Conductor size selection in radial distribution networks using robust optimization

This paper presents a robust optimization method for solving the conductor size selection problem in radial distribution networks with predefined topologies, considering load uncertainty. The method addresses the increasing unpredictability of power demand driven by electric vehicles and renewable energy sources. We employ the column and constraint generation algorithm, known for its efficiency in robust optimization, ensuring that all technical constraints are met, even under worst-case demand scenarios. The objective function incorporates annual energy losses and construction costs as annualized expenses, offering a balanced evaluation of economic and operational efficiency. Numerical results from case studies demonstrate the method’s effectiveness, showing optimal conductor sizes for various load scenarios and validating its application for reconductoring in medium voltage distribution networks. The results highlight the model’s ability to balance cost and reliability under uncertainty, providing a robust solution for real-world distribution network planning.