Active Distribution System Synthesis via Unbalanced Graph Generative Adversarial Network
Active Distribution System Synthesis via Unbalanced Graph Generative Adversarial Network
复制标题
通过不平衡图生成对抗网络的主动分布系统综合
DOI：
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发表时间：
2023
影响因子：
6.6
通讯作者：
Q. Jiang
中科院分区：
文献类型：
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作者：
Rong Yan;Yuxuan Yuan;Zhaoyu Wang;Guangchao Geng;Q. Jiang
真实的有源配电网及其相关的智能电表（SM）数据对电力研究人员至关重要。然而，由于隐私问题，研究人员实际上很难从公用事业公司获得如此全面的数据集。为了弥补这一差距，Wasserstein GAN目标的隐式生成模型，即不平衡图生成对抗网络（UG-GAN），被设计用于生成合成的三相不平衡有源配电系统连通性。其基本思想是学习随机游走在真实世界系统和线段的每个相位上的分布，捕获单个真实世界分布网络的潜在局部属性，并相应地生成特定的合成网络。然后，创建一个全面的综合测试情况下，网络校正和扩展过程中提出了获得时间序列节点的需求和标准的配电网组件与现实的参数，包括分布式能源（DER）和电容器组。一个中西部配电系统的1年SM数据已被用来验证我们的方法的性能。几个电力应用的案例研究表明，所提出的框架生成的合成有源网络可以模仿几乎所有的功能，同时避免泄露机密信息的真实世界的网络。
Real active distribution networks with associated smart meter (SM) data are critical for power researchers. However, it is practically difficult for researchers to obtain such comprehensive datasets from utilities due to privacy concerns. To bridge this gap, an implicit generative model with Wasserstein GAN objectives, namely unbalanced graph generative adversarial network (UG-GAN), is designed to generate synthetic three-phase unbalanced active distribution system connectivity. The basic idea is to learn the distribution of random walks both over a real-world system and across each phase of line segments, capturing the underlying local properties of an individual real-world distribution network and generating specific synthetic networks accordingly. Then, to create a comprehensive synthetic test case, a network correction and extension process is proposed to obtain time-series nodal demands and standard distribution grid components with realistic parameters, including distributed energy resources (DERs) and capacitor banks. A Midwest distribution system with 1-year SM data has been utilized to validate the performance of our method. Case studies with several power applications demonstrate that synthetic active networks generated by the proposed framework can mimic almost all features of real-world networks while avoiding the disclosure of confidential information.
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基于真实公用事业数据的时间序列分布测试系统
DOI：
10.1109/naps46351.2019.8999982
发表时间：
2019
期刊：
2019 North American Power Symposium (NAPS
影响因子：
--
作者：
Bu, Fankun;Yuan, Yuxuan;Wang, Zhaoyu;Dehghanpour, Kaveh;Kimber, Anne
通讯作者：
Kimber, Anne
影响因子：
11.2
作者：
Sathsara Abeysinghe;Jianzhong Wu;M. Sooriyabandara;M. Abeysekera;Tao Xu;Chengshan Wang
通讯作者：
Sathsara Abeysinghe;Jianzhong Wu;M. Sooriyabandara;M. Abeysekera;Tao Xu;Chengshan Wang
影响因子：
3.8
作者：
Li, Hanyue;Wert, Jessica L.;Palmintier, Bryan
通讯作者：
Palmintier, Bryan
影响因子：
6.6
作者：
Yifei Guo;Yuxuan Yuan;Zhaoyu Wang
通讯作者：
Yifei Guo;Yuxuan Yuan;Zhaoyu Wang