Article ID Journal Published Year Pages File Type
4961387 Procedia Computer Science 2017 11 Pages PDF
Abstract

The study aims to generate Building system performance design optimization for 11 nearly zero energy new building (nZEnB) types in the cold climate conditions for decision making. The coupling evolutionary algorithms with a building dynamic simulation engine has been applied to reach the “true” optimal solutions. Life cycle cost and performance modulation was carried out in the multi-objective computer model. The calculation of cost optimality was performed on predefined 11 reference building types by taking into account prices as they have been paid by the end consumer including taxes. 960 000 simulation variants were calculated for each building type. This paper proposes coupling of multivariate engine with the Pareto analysis for reduction of costs and energy use, while taking in consideration fiscal and resource economy long term trends as well as fossil energy replacement with the renewable ones from investment perspective.

Keywords
Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
Authors
, , ,