Mining Smart Meter Data to Enhance Distribution Grid Observability for Behind-the-Meter Load Control: Significantly improving system situational awareness and providing valuable insights
Mining Smart Meter Data to Enhance Distribution Grid Observability for Behind-the-Meter Load Control: Significantly improving system situational awareness and providing valuable insights
复制标题
挖掘智能电表数据以增强配电网可观测性以实现电表后负荷控制:显着提高系统态势感知并提供有价值的见解
DOI:
10.1109/mele.2021.3093636
复制
发表时间:
2021
影响因子:
3.4
通讯作者:
Wang, Zhaoyu
中科院分区:
文献类型:
--
作者:
Yuan, Yuxuan;Wang, Zhaoyu
Distributed Energy Resources (DERs) are playing an increasingly important role in power systems. In 2023, five categories of DERs-distributed solar, electric vehicles (EVs), energy storage, residential smart thermostats, and small-scale combined heat and power-are expected to contribute about 104 GW to the U.S. summer peak (see GTM, 2018). With the increasing integration of DERs in power distribution systems, distributed load control is imperative to smooth the fluctuations that they introduce. However, a main challenge is that distribution systems lack systematic situational awareness because of their limited sensors. Furthermore, most customer-level behind-the-meter (BTM) DERs, such as rooftop photovoltaics (PVs), are being integrated into distribution systems, which complicates the system monitoring and control. Enhanced electric grid monitoring is needed to promote renewable integration while ensuring reliability, but current approaches rely on expensive sensors.
影响因子:
6.6
作者:
Yuxuan Yuan;K. Dehghanpour;Fankun Bu;Zhaoyu Wang
通讯作者:
Yuxuan Yuan;K. Dehghanpour;Fankun Bu;Zhaoyu Wang
影响因子:
6.6
作者:
Yifei Guo;Yuxuan Yuan;Zhaoyu Wang
通讯作者:
Yifei Guo;Yuxuan Yuan;Zhaoyu Wang