آموزش الگوریتم بهینه سازی بر اساس یادگیری برای برنامه ریزی توان راکتیو
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|56398||2016||6 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Electrical Power & Energy Systems, Volume 81, October 2016, Pages 248–253
Reactive power planning is one of the most challenging problem for efficient and source operation of an interconnected power network. It requires effective and optimum co-ordination of all the reactive power sources present in the network. Recently, Teaching Learning Based Optimization (TLBO) algorithm is evolved and finds its application in the field of engineering optimization. In the proposed work TLBO based optimization algorithm is used for reactive power planning and applied in IEEE 30 and IEEE 57 bus system. The results obtained by this method are compared with the results obtained by other optimization techniques like PSO (Particle swarm optimization), Krill heard, HSA (Harmony search algorithm) and BB-BC (Big Bang-Big Crunch). At the end, TLBO appears as the most effective method for reactive power planning among all the methods discussed and can be considered as one of the standard method for reactive power optimization.