发表机构
School of Electrical & Electronic Engineering, University College Dublin（都柏林大学电气与电子工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对可再生能源高渗透下的区域频率越限问题，本文提出结合Vine-Copula与物理信息神经网络的区域频率约束调度方法，在IEEE 118节点系统上验证其性能优于统一惯性中心嵌入方法
AI 中文摘要
可再生能源渗透率的不断提高因其高波动性和惯量降低而对频率稳定性提出挑战。传统的频率安全约束调度方法无法捕捉区域频率异质性和空间相关的随机扰动，导致频率安全执行不准确。为解决该问题，本文提出一种考虑空间联合随机扰动与故障的区域频率约束调度方法。首先，构建多区域频率响应模型，结合基于Vine-Copula的区域随机扰动表征与区域频率支撑；然后，采用渐进式潜瓶颈物理信息神经网络，通过编码器-解码器结构表征频率最低点项与区域频率支撑积分项，从而实现与优化兼容的系统频率动力学表达式；最后，构建日前调度模型，其中采用基于CVaR的公式嵌入区域随机频率约束。对IEEE 118节点系统的案例研究表明，所提方法在缓解区域频率越限方面优于统一惯性中心嵌入方法，区域频率最低点与变化率（RoCoF）分别提升32.76%和2.06%。
英文摘要
The increasing penetration of renewable energy challenges frequency stability due to high variability and declining inertia. Traditional frequency security constrained dispatch methods fail to capture regional frequency heterogeneity and spatially correlated stochastic disturbances, resulting in inaccurate frequency security enforcement. To address this, a regional frequency constrained dispatch method is proposed, considering the spatially joint stochastic disturbances and contingencies. Firstly, a multi-regional frequency response model is constructed, incorporating the Vine-Copula based characterization of regional stochastic disturbances and regional frequency support. Then, a progressive latent-bottleneck physics-informed neural network is applied to characterize differential frequency nadir terms and regional frequency support integral terms via an encoder-decoder architecture, which enables optimization compatible expressions of system frequency dynamics. Finally, a day ahead dispatch model is developed in which regional stochastic frequency constraints are embedded using a CVaR-based formulation. A case study on the IEEE 118-bus system shows that the proposed method outperforms the unified center of inertia embedded approach in mitigating regional frequency violations, with the regional frequency nadir and RoCoF improved by 32.76% and 2.06%, respectively.
