Charging EV station forecasting and location model for Mexico’s private sector

Abstract

The decarbonization of the transport sector is critical for addressing climate change, with electric vehicles (EV) representing a pivotal solution. This thesis focuses on forecasting EV adoption and optimizing charging stations’ location in Mexico’s private sector. The study examines relevant national and international regulations and existing EV adoption models through a comprehensive literature review. Data collection incorporates national statistics, energy consumption records, and market reports on EV sales and adoption rates. Using statistical methods, the research develops multiple scenarios for EV adoption up to 2030. A mixed integer programming model is then constructed to maximize the profitability of charging station placements, considering constraints such as budget, parking availability, and electrical capacity. A detailed case study with anonymized data from Iberdrola’s clients is conducted, simulating the model to determine optimal charging station locations and configurations. The results provide valuable insights into the infrastructure needed to support the transition to EVs in Mexico, offering strategic recommendations for stakeholders. The study concludes with suggestions for future research, emphasizing the importance of real-time data and expanding the analysis to public charging infrastructure. This work aims to contribute significantly to Mexico’s sustainable energy transition and develop an efficient, widespread EV charging network.