发表机构
ETH Zürich; Empa; Vienna University of Technology（苏黎世联邦理工学院; 瑞士联邦材料科技与研究所; 维也纳工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对柔性负荷最优备用量化难题，推导两种解析重构方法，提出柔性负荷最优组合概念，通过理论与数值分析验证方法有效性及最优负荷分组的存在性。
AI 中文摘要
柔性负荷可通过提供备用容量增强电力系统稳定性，但有限的能量容量和不确定的可用性使其区别于传统发电机。为适配这些特性，丹麦输电系统运营商（TSO）近期推出了纳入能量约束、放宽可靠性要求的新备用市场规则。在此背景下，最优备用量化成为联合机会约束备用量化问题，难以求解。本文推导了该问题的两种解析重构：当备用方向占优时为精确重构，否则为近似重构。此外，当柔性负荷必须共同满足可靠性要求时，本文提出柔性负荷最优组合的概念：向现有组合中添加期望价值相似但随机行为不同的负荷，可能改变总组合的备用容量。为支撑该思路，本文从理论上研究了添加负荷带来的备用容量边际增量。数值结果表明，本文的解析重构与精确重构高度匹配，平均绝对误差为2.5%。案例研究进一步证明了最优负荷分组的存在，以及本文可借助理论分析预测负荷边际价值最高的组合。
英文摘要
Flexible loads can enhance power system stability by providing reserves, but their limited energy capacity and uncertain availability distinguish them from conventional generators. To accommodate these characteristics, the Danish Transmission System Operator (TSO) recently introduced new reserve market rules that incorporate energy constraints and relax reliability requirements. In this context, the optimal reserve quantification becomes a joint chance-constrained reserve quantification problem, which is difficult to solve. In this paper, we derive two analytical reformulations of this problem: an exact one when a reserve direction dominates and an approximate one, otherwise. Furthermore, when flexible loads must collectively satisfy a reliability requirement, we introduce the concept of an optimal portfolio of flexible loads: adding loads with similar expected values but different stochastic behaviors to an existing portfolio may change the total portfolio's reserves. To support this idea, we theoretically study the marginal increase in reserves resulting from adding a load. Numerical results show that our analytical reformulations closely match the exact formulation, with a mean absolute error of 2.5%. Case studies further demonstrate the existence of optimal load groupings and our ability to predict the portfolio in which a load's marginal value is highest, leveraging our theoretical analysis.
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