A new methodology for optimization of overcurrent protection relays in active distribution networks regarding thermal stress curves

Rojnić, Michele; Prenc, Rene; Topić, Danijel; Strnad, Ivan

doi:10.1016/j.ijepes.2023.109216

Cited by 3 publications

(2 citation statements)

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“…Protection systems in networks are a critical component that ensures the safe and reliable operation of the entire power grid [2]. Requirements for safe and reliable operation of the power grid are very strict and mandate the quickest possible time of fault isolation [3]. The electrical network is subject to short-circuit faults that can damage equipment and cause hazardous conditions for utility crews and consumers.…”

Section: Introductionmentioning

confidence: 99%

Voltage Frequency Differential Protection Algorithm

Matišić,

Antić,

Havelka

et al. 2024

Energies

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Advancements in new technologies, a reduction in CO2 emissions, and the rising demand for energy are causing a growth in the share of renewable energy sources. In distribution networks, an increasing number of distributed generators (DGs) makes the utility grid’s protection complex and demanding. Vector surge and rate-of-change-of-frequency are the established anti-islanding protection methods, recognizing that the standard paradigm for protection, involving distributed generation, cannot be set only once but has to be continuously updated following the requirements and changes in the system. One of the requirements is active participation in the preservation of system frequency and voltage, which can be interrupted if the DG trips and disconnects from the utility grid. Anti-islanding protection and spurious tripping can be avoided by implementing new algorithms and techniques. This paper presents a novel protection scheme based on a voltage frequency differential. The proposed algorithm employs remote and local frequency measurements in such a manner that, for the occurrence of a frequency difference, it is assumed that the DG is in an islanding state. In this article, we demonstrate the feasibility of the algorithm through numerical analysis of grid events and laboratory testing emulating real grid-measured values. The test results show that the algorithm is resilient to false tripping for non-islanding events and more reliable than conventional methods in islanding detection. The algorithm can be set to low-frequency differential values, drastically reducing the non-detection zone in any DG type, regardless of its size and voltage level at the point of common coupling. Unlike standard anti-islanding methods, the algorithm supports the ability of the DG to fault-ride through demand.

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Section: Introductionmentioning

confidence: 99%

Voltage Frequency Differential Protection Algorithm

Matišić,

Antić,

Havelka

et al. 2024

Energies

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“…Additionally, reference [32] combines the TLBO algorithm to propose a comprehensive microgrid overcurrent relay (OCR) coordination the method, considering three optimization parameters. Reference [33] develops an improved genetic algorithm for the directional overcurrent relays in active distribution networks, considering a thermal equivalent short-circuit current. Even with the advantages of the genetic algorithm (GA), it has complexity and lower computational efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Setting Optimization Ensemble for a Distributed Power Grid Protective Relay

Luo,

Sun,

et al. 2024

Applied Sciences

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To ensure a stable and reliable power supply, the valid and timely response of protective relays are indispensable. Through the prevention of fault expansions, potential equipment damage or system collapse can be averted, where their setting is one vital prerequisite for such effective implementations. However, the increasing complexity of distribution power systems results in more challenges for protection tuning strategies. Ergo, this paper presents an ensemble that combines the independent factor evaluation (IFE) and quantum genetic optimization (QGO) models to further optimize the performance of relays according to their distributed tuning environment. In this ensemble, both near and far-end fault characteristics can be incorporated. In the first stage, the IFE dimensional reduction model is deployed for massive heterogeneous input data, where the statistical independence of input signals is calculated, the linear transformation matrix to decouple mixed signals is found, the linear combination of such signals is formed, and the non-Gaussian property to sort them is established. This can ameliorate the following calculation efficiency under those high-dimensional data scenarios. Subsequently, the QGO model is designed to further improve relay settings, where qubit representation is built to reduce required chromosomes, the linear superposition of the optimal solution probability in different states is implemented for a better diversity and convergence performance, and a self-adaption quantum gate is established to dynamically update the qubit chromosome groups and two-state solution combinations. Lastly, an empirical case study is presented, which validates the enhanced convergence, accuracy, and rapidity of the proposed ensemble.

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