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Two models are proposed for forecasting global solar radiation. The forecasted values are used to predict the output power of photovoltaic systems installed in power systems and control the output of other generators to meet the electricity demand. One of the models is used for at least one-day-ahead demand and supply planning. The other model is used for three-hour-ahead demand and supply operation. The models are based on weather information and use descriptive statistics and binary trees respectively. The focus is on estimation of the anticipated variations in the forecasts and dealing with the nonlinearity of the relationship between the global solar radiation and the input variables. In addition, the smoothing effect of the errors is investigated and utilized when they are applied to wide area forecasting. The results show that they are promising in keeping the balance between demand and supply in power systems with photovoltaic systems installed.