GGO Algorithm: A Nature-inspired Solution for High Renewable Energy Penetration in Grids

Renewable energy has grown due to emissions and fossil fuel depletion concerns.Smart grids, whether connected or not, have great renewable energy potential.Sector-wide improvements are needed for distributed generation (DG).City power should become safer and more reliable with advanced networks.Inspired by the Grey Lag Goose's migratory and adaptive behaviours, the Grey Lag Goose Optimization (GGO) algorithm improves DG integration in power grids with high renewable energy penetration.The GGO algorithm optimizes DG unit placement and sizing in radial distribution networks by dynamically adjusting exploration and exploitation phases.IEEE 33-and 69-node RDNs at 25%, 50%, and 75% PLs are used to analyze power loss and voltage profiles as a function of DG penetration.Unreliable renewables like wind and solar affect power quality.Grey Lag Goose Optimisation improved power quality by optimizing DG placement.GGO algorithm manages intermittent wind and solar power sources to maintain power quality and system stability, a smart grid management breakthrough.