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All Journal Control Systems and Optimization Letters
Sunita Pahadasingh Pahadasingh
Odisha University of Technology and Research
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Artificial Neural Network Optimized Load Forecasting of Smartgrid using MATLAB Bibhu Prasad Ganthia; Monalisa Mohanty; Sushree Shataroopa Mohapatra; Rosalin Pradhan; Subhasmita Satapathy; Shilpa Patra; Sunita Pahadasingh Pahadasingh
Control Systems and Optimization Letters Vol 1, No 1 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i1.14

Abstract

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.
Co-Authors Bibhu Prasad Ganthia Monalisa Mohanty Rosalin Pradhan Shilpa Patra Subhasmita Satapathy Sushree Shataroopa Mohapatra