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(searched for: doi:10.1016/j.rser.2018.02.011)
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, Bharat Singh Rajpurohit,
Energy Conversion and Economics; doi:10.1049/enc2.12035

Abstract:
This paper proposes the implementation of Affine Projection Sign Algorithm (APSA) based control for DSTATCOM to mitigate distribution side power quality issues like harmonic elimination, reactive power compensation, load balancing, power factor compensation, voltage regulation, etc. Affine projection algorithms have already finds application in power quality mitigation, but they suffer from high complexity and degraded performance due to impulsive interference. Whereas, sign algorithms are known to be robust against the impulsive noise and converges faster. Hence sign algorithm with affine projection is proposed for mitigation of power quality problems in this work. APSA is used to estimate the reference active and reactive power component of polluted load current, which is further used to generate the reference signal for DSTATCOM. The performance of the algorithm is investigated for some real operating conditions of power system network in MATLAB/SIMULINK environment. The algorithm is tested in real time simulator for validation. The result shows that the control algorithm is able to resolve distribution side power quality problems with fast convergence.
Published: 24 February 2021
Energies, Volume 14; doi:10.3390/en14051215

Abstract:
Distribution systems are under constant stress due to their highly variable operating conditions, which jeopardize distribution transformers and lines, degrading the end-user service. Due to transformer regulation, variable loads can generate voltage profiles out of the acceptable bands recommended by grid codes, affecting the quality of service. At the same time, nonlinear loads, such as diode bridge rectifiers without power factor correction systems, generate nonlinear currents that affect the distribution transformer operation, reducing its lifetime. Variable loads can be commonly found at domiciliary levels due to the random operation of home appliances, but recently also due to electric vehicle charging stations, where the distribution transformer can cyclically vary between no-load, rated and overrated load. Thus, the distribution transformer can not safely operate under highly-dynamic and stressful conditions, requiring the support of alternative systems. Among the existing solutions, hybrid transformers, which are composed of a conventional transformer and a power converter, are an interesting alternative to cope with several power quality problems. This article is a review of the available literature about hybrid distribution transformers.
Published: 14 February 2021
Sensors, Volume 21; doi:10.3390/s21041348

Abstract:
The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From any of these points of view, an instantaneous characterization of power quality (PQ) aspects becomes an important task. For this purpose, a wavelet-based power quality indices (PQIs) are introduced in this paper. An instantaneous disturbance index (ITD(t)) and a Global Disturbance Ratio index (GDR) are defined to integrally reflect the PQ level in Power Distribution Networks (PDN) under steady-state and/or transient conditions. With only these two indices it is possible to quantify the effects of non-stationary disturbances with high resolution and precision. These PQIs offer an advantage over other similar because of the suitable choice of mother wavelet function that permits to minimize leakage errors between wavelet levels. The wavelet-based algorithms which give rise to these PQIs can be implemented in smart sensors and used for monitoring purposes in PDN. The applicability of the proposed indices is validated by using a real-time experimental platform. In this emulated power system, signals are generated and real-time data are analyzed by a specifically designed software. The effectiveness of this method of detection and identification of disturbances has been proven by comparing the proposed PQIs with classical indices. The results confirm that the proposed method efficiently extracts the characteristics of each component from the multi-event test signals and thus clearly indicates the combined effect of these events through an accurate estimation of the PQIs.
IET Generation, Transmission & Distribution; doi:10.1049/gtd2.12122

Abstract:
Recognition of power quality (PQ) troubles is a critical task in the electrical power system. All previous works solve this problem using two‐step methodology: Feature extraction and classification steps with each step using its own techniques, and this consumes a computation time. The purpose of this study is to utilise a novel artificial intelligence (AI) technique for recognition of PQ events. The proposed AI technique is the long short‐term memory (LSTM) network, which detects and classifies the PQ events in one step. This technique extracts amplitude, disturbance duration and total harmonic distortion from the captured waveform, and the LSTM uses its own rules to classify the PQ events. Many simple PQ events such as interruption, sag, flicker, swell and surge or complex PQ events such as sag plus harmonics and swell plus harmonics are generated using MATLAB programming environment to evaluate the performance of LSTM. Also, real‐time measurements are collected from an industrial substation and are used to ensure the effectiveness of the proposed LSTM technique. A comparison with other techniques is conducted and the results verify the good performance of LSTM in classifying the PQ problems.
, Raheef Aljefri
Published: 15 December 2020
by Wiley
Green Energy pp 191-219; doi:10.1002/9781119760801.ch7

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Ch. Siva Kumar, G. Mallesham
Microsystem Technologies, Volume 26, pp 2673-2682; doi:10.1007/s00542-020-04810-z

Emiyamrew Minaye Molla, Chien-Hsun Liu,
Microsystem Technologies, Volume 26, pp 1799-1811; doi:10.1007/s00542-019-04726-3

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Manish Kumar Saini, Rajiv Kapoor, Rajender Kumar Beniwal, Akanksha Aggarwal
Transactions of the Institute of Measurement and Control, Volume 41, pp 2851-2863; doi:10.1177/0142331218814292

The publisher has not yet granted permission to display this abstract.
Published: 5 July 2018
Sustainability, Volume 10; doi:10.3390/su10072326

Abstract:
In a context with an increased level of competitiveness, companies are more and more interested in aspects concerning sustainable development. The implications of inadequate power quality (PQ) can determine important financial losses and influence companies’ sustainable development through the generated effects. This article aims to facilitate the management of PQ by proposing a method for estimating the economic consequences of a poor PQ, with priority for the disturbances with significant economic effects. To determine the total cost for each type of PQ perturbation that may occur a classification of cost categories was made such as interruptions, process slowdowns, equipment failure, equipment downtime, reduced energy efficiency, lower product quality, lower labor productivity, and other indirect costs. Each PQ disturbance affects the final end-user differently. For calculating the total value for each type of PQ issues, different calculation formulas have been proposed so that each perturbation includes only those components associated with that perturbation. A case study was used to validate the proposed method. Also, the paper includes a technical and economic analysis of the possible compensation solutions for PQ disturbances that may affect the studied company. In conclusion, an understanding of PQ issues’ consequences and an appropriate approach to PQ compensation solutions can be beneficial to any electrical power end-user.
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