018– Mar. 2021) – Marine System Dynamics and Vibration Lab, Dept. of Marine Technology, Norwegian University of Science & Technology, THESIS: Vibration-Based Condition Monitoring of Drivetrains in Large Offshore Wind Turbines in a Digital Twin Perspective, Research Focus: One main focus is on system-level optimization of power train as a multi-physical system including the conceptual and analytical design of the electric generator, gearbox and electronic converter for offshore wind turbines by applying a life-cycle assessment approach. The other focus is on power train fault diagnosis and prognosis in system- and component-level for floating offshore wind turbines by using vibrational measurements and digital twin approach. For this purpose, physical & data-driven models for load calculation, feature extraction, model estimation and uncertainty analysis are employed. The analysis is supported by classical and advanced time and frequency domains load-response analysis.Stochastic modelling and statistical analysis approaches are applied to address different sources of uncertainties in digital twin models. Time-domain computationally efficient system identification techniques are applied for estimation of equivalent models in real time, and near real-time virtual observers are designed for estimating of load and stress in different drivetrain components. An innovative operational modal analysis technique based on encoders measurements is also proposed in my PhD work.
- M.Sc. in Electrical Engineering– Power Electronics (Sept. 2011– Sept. 2013)– Sharif University of Technology– The Department of Electrical & Computer Engineering– Tehran– Iran, THESIS: Optimal Doubly-Fed Induction Generator Controller, for Wind Turbines Application, under Permanent and Transient Grid Voltage Unbalances, Research Focus: The performance of power converter baseline controller in both transient and steady-state voltage unbalances at turbine terminal is demonstrated, and auxiliary controller is designed by applying multi-objective optimization based on optimal control theory to compensate the side effects of negative sequence voltage.
- B.Sc. in Electrical Engineering– Power Engineering (Sept. 2007– Sept. 2011)– Amirkabir University of Technology– The Department of Electrical & Computer Engineering– Tehran– Iran, THESIS: Nonlinear Control of Cascaded Multi-level Inverter Based STATCOM in the Presence of Shunt Passive Filter, Research Focus: The real switching model of STATCOM accompanied by an efficient controller in presence of a shunt power filter is proposed. This model makes it possible to to easily adapt the controller operation in presence of filter.
Experiences
- Making a 15 KW Standalone AC energy system representing a ship propulsion system, in Marine System Dynamics and Vibration Lab, IMT, NTNU
- Sonnen Batterie GMBH – Summer 2018 – Internship - Position: Power Electronics Engineer at Power Electronics Development Group
- Complex Systems Control Laboratory at the University of Georgia (UGA) - (August 2016- July 2018)- Full time job - Position: Graduate Research Assistant
- MAPNA Electrical and Control Engineering & Manufacturing Company (MECO) - www.mapnaec.com - (August 2014- August 2016)- Full time job
Position: Power Electronics Systems engineer at Wind Power Plants Department
- MAPNA Generator Engineering and Manufacturing Company (PARS) - www.mapnagenerator.com- (October 2012- April 2013)- Part time job - Position: Electrical Machines Design Engineer.
- GHODSNIROO Co. - www.ghods-niroo.com- (August 2011- March 2012 )- Part time job - Position: Power Distribution Grids Design Engineer.
- JABOUN Co. - www.jaboun.com- (June 2010- September 2010) – B.Sc. Internship - Position: Designer of low-voltage and medium voltage electrical switchboards (under the license of Schneider Company)
Publications
2024
-
Khazaeli Moghadam, Farid;
Gao, Zhen;
Chabaud, Valentin Bruno;
Chapaloglou, Spyridon.
(2024)
Yaw misalignment in powertrain degradation modeling for wind farm control in curtailed conditions.
Frontiers in Energy Research
Academic article
2023
-
Khazaeli Moghadam, Farid;
Desch, Nils.
(2023)
Life Cycle Assessment of Various PMSG-Based Drivetrain Concepts for 15 MW Offshore Wind Turbines Application.
Energies
Academic article
-
Khazaeli Moghadam, Farid;
Chabaud, Valentin Bruno;
Gao, Zhen;
Chapaloglou, Spyridon.
(2023)
Power train degradation modelling for multi-objective active power control of wind farms.
Forschung im Ingenieurwesen
Academic article
2022
-
Nejad, Amir R.;
Keller, Jonathan ;
Guo, Yi;
Sheng, Shawn;
Polinder, Henk;
Watson, Simon.
(2022)
Wind turbine drivetrains: state-of-the-art technologies
and future development trends.
Wind Energy Science
Academic article
-
Khazaeli Moghadam, Farid;
Vrana, Til Kristian.
(2022)
Wind power plant grid-forming control and influences on
the power train and power system oscillation.
Institution of Engineering and Technology (IET)
Academic chapter/article/Conference paper
2021
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Vibration-Based Condition Monitoring of Drivetrains in Large Offshore Wind Turbines in a Digital Twin Perspective.
Norwegian University of Science and Technology
Doctoral dissertation
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Online condition monitoring of floating wind turbines drivetrain by means of digital twin.
Mechanical systems and signal processing
Academic article
-
Khazaeli Moghadam, Farid;
Rebouças, G. F. S.;
Nejad, Amir R..
(2021)
Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains
.
Forschung im Ingenieurwesen
Academic article
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Theoretical and experimental study of wind turbine drivetrain fault diagnosis by using torsional vibrations and modal estimation.
