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The Future of Adaptive Grids using the Kalman Filter, for Data Smoothing and Data Prediction

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http://hdl.handle.net/20.500.14044/32468
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  • Acta Polytechnica Hungarica [175]
Abstract
The modern power grid is facing unprecedented challenges, due to a rapid integration of renewable energy sources. Renewable sources, such as solar and wind power, are inherently variable and unpredictable, introducing fluctuations in power generation that can destabilize the grid. Additionally, the increasing interconnectedness of power grids across regions and countries further complicates grid management. To address these challenges and ensure the continued reliable operation of the power grid, adaptive control techniques, and real-time monitoring systems are emerging as indispensable tools. Adaptive control systems can dynamically adjust generation and load to maintain grid stability and resilience while optimizing power flow and efficiency. Real-time monitoring systems provide valuable data for these control algorithms to operate effectively, enabling the grid to adapt to changing conditions and minimize disruptions. This paper provides an overview of the challenges and opportunities presented by the integration of renewable energy sources into the power grid. It discusses the role of adaptive control and real-time monitoring in addressing these challenges and ensuring the reliable operation of the power grid. Additionally, the paper explores emerging technologies, that aim to enhance the capabilities of adaptive control systems and further optimize grid operations.
 
The modern power grid is facing unprecedented challenges, due to a rapid integration of renewable energy sources. Renewable sources, such as solar and wind power, are inherently variable and unpredictable, introducing fluctuations in power generation that can destabilize the grid. Additionally, the increasing interconnectedness of power grids across regions and countries further complicates grid management. To address these challenges and ensure the continued reliable operation of the power grid, adaptive control techniques, and real-time monitoring systems are emerging as indispensable tools. Adaptive control systems can dynamically adjust generation and load to maintain grid stability and resilience while optimizing power flow and efficiency. Real-time monitoring systems provide valuable data for these control algorithms to operate effectively, enabling the grid to adapt to changing conditions and minimize disruptions. This paper provides an overview of the challenges and opportunities presented by the integration of renewable energy sources into the power grid. It discusses the role of adaptive control and real-time monitoring in addressing these challenges and ensuring the reliable operation of the power grid. Additionally, the paper explores emerging technologies, that aim to enhance the capabilities of adaptive control systems and further optimize grid operations.
 
Title
The Future of Adaptive Grids using the Kalman Filter, for Data Smoothing and Data Prediction
Author
Palfi, Judith
xmlui.dri2xhtml.METS-1.0.item-date-issued
2024
xmlui.dri2xhtml.METS-1.0.item-rights-access
Open access
xmlui.dri2xhtml.METS-1.0.item-identifier-issn
1785-8860
xmlui.dri2xhtml.METS-1.0.item-language
en
xmlui.dri2xhtml.METS-1.0.item-format-page
16 p.
xmlui.dri2xhtml.METS-1.0.item-subject-oszkar
power grid, renewable source, WAMS, frequency stability, voltage stability, protections, real-time monitoring, adaptive control algorithm, Kalman filter, smoothing, prediction
xmlui.dri2xhtml.METS-1.0.item-description-version
Kiadói változat
xmlui.dri2xhtml.METS-1.0.item-identifiers
DOI: 10.12700/APH.21.10.2024.10.22
xmlui.dri2xhtml.METS-1.0.item-other-containerTitle
Acta Polytechnica Hungarica
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalYear
2024
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalVolume
21. évf.
xmlui.dri2xhtml.METS-1.0.item-other-containerPeriodicalNumber
10. sz.
xmlui.dri2xhtml.METS-1.0.item-type-type
Tudományos cikk
xmlui.dri2xhtml.METS-1.0.item-subject-area
Műszaki tudományok - anyagtudományok és technológiák
xmlui.dri2xhtml.METS-1.0.item-publisher-university
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