Spatial short-term load forecasting using grey dynamic model specific in tropical area

Grey systems theory is the one of the most important research of uncertainty system, developed into a set of address information is not a complete systems. This theory realizes the correct description and effective supervision in operation action and evolution law of system, mainly through generating, exploring and extracting valuable information from a little part known information to predict the unknown information value. Dynamic forecasting model is needed due to the uncertain nature of the load predicting process specifically when load changes is correlated 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 substations 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 of hourly load demand affected to the tropical climate change variable, i.e. local ambient temperature. The daily load curve for Cawang and Cibatu substations, 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 season, The model adequacy and weekly forecasting result had indiced a good grade in error diagnostic checking (MAPE) in each location.