本文讨论了智能窗口的先进控制策略。由于智能窗户既可用于降低能耗，又可改善热舒适性和视觉舒适性，因此通过窗户的最佳太阳能通量是采光和热流平衡之间复杂权衡的结果。典型的办公楼区域在TRNSYS中建模，带有集成的电致变色智能窗。研究了两种先进的软件控制器，即（i）基于遗传算法的控制器和（ii）基于模型预测控制的控制器，并与基本情况进行了比较。高级控制器评估智能窗的逐小时状态，以最小化总能耗（加热、冷却、照明），同时考虑与热舒适性和视觉舒适性相关的约束。 结果表明，这两种控制器虽然提出了不同的控制策略，但在节能和降低峰值负荷方面提供了非常相似和有希望的结果。最后，讨论了当前工作带来的机遇。引用:2016年冬季会议，佛罗里达州奥兰多，会议论文

Advanced control strategies for smart windows (SW) are discussed in this paper. Since smart windows are used both to reduce energy consumption and to improve thermal and visual comfort, the optimal solar flux passing throught the window is the result of a complex trade-off between daylighting and heat flow balance. A typical office building zone is modeled in TRNSYS with an integrated electrochromic smart window. Two types of advanced SW controllers, i.e. (i) a genetic algorithm based controller and (ii) a model predictive control based controller, are studied and compared to a base case scenario. The advanced controllers evaluate the hour-by-hour state of the smart window required to minimize the overall energy consumption (heating, cooling, lighting) while respecting constraints related to thermal and visual comfort. Results have shown that the two controllers, while presenting different control strategies, offer very similar and promising results in terms of energy savings and peak load reductions. Finally, opportunities resulting from the present work are discussed.