توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Evaluating the effects of Uncertainty in Fuel Price on Transmission Network Expansion Planning Using IDPSO approach
اطلاعات انتشار: هشتمین همایش ملی انرژی، سال
تعداد صفحات: ۹
Transmission Network Expansion Planning (TNEP) is one of the important parts of power system planning which determines the number, time and location of new lines for adding to transmission network so that the load is adequately supplied. There are several factors affecting TNEP, which sometimes make the problem results inaccurate and impractical because of their complicacy. Therefore, it should be tried to possibly introduce them in TNEP problem by using appropriate scientific tools. One of these parameters which is significantly effective in TNEP result, is the uncertainty of different parameters such as load growth, location of power plants in horizon year, and especially fuel price which indirectly affects the transmission lines loading and consequently the optimality of transmission plans via changing of loss and unsupplied load which are dependent on the power generation of power plants. Thus, in this paper, by considering the uncertainty of fuel price, in different scenarios, its determining role in TNEP result has been evaluated using IDPSO algorithm. To study the proposed approach, the 18–bus real network of Azerbaijan Regional Electrical Company is considered.<\div>

۲Application of IDABC and DABC Approaches for TNEP Problem Considering the Loss and Uncertainty in load growth
نویسنده(ها): ، ،
اطلاعات انتشار: بیستمین کنفرانس مهندسی برق ایران، سال
تعداد صفحات: ۶
The main goal of Transmission Network Expansion Planning (TNEP) is determination of the number, time and location of new lines to be added to transmissionnetwork. 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 inan 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 Artificial Bee Colony Algorithm (IDABC) is employed for thesolution of STNEP problem considering simultaneously theloss and uncertainty in load demand. Finally, the proposed approach is applied to the real transmission network ofAzerbaijan Regional Electrical Company located in northwest of Iran. Comparison of the results obtained from the proposed method with those of Discrete Artificial BeeColony Algorithm (DABC) approach verifies the effectiveness and accuracy of the method in STNEP problem.<\div>

۳Application of IBSFLA and BSFLA Approaches for Locating of Fault Indicators in Distribution Networks
اطلاعات انتشار: کنفرانس منطقه ای سیرد، سال
تعداد صفحات: ۸
Fast and accurate detection of fault location in distribution networks is one of the important issues in operation of electric lines. In this paper, application of IBSFLAand BSFLA algorithms has been proposed for placement of fault indicators in distribution networks. By using this method, the problem of locating faultindicators can be solved faster and more accurately by minimizing of cost function. In this paper, in addition to describing theImproved Binary Shuffled Frog Leaping Algorithm (IBSFLA) algorithm, the fault indicator placement has been implemented using this method on a test system, and thesimulation results have been compared with those of BSFLA algorithm, and the accuracy and fastness of the proposedmethod has been demonstrated.<\div>

۴Associative learning and memory duration of Trichogramma brassicae
اطلاعات انتشار: Progress in Biological Sciences، چهارم،شماره۱، ۲۰۱۴، سال
تعداد صفحات: ۱۰
Learning ability and memory duration are two inseparable factors which can increase theefficiency of a living organism during its lifetime. Trichgramma brassice Bezdenko (Hym.:Trichogrammatidae) is a biological control agent widely used against different pest species.This research was conducted to study the olfactory associative learning ability and memory duration of T. brassicae under laboratory conditions. According to our results, T. brassicae showed olfactory learning ability in response to conditioned odors, and this learned olfactory stimuli lasted for 20 hours. In a second experiment, the effects of frequent experiences on the memory duration of females were studied. A direct relationship between frequent experiences and memory duration was observed. When exposed to a conditioned odor, wasps’ memory duration increased in response to the number of experiences. Memory was observed at 28 h after one extra conditioning. The duration of the associative memory lasted 42 hours when 2 extra experiences were given, 50 hours after 3 experiences, and 58 hours after 4 extra conditioning experiences. Our results showed that T. brassicae can associate new odors to host existence, and they will show increased memory duration after multiple experiences.
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