Generation adequacy indices (GAI) calculations are performed not only for electrical power system development problems but also for on-line control problems. Liberalization of power and energy market along with increased focus on renewable energy sources, which is motivated by both ecological and economical incentives, has led to comprehensive changes in power systems. Practically, the main mathematical method for calculating GAI of an electrical grid with complex structure is Monte-Carlo simulation (MCS) technique. It can provide sufficiently accurate results, but the simulation consumes really huge amount of computational time, especially for large power systems. Generation capacity that has to be installed in a power system for meeting reliability criteria depends not only on system demand but also on generation mix. The problem at hand is to improve computational efficiency of the GAI calculating technique without decrease in calculations accuracy. In order to solve the problem, this paper proposes an analytical method for GAI calculations, that is referred to as supplied demand algorithm (SDA). The paper compares the MCS technique and the SDA. The analyzed methods have been developed using the C# and VBA programming language. Input data for the methods includes generation mix data, generation and load probability indices. The comparison results allow to select the proper method for the GAI calculations and show the main factors that affect the resulting GAI.