The unified power quality conditioner (UPQC) is known as an effective compensation device to improve PQ for sensitive end-users. This paper investigates the operation and control of a single-phase ...three-leg UPQC (TL-UPQC), where a novel space vector modulation method is proposed for naturally solving the coupling problem introduced by the common switching leg. The modulation method is similar to the well-known space vector modulation widely used with three-phase voltage source converters, which thus brings extra flexibility to the TL-UPQC system. Two optimized modulation modes with either reduced switching loss or harmonic distortion are derived, evaluated, and discussed, in order to demonstrate the flexibility brought by the space vector modulated TL-UPQC. Simulations and experimental results are presented to verify the feasibility and effectiveness of the proposed space vector modulation approach as well as two mentioned modulation modes.
In Australia and many other countries, distribution network service providers (DNSPs) have an obligation to their customers to provide electrical power that is reliable and of high quality. Failure ...to do so may have significant implications ranging from financial penalties theoretically through to the loss of a license to distribute electricity. In order to ensure the reliability and quality of supply are met, DNSPs engage in monitoring and reporting practice. This paper provides an overview of a large long-running power-quality monitoring project that has involved most of Australia's DNSPs at one time or another. This paper describes the challenges associated with conducting the project as well as some of the important outcomes and lessons learned. A number of novel reporting techniques that have been developed as part of the monitoring project are also presented. A discussion about large-volume data management, and issues related to reporting requirements in future distribution networks is included.
Increasing awareness for green energy and sustainable energy management has accelerated the popularity for the incorporation of distributed energy resources and distributed energy storage into the ...distribution network and microgrid. This has proliferated the use of power electronic-based devices giving rise to a serious issue of deteriorating power quality (PQ) in the distribution system. In this context, this article presents a photovoltaic (PV) integrated unified power quality conditioner (UPQC) operating with an adaptive compensating technique based on variable leaky least mean square (VLLMS) algorithm. It is a soft computing-oriented method that offers quicker convergence to the desired condition in an iterative approach keeping the weight of the updating parameters within the specified limit. The VLLMS-based algorithm eliminates the use of low pass or moving average filter for the extraction of fundamental components from polluted source voltage and load current to generate reference signal for the switching of shunt as well as series voltage source converters (VSC) of the UPQC. Due to the involvement of feed-forward component of PV in the compensating technique of shunt VSC, it efficiently and smoothly manages power balance between grid, load, and PV besides resolving the PQ issues of current harmonics and poor power factor at PCC. It also ensures the regulation of dc-link voltage. The series converter maintains pure sinusoidal voltage at the load terminal irrespective of sag/swell and harmonics present in the grid voltage. The effectiveness of the proposed system is verified through simulation as well as hardware implementation under different static and dynamic operating conditions.
This paper presents a new synchronous-reference-frame (SRF)-based control method to compensate power-quality (PQ) problems through a three-phase four-wire unified PQ conditioner (UPQC) under ...unbalanced and distorted load conditions. The proposed UPQC system can improve the power quality at the point of common coupling on power distribution systems under unbalanced and distorted load conditions. The simulation results based on Matlab/Simulink are discussed in detail to support the SRF-based control method presented in this paper. The proposed approach is also validated through experimental study with the UPQC hardware prototype.
The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) ...disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.
A hybrid connected unified power quality conditioner integrating distributed generation (HCUPQC-DG) is proposed. Two dc ports are created at the dc link of the HCUPQC-DG, in which one low-voltage ...(LV) dc port is directly connected to DG, and the other high-voltage (HV) dc port is indirectly connected to DG through the front-end dc-dc converter. With the hybrid connected configuration, the HV is designed to ensure the dc-ac voltage conversion capability, while the LV, i.e., the voltage of DG, can be relatively low and vary in a wide range. Besides, most active power can be directly transferred from DG to the ac load or grid through the direct power flow path. Hence, the conversion efficiency is enhanced, and the power capacity of the front-end dc-dc converter is significantly reduced. The operating principle and the control and modulation strategies of the proposed HCUPQC-DG are discussed. Moreover, the power flow through the HCUPQC-DG is analyzed in detail to understand the system operation. Experimental results with a 3-kVA prototype are provided to verify the feasibility and effectiveness of the proposed HCUPQC-DG.
