Abstract-Grey system theory is the one of the most important research of uncertainty system, developed into a set of address information is not a complete system. This story realizes the correct description and effective supervision in operation action and evolution law of system, mainly through generating, exploring and extracting valuable information to predict the unknown information value. Dynamic fore casting model is needed due to the uncertain nature of the load predicting process specifically when load changes is corelated to the tropical temperature effect in Indonesia. A grey predicting approach is implemented in this paper to solve dynamic short term load forecasting in local substation of the Indonesian high voltage grid, as provided by Jawa Bali load control and operator center (PLN P3B Gandul). Traditional GM (1,1) model is presented to compare with the GM (1,2) for weekday and weekend load conditions refer to the temperature variation pattern during the year 2009. GM(1,2) model denotes the relationship hourly load demand affected to the tropical climate change variable, i.e., local ambient temperature. The daily load curve for Cawang and Cibatu substation, as representing Jakarta Area, was used to validate the models. Typical combination Grey model specified in Tropical Climates was implemented to capture the load changes correlated to the temperature effect in each particular seasons, The model adequacy and weekly fore casting results had indiced a good grade in error diagnostic checking (MAPE) in each location.