self organizing fuzzy neural network

The distribution transformer Load forecasting is very essential in the control of future smart grids and an 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. In this regard, this paper firstly introduces a new Self-Organizing Fuzzy Neural Network (SOFNN). Then, it applies SOFNN to perform a five-minute load forecasting for a real-life distribution transformer in Lorestan Electric Power Distribution Company (LEPDC). Simulation results for active and reactive powers show that the proposed SOFNN outperforms ANFIS.

The distribution transformer Load forecasting is very essential in the control of future smart grids and an 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. In this regard, this paper firstly introduces a new Self-Organizing Fuzzy Neural Network (SOFNN). Then, it applies SOFNN to perform a five-minute load forecasting for a real-life distribution transformer in Lorestan Electric Power Distribution Company (LEPDC). Simulation results for active and reactive powers show that the proposed SOFNN outperforms ANFIS.