Martinez-Villaseñor, LourdesLourdesMartinez-VillaseñorPonce, HiramHiramPonceMarmolejo Saucedo, José AntonioJosé AntonioMarmolejo SaucedoRamírez, Juan ManuelJuan ManuelRamírezHernández, AgustinaAgustinaHernández2023-07-242023-07-24201897830300449099783030044916https://scripta.up.edu.mx/handle/20.500.12552/429310.1007/978-3-030-04491-6_1In this paper, a deterministic dynamic mixed-integer programming model for solving the generation and transmission expansion-planning problem is addressed. The proposed model integrates conventional generation with renewable energy sources and it is based on a centralized planned transmission expansion. Due a growing demand over time, it is necessary to generate expansion plans that can meet the future requirements of energy systems. Nowadays, in most systems a public entity develops both the short and long of electricity-grid expansion planning and mainly deterministic methods are employed. In this study, an heuristic optimization approach based on genetic algorithms is presented. Numerical results show the performance of the proposed algorithm. © 2018, Springer Nature Switzerland AG.enGeneration and transmission problemGenetic algorithmsPower system planningArtificial intelligenceElectric power transmissionHeuristic algorithmsInteger programmingRenewable energy resourcesSoft computingConventional generationResource Types::text::book::book part