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Prof. Dr. Saeid Gholami Farkoush
Yeungnnam University

Basic Info


Research Keywords & Expertise

0 Smart Grid
0 power system
0 Electric Vehicle
0 FACT Devices
0 Grounding Grid

Honors and Awards

Best Conference paper Award

The Korean Institute of Illuminating and Electrical Installation Engineers Conference


University Full Scholarship Program 2011 for Studying Ph.D.

Yeungnam University, Korea




Career Timeline

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Short Biography

I received the B.S. degree in electrical engineering from Azad University, Ardebil, Iran, in 2005, and the M.S. from the Department of Electrical Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran in 2008, and the Ph.D. degree from in the dept. of electrical engineering at Yeungnam University, Gyeongbuk, Korea, in 2017. I am currently Assistant Professor in the dept. of electrical engineering at Yeungnam University. My current research interests include power factor correction system for EV chargers in the smart grid by using FACTS devices.

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Project

Project Goal: Power system protection

Starting Date:01 May 2017

Current Stage: Finished

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Project

Project Goal: Power optimization

Starting Date:01 November 2015

Current Stage: Finished

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Journal article
Published: 15 June 2021 in Sustainable Energy Technologies and Assessments
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This study was an attempted to present an organized structure of double-fed induction generator wind power plant with power oscillation damper (POD) in operational way and adjustable error-driven stabilizer to increase low-band oscillation reacted to their impacts in the energy system in state of charging. A novel non-linear stabilizer is suggested in the current research to compensate for the drawback of traditional stabilizers in monitoring the oscillation conditions which are internal and consequently to achieve better results in a greater range of disorders. Actually, the applied stabilizer is elastic and error-driven. Adjusting parameters of the suggested method properly plays a vital role in its efficiency. Consequently, the parameters set serve as an optimization problem which is solved by an algorithm of virus colony search (VCS) with several objectives time-domain and complex-domain. The reason behind using this algorithm is to make sure that solutions are not entrapped in local optima under the condition that the grid undergoes optimizing a great number of variables. The developed probabilistic method in frequency-domain chooses just the most favorable positions under the condition of providing the whole generators with stabilizer due to decreasing the initial expense. Lastly, a novel improved virus colony search algorithm with several objectives is implemented to provide solution for optimum adjusting of suggested stabilizer and power oscillation damper variables which serve as an optimization problem with several objectives. Confirming the efficiency of the planned method was conducted via concurrent use of eigenvalue analysis and time domain non-linear modeling in terms of various functioning states. The low frequency oscillations (LFOs) could be damped in the optimal way and as a result the stability performance of the case study system would develop meaningfully.

ACS Style

Guangli Fan; Fan Yang; Peixi Guo; Chengfeng Xue; Saeid Gholami Farkoush; Jaber Karimpoor Majd. A new model of connected renewable resource with power system and damping of low frequency oscillations by a new coordinated stabilizer based on modified multi-objective optimization algorithm. Sustainable Energy Technologies and Assessments 2021, 47, 101356 .

AMA Style

Guangli Fan, Fan Yang, Peixi Guo, Chengfeng Xue, Saeid Gholami Farkoush, Jaber Karimpoor Majd. A new model of connected renewable resource with power system and damping of low frequency oscillations by a new coordinated stabilizer based on modified multi-objective optimization algorithm. Sustainable Energy Technologies and Assessments. 2021; 47 ():101356.

Chicago/Turabian Style

Guangli Fan; Fan Yang; Peixi Guo; Chengfeng Xue; Saeid Gholami Farkoush; Jaber Karimpoor Majd. 2021. "A new model of connected renewable resource with power system and damping of low frequency oscillations by a new coordinated stabilizer based on modified multi-objective optimization algorithm." Sustainable Energy Technologies and Assessments 47, no. : 101356.

Journal article
Published: 23 March 2021 in Journal of the Optical Society of America B
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We demonstrate a reconfigurable optical bandpass filter based on subwavelength grating (SWG) waveguide operating in the Bragg reflection regime and integrated with a cavity of the phase-change material ${\rm Ge}_2{\rm Sb}_2{\rm Te}_5$ (GST). Partial crystallization of GST provides us with an efficient tool to modify the effective optical properties of the GST governed by the effective medium theory. Consequently, the resonance wavelength as well as the transmission peak can be tuned in the designed filters. Numerical simulations indicate that the presented SWG waveguide with a single GST cavity offers up to 8.8 nm redshift while the transmission amplitude can be modulated from 0.544 to 0.007. The presented Fabry–Perot structure can also be used as a nonvolatile optical switch with a high extinction ratio of about 24 dB at the wavelength of 1548.3 nm.

