Multi-variable optimization of thermal energy efficiency retrofitting of buildings using static modelling and genetic algorithms – A case study

• Simulation based optimisation using a static energy modelling approach and the genetic algorithms optimization technique.
• Multi-variable optimization in the area of energy efficiency using discrete data sets.
• Application of the optimal retrofit decision support tool to a real non-domestic building.
• Optimal retrofit solutions identified for differing objective functions and constraint criteria.

The retrofitting of existing buildings is an area of research that requires development in order to overcome the ‘rule of thumb’ based approach currently being undertaken. Simulation-based optimization is one approach that can assist consultant engineers, architects and other professionals who undertake retrofit projects. This paper presents a degree-days simulation technique coupled with a genetic algorithms optimization procedure to propose optimal retrofit solutions. The research is applied to a recently retrofitted case-study building. A comparison between the implemented retrofit solution and the simulation-based optimal solution is included to demonstrate the applicability of the research to real-world situations. This research demonstrates the necessity to carry out analysis of a project before retrofit works commence to ensure an optimal approach is taken in accordance with the project specific criteria.