发表机构
Huazhong University of Science and Technology; Nanyang Technological University（华中科技大学; 南洋理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对异构DER聚合的两大挑战，提出偏好导向聚合方法，通过矩阵变换解决维度异构性，开发分布式框架降低类型异构性的灵活性损失，数值测试验证了方法的有效性。
AI 中文摘要
聚合分布式能源资源（DER）旨在将其集体灵活性编码为单一集合，以实现电网的高效调度。然而，现有的聚合方法对于异构DER过于保守，存在两大主要挑战：1）维度异构性，即不同时间维度的灵活性组合较为复杂；2）类型异构性，即多样且不规则的DER特性阻碍了精确近似，导致灵活性显著损失。为解决这些挑战，本文提出一种面向备用调度的新型偏好导向聚合方法。针对维度异构性，我们采用矩阵变换技术将闵可夫斯基和重新表述为多面体投影问题，扩展了现有技术；通过在更高维空间中统一DER并将其投影回聚合可行域，所提技术可有效聚合维度异构的DER。针对类型异构性，我们进一步开发了分布式聚合-调度协调框架，将备用调度偏好纳入聚合过程；该框架可有效捕捉最优备用调度中优先考虑的关键主动聚合灵活性，从而大幅降低聚合类型异构DER时的灵活性损失。数值测试验证了本文方法在应对两类异构性方面的有效性，并凸显了其在高备用需求电力系统中的应用潜力。
英文摘要
Aggregating distributed energy resources (DERs) aims to encode their collective flexibility into a single set for efficient grid dispatch. However, existing aggregation methods are overly conservative for heterogeneous DERs due to two main challenges: 1) dimensional heterogeneity, which complicates the combination of flexibilities across different time dimensions, and 2) type heterogeneity, where diverse and irregular DER profiles hinder accurate approximations, resulting in significant flexibility loss. To resolve these challenges, this paper propose a novel preference-oriented aggregation method for reserve dispatch. For dimensional heterogeneity, we extend existing techniques by reformulating the Minkowski sum as a polytope projection problem using a matrix transformation technique. By unifying DERs in a higher-dimensional space and projecting them back into the aggregate feasible region, the proposed technique effectively aggregates dimensionally heterogeneous DERs. For type heterogeneity, we further develop a distributed aggregation-dispatch coordination framework that incorporates reserve dispatch preferences into aggregation. This framework effectively captures the critical, active aggregate flexibility prioritized in optimal reserve dispatch, thereby significantly reducing the flexibility loss when aggregating type-heterogeneous DERs. Numerical tests validate the effectiveness of our method in addressing both heterogeneities and highlight its promising potential for power systems with high reserve requirements.
CommentsPublished in: IEEE Transactions on Smart Grid (vol. 17, no. 2, pp. 1264-1279, 2026)
