Improving Supply Chain Resiliency through Solar Panel Delivery Optimization

Abstract

Following NextEra Energy Resources’ accelerated growth and disruptions in the solar panel supply chain, their solar panel allocation process is becoming more complex. This process results in a schedule that determines when to deliver close to 150 million solar panels to more than fifty project sites under development and construction, while balancing requirements from multiple stakeholders. Due to project and contract interdependencies, modifying the equipment delivery schedule leads to costs that have consequential impacts. This thesis presents and implements a novel mixed integer programming model to determine the optimal schedule for delivering solar panels to project sites. The model abstracts impactful and quantifiable costs and minimizes them to propose a realistic solution. It produces a schedule in significantly less time than the current manual approach by finding a feasible solution in less than 15 minutes. The thesis introduces three scenarios of supply chain disruptions that mimic real-world events, demonstrating the model’s flexibility and helping NextEra Energy Resources adapt to future supply chain disruptions.