scholarly journals Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 21
Author(s):  
Om Prakash Mahela ◽  
Yagya Sharma ◽  
Shoyab Ali ◽  
Baseem Khan ◽  
Akhil Ranjan Garg
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Rate Of Change ◽  
Discrete Wavelet ◽  
Frequency Change ◽  
Islanding Detection ◽  
Change Rate ◽  
Peak Magnitude ◽  
Time Period ◽  
Stockwell Transform

This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).

scholarly journals Alienation Coefficient and Wigner Distribution Function Based Protection Scheme for Hybrid Power System Network with Renewable Energy Penetration

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1120 ◽  
Author(s):  
Sheesh Ram Ola ◽  
Amit Saraswat ◽  
Sunil Kumar Goyal ◽  
Virendra Sharma ◽  
Baseem Khan ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Power System ◽  
Wigner Distribution ◽  
Discrete Wavelet ◽  
Protection Scheme ◽  
Double Phase ◽  
Variable Nature ◽  
Zero Sequence ◽  
Hybrid Grid

The rapid growth of grid integrated renewable energy (RE) sources resulted in development of the hybrid grids. Variable nature of RE generation resulted in problems related to the power quality (PQ), power system reliability, and adversely affects the protection relay operation. High penetration of RE to the utility grid is achieved using multi-tapped lines for integrating the wind and solar energy and also to supply loads. This created considerable challenges for power system protection. To overcome these challenges, an algorithm is introduced in this paper for providing protection to the hybrid grid with high RE penetration level. All types of fault were identified using a fault index (FI), which is based on both the voltage and current features. This FI is computed using element to element multiplication of current-based Wigner distribution index (WD-index) and voltage-based alienation index (ALN-index). Application of the algorithm is generalized by testing the algorithm for the recognition of faults during different scenarios such as fault at different locations on hybrid grid, different fault incident angles, fault impedances, sampling frequency, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, and presence of noise. The algorithm is successfully tested for discriminating the switching events from the faulty events. Faults were classified using the number of faulty phases recognized using FI. A ground fault index (GFI) computed using the zero sequence current-based WD-index is also introduced for differentiating double phase and double phase to ground faults. The algorithm is validated using IEEE-13 nodes test network modelled as hybrid grid by integrating wind and solar energy plants. Performance of algorithm is effectively established by comparing with the discrete wavelet transform (DWT) and Stockwell transform based protection schemes.

scholarly journals An Algorithm for Recognition of Fault Conditions in the Utility Grid with Renewable Energy Penetration

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2383 ◽  
Author(s):  
Govind Sahay Yogee ◽  
Om Prakash Mahela ◽  
Kapil Dev Kansal ◽  
Baseem Khan ◽  
Rajendra Mahla ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Hilbert Transform ◽  
Test System ◽  
Discrete Wavelet ◽  
Protection Scheme ◽  
Utility Grid ◽  
Hybrid Grid ◽  
Two Phases ◽  
Stockwell Transform ◽  
Three Phases

Penetration level of renewable energy (RE) in the utility grid is continuously increasing to minimize the environmental concerns, risk of energy security, and depletion of fossil fuels. The uncertain nature and availability of RE power for a short duration have created problems related to the protection, grid security, power reliability, and power quality. Further, integration of RE sources near the load centers has also pronounced the protection issues, such as false tripping, delayed tripping, etc. Hence, this paper introduces a hybrid grid protection scheme (HGPS) for the protection of the grid with RE integration. This combines the merits of the Stockwell Transform, Hilbert Transform, and Alienation Coefficient to improve performance of the protection scheme. The Stockwell Transform-based Median and Summation Index (SMSI) utilizing current signals, Hilbert Transform-based derivative index (HDI) utilizing voltage signals, and Alienation Coefficient index (ACI) utilizing voltage signals were used to compute a proposed Stockwell Transform-, Hilbert Transform-, and Alienation-based fault index (SAHFI). This SAHFI was used to recognize the fault conditions. The fault conditions were categorized using the number of faulty phases and the proposed Stockwell Transform and Hilbert Transform-based ground fault index (SHGFI) utilizing zero sequence currents. The fault conditions, such as phase and ground (PGF), any two phases (TPF), any two phases and ground (TPGF), all three phases (ATPF), and all three phases and ground (ATPGF), were recognized effectively, using the proposed SAHFI. The proposed method has the following merits: performance is least affected by the noise, it is effective in recognizing fault conditions in minimum time, and it is also effective in recognizing the fault conditions in different scenarios of the grid. Performance of the proposed approach was found to be superior compared to the discrete wavelet transform (DWT)-based method reported in the literature. The study was performed using the hybrid grid test system realized by integrating wind and solar photovoltaic (PV) plants to the IEEE-13 nodes network in MATLAB software.

