Version 1
: Received: 8 October 2024 / Approved: 9 October 2024 / Online: 9 October 2024 (13:09:29 CEST)
How to cite:
Hernandez-Hurtado, U.; Medina-Marín, J.; Seck-Tuoh-Mora, J. C.; Hernández-Romero, N.; Martin-del-Campo, C. A Methodology for the Identification of Key Factors in Power System Planning: The Case of Mexico. Preprints2024, 2024100701. https://doi.org/10.20944/preprints202410.0701.v1
Hernandez-Hurtado, U.; Medina-Marín, J.; Seck-Tuoh-Mora, J. C.; Hernández-Romero, N.; Martin-del-Campo, C. A Methodology for the Identification of Key Factors in Power System Planning: The Case of Mexico. Preprints 2024, 2024100701. https://doi.org/10.20944/preprints202410.0701.v1
Hernandez-Hurtado, U.; Medina-Marín, J.; Seck-Tuoh-Mora, J. C.; Hernández-Romero, N.; Martin-del-Campo, C. A Methodology for the Identification of Key Factors in Power System Planning: The Case of Mexico. Preprints2024, 2024100701. https://doi.org/10.20944/preprints202410.0701.v1
APA Style
Hernandez-Hurtado, U., Medina-Marín, J., Seck-Tuoh-Mora, J. C., Hernández-Romero, N., & Martin-del-Campo, C. (2024). A Methodology for the Identification of Key Factors in Power System Planning: The Case of Mexico. Preprints. https://doi.org/10.20944/preprints202410.0701.v1
Chicago/Turabian Style
Hernandez-Hurtado, U., Norberto Hernández-Romero and Cecilia Martin-del-Campo. 2024 "A Methodology for the Identification of Key Factors in Power System Planning: The Case of Mexico" Preprints. https://doi.org/10.20944/preprints202410.0701.v1
Abstract
COP21 represented a starting point for several nations to develop and implement energy transition strategies to face and mitigate climate change, making the electrical power sector crucial in achieving the established goals and commitments. This research presents a 7-step methodology to improve decision-making in energy transition strategies for the power sector by integrating an economic dispatch optimization model based on linear programming to determine vulnerable aspects of power generation and transmission in strategic planning scenarios that could jeopardize the country’s energy transition. The application of the methodology is implemented under the open-source platform Python Optimization Modelling (PYOMO) and illustrated through a case study of the Mexican Electrical Power System (SEN) during the year 2025. The case study shows that the reserve margin fluctuated due to the variable renewable energy installed despite having a vast installed capacity to supply the country’s total demand. In addition, the results showed that most of the transmission lines had a congestion frequency higher than 90% of their capacity during most of the year. Two regions were identified as the best options for reducing greenhouse gas emissions by installing new power plants. Finally, most technologies reflected an under-generation, suggesting a high dependence on some fuels to supply the Mexican demand. The model’s programming is freely available in GitHub.
Keywords
Power systems, multi-time scenarios, economic dispatch, multi region scenarios, optimization models
Subject
Computer Science and Mathematics, Other
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
