Optimal Overcurrent Relay Coordination in Presence of Inverter-Based Wind Farms and Electrical Energy Storage Devices

Javadi, Mohammad Sadegh; Nezhad, Ali Esmaeel; Anvari‐Moghaddam, Amjad

doi:10.1109/eeeic.2018.8494605

Cited by 10 publications

(2 citation statements)

References 18 publications

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“…In addition, high penetration wind generation brings more inverter-based devices connected to the grid which also leads to difficulty in system control. 8 Javadi et al 9 investigated the optimal overcurrent relay coordination in presence of inverter-based WF and energy storage system, and the optimal settings of relays are achieved in different network topologies obtained from unit commitment problem.…”

Section: Introductionmentioning

confidence: 99%

A multiobjective optimization‐based calculation framework of maximum wind power penetration limit considering system transient stability

Wang

Qiu

2020

Int Trans Electr Energ Syst

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This paper elaborates a novel optimum programming-based algorithm that embeds the stochastic multiobjective particle swarm optimization (PSO) method and the deterministic interior point method to calculate the maximum wind power penetration level. With the optimization target of promoting the wind generation capacity, the three-stage optimization strategy is established to contemplate the transient stability constraint (TSC) as well as the uncertainty factors in the high wind penetrated system. To address the uncertainty factors in system, the chance-constrained optimization approach is practiced to figure out the initial optimal operating point in the first stage. On the ground of which, the TSC is reinforced in the second stage to delineate the dynamic feasible region. Among the obtained security domain, the ultimate operation solution is calculated in the last stage and provides operators with specific operating scheme. The framework is capable of supporting alternative optimal methods and can be extended to more complex system modeling. The feasibility of the algorithm framework has been demonstrated by simulations on two benchmark systems. And it has prosperous application prospects for optimization problems that need to consider system dynamic security and uncertainty simultaneously.

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Section: Introductionmentioning

confidence: 99%

A multiobjective optimization‐based calculation framework of maximum wind power penetration limit considering system transient stability

Wang

Qiu

2020

Int Trans Electr Energ Syst

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“…A decentralized adaptive protection scheme using DOCRs, tele protection and a fuzzy system in real time was proposed in [36] for the transmission system. An optimal overcurrent relay coordination in the presence of inverter-based wind farms and electrical energy storage devices was presented in [37]. An adaptive protection system based on the IEC 61850 for MV smart grids was presented in [38].…”

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confidence: 99%

Improved Adaptive Protection Scheme Based Combined Centralized/Decentralized Communications for Power Systems Equipped With Distributed Generation

2022

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Recently, numerical relays with communication capabilities have been employed to provide adaptive solutions for Distributed Generations (DGs) protection issues. This paper presents an adaptive protection scheme based on centralized and decentralized communication to address DG protection problems. The proposed method uses two directional relays in each feeder, one at the beginning (called forward relay) and one at the end (called reverse relay). These relays can communicate with each other and the central unit. The centralized communication occurs between the central unit and the relays in the system when any relay's status changes from connected to disconnected or vice versa. It aims to define the operation mode, islanding detection, and activate the relays settings to achieve proper coordination. Protective relays are coordinated using a Genetic Algorithm (GA) to optimize protection time. The optimization problem considers pick up current (Ipu), Time Multiplier Setting (TMS), Plug Setting Multiplier (PSM), and curve type. Decentralized communication, which occurs when any relay detects a fault, increases relays' accuracy and speed of decision-making. This paper also proposes a novel method for detecting High Impedance Faults (HIF), a significant difficulty for protecting engineers as it draws a very low current that conventional overcurrent relays fail to detect in most cases. HIF is detected using wavelet transform, symlet 8, detail 2 (d2), and relay communication. On the IEC benchmark microgrid, the suggested algorithm is tested. ETAP is used for load flow analysis and short circuit analysis, whereas MATLAB is used for GA optimization, HIF modelling, and wavelet transform routines. INDEX TERMSDistributed generation, directional overcurrent relay, genetic algorithm, coordination time interval, time multiplier setting, plug setting multiplier, pickup current, wavelet transform. I. INTRODUCTION 20 Insertion of Distributed Generation (DGs) has some draw-21 backs on stability, power quality, and protection of the sys-22 tem, depending on size, location, type, and number of DGs 23 connected to the system, these drawbacks can limit both size 24 and number of DGs connected to the system [1]. The addition 25 of DGs increase the short circuit level and cause a current26

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Conditional value-at-risk model for smart home energy management systems

Javadi

Nezhad

Gough

et al. 2021

e-Prime - Advances in Electrical Engineering, Electronics and E

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Optimal Overcurrent Relay Coordination in Presence of Inverter-Based Wind Farms and Electrical Energy Storage Devices

Cited by 10 publications

References 18 publications

A multiobjective optimization‐based calculation framework of maximum wind power penetration limit considering system transient stability

A multiobjective optimization‐based calculation framework of maximum wind power penetration limit considering system transient stability

Improved Adaptive Protection Scheme Based Combined Centralized/Decentralized Communications for Power Systems Equipped With Distributed Generation

Conditional value-at-risk model for smart home energy management systems

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