An Algorithm for Efficient Urban Building Energy Modeling and Simulation
The urban population increases continuously since the industrial revolution, and the residential buildings have the primary responsibility for the total energy demand. There is a need for the analysis of the residential building stock for energy efficiency and sustainable planning. However, energy modeling and simulation in urban scale is expensive in computational complexity and time, due to various building geometries and occupancy types. This research proposes a method to increase the efficiency of the simulation process by reorganizing the building geometries with functional clustering and radiation analysis scaling. In order to accelerate the urban building energy modeling (UBEM) process, the building geometries are modified based on energy simulation standards, then, clustering is determined based on radiation analysis and outside boundary conditions. The candidates are selected according to the selection percentage that has been identified before the process to simulate in building energy software. Three different simulation types are compared to validate the performance of the proposed algorithm with complete model simulations in terms of the error rate of the objectives and the simulation runtime.
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