A secure forecasting-aided state estimation framework for power distribution systems against false data injection attacks-Reference-Cited by-同舟云学术

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A secure forecasting-aided state estimation framework for power distribution systems against false data injection attacks

Published:2022-12 Issue: Volume:328 Page:120107
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Xu Junjun,Wu Zaijun,Zhang Tengfei,Hu Qinran,Wu Qiuwei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference45 articles.

1. A novel data-driven scenario generation framework for transmission expansion planning with high renewable energy penetration;Sun;Appl Energy,2018

2. Benefits of smart control of hybrid heat pumps: an analysis of field trial data;Sun;Appl Energy,2019

3. Short-term load prediction of integrated energy system with wavelet neural network model based on improved particle swarm optimization and chaos optimization algorithm;Ge;J Mod Power Syst Clean Energy,2021

4. Optimal integrated energy system planning with DG uncertainty affine model and carbon emissions charges;Ge;IEEE Trans Sustainable Energy,2022

5. CCPA: coordinated cyber-physical attacks and countermeasures in smart grid;Deng;IEEE Trans Smart Grid,2017

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3. Localization of dummy data injection attacks in power systems considering incomplete topological information: A spatio-temporal graph wavelet convolutional neural network approach;Applied Energy;2024-04

4. Resilience enhancement of active distribution networks under extreme disaster scenarios: A comprehensive overview of fault location strategies;Renewable and Sustainable Energy Reviews;2024-01

5. A Feasibility Area Approach for Early Stage Detection of Stealthy Infiltrated Cyberattacks in Power Systems;IEEE Transactions on Information Forensics and Security;2024

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