Online Power Quality Monitoring Research Articles

Research about a fast identification method for intermittent single Sub-synchronous Resonance phenomenon in large scale doubly-fed wind farm

In this paper, a synchronous resonance (SSR) phenomenon caused by a large scale doubly-fed wind farm group after putting in series compensation device is analysed. By analysing the changing trends of the indicators during period of SSR phenomenon, 11 power quality indicators are chosen for calculated, then divided all the 11 indicators into 3 source data and 8 preliminary stage operational data by the observability of value. After divided the two kinds of data, a Pearson correlation coefficient between this two kind data was calculated to judge the relationship of them, and the characteristic indexes with stronger correlation during the resonance period were analysed. The maximum value of the above 8 characteristic indexes in the normal power generation process is used as the basic data for comparison, so as to realize the rapid and accurate judgement of the SSR moment. In the process of SSR judgement, the method has the characteristics of faster speed and simple determination, and it does not need to reform the existing power quality online monitoring device, and can realize real-time analysis and judgement of SSR phenomenon only by increasing extraction of the existing data function from the monitoring system. Finally, by testing data of two actual SSR events, the characteristic index determination method proposed in this paper is analysed and verified, and the feasibility of this method is proved.

Online Identification of Underlying Causes for Multiple and Multi-Stage Power Quality Disturbances Using S-Transform

ABSTRACT The proposed methodology aims at the identification of multiple and multi-stage power quality (PQ) disturbances along with their underlying causes. To this end, a computationally efficient S-Transform with decision tree (DT) based online PQ monitoring algorithm has been presented in this paper. This online algorithm provides a sample-based analysis of 40-dB noisy multiple and multi-stage PQ disturbance signals simulated in MATLAB environment with the different combinations of underlying causes as per the IEEE-1159 standard. The features like residual voltage, instantaneous phase-angle jump (IPAJ), and number of zero crossings (NZC) have been extracted from the transformed contours, viz., maximum voltage amplitude versus time (MVAVT) and phase-angle versus time (PAVT). Henceforth, the accurate recognition of most common underlying causes like three-phase fault, induction motor starting, and capacitor bank energizing has been achieved. For the first time, an online PQ monitoring algorithm is effectively assessing the type and underlying cause of a multiple or multi-stage disturbance simultaneously. The proposed methodology has also been experimentally validated with real-time PQ disturbance signals acquired in the laboratory.

Development of Real Time Power Quality (RTPQ) Analyzer using Lab-VIEW

Power Quality (PQ) issues and its alleviation techniques are becoming one of the vital research topics, soon after the integration of power electronic devices in power system. The non-linear nature of equipment’s introduces PQ issues such as voltage sag, swell, harmonics, unbalance and transients etc. and cause damage of end user equipment’s. Poor PQ has become a vital issue which affects production and profit of both utilities and consumers. Therefore continuous monitoring and assessment of PQ is essential for finding optimal solution to analyze and mitigate various PQ problems and also maintain quality of power within the prescribed limit. For PQ analysis, it is very difficult to generate power quality events in real life in order to observe the effects or to study their characteristics. Now days, various physical PQ analyzers are available in market to continuously monitor, analyze and record PQ problems. The major drawback of this analyzer is its hardware design, complexity and its cost which limits its usage to many places. Thus online PQ monitoring is a very big challenge for researches. This paper presents modeling and simulation of virtual PQ analyzer using Lab VIEW. Lab VIEW supports a lot of library functions for an acquisition, analysis of data and also the control of instruments. This software is mainly used to model standard real instruments used in laboratories by providing more flexibility. The proposed PQ analyzer is capable of generating, identifying various PQ problems and also measuring PQ parameters RMS Voltage (Vrms), RMS Current (Irms), Total Harmonic Distortion (THD), Real, Reactive and Apparent Power from the test system. Using Lab VIEW software, a complete quality analysis of electric energy can be done online at the user's location. So that the selection of custom power devices and mitigation methods for PQ problems can be done in a perfect manner. This RTPQ analyzer is tested using real time data of hardware are acquired by the construction of test systems such as rectifier with various resistive and inductive loads. ALL PQ parameters measured using proposed PQ Analyzer are also compared with the parameters measured using fluke PQ Analyzer. The response attained has proven that the accuracy and precision of the proposed analyzer can also be used as a very good cost effective tool for online PQ study.

