Evidence map›Paper›PMID 31744105›Full record

ArticleSensors (Basel, Switzerland)2019

A Distributed Approach for Estimating Battery State-Of-Charge in Solar Farms.

MCarmen Romero-Ternero, David Oviedo-Olmedo, Alejandro Carrasco, Joaquín Luque

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

4 authors.

MCarmen Romero-TerneroDepartamento de Tecnología Electrónica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain.ORCID 0000-0001-6965-9485
David Oviedo-OlmedoDepartamento de Tecnología Electrónica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain.
Alejandro CarrascoDepartamento de Tecnología Electrónica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain.ORCID 0000-0001-9474-3929
Joaquín LuqueDepartamento de Tecnología Electrónica, Universidad de Sevilla, Calle San Fernando, 4, 41004 Sevilla, Spain.ORCID 0000-0001-9041-0035

Funding

Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía P08-TIC-03862
6 · The paper itself

Abstract

A common problem in solar farms is to predict when accumulators stop working optimally and start losing efficiency. This paper proposes and describes how to use Bayesian networks together with expert systems to predict this moment by using a telecontrol multiagent system for monitoring solar farms with distributed sensors, which was developed in a previous work. To this end, a Bayesian network model and its implementation are proposed. The resulting system meets the requirements of telecontrol systems (reliability, flexibility, and response time), yields a solution for the prediction of lifespan batteries, and provides the multiagent system with autonomous intelligent capabilities and integrated learning.

Indexed as

battery SOCBayesian networkestimationexpert systemmulti-agent systemsensorssolar farm

Identifiers

PMID31744105
PMCPMC6891556

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.