Structured building model reduction toward parallel simulation

Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations. Parallel computing aims to im-prove simulation times without loss of accuracy but is poorly utilized by contemporary simulators and is inher-ently limited by inter-processor communication. This pa-per bridges these disparate techniques to implement ef-ficient parallel building thermal simulation. We begin with a survey of three structured reduction approaches that compares their performance to a leading unstructured method. We then use structured model reduction to find thermal clusters in the building energy model and allo-cate processing resources. Experimental results demon-strate faster simulation and low error without any inter-processor communication.