This work introduces a Genetic Algorithm–based optimization framework designed for distribution networks with high penetration of distributed energy resources (DERs). Distribution systems have traditionally not involved much automation. To better integrate the use of renewable energy resources into the grid, to improve the voltage stability of distribution grids, to improve the grid protection and to reduce harmonics, one needs to select and control devices with adjustable reactive. NLR is working to advance foundational science in distributed optimization and control into approaches for integrating distributed infrastructures into our energy systems. Current research and development efforts aim to leverage advances in optimization and control to develop distributed control. This study presents a multi-objective optimization framework based on a Genetic Algorithm (GA) to improve voltage profiles, minimize active power losses, and enhance resilience in a radial distribution network.
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