FPGA-based online power quality monitoring system for electrical distribution network

Yıldırım, Özal; Eristi, Bekis; Eri̇şti̇, Hüseyin; Ünal, Sencer; Erol, Yavuz; Demir, Yakup

doi:10.1016/j.measurement.2018.02.058

Cited by 35 publications

(13 citation statements)

References 34 publications

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“…DA provides for sensing and monitoring of voltage and power factors at different points on the distribution circuit. If it senses deviation from the expected range, it triggers automatic control of voltage regulating devices [157]. This allows the injection of reactive power and voltage to be regulated to the pre-set value.…”

Section: Distribution Automationmentioning

confidence: 99%

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

et al. 2020

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Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability.

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Section: Distribution Automationmentioning

confidence: 99%

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

et al. 2020

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“…The real-time software platform provides disturbance alerts by checking the database. However, the web tools platform provides graphical tools for user processing [220]. The detection and classification accuracy of PQDs with RE penetration obtained from the experiment framework are illustrated in Table 9.…”

Section: Experimental System Based Pq Analysis With Re Penetrationmentioning

confidence: 99%

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

et al. 2020

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The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This paper presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.

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“…Another method of research and implementation of a USB interfaced real‐time power quality disturbance classification [ 19 ] is proposed but this method differentiates between single and complex power quality disturbances by feature difference and classification of spike is considered as single event not in combination with other, in actual scenario this is impractical, which ignore correlations between single events. A FPGA based technique [ 20 ] which monitors, reports, and classifies power quality disturbances with the help of software and web application which is loaded on an internet based server. When tested on real ground performance degrades in comparison to ideal case.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Power Quality Analysis: Adaptive FEM Algorithm with Sparse Signal Decomposition

Rahul

2020

Advcd Theory and Sims

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An adaptive approach of discretized triangular mesh based on finite element method hybrid with type‐2 fuzzy is utilized for detection and classification of power quality events. The concept of sparse signal decomposition is utilized with extraction of disturbances from power signals. An adaptive finite element method is then applied with the concept of stiffness matrix which extracts some relevant features of power quality events that act as input to type‐2 fuzzy classifiers. Finally performance comparison is carried out, the results of which show that the proposed technique has potential to analyze disturbances with high accuracy and minimum computational overhead.

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FPGA-based online power quality monitoring system for electrical distribution network

Cited by 35 publications

References 34 publications

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

A Novel Approach to Power Quality Analysis: Adaptive FEM Algorithm with Sparse Signal Decomposition

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