Roadmap to modernization of line protection in active distribution systems

Kayyali, Dima; Saleh, Khaled

doi:10.1016/j.ijepes.2023.109239

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…It affects the sensitivity and selectivity of the protection system; even it may deenergize the network loads due to incorrect fault isolation. In such a situation, optimization methods can improve the performance of the protection system by optimal protection equipment and DG units locations [33]. In the normal operating condition, an active distribution system is useful for the utilities, resulting in increased use of these units [4, 21, 28, 34].…”

Section: Introductionmentioning

confidence: 99%

Fuse saving coordination scheme for active distribution systems: State‐of‐the‐art and a novel quasi‐voltage current based scheme

Bisheh,

Fani,

Shahgholian

et al. 2024

IET Generation Trans & Dist

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Increasing the penetration level of distributed generation (DG) units requires overcoming the technical challenges associated with their integration into the distribution systems, especially protection problems. Change in the current profile of the distribution system due to the presence of DG units disrupts the operation of the conventional fuse saving coordination (FSC) scheme. The first objective of this paper is to provide an overview of the state‐of‐the‐art of FSC schemes in distribution systems with distributed generators that has not been systematically presented yet. In addition to comparing the features of reliability, cost, speed, implementation, calculation burden, and requirements, the impact of presence of distributed generations on the performance of the conventional FSC scheme is investigated in details. The second objective of this paper is to propose an FSC restoration scheme for minimizing the challenges of previous works. Using a quasi‐voltage current term, the proposed scheme modifies the adjustable time coefficient of the recloser in two ways of pro and plus. The former scheme provides an approximate FSC with a simple setting while the latter scheme provides complete coordination at the expense of a more complex setting. No need for voltage measurement makes its implementation practical in available distribution systems. The effective performance of the proposed FSC scheme is verified through extensive simulation studies in the ETAP environment.

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Section: Introductionmentioning

confidence: 99%

Fuse saving coordination scheme for active distribution systems: State‐of‐the‐art and a novel quasi‐voltage current based scheme

Bisheh,

Fani,

Shahgholian

et al. 2024

IET Generation Trans & Dist

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“…Fault detection methods play a crucial role in selecting appropriate line protection strategies. The traditional power transmission network is characterized by its unidirectional current flow and susceptibility to short-circuit faults [3]. Commonly, techniques such as thresholding or a logical analysis based on distribution automation data are employed to identify the specific type and location of faults.…”

Section: Introductionmentioning

confidence: 99%

Microgrid Fault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling

Lu,

Wang,

Wang

2024

Energies

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The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current loops, imbalances, and potential short-circuit faults. To address these challenges, this study proposes a new approach to accurately locate and identify faults based on MG lines. Initially, characteristic indices such as fault voltage, voltage fundamentals at each MG measurement point, and extracted features like peak voltage values in specific frequency bands, phase-to-phase voltage differences, and the sixth harmonic components are utilized as model inputs. Subsequently, these features are classified using the Lightweight Gradient Boosting Machine (LightGBM), complemented by the bagging (Bootstrap Aggregating) ensemble learning algorithm to consolidate multiple strong LightGBM classifiers in parallel. The output classification results of the integrated model are then fed into a neural network (NN) for further training and learning for fault-type identification and localization. In addition, a Shapley value analysis is introduced to quantify the contribution of each feature and visualize the fault diagnosis decision-making process. A comparative analysis with existing methodologies demonstrates that the LightGBM-NN model not only improves fault detection accuracy but also exhibits greater resilience against noise interference. The introduction of the bagging method, by training multiple base models on the initial classification subset of LightGBM and aggregating their prediction results, can reduce the model variance and prevent overfitting, thus improving the stability and accuracy of fault detection in the combined model and making the interpretation of the Shapley value more stable and reliable. The introduction of the Shapley value analysis helps to quantify the contribution of each feature to improve the transparency and understanding of the combined model’s troubleshooting decision-making process, reduces the model’s subsequent collection of data from different line operations, further optimizes the collection of line feature samples, and ensures the model’s effectiveness and adaptability.

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Roadmap to modernization of line protection in active distribution systems

Cited by 2 publications

References 18 publications

Fuse saving coordination scheme for active distribution systems: State‐of‐the‐art and a novel quasi‐voltage current based scheme

Fuse saving coordination scheme for active distribution systems: State‐of‐the‐art and a novel quasi‐voltage current based scheme

Microgrid Fault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling

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