Simulation-assisted operation can offer flexibility in terms of prioritizing either building energy consumption or occupant thermal comfort, and in most cases, it can address these issues simultaneously. Simulation-assisted operation is the type of operation that uses the knowledge of future disturbances acting on the building, thus allowing the HVAC system operation in such a way so as to meet set goals in terms of building energy consumption and occupant thermal comfort. The most important future disturbances acting on the building are weather and occupant behavior (expectations of thermal environment). To achieve simulation-assisted operation, optimization methods are necessary. This paper presents the methodology to create daily operation strategies for existing HVAC systems serving a real building. The methodology relies on the extensive use of the building energy performance simulation software EnergyPlus, available weather data from the building site or from official weather databases including short-term forecasts, global sensitivity analysis and a custom-built optimization environment based on the particle swarm optimization method, all applied over a shifting (moving) horizon. Global sensitivity analysis with Latin hyper-cube sampling is used to reduce the number of independent variables for the optimization process. The methodology was demonstrated for the office part of an existing real building located on the outskirts of the City of Niš, Serbia. The obtained results show that the application of sensitivity analysis as a pre-step to optimization leads to similar data related to energy consumption and occupant thermal comfort, but with a significant decrease in the use of computational resources.

模拟辅助操作可以在优先考虑建筑物能耗或居住者热舒适度方面提供灵活性，并且在大多数情况下，它可以同时解决这些问题。模拟辅助操作是一种操作类型，它使用未来影响建筑物的干扰的知识，从而允许 HVAC 系统以这样一种方式操作，以满足建筑能耗和居住者热舒适度方面的既定目标。影响建筑物的最重要的未来干扰是天气和居住者行为（对热环境的预期）。为了实现模拟辅助操作，优化方法是必要的。本文介绍了为实际建筑服务的现有 HVAC 系统创建日常操作策略的方法。该方法依赖于建筑能源性能模拟软件 EnergyPlus 的广泛使用、来自建筑工地或官方天气数据库的可用天气数据，包括短期预测、全球敏感性分析和基于粒子群优化的定制优化环境方法，全部应用于移动（移动）地平线。使用拉丁超立方体采样的全局敏感性分析用于减少优化过程的自变量数量。该方法在位于塞尔维亚尼什市郊区的现有真实建筑的办公室部分进行了演示。获得的结果表明，应用敏感性分析作为优化的前一步会导致与能源消耗和居住者热舒适性相关的类似数据，