Prediction of the energy consumption is the most
important topic for planning to build an energy power station. This energy
power station can be non-renewable sources power plants or renewable power
plants like wind and solar. Prediction of the energy consumption also figures
out load modeling problem in new smart grid applications. In this study, energy
consumption model is developed for temperature control of a greenhouse.
Artificial Neural Network based modeling is advanced with temperature of inner,
temperature of outer and temperature of soil. So, these temperatures are inputs
in the ANN based model. In addition, the output of the ANN is energy demand
that is strongly related with temperature data.
Prediction of the energy consumption is the most
important topic for planning to build an energy power station. This energy
power station can be non-renewable sources power plants or renewable power
plants like wind and solar. Prediction of the energy consumption also figures
out load modeling problem in new smart grid applications. In this study, energy
consumption model is developed for temperature control of a greenhouse.
Artificial Neural Network based modeling is advanced with temperature of inner,
temperature of outer and temperature of soil. So, these temperatures are inputs
in the ANN based model. In addition, the output of the ANN is energy demand
that is strongly related with temperature data.
Primary Language | English |
---|---|
Subjects | Engineering |
Journal Section | Research Article |
Authors | |
Publication Date | March 1, 2019 |
Submission Date | November 28, 2017 |
Published in Issue | Year 2019 Volume: 22 Issue: 1 |
This work is licensed under Creative Commons Attribution-ShareAlike 4.0 International.