H
Hossein Saber
Researcher at Sharif University of Technology
Publications - 17
Citations - 215
Hossein Saber is an academic researcher from Sharif University of Technology. The author has contributed to research in topics: Computer science & Electric power system. The author has an hindex of 3, co-authored 10 publications receiving 75 citations.
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A scenario-based planning framework for energy storage systems with the main goal of mitigating wind curtailment issue
TL;DR: A new multi-objective (MO) framework for expansion studies of energy storage systems (ESSs) in high wind penetrated power system is provided and all the crucial and maybe contradictory aspects of the ESSs expansion problem are treated via a Posteriori MO optimization algorithm.
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Developing a multi-objective framework for expansion planning studies of distributed energy storage systems (DESSs)
TL;DR: All the crucial aspects of the DESSs expansion problem are treated via a well-organized posteriori multi-objective (MO) optimization algorithm, i.e. the Non-dominated Sorting Genetic Algorithm II (NSGA-II).
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Expansion Planning Studies of Independent-Locally Operated Battery Energy Storage Systems (BESSs): A CVaR-Based Study
TL;DR: A new bi-level framework for expansion studies of ESSs is proposed, where the long-term total cost of bulk power systems and the scheduling of independent-locally operated E SSs are modeled in the upper level (UL) and lower-level (LL) problems, respectively.
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Utilization of in-pipe hydropower renewable energy technology and energy storage systems in mountainous distribution networks
TL;DR: A stochastic mixed-integer linear programming (MILP) formulation that simultaneously determines the optimal location and size of ESS and IHS in a microgrid (MG) considering the correlation between prevailing uncertainties is developed.
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Network-Constrained Transactive Coordination for Plug-In Electric Vehicles Participation in Real-Time Retail Electricity Markets
TL;DR: In this article, a real-time retail electricity market for plug-in electric vehicles (PEVs) under a transactive energy (TE) paradigm is proposed, where PEV owners estimate their willingness to pay/accept using a user-friendly strategy and submit the estimated values to the retail market operator.