Rapid Parameter-Optimizing Strategy for Plug-and-Play Devices in DC Distribution Systems under the Background of Digital Transformation

By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement,information communication,and other fields,the digital DC distribution network can efficiently and reliably access DistributedGenerator(DG)and Energy Storage Systems(ESS),exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play(PnP)operations.However,during device plug-in and-out processes,improper systemparametersmay lead to small-signal stability issues.Therefore,before executing PnP operations,conducting stability analysis and adjusting parameters swiftly is crucial.This study introduces a four-stage strategy for parameter optimization to enhance systemstability efficiently.In the first stage,state-of-the-art technologies in measurement and communication are utilized to correct model parameters.Then,a novel indicator is adopted to identify the key parameters that influence stability in the second stage.Moreover,in the third stage,a local-parameter-tuning strategy,which leverages rapid parameter boundary calculations as a more efficient alternative to plotting root loci,is used to tune the selected parameters.Considering that the local-parameter-tuning strategy may fail due to some operating parameters being limited in adjustment,a multiparameter-tuning strategy based on the particle swarm optimization(PSO)is proposed to comprehensively adjust the dominant parameters to improve the stability margin of the system.Lastly,system stability is reassessed in the fourth stage.The proposed parameter-optimization strategy’s effectiveness has been validated through eigenvalue analysis and nonlinear time-domain simulations.

Robust Carbonated Structural Color Barcodes with Ultralow Ontology Fluorescence as Biomimic Culture Platform

Photonic crystal(PC)barcodes are a new type of spectrum-encoding microcarriers used in multiplex high-throughput bioassays,such as broad analysis of biomarkers for clinical diagnosis,gene expression,and cell culture.Unfortunately,most of these existing PC barcodes suffered from undesired features,including difficult spectrum-signal acquisition,weak mechanical strength,and high ontology fluorescence,which limited their development to real applications.To address these limitations,we report a new type of structural color-encoded PC barcodes.The barcodes are fabricated by the assembly of monodisperse polydopamine-(PDA-)coated silica(PDA@SiO_(2))nanoparticles using a droplet-based microfluidic technique and followed by pyrolysis of PDA@SiO_(2)(C@SiO_(2))barcodes.Because of the templated carbonization of adhesive PDA,the prepared C@SiO_(2)PC beads were endowed with simultaneous easy-to-identify structural color,high mechanical strength,and ultralow ontology fluorescence.We demonstrated that the structural colored C@SiO_(2)barcodes not only maintained a high structural stability and good biocompatibility during the coculturing with fibroblasts and tumor cells capture but also achieved an enhanced fluorescentreading signal-to-noise ratio in the fluorescence-reading detection.These features make the C@SiO_(2)PC barcodes versatile for expansive application in fluorescence-reading-based multibioassays.