Optimum design of a house and its HVAC systems using simulation-based optimisation

This paper deals with a multi-objective optimisation problem where the objective is to minimise CO2-eq emissions and investment cost of a multi-zone single-family house and its heating/cooling systems. Eight design variables are subjected to study: level of building tightness, insulation thickness of the external wall, floor and roof, type of window glazing, window shading, heat recovery and heating/cooling systems. Simulation-based optimisation is implemented to minimise the objective functions by finding optimum values of the design variables. This is done by combining the dynamic building performance simulation program IDA-ICE 3.0 with a modified genetic algorithm. The optimisation results give the optimal solutions for the problem in the form of a Pareto front, showing the trade-off between the two objectives. The obtained solutions are much better than the initial designs of the house in terms of lower CO2-eq emissions and investment cost. It is noted from the obtained results that the significance of the heating system is higher than the other design variables so that the optimal solutions can be classified according to the type of the heating system. It is also noted that there is a need to include a thermal comfort criterion as a problem constraint to limit overheating hours during summer.