Resilience and cyber-security enhancement of smart grid by using machine learning
| dc.contributor.author | ZUNAIRA NAWAZ | |
| dc.date.accessioned | 2025-12-17T11:51:20Z | |
| dc.date.available | 2025-12-17T11:51:20Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The evolution of the Smart Grid (SG) system enhanced the control and monitoring systems. The smart grid integrates data flows through power lines, intelligent metering, renewable and distributed energy sources, and a monitoring and control infrastructure. Because of the unprecedented complexity and heterogeneity of dynamic smart grid networks, they are more vulnerable to threats including Natural threats and Man-made threats. Resilience has become desired attribute to mitigate these threats. Threats caused disruptions such as blackouts, outages and power failure, etc. In this context, this paper presents a comprehensive literature review of natural and man-made threats and their regarding solutions as well as the evaluation and restoration techniques of resilience. In addition, the properties of the resilience metrics, qualitative and quantitative approaches are also highlighted in this review. | |
| dc.identifier.uri | https://escholar.umt.edu.pk/handle/123456789/16609 | |
| dc.language.iso | en | |
| dc.publisher | UMT Lahore | |
| dc.title | Resilience and cyber-security enhancement of smart grid by using machine learning | |
| dc.type | Thesis |
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