ACS Style

S. Hadi Badri; M. M. Gilarlue; Saeid Gholami Farkoush; Sang-Bong Rhee. Reconfigurable bandpass optical filters based on subwavelength grating waveguides with a Ge2Sb2 Te5 cavity. Journal of the Optical Society of America B 2021, 38, 1283 -1289.

AMA Style

S. Hadi Badri, M. M. Gilarlue, Saeid Gholami Farkoush, Sang-Bong Rhee. Reconfigurable bandpass optical filters based on subwavelength grating waveguides with a Ge2Sb2 Te5 cavity. Journal of the Optical Society of America B. 2021; 38 (4):1283-1289.

Chicago/Turabian Style

S. Hadi Badri; M. M. Gilarlue; Saeid Gholami Farkoush; Sang-Bong Rhee. 2021. "Reconfigurable bandpass optical filters based on subwavelength grating waveguides with a Ge2Sb2 Te5 cavity." Journal of the Optical Society of America B 38, no. 4: 1283-1289.

Journal article
Published: 22 March 2021 in Applied Optics
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Subwavelength engineering and utilizing phase-change materials with large contrast in their optical properties have become powerful design tools for integrated silicon photonics. Reversible phase-transition of phase-change materials such as ${\rm{G}}{{\rm{e}}_2}{\rm{S}}{{\rm{b}}_2}{\rm{T}}{{\rm{e}}_5}$ (GST) provide a new degree of freedom and open up the possibility of adding new functionalities to the designed devices. We present an optical filter based on a silicon subwavelength grating (SWG) waveguide evanescently coupled to phase-change material loading segments arranged periodically around the SWG core. The effect of the GST loading segments’ geometry and their distance from the SWG core on the filter’s central wavelength and bandwidth are studied with three-dimensional finite-difference time-domain simulations. The employment of GST in the structure adds a switching functionality with an extinction ratio of 28.8 dB. We also examine the possibility of using the proposed structure as a reconfigurable filter by controlling the partial crystallization of the GST offering a blueshift of more than 4 nm.

ACS Style

S. Hadi Badri; Saeid Gholami Farkoush. Subwavelength grating waveguide filter based on cladding modulation with a phase-change material grating. Applied Optics 2021, 60, 2803 -2810.

AMA Style

S. Hadi Badri, Saeid Gholami Farkoush. Subwavelength grating waveguide filter based on cladding modulation with a phase-change material grating. Applied Optics. 2021; 60 (10):2803-2810.

Chicago/Turabian Style

S. Hadi Badri; Saeid Gholami Farkoush. 2021. "Subwavelength grating waveguide filter based on cladding modulation with a phase-change material grating." Applied Optics 60, no. 10: 2803-2810.

Journal article
Published: 16 February 2021 in IEEE Access
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This paper introduces a transactive market design for a combined heat and power (CHP) based energy hub (hub). The proposed model allows a hub operator to supply the hub’s demands by participating in the day-ahead market and a transactive market with CHPs and also in the real-time market by using a recursive moving window algorithm. The proposed local energy market for a hub operator and CHPs is based on the double auction P2P trading mechanism. The model develops an optimal bidding and offering strategies for CHPs and hub operators, respectively, to achieve optimal transactions. The CHPs may be equipped with boiler unit and heat buffer tank (HBT) beside CHP units. The uncertain nature of the hub’s electrical load, real-time and day-ahead markets prices and wind speed is addressed by using robust optimization. The procedure aimed at minimizing the worst-case CHP-based hub’s demand procurement cost even though flexibly regulating the solution robustness. Further, case studies investigate the economic impact of robustness on the hub’s cost.

ACS Style

Manijeh Alipour; Mehdi Abapour; Sajjad Tohidi; Saeid Gholami Farkoush; Sang-Bong Rhee. Designing Transactive Market for Combined Heat and Power Management in Energy Hubs. IEEE Access 2021, 9, 31411 -31419.

