Renewable Integrated Grid Network towards Sustainability – A Study on the Stability Issues

Abstract

Energy derived from renewable sources in modern times has paved the way towards a sustainable and greener future. Although renewable energy is undisputedly the answer towards decarbonisation, there are certain challenges that need to be overcome before we can completely do away with the use of fossil fuels for power generation. Integrating renewable energy sources into power systems introduces inherent variability to electricity generation, creating a need for robust strategies to ensure system stability. This article addresses one of these challenges by developing a customized security-constrained probabilistic optimal power flow framework tailored for integrated renewable energy systems. The model incorporates solar and wind energy resources through the Two Point Estimate (2m-PEM) method, improving its accuracy and practicality. To enhance the effectiveness of this framework, two advanced evolutionary algorithms, specifically the Fox Inspired Optimization and Coronavirus Herd Immunity Optimizer, are utilized to identify optimal parameter settings for specific objectives. The results demonstrate the model's ability to maintain transient stability even in scenarios where fault clearing times are significantly extended. This study makes a significant contribution to the secure integration of renewable energy sources into power systems. It offers valuable insights into improving transient stability by employing a sophisticated combination of probabilistic optimization and evolutionary algorithms. These findings pave the way for a robust integration of renewable energy while adhering to the stringent stability requirements of modern power systems.