Journal of Sound and Vibration
Academic article
2020
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2020)
Natural frequency estimation by using torsional response, and applications for wind turbine drivetrain fault diagnosis
.
Journal of Physics: Conference Series (JPCS)
Academic article
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2020)
Evaluation of PMSG-based drivetrain technologies for 10 MW floating offshore wind turbines: pros and cons in a life-cycle perspective.
Wind Energy
Academic article
2019
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2019)
Experimental Validation of Angular Velocity Measurements for Wind Turbines Drivetrain Condition Monitoring.
The American Society of Mechanical Engineers (ASME)
Academic chapter/article/Conference paper
Journal publications
-
Khazaeli Moghadam, Farid;
Gao, Zhen;
Chabaud, Valentin Bruno;
Chapaloglou, Spyridon.
(2024)
Yaw misalignment in powertrain degradation modeling for wind farm control in curtailed conditions.
Frontiers in Energy Research
Academic article
-
Khazaeli Moghadam, Farid;
Desch, Nils.
(2023)
Life Cycle Assessment of Various PMSG-Based Drivetrain Concepts for 15 MW Offshore Wind Turbines Application.
Energies
Academic article
-
Khazaeli Moghadam, Farid;
Chabaud, Valentin Bruno;
Gao, Zhen;
Chapaloglou, Spyridon.
(2023)
Power train degradation modelling for multi-objective active power control of wind farms.
Forschung im Ingenieurwesen
Academic article
-
Nejad, Amir R.;
Keller, Jonathan ;
Guo, Yi;
Sheng, Shawn;
Polinder, Henk;
Watson, Simon.
(2022)
Wind turbine drivetrains: state-of-the-art technologies
and future development trends.
Wind Energy Science
Academic article
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Online condition monitoring of floating wind turbines drivetrain by means of digital twin.
Mechanical systems and signal processing
Academic article
-
Khazaeli Moghadam, Farid;
Rebouças, G. F. S.;
Nejad, Amir R..
(2021)
Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains
.
Forschung im Ingenieurwesen
Academic article
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Theoretical and experimental study of wind turbine drivetrain fault diagnosis by using torsional vibrations and modal estimation.
Journal of Sound and Vibration
Academic article
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2020)
Natural frequency estimation by using torsional response, and applications for wind turbine drivetrain fault diagnosis
.
Journal of Physics: Conference Series (JPCS)
Academic article
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2020)
Evaluation of PMSG-based drivetrain technologies for 10 MW floating offshore wind turbines: pros and cons in a life-cycle perspective.
Wind Energy
Academic article
Part of book/report
-
Khazaeli Moghadam, Farid;
Vrana, Til Kristian.
(2022)
Wind power plant grid-forming control and influences on
the power train and power system oscillation.
Institution of Engineering and Technology (IET)
Academic chapter/article/Conference paper
-
Khazaeli Moghadam, Farid;
Rasekhi Nejad, Amir.
(2019)
Experimental Validation of Angular Velocity Measurements for Wind Turbines Drivetrain Condition Monitoring.
The American Society of Mechanical Engineers (ASME)
Academic chapter/article/Conference paper
Report
-
Khazaeli Moghadam, Farid;
Nejad, Amir R..
(2021)
Vibration-Based Condition Monitoring of Drivetrains in Large Offshore Wind Turbines in a Digital Twin Perspective.
Norwegian University of Science and Technology
Doctoral dissertation
Knowledge Transfer
2023
-
Academic lectureKhazaeli Moghadam, Farid; Gao, Zhen. (2023) The Influence of wake steering on the degradation of power train in offshore wind turbines, and the database approach to accommodate it in the farm control. DeepWind Conference 2023 2023-01-18 - 2023-01-20
2022
-
Academic lectureChabaud, Valentin Bruno; Khazaeli Moghadam, Farid; Nejad, Amir R.. (2022) Effect of tracking grid power command on drivetrain degradation – A multiscale farm control problem. EERA DeepWind'2022 conference , Trondheim 2022-01-19 - 2022-01-21
-
Academic lectureKhazaeli Moghadam, Farid; Vrana, Til Kristian. (2022) Wind power plant grid-forming control and influences on the power train and power system oscillations. IET - Institution of Engineering and Technology The 11th International Conference on Renewable Power Generation , London 2022-09-22 - 2022-09-23
2021
-
Academic lectureKhazaeli Moghadam, Farid; Nejad, Amir R.. (2021) Consequences of unequal droop control on degradation of next generation grid-forming wind turbines. ForWind Wind Energy Science Conference 2021 , Hannover, Germany 2021-05-25 - 2021-05-28
2019
-
Academic lectureKhazaeli Moghadam, Farid; Rasekhi Nejad, Amir. (2019) Experimental Validation of Angular Velocity Measurements for Wind Turbines Drivetrain Condition Monitoring. ASME 2019 2nd International Offshore Wind Technical Conference (IOWTC2019) 2019-11-03 - 2019-11-06
-
Academic lectureKhazaeli Moghadam, Farid; Rasekhi Nejad, Amir. (2019) Drivetrain technology trend in multi megawatt offshore wind turbines considering design, fabrication, installation and operation. EERA DeepWind 2019 conference 2019-01-16 - 2019-01-18
-
PosterKhazaeli Moghadam, Farid; Rasekhi Nejad, Amir. (2019) Drivetrain fault detection of multi-megawatt offshore wind turbines by statistical learning. WindEurope Offshore 2019 2019-11-26 - 2019-11-28