ANN based Intelligent Energy Management for a Standalone Wind/Photovoltaic/Diesel Hybrid System with Battery Storage

  • Sangita Bapu Patil Research Scholar, Department of Electrical Engineering, S.G.G.S. Institute of Engineering & Technology, Nanded-431 606,
  • Laxman Madhavrao Waghmare Professor, Department of Instrumentation Engineering S.G.G.S. Institute of Engineering & Technology, Nanded-431 606, India.
Keywords: Artificial Neural Network (ANN), Multi-level Feed Forward Network, State of Charge, Photovoltaic system, Wind energy, Fuzzy Logic Controller, Energy Management Control.


Hybrid renewable energy sources (HRES) similar to PV, wind and diesel generator are the most charming configurations worn for various applications and most probably for the self-contained systems to generate power. While considering different sources Energy management control will be essential. An energy conservation control system is a computer assisted tool commonly used to monitor, measure and control the generation and transmission system performance. In this article surveillance of photovoltaic, diesel and wind with battery storage is introduced. The energy stability of favoured scheme is done by the Artificial Neural Network (ANN). In this approach Multi-level FFN (Feed Forward Network) which is the form of artificial neural network is used for governing process of the hybrid renewable energy source. The Levenberg Marquardt algorithm is an interconnection of perceptron’s in which the data and calculation will flow in an accurate direction from input to output. It is quite simple and easy to resolve the different operating procedures of the hybrid system on the basis of the time varying conditions. The process is implemented under MATLAB R2016a then the attained results are displayed and the comparison results are carried out with fuzzy logic controller and displays the feasibility of the suggested method.  


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