Prediction of solar Stirling power generation in smart grid by GA-ANN model. (2017)

• Record Type: Journal Article
• Authors: Sameti, Mohammad; Jokar, Mohammad Ali; Astaraei, Fatemeh Razi
• Is Part Of: International journal of computer applications technology. Volume 55:Number 2(2017)
• Page Start: 147
• Page End: 157
• Publication Date: 2017
• Subjects: solar power -- solar energy -- Stirling heat engine -- smart grid -- artificial neural networks -- ANNs -- genetic algorithms -- power prediction -- power estimation -- power forecasting; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

A model based on the feed-forward Artificial Neural Network (ANN) optimised by the Genetic Algorithm (GA) is developed in order to estimate the power of a solar Stirling heat engine in a smart grid. Genetic Algorithm is used to decide the initial weights of the neural network. The GA-ANN model is applied to predict the power of the solar Stirling heat engine from a data set reported in literature. The performance of the GA-ANN model is compared with numerical data. The results demonstrate the effectiveness of the GA-ANN model.