To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable energy at the minimum cost. In addition, it is often challenging to accurately estimate the joint probability distribution of the renewable energy. In this paper, we propose a two-stage distributionally robust optimization model that co-optimizes the power dispatch and the DNE limits, by adopting an affinely adjustable power redispatch and an adjustable joint chance constraint that measures the renewable utilization. Notably, this model admits a second-order conic reformulation that can be efficiently solved by the commercial solvers (e.g., MOSEK). We conduct case studies based on modified IEEE test instances to demonstrate the effectiveness of the proposed approach and analyze the trade-off among the system flexibility, the renewable utilization, and the dispatch cost.

中文翻译：

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功率调度和不超过限制的分布鲁棒协同优化

为了应对可再生能源不确定性的挑战，ISO 新英格兰 (ISO-NE) 提议应用不超过 (DNE) 限制，这代表了电网可以容纳的可再生能源的最大节点注入。不幸的是，计算同时保持系统灵活性并以最低成本整合大部分可用可再生能源的 DNE 限制似乎具有挑战性。此外，准确估计可再生能源的联合概率分布通常具有挑战性。在本文中，我们提出了一种两阶段分布式鲁棒优化模型，通过采用可仿射可调节的功率重新调度和可测量可再生利用的可调节联合机会约束来协同优化功率调度和 DNE 限制。尤其，该模型承认可以由商业求解器（例如，MOSEK）有效求解的二阶圆锥重构。我们基于修改后的 IEEE 测试实例进行案例研究，以证明所提出方法的有效性，并分析系统灵活性、可再生利用和调度成本之间的权衡。