AMA Style

Manijeh Alipour, Mehdi Abapour, Sajjad Tohidi, Saeid Gholami Farkoush, Sang-Bong Rhee. Designing Transactive Market for Combined Heat and Power Management in Energy Hubs. IEEE Access. 2021; 9 (99):31411-31419.

Chicago/Turabian Style

Manijeh Alipour; Mehdi Abapour; Sajjad Tohidi; Saeid Gholami Farkoush; Sang-Bong Rhee. 2021. "Designing Transactive Market for Combined Heat and Power Management in Energy Hubs." IEEE Access 9, no. 99: 31411-31419.

Original research
Published: 02 January 2021 in Journal of Ambient Intelligence and Humanized Computing
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In recent years, the introduction of practical and useful solutions to solve the non-intrusive load monitoring (NILM) as one of the sub-sectors of energy management has posed many challenges. In this paper, an effective and applicable solution based on deep learning called convolutional neural network (CNN) is employed for this purpose. The proposed method with the layer-to-layer structure and extraction of features in the power consumption (PC) curves of each household appliances will be able to detect and distinguish the type of electrical appliances (EAs). Likewise, the load disaggregation for the total home PC will be based on identifying the PC patterns of each EA. To do this, experimental evaluation of reference energy data disaggregation dataset (REDD) related to real-world data and measurement at low frequency is used. The PC curves of each EA are used as input data for training and testing the network. After initial training and testing by the PC data of EAs, the total PC of building obtained from the smart meter are used as input for each network in order to load disaggregation. The trained networks prove to be able to disaggregate the total PC for REDD houses 1, 2, 3, and 4 with a 96.17% mean accuracy. The presented results show the precision and efficiency of the suggested technique for solving NILM problems compared to other used methods.

ACS Style

Arash Moradzadeh; Behnam Mohammadi-Ivatloo; Mehdi Abapour; Amjad Anvari-Moghaddam; Saeid Gholami Farkoush; Sang-Bong Rhee. A practical solution based on convolutional neural network for non-intrusive load monitoring. Journal of Ambient Intelligence and Humanized Computing 2021, 1 -15.

AMA Style

Arash Moradzadeh, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Amjad Anvari-Moghaddam, Saeid Gholami Farkoush, Sang-Bong Rhee. A practical solution based on convolutional neural network for non-intrusive load monitoring. Journal of Ambient Intelligence and Humanized Computing. 2021; ():1-15.

Chicago/Turabian Style

Arash Moradzadeh; Behnam Mohammadi-Ivatloo; Mehdi Abapour; Amjad Anvari-Moghaddam; Saeid Gholami Farkoush; Sang-Bong Rhee. 2021. "A practical solution based on convolutional neural network for non-intrusive load monitoring." Journal of Ambient Intelligence and Humanized Computing , no. : 1-15.

Journal article
Published: 29 December 2020 in Energy Strategy Reviews
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Participation of nondispatchable renewable energy resources (RER) such as wind turbines (WT) and photovoltaic (PV) systems is one of the main challenges of these clean energy resources. Due to the uncertain nature of these resources, predictions of their amount of power in the day-ahead market is very difficult and associated with error. This paper introduces a novel model for the participation of the mentioned resource in the day-ahead power market based on error and economic loss minimization. An intra-market (IM) model was considered to update the predicted power of these resources before the planned time horizon. Furthermore, a new probabilistic forecasting model was proposed for uncertain parameters in both the day-ahead and intramarket. The mentioned model included an integrated system of renewable energy with another distributed generation, storage device, and demand response to compensate for all resource and load economic losses. By this approach, it can be claimed that, all microgrid participants i.e., load, producer and storage, have more profits in comparison with the power supply individually. To demonstrate the efficiency of the proposed model, we considered a test case that consisted of a wind turbine, PV, fuel cell, storage unit, and demand response, by taking into account the day-ahead, intra and unbalanced market. In this case study, daily, weekly, and monthly analyses were performed. The simulation results revealed the effectiveness and performance of the proposed modelling in comparison with other participation model.

ACS Style

Lan Dai; Shumin Sun; Ting Li; Saeid Gholami Farkoush. Probabilistic model for nondispatchable power resource integration with microgrid and participation in the power market. Energy Strategy Reviews 2020, 33, 100611 .

