Modeling,Parameter Measurement,and Control of PMSG-based Grid-connected Wind Energy Conversion System

The design of reliable controllers for wind energy conversion systems(WECSs)requires a dynamic model and accurate parameters of the wind generator.In this paper,a dynamic model and the parameter measurement and control of a direct-drive variable-speed WECS with a permanent magnet synchronous generator(PMSG)are presented.An experimental method is developed for measuring the key parameters of the PMSG.The measured parameters are used in the design of the controllers.The generator-side converter is controlled using a vector control scheme that maximizes the power extraction under varying wind speeds.A model predictive controller(MPC)is designed for the grid-side voltage source converter(VSC)to regulate the active and reactive power flows to the power grid by controlling the d-and q-axis currents in the synchronous reference frame.The MPC predicts the future values of the control variables and takes control actions based on the minimum value of the cost functions.To comply with the grid code requirement,a modified design approach for an LCL filter is presented and incorporated into the system.The design process is simple and incorporates significant filter parameters while avoiding iterative calculations.The comparative analysis of the designed filter with conventional L,LC,and iterative LCL filters demonstrates the effectiveness of the modified design approach.The proposed wind energy system with MPC and LCL filter is simulated in MATLAB/Simulink and experimentally implemented in the laboratory using the dSpace digital signal processor(DSP)system.The simulation and experimental results validate the efficacy of the designed controllers using the measured parameters and show dynamic and steady-state performance under varying wind speeds.

Modified robust finite-horizon filter for discrete-time systems with parameter uncertainties and missing measurements

A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.

A Technology for Online Parameter Identification of Permanent Magnet Synchronous Motor

Accuracy of the motor parameters is important in realizing high performance control of permanent magnet synchronous motor(PMSM).However,the inductance and resistance of motor winding vary with the change of temperature,rotor position and current frequency.In this paper,a technology based on circuit model is introduced for realizing online identification of the parameter of PMSM.In the proposed method,a set of nonlinear equations containing the parameters to be identified is established.Considering that it is very difficult to obtain the analytical solution of a nonlinear system of equations,Newton iterative method is used for solving the equations.Both the simulation and testing results confirm the effectiveness of the method presented.

Multi-use laser impulse pendulum and laser propulsion parameters measurement

In order to investigate the mechanisms of both the air-breathing and the ablation modes of laser propulsion under laboratory conditions, a multi-use laser impulse pendulum (MULIP) is developed. The measurable impulse range is from 1.0×10-4 to 3.8×10-3 N·s. The experimental calibration data agree well with the theoretical calculated data. With MULIP, the ablation mode has been performed, in which a high power pulsed Nd:glass laser (λ= 1.06μm, τ=20 ns) and a gray PVC film sample are used. The experimental results show that the maximum momentum coupling coefficient Cm is 7.73×10-5 N/W, and the maximum specific impulse Isp is 208.6 s.

Measurement of algae PSII photosynthetic parameters using high-frequency excitation flashes

We establish a system to measure the functional absorption cross section of photosystem lI （PSII） （O-PSII） and maximum quantum yield of photochemistry in PSII （Fv/Fm）. The system utilizes a sequence of high-frequency excitation flashes at microsecond intervals to induce a microsecond-level fluorescence yield curve. Parameters o-Psii and Fv/Fm are calculated by fitting the curve using nonlinear regression. Experimental results show that the relative standard deviation （RSD） of the system is less than 3%, and the correlation coefficient of Fv/Fm values measured by this system and those measured by pulse amplitude modulation method is 0.950.

Real-time measurement of atmospheric parameters for the 127-element adaptive optics system of 1.8-m telescope

A real-time method for measuring atmospheric parameters based on co-processor field-programmable gate array （FPGA） and main processor digital signal processing （DSP） is proposed for ground-based telescopes with adaptive optics （AO） systems. Coherence length, outer scale, average wind speed, and coherence time are estimated according to closed-loop data on the residual slopes and the corrected voltages of AO systems. This letter introduces the principle and architecture design of the proposed method, which is successfully applied in the 127-element AO system of the 1.8-m telescope of Yunnan Astronomical Observatory. The method enables real-time atmospheric observations with the same object and path of the AO system. This method is also applicable to extended objects.

