论文标题
不确定性感知的灵活性信封封面预测，具有控制器 - 不足的电池模型
Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models
论文作者
论文摘要
建筑物是应用需求响应的灵活性来源。在这项工作中，我们介绍了一种新型的电池模型公式，以捕获单个建筑物的状态演变。在完全数据驱动的情况下，电池模型标识需要一个数据集中的一个数据集，一个数据集，一个来自具有灵活性请求的时期，而无需对基础控制器结构做出任何假设。我们考虑模型公式中的参数不确定性，并显示如何使用风险度量来编码用户在健壮的不确定性集中的风险偏好。最后，我们证明了来自Python Library Energym的建筑模拟模型的灵活性信封的不确定性感知预测。
Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identification requires one dataset from a period of nominal controller operation, and one from a period with flexibility requests, without making any assumptions on the underlying controller structure. We consider parameter uncertainty in the model formulation and show how to use risk measures to encode risk preferences of the user in robust uncertainty sets. Finally, we demonstrate the uncertainty-aware prediction of flexibility envelopes for a building simulation model from the Python library Energym.
