发表机构
State Key Laboratory of Advanced Electromagnetic Technology, Huazhong University of Science and Technology（华中科技大学先进电磁技术国家重点实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对电力系统调度中大规模灵活HVAC负荷调度的计算与不确定性难题，提出含分布鲁棒机会约束的连续时间聚合模型及分层调度框架，验证了模型的有效性与可扩展性。
AI 中文摘要
供暖、通风与空调（HVAC）负荷具备快速响应能力，可在需求侧提供可观的小时内灵活性，用于备用提供以跟踪可再生能源的快速变化。然而，由于计算复杂性和室外温度的不确定性，调度大规模HVAC负荷颇具挑战。本文首先引入一种新颖的连续时间（CT）聚合模型，以揭示HVAC负荷的潜在小时内灵活性；为实现精准聚合，设计了一种新的仿射变换以处理高维可行域中的异质性；此外，为在实际环境中实现可靠聚合，通过分布鲁棒机会约束构建室外温度不确定性，并将其整合到聚合模型中。其次，为使所提CT聚合模型的计算具有可处理性，提出了一系列定制的重构技术，包括伯恩斯坦多项式样条、多面体投影和线性化变换。第三，通过将所提CT聚合模型纳入电力系统调度的备用提供中，提出了一种定制的分层调度框架，以高效调度大规模HVAC负荷来应对可再生能源的不确定性。案例研究验证了所提CT聚合模型在聚合精度、小时内灵活性利用和不确定性处理方面的有效性和可扩展性。
英文摘要
Heating, ventilation, and air conditioning (HVAC) loads, with their rapid response capabilities, can provide considerable intra-hour flexibility on the demand side for reserve provision in order to follow the fast variations of renewables. However, scheduling massive HVACs is challenging due to computation complexity and the uncertainty of outdoor temperature. In this paper, we first introduce a novel continuous-time (CT) aggregation model to reveal the potential intra-hour flexibility of HVACs. For accurate aggregation, a new affine transformation is designed to handle the heterogeneity in high-dimensional feasible region. Further, for reliable aggregation in practical environment, the outdoor temperature uncertainty is constructed by distributionally robust chance constrains and integrated into the aggregation model. Secondly, for the tractable calculation of the proposed CT aggregation model, a cascade of tailored reformulation techniques is proposed, including the Bernstein polynomial spline, polytope projection, and linearization transformation. Thirdly, a customized hierarchical dispatch framework is proposed via incorporating the proposed CT aggregation model into reserve provision in power system dispatch, so as to efficiently schedule massive HVACs to cope with the renewable uncertainty. Case studies verify the effectiveness and scalability of the proposed CT aggregation model in aggregation accuracy, intra-hour flexibility utilization, and uncertainty handling.
CommentsPublished in: IEEE Transactions on Smart Grid (vol. 15, no. 5, pp. 4835-4849, 2024)
