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Alireza Askarzadeh
Researcher at Graduate University of Advanced Technology
Publications - 75
Citations - 6017
Alireza Askarzadeh is an academic researcher from Graduate University of Advanced Technology. The author has contributed to research in topics: Particle swarm optimization & Photovoltaic system. The author has an hindex of 32, co-authored 68 publications receiving 4369 citations. Previous affiliations of Alireza Askarzadeh include Shahid Beheshti University.
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A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm
TL;DR: Simulation results reveal that using CSA may lead to finding promising results compared to the other algorithms, and this paper proposes a novel metaheuristic optimizer, named crow search algorithm (CSA), based on the intelligent behavior of crows.
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Parameter identification for solar cell models using harmony search-based algorithms
TL;DR: Three state-of-the-art HS variants are used to determine the unknown parameters of the solar cell single and double diode models and results manifest the superiority of the HS-based algorithms over the other studied algorithms in modeling solar cell systems.
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Artificial bee swarm optimization algorithm for parameters identification of solar cell models
TL;DR: This paper proposes an ABSO-based parameter identification technique based on the single and double diode models for a 57mm diameter commercial silicon solar cell and results obtained are quite promising and outperform those found by the other studied methods.
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Optimal sizing of a PV/wind/diesel system with battery storage for electrification to an off-grid remote region: A case study of Rafsanjan, Iran
Akbar Maleki,Alireza Askarzadeh +1 more
TL;DR: In this article, an off-grid hybrid multisource system (PV/wind/diesel/battery) is considered, modeled, optimally sized, and compared with a diesel alone generation system in terms of the total annual cost and environmental emissions.
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Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system
Akbar Maleki,Alireza Askarzadeh +1 more
TL;DR: Evaluating the performance of different artificial intelligence techniques for optimum sizing of a PV/wind/FC hybrid system to continuously satisfy the load demand with the minimal total annual cost finds that particle swarm optimization has the most robustness.