Artificial Neural Network based Load Forecasting Approach-seminar report in pdf

ANN based Load Forecasting Approach report in PDF

CONTENTS PAGE NO. ACKNOWLEDGEMENT 2 CHAPTER-1: INTRODUCTION 4 CHAPTER-2: LOAD FORECASTING 7 CHAPTER-3: MACHINE LEARNING 11 CHAPTER-4: NEURAL NETWORK 13 CHAPTER-5: CONCLUSION AND FUTURE WORK 31 REFERENCES 32

CHAPTER-1: INTRODUCTION LOAD FORECASTING: Load forecasting is a technique used by power or energy-providing companies to predict the power/energy needed to meet the demand and supply equilibrium. The accuracy of forecasting is of great significance for the operational and managerial loading of a utility company.

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Most forecasting methods use numerical techniques or AI algorithms such as recession, neural networks and indistinct logic. Load forecasting can be short-term (a few hours), medium-term (a few weeks up to a year) or long-term (over a year). 

The end-use and econometric approach is used for medium- and long-term forecasting, whereas the similar-day 

approach, various regression models, time series, neural networks, statistical learning algorithms and fuzzy logic have been devised for short-term forecasting.