Enhanced Particle Swarm Optimization Algorithm for 6-Node Power Grid Planning Expansion

This represents a highly valuable and sophisticated program implemented in MATLAB, specifically designed for 6-node power grid planning expansion using an enhanced particle swarm optimization algorithm. The program features an improved algorithmic architecture that likely includes adaptive inertia weights, social learning factors, and convergence acceleration mechanisms to optimize grid configuration. In the power grid planning domain, this implementation holds significant practical value with its complex and refined coding structure that handles constraint satisfaction, load distribution optimization, and cost minimization. Through this program, engineers can achieve more efficient grid planning and expansion, enhancing both grid operational efficiency and reliability. The implementation includes key functions for population initialization, fitness evaluation considering power flow constraints, and dynamic particle position updating with boundary handling. Whether for academic research or practical applications, this program serves as a powerful tool for power grid planners and researchers, providing robust support through its well-structured MATLAB implementation containing optimization loops, constraint handling modules, and performance visualization components.