Dr. Ali Hashemifarzad

Dr. of Engineering, Energy System Integration

 

 

Contact
BASF
Carl-Bosch-Str. 38
67063 Ludwigshafen

Research topic

Electrical load forecasting with the help of the adaptive neuro-fuzzy inference system

This research attempts to propose a new approach to the problem of load forecasting in order to achieve more accurate results with a lower error rate. For this purpose, a methodology based on the theories of chaos and concept drift is introduced and the Adaptive Neuro-Fuzzy Inference System (ANFIS) plays the main role in training and testing the model.

Vita

Ali Hashemifarzad has been working as a research assistant and doctoral student at the CUTEC Institute, Energy Research Center (EFZN) and at TU Clausthal since 2015. Prior to this, Mr. Hashemifarzad completed his Bachelor’s degree in Power Electrical Engineering at Semnan University in Iran. This was followed by a Master’s degree in Energy Systems Engineering at Clausthal University of Technology. During his studies, he completed two internships in the field of renewable energies and power plant technology. His research focuses on energy system analysis and simulation of various systems (e.g. wind turbines, multi-level converters, etc.). In his doctoral thesis, Mr. Hashemifarzad works on the analysis and prediction of electrical load using the Adaptive Neuro-Fuzzy Inference System (ANFIS).

Supervision

First supervisor: Prof. Dr. Martin Faulstich, TU Dortmund University
Second supervisor: Prof. Dr. Christian Siemers, TU Clausthal
Place of doctorate: TU Clausthal

Keywords

Load forecasting, chaos theory, ANFIS, artificial intelligence, energy system modeling

Publications

2018 “The Conceptual Design of Auto-Rotary Mono-Wing Decelerators Based on Maple Seeds as an entry decent landing system for Mars explorations”, European Rotorcraft Forum, September 2018, TU Delft, Netherlands – 2nd Author

2018 “New approach in Load forecasting based on Concept Drift and ANFIS”, International Conference on Sustainable Energy and Environment Sensing (SEES), June 2018 , University of Cambridge , Cambridge city, United Kingdom –Oral presentation

2018 “Impact of Electromobility on the Future Standard Load Profile”, 2nd international conference on Energy Economics and Energy Policy, ICEEEP 2018, Barcelona, Spain – Published in Conference Proceeding Journal

2017 “Short and Long Term load forecasting using Artificial Intelligence” 12th SDEWES Conference, Dubrovnik, Croatia – Oral Presentation- Under review

2016 “Case study of CCS Vs. power plant phasing out as solutions for power plant produced CO2 emission control”, 11th SDEWES Conference, Lisbon, Portugal – Published in Conference Proceeding Journal

2016 “Application of heat storage in modern decentralized energy supply systems”, Power to Heat 2016, Goslar, Germany- Published in Conference Proceeding Journal