The processes of liberalization of electricity markets are having effect on power companies by making their decision process even more difficult in medium-term and long-term planning; such as production planning, maintenance, construction of new facilities etc. Various simulation methods of power system are available to deal with complex issues and also for consideration of strategic objectives. The aim is to predict behaviour of electricity market in a given time period with simulations based on a limited number of input data. Two such simulation methods are demonstrated in this paper: graphoanalytical probabilistic production cost simulation and Monte Carlo simulation made in DIgSILENT software. Model of thermal power plants, wind power model, calculation of water value of dispatchable hydro power and calculation of relevant electric market system indices, by creating equivalent load duration curve, is shown using graphoanalytical method. Unlike the graphoanalytical method DIgSILENT simulator considers the real structure of system, primarily transmission capacity with its technical constraints. Reliability test system was selected for Monte Carlo simulation with different scenario parameters, such as load increase and input of new generating capacities, making a total of 3 simulations. Important technical aspects of the power system, such as the adequacy of capacity and security of supply, are output variables of these simulations - with particular emphasis on the introduction of cogeneration biomass power plants with smaller installed generation capacity that are added into the generation mix. Comparison of simulations shows that graphoanalytical method has limited use in practice if more complex systems are considered, while computer simulation represents an appropriate choice in defining the strategic behaviour of participants in electricity market. Used software in its current version is unable to display all of the key indices of market quality using Monte Carlo method, which represents the only disadvantage of computer simulation.