توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Inrush Current Identification in Power Transformers Using Weight Functions
نویسنده(ها): ، ، ،
اطلاعات انتشار: دوازدهمین کنفرانس دانشجویی مهندسی برق، سال
تعداد صفحات: ۴
Identification of inrush current from other existing faults is an important issue in protection of the power transformers. In order to analyze the inrush current and the single phase to ground fault current from the harmonic point of view, it is necessary that a proper method is presented for identifying these two currents. The proposed method is based on the weight functions of the calculated vectors by the positive sequence harmonic components of the inrush and the single phase o ground fault current. Regarding the variation range of the weight functions in this study, the usefulness of the proposed method is illustrated<\div>

۲APPLICATION OF IDPSO APPROACH FOR TNEP PROBLEM CONSIDERING THE LOSS AND UNCERTAINTY IN LOAD GROWTH
نویسنده(ها): ، ، ،
اطلاعات انتشار: ششمین کنفرانس بین‌المللی مسائل فنی و فیزیکی در مهندسی قدرت، سال
تعداد صفحات: ۵
The main goal of Transmission Network Expansion Planning (TNEP) is determination of the number, time and location of new lines to be added to transmission network. Up to now, different methods have been used to solve the static TNEP (STNEP). In most of them, this problem is implemented regardless of power loss and the uncertainty in the load demand. With respect to the importance of these two parameters (loss and uncertainty) and their key role in an effective and precise planning, the evaluation and solution of STNEP using more efficient methods can be very useful. Hence, in this paper, a new method named Improved Discrete Particle Swarm Optimization (IDPSO) is employed for the solution of STNEP problem considering simultaneously the loss and uncertainty in load demand. Finally, the proposed approach is applied to the real transmission network of Azarbaijan Regional Electrical Company located in northwest of Iran. Comparison of the results obtained from the proposed method with those of Discrete Particle Swarm Optimization (DPSO) approach verifies the effectiveness and accuracy of the method in STNEP problem.<\div>
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