Automatic Control of Hybrid Renewable Energy System Using Artificial Neural Network
ANN- Artificial Neural networks, Real power, Harmonics, Point of common coupling, Reactive power.
Hybrid renewable energy systems are the most preferred generation systems than the conventional one. The attributes which makes it more preferable are like low fuel cost, pollution free and eco-friendly as well. Besides its series of advantages it has some disadvantages like presence of harmonics and grid connected issues where it fails to have a control over reactive power. These disadvantages can be overcome by using artificial neural network. The artificial neutral network (ANN) is the computational model based on the structure and functions of biological neural networks. It is the one of the best methods which enables automatic control over the hybrid renewable systems. This paper mainly focus on the control of the real and reactive power, power factor and total harmonic distortion. A successful control of this will eventually increase the efficiency of the system and hence quality power can be supplied to the consumers. Our proposed system deals with the use of artificial neural network between the point of common coupling and the grid. Current from the point of common coupling is compared with the reference signal by ANN. In accordance to the output, power injected into the grid is varied to maintain the real power.