A simulation/optimization tool has been developed to design building shell that minimizes energy use costs associated with heating and cooling systems. The tool couples an optimization algorithm to a building energy simulation engine to select optimal values of a comprehensive list of parameters associated with the envelope of residential buildings including the building shape. Three optimization methods are utilized including genetic algorithm (GA) approach, sequential search technique, and particle swarm technique. In this paper, the performance in terms of accuracy and efficiency of the three optimization approaches was compared for various sets of building envelope parameters.
For relatively large search spaces, it was found that the GA could identify the minimum cost point to with an accuracy of 0.4% using 60% of the simulations required by sequential search technique and only 40% of the simulations needed by the particle swarm optimization method.
Units: Dual
Citation: ASHRAE Transactions, vol. 115, pt. 2, Louisville 2009
Product Details
- Published:
- 2009
- Number of Pages:
- 9
- File Size:
- 1 file , 600 KB
- Product Code(s):
- D-LO-09-052
