Artificial Super Intelligence Driven Electric Spring For Voltage Regulation

¹ Department of EEE, Associate Professor, Vidya Jyothi Institute of Technology, Hyderabad, 500075, India
² Department of EEE, Associate Professor, Vidya Jyothi Institute of Technology, Hyderabad, 500075, India
³ Department of EEE, Associate Professor, Vidya Jyothi Institute of Technology, Hyderabad, 500075, India
⁴ Department of EEE, Associate Professor, Vidya Jyothi Institute of Technology, Hyderabad, 500075, India
⁵ Department of ECE, Professor, KG Reddy College of Engineering and Technology, Hyderabad, 501504, Telangana, India

^* Corresponding author: naag198222@gmail.com

Abstract

This article details the design of an advanced smart grid model that utilizes an enhanced optimal variation strategy through the integration of renewable energy sources. A key innovation presented here is the development of a renewable energy-based smart grid system that incorporates an Artificial Super Intelligence Network (ASIN) to maintain a stable voltage profile and balanced reactive power levels throughout the grid. This goal is achieved by deploying solar energy source, along with ASI technique, for effective reactive power control using Electric Spring technology. The smart grid’s power demands are met by managing the reactive power levels through the integration of these renewable sources. A Feed Forward Neural Network is utilized to optimize power calculations, determining voltage profiles and power loss based on system load. The Electric Spring serves as an optimal VAR compensating device, ensuring that reactive power remains within permissible limits across the smart grid. The proposed system enhances the voltage profile, reduces power loss, and maintains reactive power balance in the grid. The implementation of this approach is carried out in a MATLAB/Simulink environment, where performance is analysed for different scenarios. The solar energy-powered smart grid effectively achieves its objectives in these cases. Notably, the integration renewable energy sources with the ASI Network results in an improved voltage profile of approximately 98.45%, with the profile rating increasing from 1.05 to 1.06 p.u. Additionally, real power loss is minimized from 3.75 MW to 3.52 MW.