Optimizing the producing and consuming the Energy in Smart houses by using Neural Networks

introducing a hybrid solar cell system and wind turbine for optimizing the production of electric energy and consequently decreasing the consumption of town electricity For accessing to thesis goal and presenting a more accurate method, 7 districts of different climates were chosen in Iran. By providing sun shine and wind data of these districts and analyzing them we started the operation. The daily sun shine data and wind related data were set based on every 10 minute time, and it made the deduction more difficult. The format of all data was in PDF. By working hard for some hours a joint interval of date were chosen between them, and it made their format similar. By analyzing the data by Excel and Visual Basic, the amount of energy for every district were obtained. Then by using neural network of the Matlab software of 2015 and 2016, the amount of receiving wind and sun energy were anticipated. The result of these measures was the possibility of evaluating the ability of hybrid production of energy in the districts which we are surviving on them, in the districts with high and low production, the possibility of making the intelligent house with very low level of town electricity consumption and even with zero level of consumption.

Keywords:

production and consumption of energy , intelligent house , neurotic network , and hybrid sun cell system and turbine