Prediction of solar Stirling power generation in smart grid by GA-ANN model. (2017) - Sameti, Mohammad; Jokar, Mohammad Ali; Astaraei, Fatemeh Razi
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.