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Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

Energy Engineering 2023年第9期120卷 2013-2027页

作者： Zhonghao Qian Hanyi Ma jun Rao jun Hu Lichengzi Yu Caoyi Feng Yunxu Qiu Kemo Ding State Grid jiangsu Nantong Electric Power Co. Ltd.Nantong226000China College of Energy and Electrical Engineering Hohai UniversityNanjing211100China

The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind *** improve the voltage stability and reactive power economy of wind farms,the improved particle swarmoptimization is used to optimize the reactive power planning in wind ***,the power flow of offshore wind farms is modeled,analyzed and *** improve the global search ability and local optimization ability of particle swarm optimization,the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning *** the minimum active power loss of the offshore wind farms as the objective function,the installation location of the reactive power compensation device is compared according to the node voltage amplitude and the actual engineering ***,a reactive power optimizationmodel based on Static Var Compensator is established inMATLAB to consider the optimal compensation capacity,network loss,convergence speed and voltage amplitude enhancement effect of *** the compensation methods in several different locations,the compensation scheme with the best reactive power optimization effect is ***,the optimization results of the standard particle swarm optimization and the improved particle swarm optimization are compared to verify the superiority of the proposed improved algorithm.

关键词： Offshore wind farms improved particle swarm optimization reactive power optimization adaptive weight asynchronous learning factor voltage stability

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Characterization of bacteriophage BUCT631 lytic for K1 Klebsiella pneumoniae and its therapeutic efficacy in Galleria mellonella larvae

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Virologica Sinica 2023年第5期38卷 801-812页

作者： Pengjun Han Mingfang Pu Yahao Li Huahao Fan Yigang Tong College of Life Science and Technology Beijing University of Chemical TechnologyBeijing100029China Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical TechnologyBeijing100029China

Severe infections caused by multidrug-resistant Klebsiella pneumoniae(***)highlight the need for new therapeutics with activity against this *** therapy is an alternative treatment approach for multidrug-resistant *** ***,we report a novel bacteriophage(phage)BUCT631 that can specifically lyse capsule-type K1 *** characterization revealed that phage BUCT631 could rapidly adsorb to the surface of *** and form an obvious halo ring,and it had relatively favorable thermal stability(4–50C)and pH tolerance(pH?4–12).In addition,the optimal multiplicity of infection(MOI)of phage BUCT631 was 0.01,and the burst size was approximately 303 PFU/*** analysis showed that phage BUCT631 has double-stranded DNA(total length of 44,812 bp)with a G t C content of 54.1%,and the genome contains 57 open reading frames(ORFs)and no virulence or antibiotic resistance related *** on phylogenetic analysis,phage BUCT631 could be assigned to a new species in the genus Drulisvirus of the subfamily *** addition,phage BUCT631 could quickly inhibit the growth of *** within 2 h in vitro and significantly elevated the survival rate of *** infected Galleria mellonella larvae from 10%to 90%in *** studies suggest that phage BUCT631 has promising potential for development as a safe alternative for control and treatment of multidrug-resistant *** infection.

关键词： Bacteriophage BUCT631 Klebsiella pneumoniae Genomic analysis Phage therapy Galleria mellonella

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High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning

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Photonics Research 2022年第10期10卷 2343-2348页

作者： BING DUAN HANYING ZOU jIN-HUI CHEN CHUN HUI MA XINGYUN ZHAO XIAOLONG ZHENG CHUAN WANG LIANG LIU DAQUAN YANG State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia Beijing University of Posts and TelecommunicationsBeijing 100876China Institute of Electromagnetics and Acoustics and Fujian Provincial Key Laboratory of Electromagnetic Wave Science and Detection Technology Xiamen UniversityXiamen 361005China Shenzhen Research Institute of Xiamen University Shenzhen 518000China School of Artificial Intelligence Beijing Normal UniversityBeijing 100875China

Whispering gallery mode(WGM)microcavities provide increasing opportunities for precision measurement due to their ultrahigh sensitivity,compact size,and fast ***,the conventional WGM sensors rely on monitoring the changes of a single mode,and the abundant sensing information in WGM transmission spectra has not been fully ***,empowered by machine learning(ML),we propose and demonstrate an ergodic spectra sensing method in an optofluidic microcavity for high-precision pressure *** developed ML method realizes the analysis of the full features of optical *** prediction accuracy of 99.97%is obtained with the average error as low as 0.32 kPa in the pressure range of 100 kPa via the training and testing *** further achieve the real-time readout of arbitrary unknown pressure within the range of measurement,and a prediction accuracy of 99.51%is ***,we demonstrate that the ergodic spectra sensing accuracy is∼11.5%higher than that of simply extracting resonating modes’*** the high sensitivity and prediction accuracy,this work opens up a new avenue for integrated intelligent optical sensing.

关键词： measurement spectra prediction

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