COMPUTATIONAL INTELLIGENCE-BASED ASSESSMENT AND IMPROVEMENT OF VOLTAGE STABILITY

Abstract

As the global demand for electricity rises and the integration of renewable resources will become extra accepted, making sure the stableness, manipulate, and protection of power systems has by no means been greater important. Traditional methods are an increasing number of insufficient for coping with the complex dynamics of contemporary power grids. This evaluation presents a complete examination of the function of synthetic intelligence (AI) and related clever techniques in addressing those demanding situations. It explores the software of AI, deep mastering (DL), device studying (ML), and metaheuristic optimization algorithms in improving energy machine balance and reliability. The evaluate additionally highlights the usage of fuzzy good judgment for decision-making under uncertainty, reinforcement studying for adaptive balance manage, and version predictive manage for proactive device management. Emphasis is positioned on the combination of Internet of Things (IoT) and massive information analytics for actual-time monitoring and optimization. Through case studies and giant literature assessment, the paper demonstrates the effectiveness of those advanced strategies in predictive upkeep, fault detection, and actual-time manipulate. The review identifies modern limitations and proposes future studies instructions, stressing the  need for robust, scalable, and flexible clever systems. This paper is a valuable useful resource for researchers, engineers, and policymakers, presenting an in depth expertise of the ability and future instructions of wise strategies in strength system.