A comparative study of clustering techniques for electrical load pattern segmentation

Rajabi, Amin; Eskandari, Mohsen; Ghadi, Mojtaba Jabbari; Li, Li; Jiangfeng, Zhang; Siano, Pierluigi

doi:10.1016/j.rser.2019.109628

Cited by 132 publications

(74 citation statements)

References 89 publications

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“…In the rest of this study only the ward linkage criterion is considered, for it produces the most even spread of prosumers among clusters. This observation is consistent with the results in [23].…”

Section: B Hierarchical Clusteringsupporting

confidence: 94%

“…Clustering algorithms for identifying load patterns have been studied extensively in the literature [19], [20], [22], [23], [29]. K-means clustering is often used as a baseline clustering technique [22], [29], and a recent comparative study identifies hierarchical clustering with ward linkage and Gaussian Mixture Model (GMM) with a full-unshared covariance matrix as the best performing clustering techniques in classifying load profiles [23]. These three clustering techniques are used to validate the performance of the proposed clustering based method for nucleolus estimation, which is detailed in Section IV.…”

Section: Clustering Techniques For Classifying Load Profilesmentioning

confidence: 99%

“…It is done by either an agglomerative (bottom-up) or a divisive (top-down) approach. Here, only the agglomerative approach is investigated as it is preferred in power system applications [23]. It begins by treating each instance as an individual cluster, and proceeds by continuously merging clusters that are most similar to each other.…”

Section: B Hierarchical Clusteringmentioning

confidence: 99%

“…To scale up the cooperative energy management scheme while maintaining a high accuracy of nucleolus estimation, this study proposes a new clustering based method, which directly estimates the nucleolus for individual prosumers. For categorizing energy load patterns, K-means clustering is widely used as a reliable baseline clustering technique [22], but hierarchical clustering and Gaussian mixture model (GMM) are shown to have superior performances measured by the Clustering Validity Indexes (CVIs) according to [23]. K-means, hierarchical, and GMM are chosen in this study to demonstrate the effectiveness of the proposed method, but the method can incorporate a wide range of clustering algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Section: B Hierarchical Clusteringsupporting

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Section: Clustering Techniques For Classifying Load Profilesmentioning

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Scaling Up Cooperative Game Theory-Based Energy Management Using Prosumer Clustering

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“…Clustering techniques have been widely used in power system analysis and Rajabi et al [ 20 ] have discussed a literature survey of various clustering techniques available and their application towards smart metering. Out of all the available models for unsupervised learning, the most popular is k-means clustering, which groups data according to a distance-based calculation with respect to a centroid [ 21 ].…”

Section: Gaussian Mixture Model Clustering Technique and Classification Modelmentioning

confidence: 99%

Application of the Gaussian Mixture Model to Classify Stages of Electrical Tree Growth in Epoxy Resin

Mas’ud

Sundaram

Ardila-Rey

et al. 2021

Sensors

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In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters.

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Sustainability assessment in cities in the eastern amazon

Lima,

Progênio,

Costa

et al. 2023

Sustainable Development

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Indicators are important tools that help monitor and assess sustainability, providing crucial information for public management. This study aimed to analyze the behavior of municipalities in eastern amazon (State of Pará), through sustainability indicators that cover social, economic, environmental and basic sanitation dimensions, applying the statistical method of multivariate analysis. For the selection of indicators, a checklist of academic papers on sustainability was carried out. For the composition of the clusters, the Ward method was applied. To validate the number of groups, the Pakhira‐Bandyopadhyay‐Maulik (PBM) index was used, obtaining 2 groups for the sanitation and general dimensions, 3 for environmental and social and 7 groups for economic. In this study, it was possible to demonstrate that several municipalities have deficiencies related to access to water supply and mainly sewage collection and treatment, causing various consequences for the population, as they do not comply with the commitments of the Sustainable Development Goals.

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A comparative study of clustering techniques for electrical load pattern segmentation

Cited by 132 publications

References 89 publications

Scaling Up Cooperative Game Theory-Based Energy Management Using Prosumer Clustering

Scaling Up Cooperative Game Theory-Based Energy Management Using Prosumer Clustering

Application of the Gaussian Mixture Model to Classify Stages of Electrical Tree Growth in Epoxy Resin

Sustainability assessment in cities in the eastern amazon

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