Optimization Model Applied to the Generation of Electrical Energy for a Multi-Region Scenario

Introduction

Electrical energy is a fundamental resource for humanity to continue developing, which is necessary for economic growth and the increase in the well-being of society. This allows us to have a pleasant environment in homes, the operation of businesses and industries. (SENER, 2019). That is why in countries where their economy is increasing, the demand for electrical energy is also increasing. This is how the United Nations Development Program uses the Human Development Index to determine the development of countries.

In Mexico, the main energy generating company is the Federal Electricity Commission (CFE), which is a public organization that has total management of the national electricity fleet (CFE,2022). The energy generated in the country is conducted through an extension of 752 thousand kilometers of transmission and distribution lines, having a supply range for a total of 190 thousand locations present in the nation. This energy supply means that 97.60% of the national population is covered by electrical energy (Ramos-Gutiérrez et al., 2023). In recent years, there has been an increase in installed capacity in the country due to the increases in electricity demand that occur year after year. Currently, the National Electric System (SEN) has an effective capacity of 88,748 MW belonging to the public and private sectors (Secretaría de Energía, 2021). Many of the plants that make up the SEN are about to reach their life cycle, making it necessary to incorporate new generation plants.

The incorporation of new generation plants, as well as the increase in the demand for electrical energy brings with it a challenge for the administration of resources, at the time of efficient allocation of the loads to be generated in each of the plants that make up the system. This is due to the different variables and parameters that govern the operation of the plants. To have efficient planning, it is necessary to rely on optimization techniques that guarantee the efficient use of resources considering the operating characteristics of the system. Such optimization techniques according to Marquez (2014) have been applied for many years, such as Herrera (2009) for operation cost reduction, greenhouse gas emissions minimization using deep learning algorithms (Renjie Zhu et al., 2023), loss minimization of power through semi-definite programming (Glover 2003), among others.