In our day-to-day life, electricity has become the most necessary to lead an everyday life. Many researchers are working on practical methods and technologies for choosing the effective power source for the distribution to the smart girds. In this paper, Machine Learning (ML) andDeep Learning (DL) concepts have been used to predict the valuable source in different months of a year also the cost-effective in such situations. In this research work, optimizing the decision to choose the right start with optimized deep learning neural networks has been implemented. The results highlight the excellent responsiveness of optimized decisionsthrough the benefit of DNN.

Machine Learning, Deep Learning, Smart Gird, Predictive measures, Solar Source, Wind Mill, and Thermal Sources.