This paper deals with control of a solar-photovoltaic (PV) power-generating system interfaced with the grid. A sliding mode control approach is used for achieving maximum power tracking control of a ...solar-PV array. The Lyapunov function-based control approach is designed and modeled for the dc-ac inverter to serve the functions of an active power injection to the grid, balanced grid currents at unity power factor and load currents harmonics compensation. The proposed approaches eliminate the need of adjustment of system parameters under changing loads and generation scenario. The effectiveness of the proposed control strategies is established using its stability analyses. The performance of the solar-PV power-generating system with the proposed control algorithms is demonstrated using simulation and experimental studies under various operating conditions.
This paper presents an effective approach to identify power quality (PQ) events based on IEEE Std 1159-2009 caused by intermittent power sources like those of renewable energy. An efficient ...characterization of these disturbances is granted by the use of two useful wavelet-based indices. For this purpose, a wavelet-based global disturbance ratio (GDR) index, defined through its instantaneous precursor instantaneous transient disturbance ITD(t) index, is used in power distribution networks (PDNs) under steady-state and/or transient conditions. An intelligent disturbance classification is done using a support vector machine (SVM) with a minimum input vector based on the GDR index. The effectiveness of the proposed technique is validated using a real-time experimental system with single event and multi-event signals.
To accomplish feasible large-scale integration of distributed energy resources (DER) into the existing grid system, microgrid implementation has proven to be the most effective. This article reviews ...the vital aspects of DER based microgrid and presents simulations to investigate the impacts of DER sources, electric vehicles (EV), and energy storage system (ESS) on practicable architectures' resilient operation. The focus is primarily on the concept and definition of microgrid, comparison of control strategies (primary, secondary, and tertiary strategies), energy management strategies, power quality (PQ) issues associated with DER based microgrid, and state-of-the-art entities such as ESS and EV's applications toward microgrid reliability. Following discussion on the different attributes of DER sources-based microgrid, simulations are performed to verify the results of the past works on the effects of solar, wind energy sources, ESS, and EVs on the microgrid frequency response. Additional simulations are conducted to assess the influences of DERs, ESS, EVs, and their operational strategies on the microgrid reliability aspects.
Power quality issues are required to be addressed properly in forthcoming era of smart meters, smart grids and increase in renewable energy integration. In this paper, deep auto-encoder (DAE) ...networks is proposed for power quality disturbance (PQD) classification and its location detection without using complex signal processing techniques and complex classifiers. In this technique, Gabor filter is used to extract a set of general Gabor features from the convolution of PQD image. Subsequently, through sparse based DAE network, essential and optimal features are extracted and learnt which are used by a simple classifier (SoftMax) to classify the PQD type. Furthermore, the temporal information of the PQD is obtained using the PQD image to correctly locate the disturbance's initiating and terminating instants. The proposed DAE network has the benefits of deep learning-based networks in terms of automatic feature selection, but it requires smaller data sets. The issue of obtaining optimised, robust, and strong features from the PQD signal is thus resolved. Excellent classification accuracy of PQD is obtained with appropriate network parameter setting of the proposed DAE network. The proposed technique is compared with three other methods support vector machine (SVM), stacked auto-encoder (SAE) and principal component analysis (PCA) for PQD classification by implementing all the four techniques on python platform using the same data set. It has an overall classification accuracy of more than 97% at a signal to noise ratio (SNR) of 20dB, which is on the higher side when compared to other methods of PQD detection under noisy environment. Additionally, this method requires less computation time with the same data set than alternative approaches like SVM. Thus, the proposed method outperforms existing methods for PQD classification and detection of single disturbance and multi-disturbance in terms of greater accuracy and reduced computation complexity and computation time.
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