Total Power Quality Index for Electrical Networks Using Neural Networks

Raptis, T. E.; Vokas, Georgios A.; Langouranis, P.A.; Kaminaris, Stavrοs D.

doi:10.1016/j.egypro.2015.07.706

Cited by 27 publications

(12 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, the cluster analysis results are analyzed to establish an evaluation system. Also, the concept of "global/synthetic/unified/total" power quality indices are indicated in the literature, such as total power quality index [49,50], synthetic power quality index [51,52], unified power quality index [53,54], or global power quality index [55,56]. All of these approaches are aimed toward reducing the number of analyzing power quality data.…”

Section: Introductionmentioning

confidence: 99%

A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements

et al. 2021

View full text Add to dashboard Cite

One of the recent trends that concern renewable energy sources and energy storage systems is the concept of virtual power plants (VPP). The majority of research now focuses on analyzing case studies of VPP in different issues. This article presents the investigation that is based on a real VPP. That VPP operates in Poland and consists of hydropower plants (HPP), as well as energy storage systems (ESS). For specific analysis, cluster analysis, as a representative technique of data mining, was selected for power quality (PQ) issues. The used data represents 26 weeks of PQ multipoint synchronic measurements for 5 related to VPP points. The investigation discusses different input databases for cluster analysis. Moreover, as an extension to using classical PQ parameters as an input, the application of the global index was proposed. This enables the reduction of the size of the input database with maintaining the data features for cluster analysis. Moreover, the problem of the optimal number of cluster selection is discussed. Finally, the assessment of clustering results was performed to assess the VPP impact on PQ level.

show abstract

Section: Introductionmentioning

confidence: 99%

A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Thus, the concept of the global index was introduced. Such an approach, in the literature, is known under different names e.g., global power quality index [15,16]; unified power quality index [17,18]; total power quality index [19,20]; or synthetic power quality index [21,22].…”

Section: Introductionmentioning

confidence: 99%

A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data

et al. 2021

View full text Add to dashboard Cite

The integration of virtual power plants (VPP) has become more popular. Thus, research on VPP for different issues is highly desirable. This article addresses power quality issues. The presented investigation is based on multipoint, synchronic measurements obtained from five points that are related to the VPP. This article provides a proposition and discussion of using one global index in place of the classical power quality (PQ) parameters. Furthermore, in the article, one new global power quality index was proposed. Then the PQ measurements, as well as global indexes, were used to prepare input databases for cluster analysis. The mentioned cluster analysis aimed to detect the short-term working conditions of VPP that were specific from the point of view of power quality. To realize this the hierarchical clustering using the Ward algorithm was realized. The article also presents the application of the cubic clustering criterion to support cluster analysis. Then the assessment of the obtained condition was realized using the global index to assure the general information of the cause of its occurrence. Furthermore, the article noticed that the application of the global index, assured reduction of database size to around 74%, without losing the features of the data.

show abstract

“…Relevant standards and methods of data analysis are presented in [5,6]. Algorithms based on machine learning [7], known as Support Vector Machines (SVM) [8,9], Artificial Neural Networks (ANN) [10,11], Genetic Algorithms (GA) [12] and their combinations, are the main approaches to this issue. On the other hand, there are scientific works in which methods, such as Wavelet Transformations (WT) [13] or Fuzzy based detection [14], are used for detecting the decrease of the power quality on the basis of learned patterns.…”

Section: Introductionmentioning

confidence: 99%

The Estimation of the Influence of Household Appliances on the Power Quality in a Microgrid System

et al. 2020

View full text Add to dashboard Cite

This article presents the analysis of the influence of household appliances on the quality of the energy consumed by the end-user. The results of the research, then, concern the final consumer (the lowest level of the power grid). The research was conducted on 120 combinations of electrical appliances connected into a grid. Each combination consisted of three devices working simultaneously in a micro-grid. The obtained and statistically analyzed data proved that there are several types of appliances that have a great influence on the power quality (PQ) parameters changes. The results of the conducted experiments indicate the devices which influenced significantly the total harmonic distortion of voltage (THDV), the voltage frequency (FREQ) and the voltage fluctuation (V). Specific features of particular devices were examined in terms of their significance for the power quality deviation. This showed the most important features which should be considered while working out the prediction model. The future of smart grids resides in data analysis, predictive models and real-time optimization. One of the key characteristics is the reducing energy consumption generated by renewable energy sources. This phenomenon, namely looking for problems connected with sustainable power quality and their appropriate solution, is described in this article. We performed an extended analysis of the smart home appliances influence of individual quantities on a real model. Furthermore, we explored devices with a high impact on chosen power quality indicators. In the end, we discuss their specific behavior and relevance to the above-described phenomenon to improve the predictive model utility.

show abstract

Total Power Quality Index for Electrical Networks Using Neural Networks

Cited by 27 publications

References 16 publications

A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements

A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements

A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data

The Estimation of the Influence of Household Appliances on the Power Quality in a Microgrid System

Contact Info

Product

Resources

About