AMA Style

Lan Dai, Shumin Sun, Ting Li, Saeid Gholami Farkoush. Probabilistic model for nondispatchable power resource integration with microgrid and participation in the power market. Energy Strategy Reviews. 2020; 33 ():100611.

Chicago/Turabian Style

Lan Dai; Shumin Sun; Ting Li; Saeid Gholami Farkoush. 2020. "Probabilistic model for nondispatchable power resource integration with microgrid and participation in the power market." Energy Strategy Reviews 33, no. : 100611.

Journal article
Published: 24 December 2020 in Journal of Cleaner Production
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A novel power and freshwater generation system is presented based on the gas turbine cycle as the main system and Kalina cycle and humidification-dehumidification desalination unit as the waste heat recovery subsystems. To evaluate the system’s performance, energy, exergy, economic, and environmental analysis is performed. The optimum performance of all optimization scenarios is found by applying the multi-objective genetic algorithm and using the technique for order of preference by similarity to ideal solution (TOPSIS) method. The sensitivity analysis is also performed to assess the effect of various parameters on the system’s performance. By using Net present value, the feasibility of the plant for the construction from the economic viewpoint is analyzed. Based on the base case results, the performance metrics are evaluated as the energy efficiency of 0.9398, exergy efficiency of 43.11%, sum unit cost of 19.44 $.GJ−1, Levelized total emission of 63571 kg.kW−1, and freshwater production rate of 10.39 kg.s−1. Among all system components, the combustion chamber is contributed to the highest rate of exergy destruction rate by 16544 kJ.s−1. For fuel cost of 3 $.GJ−1 and electricity price of 0.09 $.kWh−1, the total net present value for the plant lifetime is obtained 1.736×107 $, which means that the plant is feasible for construction from the economic perspective. Based on the optimization results, the maximum value of exergy efficiency and minimum value of Levelized total emission are obtained in LTE-ε-TGOR scenario by 43.84% and 62602 kg.kW−1, respectively.

ACS Style

Pan Ding; Xiaojuan Liu; Hongling Qi; Hongtao Shen; Xiaochan Liu; Saeid Gholami Farkoush. Multi-objective optimization of a new cogeneration system driven by gas turbine cycle for power and freshwater production. Journal of Cleaner Production 2020, 288, 125639 .

AMA Style

Pan Ding, Xiaojuan Liu, Hongling Qi, Hongtao Shen, Xiaochan Liu, Saeid Gholami Farkoush. Multi-objective optimization of a new cogeneration system driven by gas turbine cycle for power and freshwater production. Journal of Cleaner Production. 2020; 288 ():125639.

Chicago/Turabian Style

Pan Ding; Xiaojuan Liu; Hongling Qi; Hongtao Shen; Xiaochan Liu; Saeid Gholami Farkoush. 2020. "Multi-objective optimization of a new cogeneration system driven by gas turbine cycle for power and freshwater production." Journal of Cleaner Production 288, no. : 125639.

Journal article
Published: 28 November 2020 in Journal of Energy Storage
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The renewable energy resources (RESs) are naturally generated such as wind turbine, photovoltaic cell and etc., which can be used in microgrids. In this paper, a heuristic method has been proposed for load demand management based on the produced power and the forecasted market clearing price in which the uncertain parameters of uncontrolled resources and load demand is taken into consideration. With the intermittent output of RESs due to the uncertainty in solar irradiation and wind speed, the forecasting unit will inform the operator on the power production levels in the upcoming 24 h. The energy storage system (ESS) is added to the network based on the modeling of demand management to induce operation costs of the microgrid (MG). Afterwards, the optimization unit utilizes a new decision-making criterion and the particle swarm optimization (PSO) method to define generation schedule and resources’ economic dispatch to reduce consumers’ costs. Moreover, the proposed model is used to guarantee voltage stability and basic load support. The simulation results are presented by three scenarios with and without price-based demand response. The comparisons among the results illustrate the effectiveness of demand management on system costs. As shown in simulation results, demand response has highly reduced total cost (20–30% related to the case without that) where voltage dip (maximum 1.4%) and power deviation (maximum 1.25%) are also improved in the microgrid.

