Evidence map›Paper›PMID 31083377›Full record

ArticleSensors (Basel, Switzerland)2019

Power Factor Compensation Using Teaching Learning Based Optimization and Monitoring System by Cloud Data Logger.

Antonio Cano Ortega, Francisco Jose Sánchez Sutil, Jesús De la Casa Hernández

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Antonio Cano OrtegaDepartment of Electrical Engineering, University of Jaen, 23071 EPS Jaen, Spain. acano@ujaen.es.ORCID 0000-0002-6440-021X
Francisco Jose Sánchez SutilDepartment of Electrical Engineering, University of Jaen, 23071 EPS Jaen, Spain. fssutil@ujaen.es.
Jesús De la Casa HernándezDepartment of Electrical Engineering, University of Jaen, 23071 EPS Jaen, Spain. jcasa@ujaen.es.ORCID 0000-0001-9117-1689

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main objective of this paper is to compensate power factor using teaching learning based optimization (TLBO), determine the capacitor bank optimization (CBO) algorithm, and monitor a system in real-time using cloud data logging (CDL). Implemented Power Factor Compensation and Monitoring System (PFCMS) calculates the optimal capacitor combination to improve power factor of the installation by measure of voltage, current, and active power. CBO algorithm determines the best solution of capacitor values to install, by applying TLBO in different phases of the algorithm. Electrical variables acquired by the sensors and the variables calculated are stored in CDL using Google Sheets (GS) to monitor and analyse the installation by means of a TLBO algorithm implemented in PFCMS, that optimizes the compensation power factor of installation and determining which capacitors are connected in real time. Moreover, the optimization of the power factor in facilities means economic and energy savings, as well as the improvement of the quality of the operation of the installation.

Indexed as

capacitor bank optimization CBOCloud data logger CDLPower factor compensation monitoring system PFCMSpower factor PFTeaching learning based optimization TLBO

Identifiers

PMID31083377
PMCPMC6539470

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.