A polynomial hybrid reflection model and measurement of its parameters based on images of sample

Reflectance model is a basic concept in computer vision. Some existing models combining the classical diffuse reflectance model and those for surfaces containing specular components can approximately describe real reflectance. But the ratio of diffuse and specular reflection decided manually has no clear meaning. We propose a new polynomial hybrid reflectance model. The reflectance map equation with a known shape （for example cylinder） as a sample is used to estimate parameters of the proposed reflectance model by least square regression algorithm. Then the reflectance parameters for surfaces of the same class of materials can be determined. Experiments are performed for a metal surface. The synthesis images produced by the proposed method and existing ones are compared with the real acquired image, and the results show that the proposed reflectance model is suitable for describing real reflectance.

Decision Bayes Criteria for Optimal Classifier Based on Probabilistic Measures

This paper addresses the high dimension sample problem in discriminate analysis under nonparametric and supervised assumptions. Since there is a kind of equivalence between the probabilistic dependence measure and the Bayes classification error probability, we propose to use an iterative algorithm to optimize the dimension reduction for classification with a probabilistic approach to achieve the Bayes classifier. The estimated probabilities of different errors encountered along the different phases of the system are realized by the Kernel estimate which is adjusted in a means of the smoothing parameter. Experiment results suggest that the proposed approach performs well.

Single-turnover and multiple-turnover measurement of phytoplankton photosynthesis parameters using variable light pulse induced fluorescence

Using a measurement system based on fluorescence induced by variable pulse light, photosynthesis parameters of chlorella pyrenoidosa are obtained, employing single-turnover and multiple-turnover protocols under darkadapted and light-adapted conditions. Under the light-adapted condition,σ’PSII is larger, and F’v/F’m（ST） and F’v/F’m（MT） are smaller than those of the dark-adapted condition, but the corresponding parameters possess good linear correlations.Fm（MT）, F’m（MT）, Fv/Fm（MT） and F’v/F’m（MT） which are measured using the multipleturnover protocol, are larger than those of the single-turnover protocol. The linear correlation coefficient between Fm（ST） and Fm（MT） is 0.984,and Fv/Fm（MT） = 1.18 Fv/Fm（ST） The linear correlation coefficient between F’m（ST） and F’m（MT） is 0.995, and F’v/F’m（MT） = 1.36 F’v/F’m/（ST）.

A novel virtual four-ocular stereo vision system based on single camera for measuring insect motion parameters

A novel virtual four-ocular stereo measurement system based on single high speed camera is proposed for measuring double beating wings of a high speed flapping insect. The principle of virtual monocular system consisting of a few planar mirrors and a single high speed camera is introduced. The stereo vision measurement principle based on optic triangulation is explained. The wing kinematics parameters are measured. Results show that this virtual stereo system not only decreases system cost extremely but also is effective to insect motion measurement.

In-Situ Measurements of Cloud-Precipitation Microphysics in the East Asian Monsoon Region Since 1960

A large number of in-situ measurements of cloud-precipitation microphysical properties have been made since 1960, including measurements of particle size distribution, particle concentration, and liquid water content of clouds and rain. These measurements have contributed to considerable progress in understanding microphysical processes in clouds and precipitation and significant improvements in parameterizations of cloud microphysics in numerical models. This work reviews key findings regarding cloud-precipitation microphysics over China. The total number concentrations of various particles vary significantly, with certain characteristic spatial scales. The size distributions of cloud droplets in stratiform clouds can generally be fit with gamma distributions, but the fit parameters cover a wide range. Raindrop size distributions（RSDs）associated with stratiform clouds can be fit with either exponential or gamma distributions, while RSDs associated with convective or mixed stratiform-cumuliform clouds are best fit with gamma distributions.Concentrations of ice nuclei（IN） over China are higher than those observed over other regions, and increase exponentially as temperature decreases. The particle size distributions of ice crystals, snow crystals, and hailstones sampled at a variety of locations can be reliably approximated by using exponential distributions,while aerosol particle size distributions are best described as the sum of a modified gamma distribution and a Junge power-law distribution. These results are helpful for evaluating and improving the fidelity of physical processes and hydrometeor fields simulated by microphysical parameterizations. The comprehensive summary and analysis of previous work presented here also provide useful guidelines for the design of future observational programs.

Quantum Parameter Estimation: From Experimental Design to Constructive Algorithm

In this paper we design the following two-step scheme to estimate the model parameter ω0 of the quantum system: first we utilize the Fisher information with respect to an intermediate variable v = cos(ω0 t) to determine an optimal initial state and to seek optimal parameters of the POVM measurement operators; second we explore how to estimate ω0 from v by choosing t when a priori information knowledge of ω0 is available. Our optimal initial state can achieve the maximum quantum Fisher information. The formulation of the optimal time t is obtained and the complete algorithm for parameter estimation is presented. We further explore how the lower bound of the estimation deviation depends on the a priori information of the model.

Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.