Preventing transmission distance relays maloperation under unintended bulk DG tripping using SVM-based approach

Tasdighi, Mohammad; Kezunovic, Mladen

doi:10.1016/j.epsr.2016.09.024

Cited by 20 publications

(7 citation statements)

References 14 publications

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“…The transmission networks face different protection challenges due to bulk penetration of the wind power including under/overreach issue of the relays due to change of fault impedance [110]. In response, many protection schemes have been proposed including adaptive logic program based scheme [111], adaptive distance relay setting scheme [112], support vector machine-based scheme [113], data-mining-based intelligent differential relaying [114], and wavelet and Fourier Transform based differential relaying [115]. The level of fault current, in addition to the selection and coordination of protective devices, are the main challenges of the microgrids incorporated with the wind [110].…”

Section: G Protection Challengesmentioning

confidence: 99%

Grid Integration Challenges of Wind Energy: A Review

et al. 2020

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The strengthening of electric energy security and the reduction of greenhouse gas emissions have gained enormous momentum in previous decades. The integration of large-scale intermittent renewable energy resources (RER) like wind energy into the existing electricity grids has increased significantly in the last decade. However, this integration poses many operational and control challenges that hamper the reliable and stable operation of the grids. This article aims to review the reported challenges caused by the integration of wind energy and the proposed solutions methodologies. Among the various challenges, the generation uncertainty, power quality issues, angular and voltage stability, reactive power support, and fault ride-through capability are reviewed and discussed. Besides, socioeconomic, environmental, and electricity market challenges due to the grid integration of wind power are also investigated. Many of the solutions used and proposed to mitigate the impact of these challenges, such as energy storage systems, wind energy policy, and grid codes, are also reviewed and discussed. This paper will assist the enthusiastic readers in seeing the full picture of wind energy integration challenges. It also puts in the hands of policymakers all aspects of the challenges so that they can adopt sustainable policies that support and overcome the difficulties facing the integration of wind energy into electricity grids. INDEX TERMS Angular stability, energy storage system, fault ride-through capability, frequency response, grid codes, reactive power support, voltage stability, wind intermittency. • Induction generator (squirrel cage (type 1) and wound rotor (type 2))

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Section: G Protection Challengesmentioning

confidence: 99%

Grid Integration Challenges of Wind Energy: A Review

et al. 2020

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“…x k+1 =cx k +dv k+1 (9) Here Vk+1 is the current value of velocity, a is the weight factor, b1 and b2 are the learning factor which can be selected as 1 or 2 any random value. Then the r1 and r2 values are random values which is taken between 0 to 1.…”

Section: 𝑚𝑖𝑛 ∑ 𝑊 𝑗 𝑌 𝑗 𝑛 𝑗=1mentioning

confidence: 99%

“…These strategies, however, are extremely dependent on system parameters and cannot be used when the topology of the system changes. Soft computing approaches like neural networks and fuzzy logic [8], [9] have sparked a lot of interest in power system failure analysis because of their capacity to learn and recognize fault events. Neural networks have been used to improve real-time transmission line protection in many areas of power system operation [10 [13].…”

Section: Introductionmentioning

confidence: 99%

Fault detection in an interconnected power system using optimal number of phasor measurement unit

Krishnan

Srivani

2022

IJPEDS

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<p>Fault identification in a power system is crucial. In recent days, there have been multiple microgrids connected to the power system. And if many buses are connected, then there is a need for an increase in the phasor measurement unit. By using an optimization technique, the number of phasor measurement unit PMUs can be reduced by placing them optimally. In this paper, the fault detection algorithm is implemented using a reduced number of PMUs with the help of the particle swarm optimization (PSO) algorithm. The optimal locations of PMUs are identified using the PSO algorithm. Here, the reduction in the count of PMUs and the PMUs are designed in MATLAB as a model. This is done using the Simulink and dashboard block sets. The IEEE 9 and IEEE 30 test systems are used here for the analysis and tests. The IEEE 9 bus system is constructed in simulation and then the PMU is constructed using the data taken from the phasor measurement blocks. This data is used in the dashboard block set to represent the PMU-based fault detection system.</p>

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“…The normalization of the training set and the prediction set is processed, and the normalized mapping is treated as follows (Meena1, Panwar, Negi, & Jarial, 2012;Tasdighi & Kezunovic, 2017):…”

Section: Data Preprocessingmentioning

confidence: 99%

An electric power generation forecasting method using support vector machine

Guo

Chen

et al. 2018

Systems Science & Control Engineering

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The diversity of power generation provides an important guarantee for the electric reliability of human society. The forecasting of power generation is an important topic in the electrical industry. However, most of recent work are focus on some special type power generation, overall electric load forecasting is lacking attention. In order to improve practical applications, this paper proposes a power generation predication method based on one of popular machine learning algorithm that is support vector machine, so as to predict both overall power generation and some special types of power generation. The nonlinear relation of electric net power generation is explored by historical monthly recorded data, this relation can help the predication of net electric generation for the next month. Experimental results show that our proposed electric generation forecasting method based on support vector machine can get suitable predication model and achieve high predicted precision, which is in accordance with the real data in the record. ARTICLE HISTORY

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Preventing transmission distance relays maloperation under unintended bulk DG tripping using SVM-based approach

Cited by 20 publications

References 14 publications

Grid Integration Challenges of Wind Energy: A Review

Grid Integration Challenges of Wind Energy: A Review

Fault detection in an interconnected power system using optimal number of phasor measurement unit

An electric power generation forecasting method using support vector machine

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