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

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 w...

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Detalles Bibliográficos
Autores principales: Romero-Ternero, MCarmen, Oviedo-Olmedo, David, Carrasco, Alejandro, Luque, Joaquín
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891556/
https://www.ncbi.nlm.nih.gov/pubmed/31744105
http://dx.doi.org/10.3390/s19224998
Descripción
Sumario: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.