Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents...Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.展开更多
A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance i...A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance into consideration,is first determined based on the device＇s physical structure. The photodetector＇s S parameters are then on-wafer measured, and the measured raw data are processed with further calibration. A genetic algorithm is used to fit the measured data, thereby allowing us to calculate each parameter value of the model. Experimental resuits show that the modeled parameters are well matched to the measurements in a frequency range from 130MHz to 20GHz, and the proposed method is proved feasible. This model can give an exact description of the photodetector chip＇s high frequency performance,which enables an effective circuit-level prediction for photodetector and optoelectronic integrated circuits.展开更多
This article proposes the hybrid method to inverse the equivalent electric charge of thunder cloud based on the data of multi-station atmospheric electric field. Firstly,the method combines the genetic algorithm( GA) ...This article proposes the hybrid method to inverse the equivalent electric charge of thunder cloud based on the data of multi-station atmospheric electric field. Firstly,the method combines the genetic algorithm( GA) and New ton method through the mosaic hybrid structure. In addition,the thunder cloud equivalent charge is inversed based on the forw ard modeling results by giving the parameters of the thunder cloud charge structure. Then an ideal model is built to examine the performance compared to the nonlinear least squares method. Finally,a typical thunderstorms process in Nanjing is analyzed by Genetic-New ton algorithm with the help of weather radar. The results show the proposed method has the strong global searching capability so that the problem of initial value selection can be solved effectively,as well as gets the better inversion results. Furthermore,the mosaic hybrid structure can absorb the advantages of tw o algorithms better,and the inversion position is consistent with the strongest radar echo.The inversion results find the upper negative charge is small and can be ignored,w hich means the triple-polarity charge structure is relatively scientific,w hich could give some references to the research like lightning forecasting,location tracking.展开更多
We present a rigorous proof that quantum circuit algorithm can be transformed into quantum adiabatic algorithm with the exact same time complexity. This means that from a quantum circuit algorithm of L gates we can co...We present a rigorous proof that quantum circuit algorithm can be transformed into quantum adiabatic algorithm with the exact same time complexity. This means that from a quantum circuit algorithm of L gates we can construct a quantum adiabatic algorithm with time complexity of O（L）. Additionally, our construction shows that one may exponentially speed up some quantum adiabatic algorithms by properly choosing an evolution path.展开更多
基金supported by the Science and Technology Project of Central China Branch of State Grid Corporation of China under 5214JS220010.
文摘Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.
文摘A small-signal equivalent circuit model and the ted. The equivalent lumped circuit, which takes the main extraction techniques for photodetector chips are presen- factors that limit a photodetector＇s RF performance into consideration,is first determined based on the device＇s physical structure. The photodetector＇s S parameters are then on-wafer measured, and the measured raw data are processed with further calibration. A genetic algorithm is used to fit the measured data, thereby allowing us to calculate each parameter value of the model. Experimental resuits show that the modeled parameters are well matched to the measurements in a frequency range from 130MHz to 20GHz, and the proposed method is proved feasible. This model can give an exact description of the photodetector chip＇s high frequency performance,which enables an effective circuit-level prediction for photodetector and optoelectronic integrated circuits.
基金supported by the National Natural Science Foundation of China ( Grant No. 61072133 )the Production,Learning and Research Joint Innovation Program of Jiangsu Province, China ( Grant Nos. BY2013007-02, SBY201120033)+2 种基金the Major Project Plan for Natural science Research in Colleges and Universities of Jiangsu Province, China( Grant No. 15KJA460008)the Open Topic of Atmospheric Sounding Key Open Laboratory of China Meteorological Administration ( Grant No. KLAS201407)the advantage discipline platform " Information and Communication Engineering" of Jiangsu Province,China
文摘This article proposes the hybrid method to inverse the equivalent electric charge of thunder cloud based on the data of multi-station atmospheric electric field. Firstly,the method combines the genetic algorithm( GA) and New ton method through the mosaic hybrid structure. In addition,the thunder cloud equivalent charge is inversed based on the forw ard modeling results by giving the parameters of the thunder cloud charge structure. Then an ideal model is built to examine the performance compared to the nonlinear least squares method. Finally,a typical thunderstorms process in Nanjing is analyzed by Genetic-New ton algorithm with the help of weather radar. The results show the proposed method has the strong global searching capability so that the problem of initial value selection can be solved effectively,as well as gets the better inversion results. Furthermore,the mosaic hybrid structure can absorb the advantages of tw o algorithms better,and the inversion position is consistent with the strongest radar echo.The inversion results find the upper negative charge is small and can be ignored,w hich means the triple-polarity charge structure is relatively scientific,w hich could give some references to the research like lightning forecasting,location tracking.
基金Supported by the The National Key Research and Development Program of China under Grant Nos 2017YFA0303302 and 2018YFA030562the National Natural Science Foundation of China under Grant Nos 11334001 and 11429402
文摘We present a rigorous proof that quantum circuit algorithm can be transformed into quantum adiabatic algorithm with the exact same time complexity. This means that from a quantum circuit algorithm of L gates we can construct a quantum adiabatic algorithm with time complexity of O（L）. Additionally, our construction shows that one may exponentially speed up some quantum adiabatic algorithms by properly choosing an evolution path.
文摘采用自主水下航行器(Autonomous Underwater Vehicle,AUV)磁测平台可开展海洋地磁场测量、水下磁性目标探测和识别等工作,AUV磁测平台具有广阔的应用前景,但目前AUV载体磁干扰补偿技术研究尚不成熟,制约着水下航行器测磁精度。基于磁测平台抗磁干扰基本原理,提出一种基于线性种群规模缩减和成功历史的参数自适应差分进化(Success History-based Adaptive Differential Evolution with Linear Population Size Reduction,L-SHADE)算法的AUV载体磁干扰参数辨识的数值模拟方法。用磁偶极子和旋转椭球壳混合模型来等效模拟AUV载体磁干扰,通过模拟航行获得多组磁测数据,据此建立磁干扰参数辨识模型,并采用L-SHADE算法求解。通过数值模拟实验定量分析研究磁测平台测磁精度随磁传感器、平台姿态及航向等误差的传播规律。研究结果表明:当磁传感器测量精度为10 nT、姿态测量精度为0.01°、航向测量精度为0.1°时,测磁误差可小于100 nT。设计的AUV磁测平台抗干扰试验表明,地磁场总量最大相对误差为1.07%。
