Optimal retrofitting scenarios of multi-objective energy-efficient historic building under different national goals integrating energy simulation, reduced order modelling and NSGA-II algorithm

Retrofitting a historic building under different national goals involves multiple objectives, constraints, and numerous potential measures and packages, therefore it is time-consuming and challenging during the early design stage. This study introduces a systematic retrofitting approach that incorporates standard measures for the building envelope (walls, windows, roof), as well as the heating, cooling, and lighting systems. Three retrofit objectives are delineated based on prevailing Chinese standards. The retrofit measures function as genes to optimize energy-savings, carbon emissions, and net present value (NPV) by employing a log-additive decomposition approach through energy simulation techniques and NSGA-II, yielding 185, 163, and 8 solutions. Subsequently, a weighted sum method is proposed to derive optimal solutions across multiple scenarios. The framework is applied to a courtyard building in Nanjing, China, and the outcomes of the implementation are scrutinized to ascertain the optimal retrofit package under various scenarios. Through this retrofit, energy consumption can be diminished by up to 63.62%, resulting in an NPV growth of 151.84%, and maximum rate of 60.48% carbon reduction. These three result values not only indicate that the optimal values are achieved in these three aspects of energy saving, carbon reduction and economy, but also show the possibility of possible equilibrium in this multi-objective optimization problem. The framework proposed in this study effectively addresses the multi-objective optimization challenge in building renovation by employing a reliable optimization algorithm with a computationally efficient reduced-order model. It provides valuable insights and recommendations for optimizing energy retrofit strategies and meeting various performance objectives.