ACS Style

Chong Wang; Zheng Zhang; Oveis Abedinia; Saeid Gholami Farkoush. Modeling and analysis of a microgrid considering the uncertainty in renewable energy resources, energy storage systems and demand management in electrical retail market. Journal of Energy Storage 2020, 33, 102111 .

AMA Style

Chong Wang, Zheng Zhang, Oveis Abedinia, Saeid Gholami Farkoush. Modeling and analysis of a microgrid considering the uncertainty in renewable energy resources, energy storage systems and demand management in electrical retail market. Journal of Energy Storage. 2020; 33 ():102111.

Chicago/Turabian Style

Chong Wang; Zheng Zhang; Oveis Abedinia; Saeid Gholami Farkoush. 2020. "Modeling and analysis of a microgrid considering the uncertainty in renewable energy resources, energy storage systems and demand management in electrical retail market." Journal of Energy Storage 33, no. : 102111.

Journal article
Published: 05 August 2020 in International Journal of Hydrogen Energy
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Due to the unstable situation of the atmosphere, the wind power forecasting of the wind farms (WFs) will be so complex. This unsteady provides an opportunity in order to investigate the wind power probabilistic prediction. This paper proposed a novel method based on Gaussian Processes (GPs) to improve the probabilistic prediction of a group or regional of WFs. Covariance Functions (CFs), known as Kernel, are the key ingredient in using GPs. One of the most usually of these functions is Squared Exponential (SE), which is applied with other functions to the model of the proposed method. Thus, different groupings of CFs are investigated comprehensively. Additionally, evaluating the accuracy of the prediction is carried out. This study went through two types of comparisons of dynamic and static GP as well as direct and indirect prediction plan. The result of the comparison between dynamic and static GP revealed that the dynamic GP generates keen Prediction Intervals (PIs). Besides, comparing the accuracy of direct and indirect prediction plan, it shows that indirect prediction strategy brings about wider PIs with higher coverage probability on the part of net demand prediction. Moreover, the proposed model provides precise results of forecasted energy in every time step.

ACS Style

Ali Ahmadpour; Saeid Gholami Farkoush. Gaussian models for probabilistic and deterministic Wind Power Prediction: Wind farm and regional. International Journal of Hydrogen Energy 2020, 45, 27779 -27791.

AMA Style

Ali Ahmadpour, Saeid Gholami Farkoush. Gaussian models for probabilistic and deterministic Wind Power Prediction: Wind farm and regional. International Journal of Hydrogen Energy. 2020; 45 (51):27779-27791.

Chicago/Turabian Style

Ali Ahmadpour; Saeid Gholami Farkoush. 2020. "Gaussian models for probabilistic and deterministic Wind Power Prediction: Wind farm and regional." International Journal of Hydrogen Energy 45, no. 51: 27779-27791.

Journal article
Published: 26 May 2020
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ACS Style

Saeid Gholami Farkoush. Reactive Power Optimization using Grey Wolf Optimizer. 2020, 1 .

AMA Style

Saeid Gholami Farkoush. Reactive Power Optimization using Grey Wolf Optimizer. . 2020; ():1.

Chicago/Turabian Style

Saeid Gholami Farkoush. 2020. "Reactive Power Optimization using Grey Wolf Optimizer." , no. : 1.

Journal article
Published: 07 April 2020 in Energies
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This paper proposes a novel high voltage conversion gain DC/DC boost converter for renewable energy applications and systems. The proposed converter utilizes a three-winding coupled inductor. The presented converter benefits from a unique advantage, as the actual turn ratio of the coupled inductor is decreased in the charging state of the coupled inductor. However, while the inductor is discharging, the actual turn ratio is increased. This feature leads to a very high voltage conversion gain. Furthermore, a passive clamp circuit is employed to recover the leakage current of the coupled inductor. The voltage stresses on the semiconductors are also reduced. In addition, the average current of the primary side of the coupled inductor is zero. This will reduce the total energy stored in the passive elements of the converter. The paper analyzes the Continuous Conduction Mode (CCM) and the operation principles of the presented converter are thoroughly derived. A 250 W laboratory hardware prototype is prepared to verify the proper operation of the presented converter. The obtained experimental results validate the feasibility of the presented converter.

