This work presents a Mixed Integer Linear Programming (MILP) model for the optimal interconnected power systems planning over a time horizon of one year. The power generation units include thermal units, hydroelectric units and renewable units (wind and solar power plants). Each system can produce power in order to satisfy its demand and/or supply energy to another system via interconnections. The time horizon of interest, consists of a representative day for each month of the year. The model considers the possibility of building new units selected from a set of proposed ones, as well as expanding the capacity of existing renewable energy units (generation expansion planning), stressing the flexibility that electricity trade provides to power systems. The possibility of expanding the existing interconnection capacity between systems is also considered (transmission expansion planning). The proposed optimization model relies on balance, design, operational and logical constraints. Environmental-related constraints for the annual production of a series of emission types including CO2, NOx, SOx and PMx emissions are also taken into account. The main objective is the minimization of the total annualized cost. The applicability of the proposed model is illustrated in several case studies involving different objectives, such as the minimization of the total cost and the minimization of the emissions. Finally, an extensive sensitivity analysis is performed in order to investigate the effects of key input parameters on the final power generation policies.