Study On The Related Power Quality Disturbance Problems

With the development of electric power industry, and the wide use of electric and electronic equipments and impulse load in power system, power quality (PQ) is becoming increasingly serious. Among the PQ problems caused by various disturbances, researches on PQ are limited in terms of the detection algorithm, the related PQ index, industry standard and national standard, detection device and suppression method. Although some researches on PQ have been made and some achievements have been obtained,up to now, there is no perfect analysis method. Owing to the extensive harm of PQ and the deficiency of analysis and detection methods, it is necessary to strengthen the researches on the algorithms of denoising, compression, detection and classification of PQ disturbances and develop practical detection device as soon as possible.Based on the related PQ disturbance problems, the algorithms of denoising, compressing, detection and classification of PQ disturbances are studied in this paper. The main achievements of this paper are as follows.(1) A new device is designed to on-line detect and classify of PQ disturbances. This device applies DSP and FPGA and simple peripheral circuit to realize the function of signal acquisition, processing and display. A simple and effective methodology for classification and quantification of nine typical kinds of PQ disturbances is proposed in this paper. Five distinguished time-frequency statistical features of each type of PQ disturbances are extracted. Using a rule-based decision tree, the PQ disturbance pattern can be recognized easily. Finally, the proposed method is implemented and its performance is verified on detection and classification of real and simulated PQ disturbances in the device. The results show that the developed device offers good classification accuracy and real-time performances.(2) This paper proposes an adaptive threshold estimation algorithm for PQ signal denoising based wavelet neighboring thresholding classification. For input signals, firstly the optimal neighboring window size is proposed by modulus maximum wavelet domain. In wavelet domain, it shows that detail wavelet coefficients come as groups and have high local correlation. Then according to its corresponding neighboring threshold, each coefficient in a subband is classified as "large" or "small" category. Those "small" coefficients are set to zero; whereas those "large" coefficients are obtained by minimum mean squared error criterion. The effectiveness of the proposed method is illustrated for the actual PQ signals denoising. Simulation results show that the proposed method has outperformed the other traditional adaptive denoising algorithms.(3) A PQdisturbance data compression method is presented using the harmonic notch filters (HNF) technique. The proposed method makes use of the HNFs technique for estimating the parameters (amplitude, frequency, and phase) of the fundamental and harmonic components and separate them from the transient ones in the PQ signals. Then, the deterministic sinusoidal component and the residual signal are compressed by the parameter quantization and wavelet transform (WT)-based compression techniques, respectively. The proposed method has been verified by using actual PQ disturbance data. The experimental results show that the proposed method is suitable for various morphologies of PQ disturbance data, and achieves higher compression ratio with the characteristic features well preserved. The proposed algorithm is promising for practical use.JPEG2000 is the latest international standard for compression of still images. Although the JPEG2000 codec is designed to compress images, here we illustrate how the JPEG2000 codec can be used to compress PQ disturbance data. Experiments using the actual PQ disturbance signals illustrate that the proposed approach outperforms some existing PQ data compression methods. The proposed method allows the use of existing hardware and software JPEG2000 codecs for PQ data compression, and can be especially useful in eliminating the need for specialized hardware development. The desirable characteristics of the JPEG2000 codec, such as precise rate control and progressive transmission, are retained in the presented scheme.