Battery Sizing Optimization in Power Smoothing Applications

The main objective of this work was to determine the worth of installing an electrical battery in order to reduce peak power consumption. The importance of this question resides in the expensive terms of energy bills when using the maximum power level. If maximum power consumption decreases, it affects not only the revenues of maximum power level bills, but also results in important reductions at the source of the power. This way, the power of the transformer decreases, and other electrical elements can be removed from electrical installations. The authors studied the Spanish electrical system, and a particle swarm optimization (PSO) algorithm was used to model battery sizing in peak power smoothing applications for an electrical consumption point. This study proves that, despite not being entirely profitable at present due to current kWh prices, implanting a battery will definitely be an option to consider in the future when these prices come down.The authors were supported by the government of the Basque Country through research grants ELKARTEK 21/10: BASQNET: Estudio de nuevas técnicas de inteligencia artificial basadas en Deep Learning dirigidas a la optimización de procesos industriales

Cystoid Macular Edema: Causes, Diagnosis and Treatment

The purpose of this paper is to conduct a review of studies on cystoid macular edema published in the last seven years. Cystoid macular edema is a major cause of loss of visual acuity. It is the final common pathway of many diseases and can be caused by numerous processes including inflammatory, vascular, adverse drug reactions, retinal dystrophy or intraocular tumors. These processes disrupt the blood-retinal barrier, with fluid extravasation to the macular parenchyma. Imaging tests are essential for both detection and monitoring of this pathology. Fluorescein angiography and autofluorescence show the leakage of liquid from perifoveal vessels into the tissue where it forms cystic spaces. Optical coherence tomography is currently the gold standard technique for diagnosis and monitoring. This allows objective measurement of retinal thickness, which correlates with visual acuity and provides more complete morphological information. Based on the underlying etiology, the therapeutic approach can be either surgical or medical with anti-inflammatory drugs. We found that disruption of the blood-retinal barrier for various reasons is the key point in the pathogenesis of cystoid macular edema, therefore we believe that studies on its treatment should proceed on this path

Online Identification of VLRA Battery Model Parameters Using Electrochemical Impedance Spectroscopy

This paper introduces the use of a new low-computation cost algorithm combining neural networks with the Nelder–Mead simplex method to monitor the variations of the parameters of a previously selected equivalent circuit calculated from Electrochemical Impedance Spectroscopy (EIS) corresponding to a series of battery aging experiments. These variations could be correlated with variations in the battery state over time and, therefore, identify or predict battery degradation patterns or failure modes. The authors have benchmarked four different Electrical Equivalent Circuit (EEC) parameter identification algorithms: plain neural network mapping EIS raw data to EEC parameters, Particle Swarm Optimization, Zview, and the proposed new one. In order to improve the prediction accuracy of the neural network, a data augmentation method has been proposed to improve the neural network training error. The proposed parameter identification algorithms have been compared and validated through real data obtained from a six-month aging test experiment carried out with a set of six commercial 80 Ah VLRA batteries under different cycling and temperature operation conditions.Special thanks should also be expressed to the Torres Quevedo (PTQ) 2019 Aid from the State Research Agency, within the framework of the State Program for the Promotion of Talent and its Employability in R + D + i, Ref. PTQ2019-010787/AEI/10.13039/501100011033

Cystoid Macular Edema: Causes, Diagnosis and Treatment

The purpose of this paper is to conduct a review of studies on cystoid macular edema published in the last seven years. Cystoid macular edema is a major cause of loss of visual acuity. It is the final common pathway of many diseases and can be caused by numerous processes including inflammatory, vascular, adverse drug reactions, retinal dystrophy or intraocular tumors. These processes disrupt the blood-retinal barrier, with fluid extravasation to the macular parenchyma. Imaging tests are essential for both detection and monitoring of this pathology. Fluorescein angiography and autofluorescence show the leakage of liquid from perifoveal vessels into the tissue where it forms cystic spaces. Optical coherence tomography is currently the gold standard technique for diagnosis and monitoring. This allows objective measurement of retinal thickness, which correlates with visual acuity and provides more complete morphological information. Based on the underlying etiology, the therapeutic approach can be either surgical or medical with anti-inflammatory drugs. We found that disruption of the blood-retinal barrier for various reasons is the key point in the pathogenesis of cystoid macular edema, therefore we believe that studies on its treatment should proceed on this path

Online Identification of VLRA Battery Model Parameters Using Electrochemical Impedance Spectroscopy

This paper introduces the use of a new low-computation cost algorithm combining neural networks with the Nelder–Mead simplex method to monitor the variations of the parameters of a previously selected equivalent circuit calculated from Electrochemical Impedance Spectroscopy (EIS) corresponding to a series of battery aging experiments. These variations could be correlated with variations in the battery state over time and, therefore, identify or predict battery degradation patterns or failure modes. The authors have benchmarked four different Electrical Equivalent Circuit (EEC) parameter identification algorithms: plain neural network mapping EIS raw data to EEC parameters, Particle Swarm Optimization, Zview, and the proposed new one. In order to improve the prediction accuracy of the neural network, a data augmentation method has been proposed to improve the neural network training error. The proposed parameter identification algorithms have been compared and validated through real data obtained from a six-month aging test experiment carried out with a set of six commercial 80 Ah VLRA batteries under different cycling and temperature operation conditions