Hossein SHAYEGHI

Prof. Dr. Hossein SHAYEGHI

Energy Management Research Center, University of Mohaghegh Ardabili, Ardabīl, Iran
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Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2016 in Applied Energy
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Journal Article
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AGA. Ghasemi
A. Ghasemi
Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
MMM. Moradzadeh
M. Moradzadeh
MNM. Nooshyar
M. Nooshyar
5 June 2019 in Energies
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Journal Article
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Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
ESElnaz Shahryari
Elnaz Shahryari
MMMohammad Moradzadeh
Mohammad Moradzadeh
PSPierluigi Siano
Pierluigi Siano
Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.
2 October 2019 in IEEE Transactions on Power Electronics
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Journal Article
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MAMahmoodreza Eskandarpour Azizkandi
Mahmoodreza Eskandarpour Azizkandi
FSFarzad Sedaghati
Farzad Sedaghati
Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
Frede BlaabjergFrede Blaabjerg
Frede Blaabjerg
This paper introduces a single-switch, high step-up, DC-DC converter based on coupled-inductor (CL) with three winding and voltage multiplier cell (VMC) to obtain a very high voltage conversion ratio. A passive clamp circuit is applied in the converter to recycle the energy of leakage inductance and reduce voltage stress of the main power switch. This leads to utilize a power switch with low on-state resistance and low voltage-rating that decreases the conduction losses. Several advantages include low operating duty cycle, high voltage conversion ratio, low turn ratio of the coupled inductor, leakage inductance reverse recovery, reduced voltage stress of semiconductors, alleviation of diodes reverse recovery issue and high efficiency make the presented topology appropriate for sustainable energy applications such as photovoltaic systems. The operation principle and steady-state analysis of the suggested topology in continuous conduction mode (CCM) are expressed in detail. Also, design procedure and theoretical efficiency analysis of the proposed topology are presented. Moreover, a comparison study is performed to demonstrate the superiority of the presented converter over several similar recently proposed DC-DC converters. Finally, the proposed DC-DC converter feasibility and performance are justified through fabricated 216 W laboratory prototype at 50 kHz switching frequency.
1 December 2020 in Solar Energy
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Journal Article
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Masoud AlilouMasoud Alilou
Masoud Alilou
BTBehrouz Tousi
Behrouz Tousi
Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
26 July 2021 in IEEE Access
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Journal Article
Open access
EMElham Mokaramian
Elham Mokaramian
Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
FSFarzad Sedaghati
Farzad Sedaghati
ASAmin Safari
Amin Safari
Hassan Haes AlhelouHassan Haes Alhelou
Hassan Haes Alhelou
The increasing demand for energy carriers has expanded the use of energy hubs that employ distributed demand response programs to improve power system reliability and efficiency. Moreover, the unstable behavior of renewable resources, as well as the indeterminate electrical and thermal demands, create major problems for energy hub operation. Inspired by this, this paper presents a day-ahead scheduling framework for energy hubs (EH) in energy and reserve markets considering two main objectives of economy and pollution emission. The studied energy hub consists of a novel hybrid energy storage facility based on a fuel cell, wind power, photovoltaic energy, and a particular fuel cell unit in the presence of elastic demand. This multi-component system participates in energy and reserve markets as a single entity to optimize energy hub operation. The proposed method also models the uncertainty of wind speed, photovoltaic irradiance, and load using the Mont-Carlo method. The energy hub risk level is analyzed using the conditional value at risk (CVaR) approach to increase the EH operation and efficiency. The proposed multi-objective energy hub model is solved using the MINLP method in General Algebraic Modeling System (GAMS) to minimize operation cost and pollution emission. Finally, to prove the effectiveness of adding a new E-fuel energy storage system and considering uncertainties on energy hub operation, the proposed method is compared with other reported models.
16 March 2021 in IET Renewable Power Generation
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Journal Article
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LBLeila Bagherzadeh
Leila Bagherzadeh
Hossein SHAYEGHIHossein SHAYEGHI
Hossein SHAYEGHI
SPSasan Pirouzi
Sasan Pirouzi
Miadreza Shafie-khahMiadreza Shafie-khah
Miadreza Shafie-khah
João P. S. CatalãoJoão P. S. Catalão
João P. S. Catalão
This study presents the optimal model of the coordinated flexible energy and self‐healing management (C‐FE&SH‐M) in the active distribution network (ADN) including renewable energy sources (RESs), electric vehicles (EVs) and demand response program (DRP).The flexible energy management (FEM) is extracted using coordination between the RESs, EVs and DRP. The self‐healing method (SHM) is related to multi‐agent system‐based restoration process (MAS‐based RP) that finds the optimal restoration pattern at the fault condition according to the different zone agents (ZAs) distributing along with the network. This method minimizes the difference between energy cost and flexibility benefit related to the FEM part and difference between the number of switching operation and priority loads restored based on the SHM part. Also, this problem subjects to power flow equations, RESs and active loads constraints, restoration process formulation and system operation limits. Stochastic programming is used to model the uncertainty of loads, energy prices, RESs and EVs. Hereupon, the suggested strategy is implemented on the 33‐bus radial distribution network and it is solved by the crow search algorithm (CSA). Ultimately, the obtained results imply the high flexibility and security of the operation, incorporating the proposed strategy, and delineate the optimal restoration scheme for the ADN.