ABSTRACT

The paper presents a novel method of generating metamodels that can quantify the influence of urban form on the heating and cooling loads of dwellings for the Mediterranean climate. The goal of the metamodels is to inform the early urban design process with quick and accurate feedback on the energy demand of a given urban configuration. The proposed method generates training datasets through Monte Carlo dynamic energy simulations of a single thermal zone. The study focuses on the geometrical parameters that affect building energy balance at the urban scale, such as dwelling shape, compactness, adjacencies and shading, utilizing a set of morphological indicators to relate these parameters to heating and cooling loads. The study focuses on the Mediterranean climate of Thessaloniki, Greece and utilizes several open-source tools (Ladybug Tools, EnergyPlus and Scikit-learn) under a streamlined workflow. The metamodels, which are trained using the Random Forest algorithm are then validated on 12 real-world urban sites of Thessaloniki with a reported Mean Average Percentage Error (MAPE) of 12% and 15% for heating and cooling loads, respectively.

摘要

本文提出了一种生成元模型的新方法，该方法可以量化城市形态对地中海气候住宅热负荷和冷负荷的影响。元模型的目标是通过对给定城市配置的能源需求快速准确的反馈来通知早期的城市设计过程。所提出的方法通过单个热区的蒙特卡罗动态能量模拟生成训练数据集。该研究侧重于影响城市尺度建筑能量平衡的几何参数，例如住宅形状、紧凑性、相邻性和阴影，利用一组形态指标将这些参数与热负荷和冷负荷联系起来。该研究侧重于希腊塞萨洛尼基的地中海气候，并利用了几种开源工具（Ladybug Tools、EnergyPlus 和 Scikit-learn）在简化的工作流程下。然后，使用随机森林算法训练的元模型在塞萨洛尼基的 12 个真实城市站点上进行验证，报告的平均平均百分比误差 (MAPE) 分别为 12% 和 15% 的热负荷和冷负荷。