ACS Style

Amir Farakhor; Mehdi Abapour; Mehran Sabahi; Saeid Gholami Farkoush; Seung-Ryle Oh; Sang-Bong Rhee. A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current. Energies 2020, 13, 1780 .

AMA Style

Amir Farakhor, Mehdi Abapour, Mehran Sabahi, Saeid Gholami Farkoush, Seung-Ryle Oh, Sang-Bong Rhee. A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current. Energies. 2020; 13 (7):1780.

Chicago/Turabian Style

Amir Farakhor; Mehdi Abapour; Mehran Sabahi; Saeid Gholami Farkoush; Seung-Ryle Oh; Sang-Bong Rhee. 2020. "A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current." Energies 13, no. 7: 1780.

Journal article
Published: 01 April 2020 in Journal of Cleaner Production
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The fluctuation of the wind speed and direction is due to the stochastic nature of the wind and the enforcing atmospheric pressure. Accordingly, the output power forecasting of the wind farms (WFs) will be difficult. In this paper, a novel method based on Gaussian Processes (GPs) is proposed to improve the probabilistic prediction of the WF levels and regional WFs. The Covariance Functions (CFs) are the key ingredient in using GPs. Thus, different groupings of CFs are investigated comprehensively. The GP includes different types as dynamic, static, direct, indirect, and combined structures, which are investigated in this study. The results of comparison between dynamic and static GP, reveal that the dynamic GP generates keen Prediction Intervals (PIs). In addition, with comparing the accuracy of direct and indirect prediction plan, it shows that indirect prediction strategy brings about wider PIs. The various evaluation metrics have applied to benchmark the different methods performance, and its results show that the indirect–dynamic GP has better performance than other combined structures of GP as well as other methods, in both WF levels and regional WFs, while its maximum error has obtained as about 5% less than others. Moreover, the proposed model provides precise results of forecasted energy in every time steps in both deterministic and probabilistic wind power forecasting. The compared results between indirect–dynamic GP and other structures show the highest average coverage error, about 1% and 2.2% higher in the regional level and WF levels, respectively, the lowest prediction interval nominalized average width, about 5% and 15% lower in the regional level and WF levels, respectively, and the highest interval sharpness, about 2% and 5% higher in the regional level and WF levels, respectively.

ACS Style

Hao Xue; Yuchen Jia; Peng Wen; Saeid Gholami Farkoush. Using of improved models of Gaussian Processes in order to Regional wind power forecasting. Journal of Cleaner Production 2020, 262, 121391 .

AMA Style

Hao Xue, Yuchen Jia, Peng Wen, Saeid Gholami Farkoush. Using of improved models of Gaussian Processes in order to Regional wind power forecasting. Journal of Cleaner Production. 2020; 262 ():121391.

Chicago/Turabian Style

Hao Xue; Yuchen Jia; Peng Wen; Saeid Gholami Farkoush. 2020. "Using of improved models of Gaussian Processes in order to Regional wind power forecasting." Journal of Cleaner Production 262, no. : 121391.

Journal article
Published: 01 March 2020 in International Journal of Hydrogen Energy
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ACS Style

Shanshan Chen; Saeid Gholami Farkoush; Sebastian Leto. Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique. International Journal of Hydrogen Energy 2020, 45, 10059 -10069.

AMA Style

Shanshan Chen, Saeid Gholami Farkoush, Sebastian Leto. Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique. International Journal of Hydrogen Energy. 2020; 45 (16):10059-10069.

Chicago/Turabian Style

Shanshan Chen; Saeid Gholami Farkoush; Sebastian Leto. 2020. "Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique." International Journal of Hydrogen Energy 45, no. 16: 10059-10069.

