Short-Term Load Forecasting of a Distribution Transformer using Self-Organizing Fuzzy Neural Networks

Short-Term Load Forecasting of a Distribution Transformer using Self-Organizing Fuzzy Neural Networks

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Part of #Short-Term Load Forecasting of a Distribution Transformer using Self-Organizing Fuzzy Neural Networks# :

Publishing year : 2015

Conference : Seventh National Conference on Electrical and Electronic Engineering of Iran

Number of pages : 5

Abstract: The distribution of transformer load prediction is very important in the control of future smart grids and the economical interfacing of Distributed Resources (DRs) to distribution networks. A distribution transformer connects DRs to the main grid. Exact distribution transformer load forecasting makes an economical DRs scheduling possible. Therefore, in this paper, a self-organizing fuzzy neural network (SOFNN) is introduced to perform a five-minute load forecasting for a real-life distribution transformer in the Lorestan Electric Power Distribution Company (LEPDC). Simulation results for active and reactive powers show that the proposed SOFNN outperforms ANFIS.