GA-Based Optimization of DG Sizing and Placement for Long-Term Cost-Effective Planning of Wind and Solar Energy Integration

This study introduces a two-step methodology for optimizing the allocation and sizing of distributed generation (DG) units within a distribution network to minimize power losses. Initially, a genetic algorithm (GA) is employed to determine the optimal placement and capacity of DG resources. The objective is to reduce grid losses and improve voltage stability while ensuring compliance with performance standards and security requirements in radial distribution networks. MATLAB software is used for this optimization. The second stage involves an economic analysis to select the optimal combination of photovoltaic and wind turbine systems over 25 years, based on the first stage's results, using HOMER Pro software. The research identifies the ideal quantity of DG units required to achieve minimal active power losses and reduce overall costs. The approach is validated through a comprehensive performance analysis of a 33-bus IEEE standard system, demonstrating its effectiveness in reducing losses and costs.