Research article
Published: 22 December 2019 in Complexity
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To ensure a safe and trustworthy pattern in contradiction to the possible faults, a precise, reliable, and fast relaying strategy is of high importance in an electrical power system. These challenges give the impression of being more refined in multi-loop distribution systems. More recently, overcurrent relays (OCRs) have evolved as proficient counteragents for such cases. In this way, inaugurating an optimal protection coordination strategy is accepted as the primary precondition in guaranteeing the safe protection of the coordination strategy. This study is aimed at lessening the overall operational time of the main relays in order to reduce the power outages. The coordination problem is conducted by adjusting only one parameter, namely the time multiplier setting (TMS). In electrical power relaying coordination, the objective function to be minimized is the sum of the overall operational time of the main relays. In the prescribed work, the coordination of the OCRs in the single- and multi-loop distribution network is realized as an optimization issue. The optimization is accomplished by means of JAYA algorithm. The suggested technique depends on the idea that the result acquired for a certain issue ought to pass near the finest result and avert the worst result. This technique involves only the common control factors and does not involve specific control factors. JAYA is adopted to OCR problem and run 20 times with the same initial condition for each case study, and it has been realized that for every run, the JAYA algorithm converges to the global optimum values requiring less number of iterations and computational time. The results obtained from JAYA algorithm are compared with other evolutionary and up-to-date algorithms, and it was determined that JAYA outperforms the other techniques.

ACS Style

Abdul Wadood; Saeid Gholami Farkoush; Tahir Khurshaid; Jiang-Tao Yu; Chang-Hwan Kim; Sang-Bong Rhee. Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems. Complexity 2019, 2019, 1 -13.

AMA Style

Abdul Wadood, Saeid Gholami Farkoush, Tahir Khurshaid, Jiang-Tao Yu, Chang-Hwan Kim, Sang-Bong Rhee. Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems. Complexity. 2019; 2019 ():1-13.

Chicago/Turabian Style

Abdul Wadood; Saeid Gholami Farkoush; Tahir Khurshaid; Jiang-Tao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems." Complexity 2019, no. : 1-13.

Journal article
Published: 01 July 2019 in IEEE Access
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The directional overcurrent relays (DOCRs) coordination is a useful tool in guaranteeing the safe protection of the power system by the proper coordination of primary and backup protection systems. The optimization model of this problem is non-linear and highly constrained. The main objective of this paper is to develop a hybridized version of the Whale optimization algorithm referred to as HWOA for the optimal coordination of the DOCRs. The hybridization is done by deploying the simulated annealing (SA) in the WOA algorithm in order to improve the best solution found after each iteration and enhance the exploitation by searching the most promising regions located by the WOA algorithm, which leads toward a globally optimum solution. The proposed algorithm has been applied to five test systems, including the IEEE 3-bus, 8-bus, 9-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed HWOA are compared with those obtained using the traditional WOA and a number of up-to-date algorithms. The obtained results show the effectiveness of the proposed HWOA in minimizing the relay operating time for the optimal coordination of the DOCRs.

ACS Style

Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. An Improved Optimal Solution for the Directional Overcurrent Relays Coordination Using Hybridized Whale Optimization Algorithm in Complex Power Systems. IEEE Access 2019, 7, 90418 -90435.

AMA Style

Tahir Khurshaid, Abdul Wadood, Saeid Gholami Farkoush, Jiangtao Yu, Chang-Hwan Kim, Sang-Bong Rhee. An Improved Optimal Solution for the Directional Overcurrent Relays Coordination Using Hybridized Whale Optimization Algorithm in Complex Power Systems. IEEE Access. 2019; 7 ():90418-90435.

Chicago/Turabian Style

Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "An Improved Optimal Solution for the Directional Overcurrent Relays Coordination Using Hybridized Whale Optimization Algorithm in Complex Power Systems." IEEE Access 7, no. : 90418-90435.

Journal article
Published: 19 June 2019 in IEEE Access
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This paper discusses the step and touch voltages, based on body resistance, in a grounding grid after a lightning strike at a 434/21 kV substation. To ensure grounding grid safety, the maximum step and touch voltage should not exceed the safety criteria defined by IEEE Std. 80. In this paper, ATP-EMTP and a genetic algorithm are used to analyze and optimize the step and touch voltages in a power grid. The voltages are calculated under normal conditions of a lightning strike at a power system. Thevenin’s theorem is applied to calculate the step and touch voltages. A genetic algorithm is applied in ATP-EMTP to obtain the minimum level of step and touch voltages in the grounding grid after lightning strikes the power system. The step and touch voltages at different positions of the grounding grid are explained in this paper using ATP-EMTP and a genetic algorithm. The computer simulation shows that the proposed scheme is highly feasible and technically attractive.

