Artificial Neural Network Optimized Load Forecasting of Smartgrid using MATLAB

Bibhu Prasad Ganthia (Indira Gandhi Institute of Technology)
Monalisa Mohanty (SOA University)
Sushree Shataroopa Mohapatra (KIIT University)
Rosalin Pradhan (Indira Gandhi Institute of Technology)
Subhasmita Satapathy (Indira Gandhi Institute of Technology)
Shilpa Patra (Indira Gandhi Institute of Technology)
Sunita Pahadasingh Pahadasingh (Odisha University of Technology and Research)

Control Systems and Optimization Letters
Vol 1, No 1 (2023)

The motivation behind the research is the requirement of error-free load prediction for the power industries in India to assist the planners in making important decisions on unit commitments, energy trading, system security reliability, and optimal reserve capacity. The objective is to produce a desktop version of a personal computer-based complete expert system that can be used to forecast the future load of a smart grid. Using MATLAB, we can provide adequate user interfaces in graphical user interfaces. This paper devotes a study of load forecasting in smart grids, a detailed study of the architecture and configuration of Artificial Neural Network (ANN), Mathematical modeling and implementation of ANN using MATLAB, and a detailed study of load forecasting using the backpropagation algorithm.