Min You Chen

Reactive Power Optimization in Distribution Network with Wind Farm

The traditional methods to adjust voltage in distribution network reactive power optimization is discretization，and it is difficult to realize the continuous voltage adjustment. A reactive power optimization model and algorithm in distribution network with wind farm is proposed. The network loss，deviation of voltage and stability of voltage are taken into account in the multi-objective reactive power optimization model. The quantum particle swarm optimization（QPSO）algorithm has been used to solve the reactive power optimization problem. The algorithm described particle state by wave function, not only increase the diversity of population，but also avoid premature convergence. The comparison of the simulation result between QPSO and PSO on the modified IEEE 33-bus system demonstrated the effectiveness and advantage of quantum particle swarm optimization.

A Novel Method for Online Measuring the Short-Circuit Impedance of Distribution Transformers

The paper proposes a novel method for online measuring the short-circuit impendence of the distribution transformers (DT). The relation expression of the short-circuit impedance with respect to the voltage and current of the primary and secondary side has been developed through the analysis of the equivalent circuit model of a transformer, in which the voltage and current of the DT is collected by 12-channel-data-acquisition unit. And the online SCI is computed by fitting the obtained voltage and current data. The simulation results and comparison illustrated that the proposed method is simpler and more efficient with high accuracy. Besides, the proposed method integrates the linear fitting technique. The simulation results based on Matlab/smulink verified the feasibility and effectiveness of the novel method for online measuring the short-circuit impendence of the DT.

Optimal Capacity Configuration of Energy Storage System for Wind Farm Using Improved Stochastic Particle Swarm Optimization

Wind power generation is not stable and cannot supply constant electrical output, which challenges the attempt to integrate large scale wind power scheme into grids. Hybrid energy storage system (HESS) composed of super-capacitor and battery generally has strong complementarities on the technical performance, which can greatly improve the economic and technical performance of the system when it is used to smooth the volatility of the wind power. However, the main factor influencing the composite energy storage system efficiency is capacity configuration of the storage system. In order to get optimal capacity configuration of the HESS, this paper presents an optimization scheme to improve performance/cost ratio of the HESS while meeting the requirement of smoothing wind power fluctuations. In the optimization model, the power output average and maximum fluctuations in wind farm are taken as main constraints, and simulated annealing method is introduced into Stochastic Particle Swarm Optimization (SPSO) to improve its convergence, which creates an Improved Stochastic Particle Swarm Optimization (ISPSO) to seek the optimal ratio of super-capacitor and battery. Simulation comparison of ISPSO, SPSO and PSO verifies the feasibility and effectiveness of the model for capacity optimization. Meanwhile, it can provide decision-making reference for energy storage system design of wind farm.

A Novel Method for Determining Harmonic Emission Responsibilities at the Point of Common Coupling

This paper presents a novel method for determining the harmonic emission responsibilities of utility and customer at the point of common coupling (PCC). The proposed approach is based on robust partial least squares regression (robust PLS), which estimates system harmonic impedance by utilizing the signals of harmonic voltage and current measured synchronously at PCC. Consequently the harmonic emission responsibilities are calculated. The presented method reduces or removes the effect of outlying data points. The simulation and the practical engineering results indicate that the proposed method is valid and feasible.

Investigation on Condition Monitoring of Convertor

Packaging-related failure has been recognized as one of the principal root causes of convertor failures, condition monitoring is a cost-effective means of improving convertor reliability by power electronic system operator. In this paper, an approach is presented to monitor failure by identifying the case temperature. Firstly, the case temperature is measured at real-time, the transient curves are built based on the measured data respectively. Then, extracting the slope of case temperature from the transient curve during its operation. It is because that the external characteristic of convertor is the reflection of internal condition, once the slope value of the transient curve is higher than that of the normal condition at the same working point, taking account of the masking effect of measuring accuracy and errors, a conclusion can be get that the convertor condition is abnormal. Finally, experiment has validated the proposed method.

An Identification Method of Harmonic Source in the Power System Based on Independent Component Analysis

In this research, an identification method of harmonic source, based on independent component analysis, was proposed. An unknown harmonic source in the equivalent circuit of power system was regarded as the signal source in the independent component analysis. The known voltage and current of PCC were taken as observed quantities. The independent component analysis and the optimization algorithm were utilized to construct a matrix that could linearly transform voltage and current of PCC into mutually independent signal sources. The harmonic impedance and harmonic source of both the user side and system side were obtained. Then the contribution of users to the harmonic distortion at PCC could be identified. With a good anti-jamming property, this algorithm only needs a condition that variations in the harmonic voltage sources at system side and user side are independent to each other. Simulation results indicated the effectiveness of the method to identify the harmonic source of PCC.

HHT-Based Selection of Optimal Time-Frequency Patterns for Motor Imagery

In this paper, a novel method based on Hilbert-Huang transform (HHT) is presented to select optimal timefrequency patterns for single-trial motor imagery electroencephalograph (EEG). The method comprises three progressive steps: 1) employ Empirical Mode Decomposition (EMD) method to decompose EEG signal into a superposition of components or functions called IMFs, and then apply Hilbert transform to the IMFs to calculate the instantaneous frequency and instantaneous amplitude; 2) select the IMFs including the most useful frequency components 3) the optimal timefrequency patterns can be selected according to the instantaneous frequency and instantaneous amplitude of the selected IMFs. After selecting the optimal timefrequency patterns, the features extracted by different methods are classified by Fisher linear discriminator. The results showed that the proposed method could improve the classification accuracy.

A Dynamic Prediction Model for Wind Farm Power Generation Based on RBF Neural Network

As a renewable energy, wind power is considered to be an important non-exhaustible energy in the times of energy crisis. Therefore, in electric power system, wind turbine generators have become important generation alternatives. As wind power penetration increases, power forecasting is crucially important for integrating wind power into a conventional power grid. A short-term wind farm power output dynamic prediction model is presented using RBF neural network with error discriminant function. Based on the wind data from a wind farm in Inner Mongolia of China, a power forecasting map is illustrated, and the errors of the model are analyzed to present the differences between dynamic model and conventional prediction model.

High Impedance Fault Identification Method of Distribution Networks

Abstract. High impedance fault has always been difficult for distribution network fault identification due to its unobvious fault signature and difficult detection. This paper decomposed the transient signal in multi-scale by utilizing the good localization performance of the wavelet in both time domain and frequency domain, reconstructed the wavelet coefficients under each scale, took the wavelet reconstruction coefficient which was under the scale 3, calculated the size spectrum of each feeder line in timing floating window and identified the circuits in which the faults lined according to the value of the size spectrum. The high impedance fault simulation system was built based upon the study of the various transient signals in power systems, and the high impedance fault simulation analysis of the distribution feeder was undertaken through PSCAD simulation platform using high impedance fault model. Simulation analysis showed that the method could effectively extract the feature of high impedance fault on high impedance fault identification.

Modeling and Simulation of Microgrid with Small Hydropower and Wind Generator on Island Operation Mode

A microgrid model with distributed generation including small hydropower source and wind generation source is presented in this paper. The corresponding control strategies for this microgrid are developed. Simulation experiments on island operation mode using Matlab/Simulink software program have been conducted. The simulation results show that the microgrid can operate stably and reliably for load power supply.