Life-Cycle Energy/Cost Optimization of Retrofit Combinations for Existing Buildings

  • Sokratis Papadopoulos

Student thesis: Master's Thesis


The increasing emphasis placed on sustainable practices, in light of environmental and socio-economic considerations, has highly prioritized the enhancement of energy performance in existing building infrastructure. The building sector contributes a large proportion of the world’s total energy consumption and at this stage, building retrofitting is the most common approach implemented for the improvement of energy efficiency in buildings. The present thesis investigates a plethora of potential retrofit actions, while a Life Cycle Analysis (LCA), based on Net Present Value (NPV) optimization, is conducted for four typical Abu Dhabi buildings. In addition, the building retrofit problem is formulated as a multi-objective optimization problem, where conflicting objectives are optimized simultaneously and their trade-offs are assessed. A coupling scheme between MATLAB and EnergyPlus is introduced in order to perform a Genetic Algorithm-based single and multi-objective optimization. The computational intensity of this approach is being addressed with a novel Ensemble Learning-based building representation that can significantly reduce the evaluation time of both the simulation and the objective function(s). The results of the study are reported and they illustrate the effectiveness of ensemble learning models in building simulation-based optimization, with important implications for the field of building efficiency.
Date of AwardMay 2015
Original languageAmerican English
SupervisorAfshin Afshari (Supervisor)


  • Sustainable Building Practices
  • Energy performance
  • Building Infrastructure
  • Energy Consumption
  • Building Retrofitting
  • Building Simulation-based Optimization
  • Building Efficiency.

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