Author : Sharweel Shende 1
Date of Publication :29th March 2018
Abstract: Hybrid power generation is the need of the hour. Solar power and wind power are the best available non-conventional energy sources. To extract the maximum electrical power from these sources at various atmospheric conditions intelligent algorithm is the solution. This paper presents improved hybrid power generation by using the artificial neural network. ANN provides improved power generation by improving the maximum power point tracking of sun and with the available wind in the atmosphere. In this paper, an adaptive control using perturbs and observes method is proposed. Neural network controller gives the enhanced and improved power output. Operational analysis is carried out by using MATLAB Simulink
Reference :
-
- Cong-Hui Huang “modified neural network for dynamic control and operation of a hybrid generation system.”vol.12, december 2014.
- Verlag Berlin Heidelberg 2017 “Intelligent hybrid power generation system using new hybrid fuzzy neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode .”
- Rati Anjan Sabat, S.M. Ali and Rashmita Panigrahy 2015 IRJET “design and simulation of reliable and efficient hybrid solar wind power system using improved MPPT P& O algorithm”.
- MD. Asiful Islam and MD Ashfanoor Kabir TENCON 2011 “neural network based maximum power point tracking of photovoltaic arrays”.
- N. Prakash , R. Ravikumar , I. Gnanambal 2012“ a stand alone hybrid power generation system by MPPT control based on neural networks .”
- Naoufel Khaldi , Hassan Mahmoudi Malika Zazi , Youseef Barradi 2014 “implementation of a
- A photovoltaic panel model in MATLAB/SIMULINK
- A hybrid wind solar energy system . A new rectifier stage topology