Harmonic emission level assessment method based on parameter identification analysis

In this study, a new method for harmonic emission level assessment is proposed. The method is based on parameter identification analysis. The quantitative relationship between standard deviation values of equivalent parameters and harmonic emission levels is studied and discussed through theoretical derivations. The complete harmonic emission level assessment method is then proposed on the basis of quantitative analysis and validated by means of simulation studies and field tests. The method has the ability of distinguishing the active injection contents in load harmonic currents and determining the actual harmonic responsibilities of the customers in power systems. On-line power quality monitoring applications and incentive management schemes can be designed by the proposed method.

Automatic Power Quality Events Recognition Based on Hilbert Huang Transform and Weighted Bidirectional Extreme Learning Machine

In this paper, Hilbert Huang transform (HHT) and weighted bidirectional extreme learning machine (WBELM) are integrated to detect and classify power quality events (PQEs) in real time. Empirical mode decomposition is used to decompose the nonstationary PQEs into the monocomponent mode of oscillation, known as intrinsic mode functions (IMFs). The efficacious features are extracted by applying the Hilbert transform (HT) on the IMFs. An efficient WBELM computational intelligence technique is proposed to recognize the single, as well as multiple PQEs and its performances are compared with the recently developed classifiers such as support vector machine, least-square support vector machine, extreme learning machine, and bidirectional extreme learning machine. The recognition architecture of HHT integrated with WBELM (HHT-WBELM) method is tested and compared with the empirical wavelet transform associated with HT and WBELM method, and tunable-Q wavelet transform along with HT and WBELM method. The faster learning speed, lesser computational complexity, superior classification accuracy, and short event detection time prove that the proposed HHT-WBELM method can be implemented in the online power quality monitoring system. Finally, a hardware prototype is developed based on the digital signal processor to verify the cogency of the proposed method in real time. The feasibility of the proposed method is tested and validated by both the simulation and laboratory experiments.

FPGA-based online power quality monitoring system for electrical distribution network

In this paper, a new generation Internet-based Power Quality Monitoring System (IPQMS) that transmits real-time power quality (PQ) data over the internet has been developed. The monitoring system has the ability to measure PQ parameters in accordance with the related standards. This monitoring system includes many hardware and software designs and presents an efficient structure. PQ parameters are determined by signal processing algorithms that are applied to the current and voltage signals continuously obtained from the electrical power network. These signal processing algorithms are performed as embedded functions in the FPGA device. The PQ data obtained from the measurement points are transmitted to a server by UDP/IP communication protocol that is implemented in the FPGA device. The monitoring, reporting and permanently storing tasks are accomplished with the real-time automation software and web applications that running on the server computer. With its innovative software and hardware designs, the proposed monitoring approach presents a very useful monitoring structure that can be used in the PQ field.

Research on classification of voltage sag sources based on recorded events

In recent years, with the wide application of power electronic devices and stringent requirement of industrial process, voltage sag has caused much attention in many countries. To design effective and efficient mitigation and management strategies, it is essential to have accurate classification of voltage sag sources. In this study, based on the analysis of massive voltage sag events in the grid recorded by online power quality monitoring systems in several different regions in China, a more extensive and practical classification of voltage sag sources is given. The voltage sags are divided into eight categories due to short-circuit faults with symmetric and asymmetric faults included, transformer energising, induction motor starting, lightning faults, self-extinguishing faults, the combined action of short-circuit faults and heavy load starting, upgrade faults and multi-stage voltage sags. For each category of the voltage sag sources, both the instantaneous value and the root mean square value of the waveform of the typical recorded events are given. In addition, the reasons are analysed and the waveform characteristics are summarised for each category of the voltage sag sources. Finally, the frequencies of eight categories under different voltage levels and the statistical result analysis are given.

