A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

Taghvaie, A.; Fernando, Tharindu; Kumar, Dinesh; Zare, Firuz; Sharma, Rahul; Vilathgamuwa, D.M.

doi:10.1109/access.2023.3260768

Cited by 14 publications

(3 citation statements)

References 93 publications

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“…Regarding the extensively used of AI in harmonic distortion studies, some of researchers focused on reviewing these previous studies in [21][22][23][24][25]. Moreover, the applications of ANNs and ANFIS in these tasks have been addressed.…”

Section: Figure 1 a Diagram Of Recent Electricity Distribution Networkmentioning

confidence: 99%

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Accurate Identification of Harmonic Distortion for Micro-Grids Using Artificial Intelligence-Based Predictive Models

Abed,

El-Sehiemy,

Bentouati

et al. 2024

IEEE Access

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This paper proposes an accurate harmonic identification strategy for microgrids and distributed power systems. The harmonic identification strategy is one of the complex tasks in microgrids due to the need of high computational burden in terms of memory and computational time. The complexity of the considered problem is resulted from solving the transcendental nonlinear equations that characterize harmonics especially in real time is considered as a highly challenged problem. The proposed identification strategy aims at detecting individual and total harmonic distortion levels that is generated from several harmonic sources. In the current paper, the Machine Learning Regression Analysis (MLRA) including location-specific data and the Artificial Neural Networks (ANNs) are proposed to identify the harmonic distortion. To enhance the identification and prediction performance, the standard IEEE 34-bus test feeder with verified harmonic sources power system is emulated for various scenarios using Electric Transient Analysis Program (ETAP). An extracting procedure for individual and total harmonic components are employed . The higher reduction level of error with approximately maximum median of 3.7127e-15 % assures the accurate prediction of harmonic components. In addition, this work investigates the impact of several practical cases when the voltages of the renewable clean energy source arrays vary (e.g., solar cell, wind turbine, and EV), and a double-stage topology is needed to have the same amount of voltage at the input of the inverter before inversion.

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Section: Figure 1 a Diagram Of Recent Electricity Distribution Networkmentioning

confidence: 99%

“…Both conventional and contemporary (smart) harmonic estimation methods are thoroughly reviewed in Ref. [23]. New, clever AI techniques that are quick, precise, and effective have been examined as alternatives to address the problems with traditional estimation techniques.…”

Section: Figure 1 a Diagram Of Recent Electricity Distribution Networkmentioning

confidence: 99%

Accurate Identification of Harmonic Distortion for Micro-Grids Using Artificial Intelligence-Based Predictive Models

Abed,

El-Sehiemy,

Bentouati

et al. 2024

IEEE Access

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“…[24] Tecnologías de inteligencia artificial para la estimación de armónicos en las redes de distribución, por la gran importancia de estimar y predecir los niveles de armónicos [24].…”

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Evaluation of Passive Filters for the Management of Harmonics in Industrial Electrical Distribution Networks

Ladino Serrano,

Paternina Durán,

Vitola Oyaga

et al. 2023

TecnoL.

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Es necesario gestionar armónicos para obtener calidad energética en sistemas de distribución. Por lo cual, este artículo tuvo como objetivo evaluar el uso de filtros pasivos como alternativa viable para la gestión armónica en redes de distribución eléctricas en media tensión con alta carga industrial, mediante el análisis de Índices de Distorsión Armónica Total que fueron calculados y graficados con el software Matlab. Así, primero se propuso un caso de estudio con base en la red de distribución IEEE 34 nodos, para posteriormente, definir cuatro escenarios de simulación que permiten la integración de bancos de condensadores, reactancias de rechazo y fuentes de armónicos. Partiendo de un diseño matemático se analizó el flujo de carga armónico diario para cada hora, y se propusieron mecanismos de diseño de reactancias de rechazo como complemento a las soluciones tradicionales de corrección de factor de potencia basadas en bancos de condensadores. Los resultados mostraron que, el uso de los filtros pasivos LC pueden ser altamente efectivos para la gestión de distorsión armónica de tensión, pero insuficientes para la eliminación de distorsión armónica de corriente. Sin embargo, esta clase de filtros sí muestran completa eficacia en la limitación de amplificación de armónicos (tanto de tensión, como de corriente) al utilizar bancos de condensadores para la corrección de factor de potencia en sistemas con problemáticas de armónicos. Concluyendo que los filtros pasivos LC con reactancias de rechazo mitigan armónicos de voltaje así se tengan bancos de condensadores y fuentes de armónicos, lo que los convierte en la forma más factible, eficaz y económica de obtener calidad energética.

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Electric vehicles as facilitators of grid stability and flexibility: A multidisciplinary overview

Štogl,

Miltner,

Zanocco

et al. 2024

WIREs Energy & Environment

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Electric vehicles (EVs), as facilitators of grid stability and flexibility, provide a critical solution to the energy infrastructure's evolving demands, underscored by the growing integration of renewable energy sources (RES) and the rapid increase in EV adoption worldwide. This trend is particularly evident in Europe which is experiencing dramatic increases in both the adoption of RES and EVs. Vehicle‐to‐grid (V2G) technology allows EVs to operate as a two‐way power flow to both draw and feed electricity into the grid. This multidisciplinary overview examines the role of V2G systems in enhancing grid performance, identifying corporate vehicle fleets as key flexibility providers, and integration with Smart Grid technologies as a key element for successful V2G implementation. In a scoping analysis of recent literature (2005–2024), we identify challenges such as privacy, security, and regulatory compliance as well as a critical gap in establishing economically sustainable models for aggregators, distribution system operators (DSOs), generation companies (GENCOs), and end‐users. Drawing from these insights, we then discuss the necessity for future research to develop models that ensure equitable benefits across stakeholders and the importance of models that can adapt to country‐specific mechanisms. The findings from our overview argue that the integration of EVs, V2G, and RES are essential components for developing future energy systems that are resilient, adaptable, decarbonized, and sustainable.This article is categorized under: Cities and Transportation > Electric Mobility Energy and Power Systems > Energy Infrastructure Energy and Power Systems > Energy Management

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A Comprehensive Review of Harmonic Issues and Estimation Techniques in Power System Networks Based on Traditional and Artificial Intelligence/Machine Learning

Cited by 14 publications

References 93 publications

Accurate Identification of Harmonic Distortion for Micro-Grids Using Artificial Intelligence-Based Predictive Models

Accurate Identification of Harmonic Distortion for Micro-Grids Using Artificial Intelligence-Based Predictive Models

Evaluation of Passive Filters for the Management of Harmonics in Industrial Electrical Distribution Networks

Electric vehicles as facilitators of grid stability and flexibility: A multidisciplinary overview

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