The target of the paper is to study how to devise an efficient discrete-event model for the yearly energy simulation of buildings. Conventionally, software tools use time-driven schemes and many components must be computed at every sampling time-point. Event-driven simulation aims at lowering this burden, by calling only those components whose state is evolving quickly. The article explores a model based on DEVS formalism and Quantized State Systems (QSS) techniques. Within this paradigm shift, our strategy was to reuse as much widely accepted knowledge as possible. One immediate difficulty was, that the well-known conduction heat transfer function (CHTF) of multi-layered walls is not suitable for DEVS in its traditional form since it is constrained to sample at a fixed time step. Instead, the paper introduces a non-conventional method: the Successive State Transition method (SST). Its distinguishing traits are: it allows variable time steps, has high accuracy and its computational workload adapts to the elapsed time between transitions. Unfortunately, although we found that SST and QSS work well together, the paper shows that the aforementioned transfer function is not adequate for event-driven simulations. Based on the paper outcomes, we propose a workaround for further research: a new transfer function, relating the conduction heat flux (input) to the time derivative of the wall superficial temperature (output) (recall that the traditional input-output relationship: superficial temperature and conduction heat flux, respectively).

Abbreviations: CHTF: Conduction Heat Transfer Functions; DEVS: Discrete Event Simulation; DRFM: Direct Root Finding methods; SST: Successive State Transitionmethod; QSS: Quantized State System

本文的目标是研究如何为建筑物的年度能源模拟设计有效的离散事件模型。按照惯例，软件工具使用时间驱动方案，并且必须在每个采样时间点计算许多组件。事件驱动的仿真旨在通过仅调用状态快速发展的那些组件来减轻这种负担。本文探讨了基于DEVS形式主义和量化状态系统（QSS）技术的模型。在这种范式转变中，我们的策略是重用尽可能多的广为接受的知识。一个直接的困难是，众所周知，多层壁的传导传热函数（CHTF）不适合传统形式的DEVS，因为它必须在固定的时间步进行采样。相反，本文介绍了一种非常规方法：连续状态转换方法（SST）。它的显着特征是：它允许可变的时间步长，具有很高的准确性，并且其计算量适应于两次转换之间所经过的时间。不幸的是，尽管我们发现SST和QSS可以很好地协同工作，但论文显示上述传递函数不足以进行事件驱动的仿真。根据论文结果，我们提出了一个进一步研究的解决方法：一种新的传递函数，将传导热通量（输入）与壁面温度（输出）的时间导数相关联（回想起传统的输入-输出关系：表面温度和传导热通量）。

缩写：CHTF：传导热传递函数；DEVS：离散事件模拟；DRFM：直接寻根方法；SST：连续状态转换方法；QSS：量化状态系统