Aliasghar Baziar

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This paper proposes a new hybrid method based on support vector regression (SVR) to predict the load value of power systems accurately. The proposed method will use the SVR to overcome some deficiencies such as overfitting and complicated structure that exist in the neural network. In order to find the optimal values of the parameters, krill herd (KH)(More)
Through this article, a novel random structure is depicted to shape the uncertainty result of the active and reactive loads in the DSTATCOM allocation and problem in sizing. The planned technique has 2m+1 point approximation method (PEM) to capture the random associated with the anticipated fault of the loads. The aims are minimization of the entire active(More)
In order to handle large scale problems, this study has used shuffled frog leaping algorithm. This algorithm is an optimization method based on natural memetics that uses a new two-phase modification to it to have a better search in the problem space. The suggested algorithm is evaluated by comparing to some well known algorithms using several benchmark(More)
This article proposes a probabilistic frame built on Scenario fabrication to considerate the uncertainties in the finest action managing of Micro Grids (MGs). The MG contains different recoverable energy resources such as Wind Turbine (WT), Micro Turbine (MT), Photovoltaic (PV), Fuel Cell (FC) and one battery as the storing device. The advised frame is(More)
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