Open Access

ARTICLE

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

Yilei Wang¹, Xin Sun¹, Guiping Zheng^2,3, Ahmar Rashid⁴, Sami Ullah⁵, Hisham Alasmary⁶, Muhammad Waqas^7,8,*

1 Zhejiang Electric-Power Corporation Research Institute, Zhejiang, 310014, China
2 Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China
3 Beijing Trusty Cloud Technology Co., Ltd., Beijing, 100022, China
4 Department of Computer Science and Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering, Topi, 23640, Pakistan
5 Department of Computer Science, Shaheed Benazir Bhutto University, Sheringal, Upper Dir, 18050, Pakistan
6 Department of Computer Science, College of Computer Science, King Khalid University, Abha, 61421, Saudi Arabia
7 School of Computing and Mathematical Science, Faculty of Engineering and Science, University of Greenwich, London, SE10 9LS, UK
8 School of Engineering, Edith Cowan University, Perth, 6027, Australia

* Corresponding Author: Muhammad Waqas. Email:

Computers, Materials & Continua 2024, 78(3), 3909-3927. https://doi.org/10.32604/cmc.2024.047767

Received 16 November 2023; Accepted 24 January 2024; Issue published 26 March 2024

Abstract

The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues. The scheme begins by establishing a hierarchical trust measurement model, elucidating the trust relationships among smart IoT terminals. It then incorporates multidimensional measurement factors, encompassing static environmental factors, dynamic behaviors, and energy states. This comprehensive approach reduces the impact of subjective factors on trust measurements. Additionally, the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units, ensuring the prompt identification and elimination of any malicious terminals. This, in turn, enhances the security and reliability of the smart grid environment. The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments. Notably, the scheme outperforms established trust metric models in terms of energy efficiency, showcasing its significant contribution to the field.

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Keywords

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