Optimal placement and sizing of distributed generators into electrical distribution system

Abstract

Optimal placement and sizing of distributed generators (DG) are crucial for enhancing distribution network performance. This thesis presents an optimization strategy for placement and sizing of distributed generators to minimize active power losses and annual operational costs using a variety of meta-heuristic techniques. The power flow analysis employs the Backward/Forwards weep method, and the optimization is implemented in Matlab. Techniques such as Particle Swarm Optimization (PSO), Hippopotamus Optimization (HO), Horned Lizard Optimizer (HLOA), and GOOSE Optimizer are tested and compared. Additionally, a modifie dversion of the GOOSE algorithm has been introduced and compared with previous works. The Optimization process includes renewable energy sources like photovoltaic and wind turbine systems. A case study based on a real Egyptian distribution network validates the methodology. The Introduced modified GOOSE algorithm has shown significant reductions in active power loss and operational costs ,improved voltage profiles, and enhanced system stability. DG integration also increases grid resilience and reduces dependency on fossil fuels, highlighting the potential of optimized DG deployment in modern power systems.