Journal ArticleDOI
Power quality recognition in distribution system with solar energy penetration using S-transform and Fuzzy C-means clustering
TLDR
In this paper, the authors presented a technique to recognize the power quality disturbances associated with solar energy penetration in distribution network using a standard IEEE-13 bus test system modified by incorporating the solar PV system.About:
This article is published in Renewable Energy.The article was published on 2017-06-01. It has received 83 citations till now. The article focuses on the topics: Photovoltaic system & Solar energy.read more
Citations
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Journal ArticleDOI
Impact of harmonic limits on PV penetration levels in unbalanced distribution networks considering load and irradiance uncertainty
TL;DR: In this article, a probabilistic and deterministic approach is proposed to determine the optimal penetration levels of PV systems in unbalanced distorted distribution networks by taking into account the uncertainty of load profile and the intermittent characteristic of PV system output power due to changes in solar irradiance.
Journal ArticleDOI
Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review
Raul Igual,Carlos Medrano +1 more
TL;DR: A critical systematic review focused specifically on real-time applications to obtain a viable, accurate, fast, low-cost, and embeddable power quality classification system that facilitates the inclusion of distributed renewable energy sources in microgrids.
Journal ArticleDOI
CMBSNN for Power Flow Management of the Hybrid Renewable Energy – Storage System-Based Distribution Generation
TL;DR: A new Combined Modified Bat Search algorithm and artificial neural network control of grid-connected Hybrid Renewable Energy System (HRES) is presented, able to significantly enhance the dynamic security of the power system.
Journal ArticleDOI
Clustering as a tool to support the assessment of power quality in electrical power networks with distributed generation in the mining industry
TL;DR: A case study of using cluster analysis (CA) as one of the data mining techniques applied in the analysis of long-term power quality data that is recorded in electrical power networks of the mining industry shows the possibility to obtain automatic classification of data into distinguishable clusters.
Journal ArticleDOI
An Algorithm for Recognition of Fault Conditions in the Utility Grid with Renewable Energy Penetration
Govind Sahay Yogee,Om Prakash Mahela,Kapil Dev Kansal,Baseem Khan,Rajendra Mahla,Hassan Haes Alhelou,Pierluigi Siano +6 more
TL;DR: A hybrid grid protection scheme (HGPS) for the protection of the grid with RE integration is introduced that combines the merits of the Stockwell Transform, Hilbert Transform, and Alienation Coefficient to improve performance of the protection scheme.
References
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Journal ArticleDOI
Localization of the complex spectrum: the S transform
TL;DR: The S transform is shown to have some desirable characteristics that are absent in the continuous wavelet transform, and provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum.
Journal Article
Localisation of the complex spectrum : The S transform
TL;DR: The S transform as discussed by the authors is an extension to the ideas of the Gabor transform and the Wavelet transform, based on a moving and scalable localising Gaussian window and is shown here to have characteristics that are superior to either of the transforms.
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Radial distribution test feeders
TL;DR: In this paper, the authors present an updated version of the same test feeders along with a simple system that can be used to test three-phase transformer models, which is a common set of data that could be used by program developers and users to verify the correctness of their solutions.
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Power quality assessment via wavelet transform analysis
TL;DR: In this article, the authors present a new approach to detect, localize, and investigate the feasibility of classifying various types of power quality disturbances using dyadic-orthonormal wavelet transform analysis.
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Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network
TL;DR: The simulation results reveal that the combination of S-Transform and PNN can effectively detect and classify different PQ events and it is found that the classification performance of PNN is better than both FFML and LVQ.