Engineering topics

Miao, Fei

Publications and source records attributed to Miao, Fei.

3 records

DOE OSTI2023

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Deep Reinforcement Learning for Distribution System Cyber Attack Defense with DERs

The use of smart inverter capabilities of distributed energy resources (DERs) enhances the grid reliability but in the meanwhile exhibits more vulnerabilities to cyber-attacks. This paper proposes a deep reinforcement learning (DRL)-based defense approach. The defense problem is reformulated as a Markov decision making process to control DERs and minimizing load shedding to address the voltage violations caused by cyber-attacks. The original soft actor-critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions for controlling DERs' setpoints and loadshedding scenarios. Numerical comparison results with other control approaches, such as Volt-VAR and Volt-Watt on the modified IEEE 33-node, show that the proposed method can achieve better voltage regulation and have less power losses in the presence of cyber-attacks.

active distribution systems↗

DOE OSTI2018

High expression of diffuse panbronchiolitis critical region 1 gene promotes cell proliferation, migration and invasion in pancreatic ductal adenocarcinoma

Highlights: • DPCR1 is overexpressed in PDAC and correlates with prognosis of PDAC patients. • Inhibition of DPCR1 suppresses PDAC cell proliferation in vitro and in vivo. • Inhibition of DPCR1 suppresses PDAC cell migration and invasion. • DPCR1 may promote tumor progression by regulating NF-κB pathway. Diffuse panbronchiolitis critical region 1 (DPCR1) is located in the major histocompatibility complex (MHC) class I. It was reported to be downregulated in invasive pituitary adenoma compared with that in non-invasive tumors, but upregulated in the precursor of gastric carcinogenesis. However, the direct effect of DPCR1 on cancer cells has rarely been reported, and the role DPCR1 in pancreatic ductal adenocarcinoma (PDAC) remains unclear. The clinical sample validation and public data analysis of the present study demonstrated that DPCR1 was upregulated markedly in PDAC and this high expression was negatively correlated with the patient prognosis. Functionally, knocking down DPCR1 in PDAC cell lines inhibited cell proliferation, migration and invasion in vitro. Tumor xenograft experiments further showed that suppression of DPCR1 inhibited tumor growth in vivo. In addition, the results of RNA deep sequencing and qRT-PCR assay showed that DPCR1 participated in PADC progression by regulating nuclear factor-kappa B signaling pathway, suggesting that it might be a novel oncogene in tumor progression and a potential therapeutic target in PDAC as well.

60 APPLIED LIFE SCIENCES↗