A new comprehensive framework for the multi-objective optimization of building energy design: Harlequin.

Graphical abstract Highlights • Harlequin optimizes energy design by using genetic algorithm and smart sampling. • Three phases allow optimizing design variables for building geometry, envelope, systems. • Different energy, comfort, economy and environment targets are investigated. • The most sustainable, the cost-optimal, the lowest investment designs are achieved. • Harlequin is applied to optimize the energy design of a typical new Italian office. Abstract The comprehensive optimization of building energy design is fundamental to promote sustainability but it is an arduous issue that involves a huge domain of variables and objectives. The proposed investigation addresses this issue through a novel comprehensive framework – Harlequin – that performs a multi-phase and multi-objective design optimization. Three phases are carried out to optimize design variables related to the whole building-plants system, considering different energy, comfort, economic and environmental performance indicators. Phase 1 implements a genetic algorithm to achieve the Pareto optimization of envelope, geometry and space conditioning set points. Phase 2 performs a smart exhaustive sampling of design scenarios to find optimal energy systems. Phase 3 provides the most sustainable, the cost-optimal and the lowest investment (but energy-efficient) design solutions. Among these, the stakeholders can choose the best solution according to their wills and needs. Harlequin uses EnergyPlus (only in phase 1) and MATLAB® and it is so-called because building geometry and envelope are optimized for each exposure, thereby providing "Harlequin buildings". The novelty and scientific significance consist in ensuring a reliable design optimization by investigating a domain of variables and objectives, as comprehensive as never before. As a case study, Harlequin is applied to design a typical Italian office in Milan. Compared to a reference design, significant reductions of primary energy consumption (PEC), global cost (GC) and CO 2 -eq emissions can be achieved, depending on the chosen solution. The maximum reductions are 43.9 kWh p /m2 a for PEC, 63.9 €/m2 for GC (discount rate of 3%) and 12.3 kg/m2 a for CO 2 -eq. [ABSTRACT FROM AUTHOR]