Md. Janibul Alam Soeb1, Muhammad Rashed Al Mamun2
Department of Farm Power and Machinery, Sylhet Agricultural University, Sylhet, Bangladesh.
Abstract: Now a day’s load forecasting leads an immense area of research in power system. It helps to generate the power with minimal cost and ensure the reliability of power systems. It is so much attractive because accurate load forecasting is a challenging task for its difficulties. This paper presents the load forecasting for the Power Grid Company Bangladesh Ltd. (PGCB) by using Advanced Back Propagation Algorithm. It is advanced because here the adaptation mechanism is used to update hidden layer. And it uses newly designed data set where only that kind of inputs are chosen which give the best prediction output. These inputs are chosen by trial and error method. The data are collected from PGCB to train the system. This paper has proposed to train the network in summer for reducing load shedding and in winter, holidays to minimize the power loss as well as the cost of generation. Experimental results show that the system provides the load forecasting with high accuracy.
Keywords: Load forecasting, PGCB, Artificial neural network, Back propagation algorithm.
Pages: 95 – 102 | Full PDF Paper