http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
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.
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.
Mahdi Rezaeian,Jamshid Kamali,Seyed Javad Ahmadi,Mohammad Amin Kiani 한국원자력학회 2017 Nuclear Engineering and Technology Vol.49 No.7
In order to perform dry interim storage and transportation of the spent-fuel assemblies of the BushehrNuclear Power Plant, dual-purpose casks can be utilized. The effectiveness of different neutron-shieldmaterials for the dual-purpose cask was analyzed through a set of calculations carried out using theMonte Carlo N-Particle (MCNP) code. The dose rate for the dual-purpose cask utilizing the recentlydeveloped materials of epoxy/clay/B4C and epoxy/clay/B4C/carbon fiber was less than the allowableradiation level of 2 mSv/h at any point and 0.1 mSv/h at 2 m from the external surface of the cask. Byutilization of epoxy/clay/B4C instead of an ethylene glycol/water mixture, the dose rates on the sidesurface of the cask due to neutron sources and consequent secondary gamma rays will be reduced by17.5% and 10%, respectively. The overall dose rate in this case will be reduced by 11%.