One-day-ahead 24-hours thermal energy collection forecasting based on time series analysis technique for solar heat energy utilization system

In recent years, introduction of alternative energy sources such as solar energy is expected. The solar heat energy utilization systems are rapidly gaining acceptance as some of the best solutions for the alternative energy sources. However, thermal energy collection of solar heat energy utilization system is influenced by solar radiation and weather conditions. In order to control the solar heat energy utilization system as accurate as possible, it requires method of solar radiation estimation. This paper proposes the thermal energy collection of solar heat energy utilization system based on solar radiation forecasting at one-day-ahead 24-hours thermal energy collection by using three different NN models. The proposed technique for application of NN is trained by weather data based on tree-based model, and tested according to forecast day. Since the tree-based-model classifies the meteorological data exactly, NN will train the solar radiation with smoothly. The validity of the proposed method is confirmed by computer simulations by use of actual meteorological data.