COMPARATIVE ANALYSIS OF SHORT TERM LOAD FORECASTSING OF SOLAR ENERGY USING ANFIS AND NN

Dr.Usha Surendra; Dr.Amruth R T; Abhishek K; Adarsh Mallik; Arpitha D; Swetha K T

Volume : V, Issue : VII, July - 2015

COMPARATIVE ANALYSIS OF SHORT TERM LOAD FORECASTSING OF SOLAR ENERGY USING ANFIS AND NN

Dr. Usha Surendra, Dr. Amruth R T, Abhishek K, Adarsh Mallik, Arpitha D, Swetha K T

Abstract :

 In the current scenario the optimum utilisation of renewable energy along with the grid tie up energy is gaining more importance. In the renewable energy solar is the cleanest and abundantly available energy. For cost effective and better utilisation of solar power, at present 10 solar panels has been installed at NIE IT of 0.24KW each. This makes a total capacity of 2.4KW, out of which only 1.6KW energy is utilized. The remaining energy can be made useful. So load forecasting is the important aspect for optimisation in the power. Solar energy is radiant light and heat from the sun harnessed using a range of ever–evolving technologies such as solar heating, photovoltaic’s, solar thermal energy, solar architecture and artificial photosynthesis. Load forecasting is a forecast, an estimate, or a prediction of how much electricity will be needed by the residences, companies, and other institutions in the future. The data of complete one year of various weeks, months has been collected. With this reference data the calculation has been made for the prediction of future two years. The prediction results has analysed the comparative analysis has been made for theoretical analysis using neural network and artificial neural fuzzy inference system (ANFIS). With these analyses the best fit technique has been suggested in the proposed work.