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RISS 인기검색어
- 검색키워드
- 저자 : Mahmoud Kiani (검색결과 4 건)
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Javadian, Abdolmajid,Zadehbagheri, Mahmoud,Kiani, Mohammad Javad,Nejatian, Samad The Korean Institute of Power Electronics 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.10
Due to the pattern of growth for electricity consumption, there is a need for developing power networks and transmission lines. The power transmission capacity of lines is limited due to a host of factors. Thus, these lines need series and parallel compensations to reduce losses, increase efficiency, and promote system security. In this paper, flexible alternating current transmission system (FACTS) devices including static VAR compensators (SVC) as parallel compensators, thyristor-controlled series compensation (TCSC) as a series compensator, and high-voltage direct current (HVDC) bonding are modeled. In addition, comprehensive modeling of the simultaneous application of these three devices for load flow is performed, and the effects of these types of compensations are compared. The obtained comprehensive model was implemented on MATLAB software using the Newton-Raphson method on two 9-bus WSCC and 5-bus test system. In this case, the calculation speed and convergence were reduced when compared to applying devices individually due to the increase in equations and the addition of new terms to the load flow equations. Furthermore, more losses were observed in this model, which can probably be improved using an optimal power flow and optimal placement of the devices in the network.
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Using Hybrid Wavelet Approach and Neural Network Algorithm to Forecast Distribution Feeders
Bagheri Mehdi,Zadehbagheri Mahmoud,Kiani Mohammad Javad,Zamani Iman,Nejatian Samad 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3
In this paper, using an algorithm based on the combination of data based on neural network virology and bacterial nutrition algorithm, improves the performance of the neural network prediction method. Also, the selection of two types of downstream and upstream filters in the wavelet transformation increases the predictive efficacy of neurological prediction. Based on the results, the optimized clustered neural network method has a more favorable response than the other methods. By selecting the appropriate filter and multichannel processing method, the maximum error percentage has improved by 15%. However, compared to the neural network prediction method, the proposed method has more computational volume due to the use of wavelet transform and also three times the use of neural prediction. Due to the large number of layers and used neurons, the neural network method has a much higher computational volume than the linear prediction method, where the linear prediction method has a higher error than the proposed method depending on the data used for training.
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Bahareh Rastegar,Ehsan Saljoughi,Seyed Mahmoud Mousavi,Shirin Kiani 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.9
Hydrophilic membranes composed of polyphenylsulfone (PPSU)/polyethylene glycol hexadecyl ether (Brij-58), with noticeable properties and performance in the filtration of dye solution, were prepared for the first time. Scanningelectron microscopy (SEM) images were utilized to examine the morphology of the obtained membranes. Attenuatedtotal reflection Fourier-transform infrared (ATR-FTIR) spectra, water contact angle, water uptake capacity, andtensile properties of the membranes confirmed that Brij-58 remained in the structure of the obtained membranes dueto the high molecular weight of the additive. Higher water contact angle and water uptake capacity obtained withincreasing the Brij-58 concentration showed enhanced membrane hydrophilicity. The addition of Brij-58 and increasingits concentration was followed by a constant increase in pure water flux (PWF) and antifouling property of themembrane. According to the results, the incorporation of 10 wt% Brij-58 into the polymeric solution contributed toalmost 54-fold higher water flux and approximately 36% higher flux recovery ratio (FRR), while the rejection ofdisperse blue was only slightly reduced.
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Biodiversity status of Tulipa (Liliaceae) in Iran inferred from molecular characterization
Davoud Asgari,Alireza Babaei,Mohammad Reza Naghavi,Mahmoud Kiani 한국원예학회 2020 Horticulture, Environment, and Biotechnology Vol.61 No.3
Here, we used data generated from amplifi ed fragment length polymorphism (AFLP) analysis to address the biodiversitystatus and taxonomic relationships among 47 wild accessions representing 9 species of the genus Tulipa in Iran. A high levelof genetic diversity within the genus was observed; the most distant taxa were T. humilis and T. schrenkii , while the highestdegree of similarity was found between T. montana and T. bifl ora . Twelve AFLP primer sets amplifi ed 342 fragments, ofwhich 304 were polymorphic (88.1%). The average number of polymorphic bands per AFLP primer pair was 28.5. A hierarchicalcluster analysis was carried out on the genetic profi le of the taxa, and the results mostly reconfi rmed the recognizedtaxonomy of the genus. However, we found evidence for recognition of a new subgenus for T. biebersteiniana .
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