ACS Style

Saeid Gholami Farkoush; Abdul Wadood; Tahir Khurshaid; Chang-Hwan Kim; Muhammad Irfan; Sang-Bong Rhee. Reducing the Effect of Lightning on Step and Touch Voltages in a Grounding Grid Using a Nature-Inspired Genetic Algorithm With ATP-EMTP. IEEE Access 2019, 7, 81903 -81910.

AMA Style

Saeid Gholami Farkoush, Abdul Wadood, Tahir Khurshaid, Chang-Hwan Kim, Muhammad Irfan, Sang-Bong Rhee. Reducing the Effect of Lightning on Step and Touch Voltages in a Grounding Grid Using a Nature-Inspired Genetic Algorithm With ATP-EMTP. IEEE Access. 2019; 7 (99):81903-81910.

Chicago/Turabian Style

Saeid Gholami Farkoush; Abdul Wadood; Tahir Khurshaid; Chang-Hwan Kim; Muhammad Irfan; Sang-Bong Rhee. 2019. "Reducing the Effect of Lightning on Step and Touch Voltages in a Grounding Grid Using a Nature-Inspired Genetic Algorithm With ATP-EMTP." IEEE Access 7, no. 99: 81903-81910.

Journal article
Published: 16 June 2019 in Energies
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In power systems protection, the optimal coordination of directional overcurrent relays (DOCRs) is of paramount importance. The coordination of DOCRs in a multi-loop power system is formulated as an optimization problem. The main objective of this paper is to develop the whale optimization algorithm (WOA) for the optimal coordination of DOCRs and minimize the sum of the operating times of all primary relays. The WOA is inspired by the bubble-net hunting strategy of humpback whales which leads toward global minima. The proposed algorithm has been applied to six IEEE test systems including the IEEE three-bus, eight-bus, nine-bus, 14-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed WOA are compared with those obtained by other up-to-date algorithms. The obtained results show the effectiveness of the proposed WOA to minimize the relay operating time for the optimal coordination of DOCRs.

ACS Style

Abdul Wadood; Tahir Khurshaid; Saeid GholamiFarkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems. Energies 2019, 12, 2297 .

AMA Style

Abdul Wadood, Tahir Khurshaid, Saeid GholamiFarkoush, Jiangtao Yu, Chang-Hwan Kim, Sang-Bong Rhee. Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems. Energies. 2019; 12 (12):2297.

Chicago/Turabian Style

Abdul Wadood; Tahir Khurshaid; Saeid GholamiFarkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems." Energies 12, no. 12: 2297.

Journal article
Published: 12 June 2019 in IEEE Access
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In an electrical power network linear and non-linear models are used for directional overcurrent relay (DOCR) coordination issue by applying different heuristic techniques. Nature inspired algorithms (NIA) have found great interest in power system optimization issues. This article proposes the recently developed meta-heuristic technique known as Firefly Algorithm (FA) that mimics the flashing behavior of fireflies. The implementation of the proposed algorithm has been utilized to solve the coordination of Directional Over-current Relay (DOCR) problems. The main aim of this work is to find out the optimum values of the Time Dial Setting (TDS) to minimize the relay operating time. The modifications to original FA has been implemented in this paper to solve the DOCR coordination issues. Self-adaptive weight and experience-based learning strategy are added in the original FA, named as improved firefly algorithm (IFA). In IFA, a self-adaptive weight is presented to change the propensity of moving the best solution and ignoring the worst solution. In addition, an experience-based learning system is created and utilized arbitrarily to keep up the populace-assorted variety and improve the exploration capacity. The IFA has been tested on IEEE 6 and 30-bus systems and tested on IEEE 9-bus system for numerical DOCRs and the results had been verified by a comparative study with other optimization techniques. The obtained results show that the IFA provides efficient and promising results compared to other meta-heuristic techniques mentioned in the literature. The IFA has been successfully implemented on MATLAB software programming.

ACS Style

Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Jiangtao Yu; Sang-Bong Rhee. Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays. IEEE Access 2019, 7, 78503 -78514.

AMA Style

Tahir Khurshaid, Abdul Wadood, Saeid Gholami Farkoush, Chang-Hwan Kim, Jiangtao Yu, Sang-Bong Rhee. Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays. IEEE Access. 2019; 7 (99):78503-78514.

Chicago/Turabian Style

Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Jiangtao Yu; Sang-Bong Rhee. 2019. "Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays." IEEE Access 7, no. 99: 78503-78514.