On the Assessment of the Chilean Solar Thermal Regulation Using a Modular Simulation Model Coupled to a Multiobjective Optimization Algorithm

Abstract

In Chile, the solar thermal regulation DS331, which utilizes a global modeling approach, governs the deployment of solar thermal systems (STSs) across highly variable climatic zones. This regulation’s one‐size‐fits‐all approach often misrepresents the solar potential and economic feasibility in different regions. To address these limitations, we introduce a refined modular energy model that incorporates a 1D multinode stratification technique for hot water storage. This model is associated with a multiobjective optimization process using the NSGA‐II algorithm, focusing on optimizing the solar collector area and storage volume to maximize solar fraction and life cycle savings (LCSs) across 20 major Chilean cities. Our results demonstrated that the optimized systems achieve solar fractions ranging from 0.92 to 1.00, significantly improving upon the current regulation’s performance, particularly in southern regions where solar radiation is lower. Notably, the optimized configurations suggested a potential reduction in collector areas by up to 20% and storage volumes by up to 15% compared to those recommended by DS331, while still exceeding the legal requirements for the solar fraction. This optimization made it possible to increase LCS by ~25%–30% across various scenarios, indicating a substantial improvement in cost‐effectiveness. Based on these findings, existing solar thermal regulations should be revised to take into account local climatic and consumption data. Such adjustments would ensure more accurate sizing of STS, enhanced economic viability, and greater incentive alignment for widespread adoption. This study underlines the critical role of detailed, location‐specific energy modeling in shaping effective energy policies and advancing the deployment of renewable technologies in diverse environmental contexts.