MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641048947 A) filed by Mohan Babu University, Tirupati, Andhra Pradesh, on April 17, for 'intelligent neural network based system for accurate electrical load forecasting in power systems.'
Inventor(s) include Dr. M. S. Sujatha; Ms. A. Vaishnavi; Ms. D. Bhavya Sree; Ms. Ganesh Harini; Mr. Golla Shanmukha Raghava; and Mr. Bukke Chanti Naik.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Electrical load forecasting plays a crucial role in modern power system planning and operation. Accurate prediction of electricity demand helps utilities maintain grid stability, optimize resource allocation, and reduce operational costs.The present invention proposes an intelligent forecasting system that utilizes neural network techniques to analyze and predict electrical load demand. The system evaluates the performance of different forecasting models including exponential smoothing, radial basis function neural networks, and co-active neuro-fuzzy inference systems. Historical load data along with environmental variables are used to train and evaluate these models. Advanced computational intelligence techniques enable the system to capture nonlinear relationships and complex patterns in electricity demand data. Performance evaluation is carried out using statistical metrics such as mean absolute error, root mean squared error, and mean absolute percentage error. The results demonstrate that neural network-based forecasting models provide improved accuracy and adaptability compared to traditional statistical techniques. The proposed system therefore offers a reliable and scalable solution for electrical load forecasting and can be integrated into modern smart grid infrastructures to enhance energy management and decision-making."
Disclaimer: Curated by HT Syndication.
