Energy, economic and environmental performance simulation of a hybrid renewable microgeneration system with neural network predictive control

The comparison was performed in terms of ability to maintain the desired indoor comfort levels, primary energy consumption, operating costs and carbon dioxide equivalent emissions during a week of the heating period and a week of the cooling period. The results showed that the ANN approach is potentially able to alleviate the intensity of thermal discomfort associated with overheating/overcooling phenomena, but it could cause an increase in unmet comfort hours. The analysis also highlighted that the ANNs based strategies could reduce the primary energy consumption (up to around 36%), the operating costs (up to around 81%) as well as the carbon dioxide equivalent emissions (up to around 36%).