Prediction of Electrical Output Power of Combined Cycle Power Plant Using Regression ANN Model

• 作者: Ahmed Hassan Ahmed Elkhawad Ali Elfaki
• 来源期刊: 电力能源(英文)
• 学科: 医学
• 关键词: NEURAL NETWORKS Regression Combined Power CYCLE MATLAB NEURAL NETWORKS TOOLBOX
• 年，卷（期）: 2018,（12）
• 页码范围: 17-38
• 页数: 22页
• 分类号: R73

摘要

Recently, regression artificial neural networks are used to model various systems that have high dimensionality with nonlinear relations. The system under study must have enough dataset available to train the neural network. The aim of this work is to apply and experiment various options effects on feed-foreword artificial neural network (ANN) which used to obtain regression model that predicts electrical output power (EP) of combined cycle power plant based on 4 inputs. Dataset is obtained from an open online source. The work shows and explains the stochastic behavior of the regression neural, experiments the effect of number of neurons of the hidden layers. It shows also higher performance for larger training dataset size;at the other hand, it shows different effect of larger number of variables as input. In addition, two different training functions are applied and compared. Lastly, simple statistical study on the error between real values and estimated values using ANN is conducted, which shows the reliability of the model. This paper provides a quick reference to the effects of main parameters of regression neural networks.