(4) With the wide application of sensitive power electronic devices in industry, the PQ disturbance problem become more concerned. The S-transform is a time-frequency localization technique that bridges the gap between the short-time Fourier transform and wavelet transforms. We propose a new method based on S-transform time-frequency analysis and Fuzzy logic was presented for PQ disturbances identification. Through S-transform time-frequency analysis, the method detects out the PQ disturbances effectively. Then, feature components were extracted from the detecting outputs for classification. Finally Fuzzy expert system was used to identify of PQ disturbances. Simulation results show that the proposed method possesses high recognition rate and strong resistances to noises, so it is suitable to the monitoring and classifications system for PQ disturbances.The PQ signals are traditionally analyzed in the time-domain by skilled engineers. However, PQ disturbances may not always be obvious in the original time-domain signal. Fourier analysis transforms signals into frequency domain,.but has the disadvantage that time characteristics will become unobvious. Wavelet analysis, which provides both time and frequency information, can overcome this limitation. In this paper, PQ signals were examined. There were two stages in analyzing PQ signals:feature extraction and disturbances classification. To extract features from PQ signals, wavelet packet transform (WPT) was first applied and feature vectors of relative wavelet log-energy entropy were constructed. Least square support vector machines (LS-SVM) was applied to these feature vectors to classify PQ disturbances. Simulation results show that the proposed method possesses high recognition rate, so it is suitable to the monitoring and classifying system for PQ disturbances.Base on multi-domain feature extraction and adaptive neuron-fuzzy inference system (ANFIS), a system for the identification of PQ disturbances is proposed. For the first stage, the waveform envelope threshold is used to detect PQ disturbances and then the feature vectors are extracted in multi-domain including time-domain, frequency-domain and wavelet-domain, which comprise of fundamental component root-mean-square (RMS) amplitude, total harmonic distortion (THD), subharmonic amplitude and wavelet energy. These feature vectors are suggested and adopted as input parameters of the ANFIS classifier. Thus, a proper organization map of the ANFIS classifier has significantly improved the identification efficiency. Simulation results confirm the aptness and the capability of the proposed system in PQ disturbances recognition.(5) This paper is focused on estimation of initial amplitude, initial phase, frequency and damping factor of oscillatory transients contained in power signal. First, the selected structures have been used to perform adaptive notch filtering for separating oscillatory transient signals from the fundamental component, which can reduce the impact the fundamental component about the results of singular value decomposition. Then, it describes algorithm called linear predictive singular value decomposition (LPSVD) to estimate parameters of oscillatory transient signals. The feasibility and effectiveness of the proposed method is illustrated by some numerical simulations.(6) Usual energy meters can't distinguish fundamental from harmonics. Therefore, these meters can't measure the electric power accurately under non-sinusoidal conditions. The paper describes a new approach to the design of digital algorithms for power measurement under non-sinusoidal conditions. The captured voltage or current signals are passed through a improved adaptive Fourier linear combiner to provide the amplitudes and phases at every sampling instant with the fast convergence. The simulated results are presented showing its effectiveness to meet the demand of real-time and high accuracy power measurement.The harmonic and interharmonic analysis recommendations are contained in the latest IEC standards on PQ. Measurement and analysis experiences have shown that great difficulties arise in the interharmonics detection and measurement with acceptable levels of accuracy. In this paper, the tunable resolution multiple signal classification (TRMUSIC) algorithm is presented, which the spectrum can be tuned to exhibit high resolution in targeted regions. Some simulation examples show that the resolution for two adjacent frequency components is usually sufficient to measure interharmonics in power systems with acceptable computation time. The proposed method is also suited to analyse interharmonics when there exists an undesirable asynchronous deviation and additive white noise.An improved particle swarm optimization (IPSO) approach for the parameters design of single-tuned passive harmonic filters in power distribution systems is presented in this paper. Conventional approaches for passive harmonic filters design only follow the experiences and simple criterions. The passive harmonic filters design is a non-linear constrained multi-objective optimization problem. This paper proposes an optimal strategy based on IPSO to improve filters design performance. It takes the voltage and current total harmonic distortion as the objectives under some constraints. By means of minimizing the fitness function plus satisfactory constraints, the optimization problem can be solved to the best trade-off of the parameters of all the filtering branches. An improved operation is embedded to avoid the common defect of the traditional method. A designing instantiation of single-tuned harmonic filters in a theater shows the superiority and availability of the novel strategy. Finally, perturbation analyzing of the designed parameters is discussed in detail.