A power quality online monitoring system oriented ZigBee routing optimization strategy

For ZigBee Cluster-Tree routing protocol in the power system applications existing not optimal routing and not real-time problems, the actual demand from on-line monitoring power quality of substation point of view, considering hops, link busy status and the residual energy, a ZigBee Cluster-Tree improved routing algorithm is proposed, calculating the hops of all neighbor nodes to the destination node and introducing an alternative node. Several NS2.34 simulation experiments show that the improved routing optimization algorithm reduces the number of hops and end to end delay, improves power quality monitoring in real time, saves overall network energy consumption, and prolongs the network life cycle.

Development of New Multi-Function Power Quality On-Line Monitoring Device

A power quality on-line monitoring device based on two CPUS is designed and implemented in this paper, which separated the data analysis from the peripheral control completely, used CPLD (Complex Programmable Logic Device) to generate control timing of peripheral devices, made full use of the DSP, so as to meet the requirements of power quality: monitoring precision and real time. The paper firstly introduces the monitor's sampling circuit, communication module circuit, storage module circuit and the flow chart of software. Then, the functions, features and designations of each module are described in detail.

Design and Realization of an Online Power Quality Monitoring System Based on DSP and GPRS

In order to evaluate power quality more accurately and synthesize the characteristics of the distribution, which has nodes in large quantity and area, an online power quality monitoring system (PQMS) is developed by using the digital signal processor (DSP) and the general packet radio service (GPRS). This PQMS consists of two parts: the power quality monitor (PQM) which is designed on the structure of DSP and the monitoring software (MS) in upper computer which is designed on the platform of LabVIEW. GPRS network provides the communication channel for these two parts. Therefore, supervisors can monitor and analyze the power quality from a long distance. In this paper, the design and realization of each part are described in detail. Experimental results show that the proposed system is fast in response with high accuracy and has the ability of real-time processing.

A Power Quality Online Monitoring Device Based on PowerPC and DSP

According to the practical requirements of setting up large scale power quality monitoring systems and monitoring power quality in digital substations, an embedded power quality online monitoring device based on PowerPC and DSP is realized. The device structure, the overall hardware design, the PowerPC and the DSP systems are introduced. The design scheme based on PowerPC and DSP can take full advantages of the fast data calculation speed of DSP and the strong network processing ability of PowerPC. The test result of the measurement accuracy shows that the device can meet the power quality indicators measuring requirements of national standards.

Adaptability of Distribution Automation System to Electric Power Quality Monitoring In Nigeria Power Distribution Network

The trend in Nigeria is shifting from providing electricity to consumers only but with improved quality as a result of deregulation. This paper demonstrates the adaptability of distribution automation system to electric power quality on-line monitoring using Nigeria distribution system as a case study. This paper reviews power quality problems, electric power distribution topology and monitoring quantities. The paper explains the development of program for the analysis of power quality. Sensors were incorporated at the substations for the measurement of substation voltages and line currents. The embedded system coordinates the activities of these sensors and initiates communication at regular intervals with the central server for analysis. The data back-up was implemented on external card which are available for down load on monthly basis. The results reveal neglect to the issues of quality, failure to comply with regulations in some of the substations investigated. The study is expected to benefit the operator in the area of planning and improved power delivery.

The Design of Power Quality Online Monitor Device under Smart Grid

With the development and construction of smart grid, more and more attentions have been paid to the detection of power quality. Study the disadvantages of wired communication network, applied wireless sensor network technology to power quality online monitoring system. Introduced the hardware and software architectures, designed the detection node and gathering node based on CC2430 and LPC2214 respectively, introduced the establishing process and algorithms of WSN based on ZigBee technology. Experimental results show that, the system can remotely monitor power quality of monitoring points on the power grid, can optimize the power grid operation, and provide enterprises with a reliable basis for energy conservation and emissions reduction.