City planning for sustainable energy and development goals in small municipalities suffers from unresolved complexities, insufficient data and prohibitive cost. We propose a low-cost urban energy system for building stock assessment and urban energy planning by combining archetype-based dynamic energy demand and coverage simulation with incentive-based citizen participation as a means to improve data quality. Combining a white-box based physical approach with multi-dimensional archetypes for individual building energy demand and supply estimation with statistical top-down validation and calibration, we obtain an energy simulation method that requires less data on the building stock than other typical methods.