Presence of solar energy driven power sources has been increasing with remarkable trends in recent years. Such growth is mostly related to photovoltaic generation and it is a direct consequence of significant fall in costs for this technology. Such generation, together with load and wind power, requires forecasting in day-ahead operation planning. Furthermore, in power system studies, it is often necessary to simulate performance of such forecasts. This paper presents models for PV power forecast error simulation based on the stochastic process simulation methods. Specificities of PV power forecast error, autocorrelation, correlation and dependence of standard deviation on forecasting horizon, can be reproduced with this model. Furthermore, two distinct models are presented in this paper. First model simulates and superposes forecast error on known PV production time series. Second model is a further improvement of the first model incorporating PV production simulation for purpose of applications in the planning phase when actual data on production is unavailable. Proposed models provide an efficient solution for studies requiring PV power forecast error time series.