Multi-objective optimization for predicting time-trajectories of combined climate-plus-energy efficiency control in a public building in San Juan, Argentina

ARBALLO, BRUNO DAMIÁN; CHUK, DANIEL; KUCHEN, ERNESTO

Science and Technology for the Built Environment

Taylor and Francis

Lugar: London; Año: 2023

2374-4731

This work presents a bioclimatic optimization strategy suited for implementation in a public building currently in use in the city of San Juan, Argentina, in a region featuring dry summer periods with high temperatures register. The Multi-Objective Predictive Optimization (MOPO) methodology combines predictive supervision and multi-objective optimization for the prediction of optimal temporal trajectories to be followed by controllers´ setpoints. The novel contribution of this work adequately performs the predictive evaluation of a given trajectory while contemplating simultaneously high-quality thermal comfort and energy savings/energy efficiency, in order to obtain an optimal set of possible solutions for attaining combined climate-plus-energy efficiency control. Here, a criterion is also proposed to select, from among said set, the fitting solution to operate the local controllers. Although this research demonstrates significant improvements in energy efficiency and thermal comfort of a specific public office building in San Juan, Argentina, during summer time and transitional period, it can be stated that its generalized features makes this procedure a viable, easily transferrable solution to face varying issues involving real-time climatic conditions and user requirements.