Enhancing Voltage Stability and DG Penetration in Smart Grids Through a Modified Genetic Algorithm Approach for Optimal Reactive Power Planning

Contemporary power networks confront several obstacles, including rising energy consumption, an ageing utility infrastructure, and the negative effects on the environment caused by traditional electric generation's emissions of greenhouse gases. Decentralized intelligence, conversation technologies, and computerized control systems are the driving forces behind the smart grid, which distribution power networks must undergo an evolution to in order to boost renewable energy penetration while simultaneously addressing reliability and security concerns. Optimal design of this smart grid can only be achieved by using intelligent optimization methods in light of this new perspective. To find the best spot for dispersed generators to provide reactive power, this study introduces a generalized optimization framework. When dealing with Reactive Power Management problems with many objectives, evolutionary algorithms are used to identify the best solution. An example of a microgrid provides a more in-depth look at how genetic algorithms evolve.