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Technical University of Munich
Technical University of Munich

Abhinav Anand

Technische Universität München
Boltzmannstr. 15
Room 2735
85748 Garching b. München
Tel.: +49 (0)89 289 16682
Email: abhinav.anand@tum.de

Research Interests

  • Grid integration, Control, and Optimization of wind turbine/farm
  • Grid service capabilities of modern wind power plants
  • Hybrid renewable generation systems
  • Digital Twin technology

Curriculum Vitae

  • 2010-2014: B.Tech. in Electronics and Electrical Engineering at Kalinga Institute of Industrial Technology, Bhubaneshwar, India. Focus areas: Signal & power electronics, Power systems, Electrical drives & Industrial Automation, Computer Communications & Networks
  • 2014-2017: Lead Engineer at Tata Power Co. Ltd., Mumbai/Delhi, India 
  • 2017-2019: M.Sc. in Power Engineering at Technische Universität München (TUM), Munich, Germany. Focus areas: Control technologies, Battery energy storage, System modelling & Implementation, Machine Learning. Master's thesis: "Optimal control of battery energy storage system for grid integration of wind turbines"
  • 2020-Present: Ph.D. Candidate at Chair of Wind Energy, Technical University of Munich, Germany

Publications

  • A. Baviskar, A. Anand, K. Das and A. D. Hansen, "Opportunities for battery energy storage in stand-alone and co-located hybrid power plant in distribution grid," 22nd Wind and Solar Integration Workshop (WIW 2023), Copenhagen, Denmark, 2023, pp. 656-660, https://doi.org/10.1049/icp.2023.2799

  • Anand, Abhinav & Bottasso, Carlo. (2023). Reducing Plant-Model Mismatch for Economic Model Predictive Control of Wind Turbine Fatigue by a Data-Driven Approach. 1473-1479. https://doi.org/10.23919/ACC55779.2023.10156501. 

  • Abhinav Anand, Stefan Loew, Carlo L. Bottasso  (2022). "Economic nonlinear model predictive control of fatigue for a hybrid wind-battery generation system", Journal of Physics: Conference Series, https://doi.org/10.1088/1742-6596/2265/3/032106

  • Zhao Song,Christoph M. Hackl, Abhinav Anand, Andre Thommesen, Jonas Petzschmann, Omar Kamel, Robert Braunbehrens, Anton Kaifel, Christian Roos, Stefan Hauptmann (2023). "Digital Twins for the Future Power System: An Overview and a Future Perspective", Journal of Sustainibility: Intelligent Mechatronic and Renewable Energy Systems,  https://doi.org/10.3390/su15065259

  • Konstanze Kölle, Tuhfe Göçmen, Paula B. Garcia-Rosa, Vlaho Petrović, Irene Eguinoa, Til Kristian Vrana, Qian Long, Vasilis Pettas, Abhinav Anand, Thanasis K. Barlas, Nicolaos Cutululis, Andreas Manjock, John Olav Tande, Renzo Ruisi, Ervin Bossanyi (2022). "Towards integrated wind farm control: interfacing farm flow and power plant controls", Journal of Advanced Control for Applications: Engineering and Industrial Systems, https://onlinelibrary.wiley.com/doi/10.1002/adc2.105

  • A. Anand, S. Loew, C.L. Bottasso, ‘Economic Control of Hybrid Energy Systems Composed of Wind Turbine and Battery’, 2021 European Control Conference (ECC), Rotterdam, The Netherlands (online conference), June 29 – July 2, 2021. https://doi.org/10.23919/ECC54610.2021.9654911

  • Loew, S., Anand, A., & Szabo, A. (2021). Economic model predictive control of Li‐ion battery cyclic aging via online rainflow‐analysis. Energy Storage, 3(3). https://doi.org/10.1002/est2.228

  • Loew S, Anand A, Obradovic D, Szabo A:  Stage Cost Formulations of Online Rainflow-counting for Model Predictive Control of Fatigue, 2020, European Control Conference, http://.doi.org/10.13140/RG.2.2.10714.08645

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