Model Statistika Prediksi Energi Surya Dengan Menggunakan Autoregresif Integrated Moving Average (ARIMA)

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 181
Author(s):  
Imriani Moroki ◽  
Alfrets Septy Wauran
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Moving Average ◽  
Arima Model ◽  
Solar Irradiation ◽  
Energy Sources ◽  
Energy Potential ◽  
Good Design ◽  
Potential Sources ◽  
The Common

Energi terbarukan adalah salah satu masalah energi paling terkenal saat ini. Ada beberapa sumber potensial energi terbarukan. Salah satu energi terbarukan yang umum dan sederhana adalah energi matahari. Masalah besar ketersediaan energi saat ini adalah terbatasnya sumber energi konvensional seperti bahan bakar. Ini semua sumber energi memiliki banyak masalah karena memiliki jumlah energi yang terbatas. Penting untuk membuat model dan analisis berdasarkan ketersediaan sumber energi. Energi matahari adalah energi terbarukan yang paling disukai di negara-negara khatulistiwa saat ini. Tergantung pada produksi energi surya di daerah tertentu untuk memiliki desain dan analisis energi matahari yang baik. Untuk memiliki analisis yang baik tentang itu, dalam makalah ini kami membuat model prediksi energi surya berdasarkan data iradiasi matahari. Kami membuat model energi surya dan angin dengan menggunakan Metode Autoregresif Integrated Moving Average (ARIMA). Model ini diimplementasikan oleh R Studio yang kuat dari statistik. Sebagai hasil akhir, kami mendapatkan model statistik solar yang dibandingkan dengan data aktualRenewable energy is one of the most fomous issues of energy today. There are some renewable energy potential sources. One of the common n simple renewable energy is solar energy. The big problem of the availability of energy today is the limeted sources of conventional enery like fuel. This all energy sources have a lot of problem because it has a limited number of energy. It is important to make a model and analysis based on the availability of the energy sources. Solar energy is the most prefered renewable energy in equator countries today. It depends on the production of solar energy in certain area to have a good design and analysis of  the solar energy. To have a good analysis of it, in this paper we make a prediction model of solar energy based on the data of solar irradiation. We make the solar and wind enery model by using Autoregresif Integrated Moving Average (ARIMA) Method. This model is implemented by R Studio that is a powerfull of statistical. As the final result, we got the statistical model of solar comparing with the actual data

scholarly journals Statistical Estimation of Accelerated Biological Brain Aging After Mild Traumatic Brain Injury in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 890-890
Author(s):  
Andrei Irimia ◽  
Jun Kim ◽  
Shania Wang ◽  
Hyung Jun Lee ◽  
Van Ngo ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Brain Aging ◽  
Rate Of Change ◽  
Time Period ◽  
Weighted Magnetic Resonance Imaging ◽  
Neurological Conditions ◽  
Magnetic Resonance Imaging Mri ◽  
Brain Age

Abstract Estimating biological brain age (BA) has the potential of identifying individuals at relatively high risk for accelerated neurodegeneration. This study compares the brain’s chronological age (CA) to its BA and reveals the BA rate of change after mild traumatic brain injury (mTBI) in an aging cohort. Using T1-weighted magnetic resonance imaging (MRI) volumes and cortical thickness, volume, surface area, and Gaussian curvature obtained using FreeSurfer software; we formulated a multivariate linear regression to determine the rate of BA increase associated with mTBI. 95 TBI patients (age in years (y): μ = 41 y, σ = 17 y; range = 18 to 83) were compared to 462 healthy controls (HCs) (age: μ = 69 y, σ = 18 y; range = 25 to 95) over a 6-month time period following mTBI. Across the initial ~6 months following injury, patients’ BAs increased by ~3.0 ± 1.2 years due to their mTBIs alone, i.e., above and beyond typical brain aging. The superior temporal and parahippocampal gyri, two structures involved in memory formation and retrieval, exhibited the fastest rates of TBI-related BA. In both hemispheres, the volume of the hippocampus decreased (left: μ=0.28%, σ=4.40%; right: μ=0.12%, σ=4.84%). These findings illustrate BA estimation techniques’ potential to identify TBI patients with accelerated neurodegeneration, whose rate is strongly associated with the risk for dementia and other aging-related neurological conditions.

scholarly journals An Islanding Detection Technique for Inverter-Based Distributed Generation in Microgrids

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 130
Author(s):  
Mazaher Karimi ◽  
Mohammad Farshad ◽  
Qiteng Hong ◽  
Hannu Laaksonen ◽  
Kimmo Kauhaniemi
Keyword(s):  
Distributed Generation ◽  
Phasor Measurement Units ◽  
Rate Of Change ◽  
Detection Technique ◽  
Islanding Detection ◽  
Simulation Studies ◽  
Local Measurements ◽  
Measurement Units ◽  
Utility Grid ◽  
Frequency Fluctuations

