This paper proposes a data-driven approach to assess the wind generation accommodation capability of the integrated electric-heat system. The overall assessment model is constructed based on the two-stage robust decision-making framework, where the uncertainty of wind generation is described by a convex hull formed by historical data. To take a balance between modeling accuracy and computation tractability, the convex hull is firstly approximated by the intersection of a set of low-dimensional convex hulls, named the approximated convex hull, and then the approximated convex hull based uncertainty set is further simplified by the vertex coefficient discretization treatment. A uniform-compression-expansion scheme for the identified worst-case data samples is derived to realize the evolution of the dynamic convex hull as well as to bridge the gap between the first- and the second-stage problems. A modified column-and-constraint generation algorithm is devised to solve the overall model. Simulation results on two test systems verify the effectiveness and the scalability of the proposed method.

中文翻译：

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集成电热系统的数据驱动风力发电可允许性评估：基于动态凸包的方法

本文提出了一种数据驱动的方法来评估集成电热系统的风力发电适应能力。基于两阶段鲁棒决策框架构建总体评估模型，其中风力发电的不确定性由历史数据形成的凸包描述。为了在建模精度和计算可处理性之间取得平衡，首先通过一组低维凸包的交集（近似的凸包）对凸包进行近似，然后通过以下方法进一步简化基于近似凸包的不确定性集：顶点系数离散化处理。导出用于识别的最坏情况数据样本的统一压缩扩展方案，以实现动态凸包的演化以及弥合第一和第二阶段问题之间的差距。设计了一种改进的列约束生成算法来求解整体模型。在两个测试系统上的仿真结果验证了该方法的有效性和可扩展性。