论文标题
动态和分布式在线凸优化商业建筑的需求响应
Dynamic and Distributed Online Convex Optimization for Demand Response of Commercial Buildings
论文作者
论文摘要
我们将对在线分布式加权双平均（DWDA）算法[1]的遗憾分析扩展到动态设置，并提供最紧密的动态遗憾，以截至迄今为止，与时间范围有关的分布式在线凸优化（OCO）算法已知。我们的界限是在连续Optima之间的累积差异中线性的，并且不明确取决于时间范围。我们使用Dynamic-Conline DWDA（D-ODWDA），并为商业建筑的加热，通风和空调（HVAC）系统制定了性能保证的在线需求响应方法。我们显示了在数值模拟中进行快速时间尺度需求响应的方法的性能，并获得了密切复制集中式最佳措施的需求响应决策。
We extend the regret analysis of the online distributed weighted dual averaging (DWDA) algorithm [1] to the dynamic setting and provide the tightest dynamic regret bound known to date with respect to the time horizon for a distributed online convex optimization (OCO) algorithm. Our bound is linear in the cumulative difference between consecutive optima and does not depend explicitly on the time horizon. We use dynamic-online DWDA (D-ODWDA) and formulate a performance-guaranteed distributed online demand response approach for heating, ventilation, and air-conditioning (HVAC) systems of commercial buildings. We show the performance of our approach for fast timescale demand response in numerical simulations and obtain demand response decisions that closely reproduce the centralized optimal ones.
