This study proposes a new urban energy demand forecasting system that includes the following improvements: (a) a facility planning information database (DB), (b) an energy and planning statistics DB, and (c) an enhancement of the accuracy of the energy calculation method. Each of these improved aspects is involved in energy demand forecasting for urban planning. The results from this study are as follows. (1). An Environment and energy Geographical Information System Database (E-GIS DB), which provides the mesh unit facility information, was utilized to allow for the forecasting and control of urban energy demands for each unit space. (2). An energy consumption unit figure was connected with an energy simulation to diversify the level of the urban energy consumption sector and the primary energy into hourly information. This figure allows for more accurate demand forecasting. (3). Urban facilities were categorized according to energy use characteristics and were modeled to allow for energy demand forecasts. (4). The energy demand was considered in an urban climate during summer with the characteristics of the heating methods that are suitable for domestic circumstances. Thus, a separate algorithm was suggested for a cooling period and a heating/intermission period to enhance the accuracy of the demand forecasts. (5). The performance of this energy demand forecasting system was validated, such that excessively high or low calculated values can be modified from the current method in a 'planned city' while the urban energy demand can be forecasted relatively correct and in detail with differences of a factor of 0.20-0.44 for the cooling period in the 'existing city'. (6). The proposed urban energy demand forecasting system was constructed as EnerISS Solver which is an automated module. This module drastically reduced time consuming for predicting energy demand and urban climate to respond for the urban energy planning subjects' needs immediately. (C) 2013 Elsevier Ltd. All rights reserved.