Topic: Optimizing Energy Systems: From Demand Response to Flexible Operation

Lecturer: Hamidreza Arasteh, Researcher

Time: April 2, 2025, 9:30-11:00, UTC+8

Venue: Conference Room 308, School of Transportation and Logistics Engineering

Biography: Hamidreza Arasteh (M’20) was born in Zanjan, Iran, in 1988. He is an electrical engineer specializing in multiple power systems fields. He received his Ph.D. from Shahid Beheshti University (SBU) in 2017. He has demonstrated academic excellence, including recognition from the University of Tabriz and the East Azerbaijan Province Government in 2010. His scholarly contributions have also earned international recognition, such as his inclusion in the Publons Global Reviewer Database as one of the “Top 1% Reviewers in Engineering” from 2017 to 2018. Since 2017, he has been with the Power System Operation and Planning Research Department at Iran’s Niroo Research Institute, where he has served as a researcher, project manager/head, and leader of microgrid research. Currently, he is also a researcher at the Microgrid and Renewable Energy Research Center of Huanjiang Laboratory at Zhejiang University. Beyond academia, he has worked at the Hydroelectric Market Economy, Investment, and Regulation Office of Iran’s Ministry of Energy, focusing on bridging academic research and industrial applications. His research interests span renewable energy integration, demand response, smart grids, microgrids, data analysis, energy management, power markets, and optimization in power systems.

Abstract: This presentation explores innovative approaches to optimizing energy systems, focusing on demand response (DR) programs and flexible operation strategies. Key research contributions are highlighted, including a study on DR implementation mechanisms involving DR aggregators. This study examines various aspects, such as regulatory, technological, and socio-cultural factors, while proposing pathways for enhanced market integration. Another project addresses the critical challenge of estimating Customer Baseline Load (CBL), analyzing methods to quantify load reductions in DR programs. It considers variables like weather and seasonality and suggests refinements to improve participation among different customer segments. Additionally, the final part introduces a novel microgrid optimization framework. This framework leverages both electrical and thermal flexibility metrics and employs an efficient technique, called Normalized Normal Constraint (NNC), to balance economic efficiency with the flexibility level of the system.

Rewritten by: Gong Mengting

Edited by: Liang Muwei

Source: School of Transportation and Logistics Engineering