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Mostafa Vahedipour dahraie

Mostafa Vahedipour dahraie

Associate Professor

Full-Time Faculty Member

Faculty: Ferdows Technical College

Department: Electrical Engineering-Power

Degree: Doctoral

Birth Year: 1982

CV
FA
Mostafa Vahedipour dahraie

Associate Professor Mostafa Vahedipour dahraie

Full-Time Faculty Member
Faculty: Ferdows Technical College - Department: Electrical Engineering-Power Degree: Doctoral | Birth Year: 1982 |

Dr. Mostafa Vahedipour received his Ph.D. in Electrical Engineering from the University of Birjand in 2017. His doctoral research focused on demand management in smart microgrids with an emphasis on ensuring system security. During this period, he was awarded a prestigious scholarship from the Iranian Ministry of Science, Research and Technology, which enabled him to conduct research as a visiting researcher at Aalborg University, Denmark, from 2016 to 2017.

After completing his Ph.D., Dr. Vahedipour continued his academic career as an Assistant Professor at the University of Birjand, where he played an active role not only in research but also in educating and training future generations of engineers. In 2020, he was awarded an international research fellowship at the University of Salerno, Italy, where he focused his research on energy management in smart grids. This collaboration expanded his research expertise and led to stronger interactions with the University of Vaasa, Finland where he was a post doc researcher.

Currently, Dr. Vahedipour is an Associate Professor in the Department of Electrical Engineering at the University of Birjand, Ferdows Faculty of Engineering. ALso, now, he is working as a team leader at Nowocert, research and Innovation Division, Dublin, Ireland. 

In parallel, he serves as a member of the Board of Directors of Saha Niroo Savis Company, a technology-based company operating in the field of energy management in Iran. His dual roles in academia and industry have enabled him to bridge the gap between research and practical solutions in energy management.

My affiliation

Department of Electrical and Computer Engineering, University of Birjand, Birjand, Iran

Nowocert, research and Innovation Division, Dublin, Ireland. 

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A bi-level risk-constrained offering strategy of a wind power producer considering demand side resources

AuthorsMostafa Vahedipour-Dahraie,Homa Rashidizadeh-Kermania,Miadreza Shafie-khah,João P.S. Catalão
JournalInternational Journal of Electrical Power and Energy Systems
Page number562-574
Serial number104
Volume number5
IF3.289
Paper TypeFull Paper
Published At2019
Journal GradeISI
Journal TypeTypographic
Journal CountryIran, Islamic Republic Of
Journal IndexJCR،Scopus

Abstract

This paper proposes a stochastic decision making problem for a wind power producer (WPP) in the day-ahead (DA) and balancing markets. In this problem, bidding strategy of the WPP in a competitive electricity market and also its participation to supply demand response (DR) and electric vehicle (EV) aggregators is determined to achieve the maximum profit. In this model, DR and EV aggregators are able to choose the most competitive WPP in such a way that their energy payments be minimized in the scheduling horizon. Therefore, the problem is formulated as a stochastic bi-level programming model with conflict objectives of the WPP and the aggregators. Moreover, owing to the uncertainties associated with market prices, offered prices by rival WPPs, demand of DR and EV aggregators, conditional value at risk (CVaR) is applied to the proposed model. The attained stochastic bi-level problem is transformed to a linear stochastic single level problem with equilibrium constraints using Karush–Kuhn–Tucker (KKT) optimality conditions. The proposed model is evaluated on a realistic case study and the impacts of risk-averse behavior and demand response participants on the decision making problem of the WPP are investigated. Numerical results indicate that with increasing DR participants of 0%, 60% and 100%, CVaR of WPP increases 33.81%, 40.79% and 46.99%, respectively. This means that if the loads are more responsive, the WPP tries to control the profit variability due to the uncertainties of loads.

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