A Holistic Methodology to Identify Cost-Effective Smooth Routes for Power Transmission Lines

The design of cost-effective power line routes is a critical step towards elaborating a consistent network expansion plan. Although several attributes are considered by planning agents, the impact of sharp curvatures is typically neglected within the route design process, thus not accounting for the need for more expensive structures to support the power line. In this work, we tackle this issue by developing a holistic methodology that combines geoprocessing technologies with a novel combinatorial optimization technique to assist practitioners in identifying cost-effective smooth power line routes. For the latter, since the fundamental mathematical structure of the proposed tool falls into the class of a Quadratic Shortest Path Problem, an efficient dynamic programming algorithm is designed to handle the typical large-scale instances of power line tracing applications. The effectiveness of the proposed methodology is illustrated with a case study based on a real-world project of the Brazilian transmission sector.

I. Introduction

A recurrent challenge in most power systems around the globe is to plan and redesign its transmission network infrastructure seeking for an appropriate accommodation of the constantly growing demand level and variability in energy production within the daily system operation [1]. In the past years, this challenge, also known as Transmission Expansion Planning (TEP) problem, has been widely studied in technical literature with main focus on determining the set of transmission corridors that improves the system operation in the long run, with a least-cost expansion as primary objective [2], [3], [4]. In this context, due to its capital-intensive nature, it is critically important to evaluate a proper description of the power transmission line route within the candidate corridor and the respective implementation and construction costs in order to achieve a consistent expansion plan, both in technical and economical terms [5].