This article proposes a new passive islanding detection technique for inverter-based distributed generation (DG) in microgrids based on local synchrophasor measurements. The proposed method utilizes the voltage and current phasors measured at the DG connection point (point of connection, PoC). In this paper, the rate of change of voltages and the ratio of the voltage and current magnitudes (VoI index) at the PoC are monitored using micro-phasor measurement units. The developed local measurements based decentralized islanding detection technique is based on the VoI index in order to detect any kind of utility grid frequency fluctuations or oscillations and distinguishing them from islanding condition. The simulation studies confirm that the proposed scheme is accurate, robust, fast, and simple to implement for inverter-based DGs.

scholarly journals Dual Efficiency and Productivity Analysis of Renewable Energy Alternatives of OECD Countries

2021 ◽  
Vol 13 (13) ◽  
pp. 7401
Author(s):  
Sedef E. Kara ◽  
Mustapha D. Ibrahim ◽  
Sahand Daneshvar
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Wind Energy ◽  
Oecd Countries ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Analysis ◽  
Average Efficiency ◽  
Efficiency And Productivity

This paper examines the dual efficiency of bioenergy, renewable hydro energy, solar energy, wind energy, and geothermal energy for selected OECD countries through an integrated model with energy, economic, environmental, and social dimensions. Two questions are explored: Which renewable energy alternative is more dual efficient and productive? Which renewable energy alternative is best for a particular country? Data envelopment analysis (DEA) is used for the efficiency evaluation, and the global Malmquist productivity index is applied for productivity analysis. Results indicate bioenergy as the most efficient renewable energy alternative with a 20% increase in average efficiency in 2016 compared to 2012. Renewable hydro energy, wind energy, and solar energy show a 17.5%, 16%, and 11% increase, respectively. The average efficiency growth across all renewable energy alternatives signifies major advancement. Country performance in renewable energy is non-monolithic; therefore, they should customize their renewable energy portfolio accordingly to their strengths to enhance renewable energy efficiency. Renewable hydro appears to have the most positive productivity change in 2016 compared to 2012, while solar energy regressed in productivity due to its scale inefficiency. All renewable energy alternatives have relatively equal average pure efficiency change. The positive trend in efficiency and productivity provides an incentive for policy makers to pursue further development of renewable energy technologies with a focus on improving scale efficiency.

An Improved Airborne Single Observer Passive Location

2012 ◽  
Vol 157-158 ◽  
pp. 1533-1536
Author(s):  
Yong Wang ◽  
Chang Qiang Huang ◽  
Zheng Wang ◽  
Wang Xi Li
Keyword(s):  
Angular Velocity ◽  
Phase Difference ◽  
Measurement Problem ◽  
Doppler Frequency ◽  
Original Method ◽  
Parameter Measurement ◽  
Frequency Change ◽  
Passive Location ◽  
Change Rate ◽  
Domain Information

Using phase difference change rate’s augmentation to angular velocity, an improved passive location is developed,which solves the high precision parameter measurement problem of angular velocity in passive location and tracking via spatial-frequency domain information. The simulation shows that this method can reduce the difficulties of parameter measurement. The ranging error is mainly affected by the measurement error of phase difference change rate and doppler frequency change rate. Compared with the original method, it has higher passive location precision.

Design, Installation, and Performance Characterization of a Laboratory-Scale Solar Thermal System for Experiments in Solar Energy Utilization

2012 ◽  
Author(s):  
Stephanie Drozek ◽  
Christopher Damm ◽  
Ryan Enot ◽  
Andrew Hjortland ◽  
Brandon Jackson ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Solar Energy ◽  
Laboratory Scale ◽  
Energy Utilization ◽  
Solar Thermal ◽  
Thermal System ◽  
Performance Characterization ◽  
And Performance ◽  
Solar Thermal System

The purpose of this paper is to describe the implementation of a laboratory-scale solar thermal system for the Renewable Energy Systems Laboratory at the Milwaukee School of Engineering (MSOE). The system development began as a student senior design project where students designed and fabricated a laboratory-scale solar thermal system to complement an existing commercial solar energy system on campus. The solar thermal system is designed specifically for educating engineers. This laboratory equipment, including a solar light simulator, allows for variation of operating parameters to investigate their impact on system performance. The equipment will be utilized in two courses: Applied Thermodynamics, and Renewable Energy Utilization. During the solar thermal laboratories performed in these courses, students conduct experiments based on the American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE) 93-2010 standard for testing and performance characterization of solar thermal systems. Their measurements are then used to quantify energy output, efficiency and losses of the system and subsystem components.

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