Application of BICA-NM hybrid algorithm for optimal locating of fault indicators in distribution networks

Beykverdi, Mehrdad; Ashouri, Ahmad

doi:10.3233/ifs-130870

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…An improved estimate of SCADA measurements can be made with PMU measurements at the time of SCADA data capture. A PMU‐based system is provided in paper [14] for categorizing harmful events in distribution networks. In contrast to sudden load fluctuations in distribution networks, two destructive occurrences, namely capacitor bank switching and on‐load tap changeover switching (OLTC), are considered fault regulators.…”

Section: Related Workmentioning

confidence: 99%

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Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Khosravi,

Trik,

Ansari

2024

The Journal of Engineering

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The dynamic nature of distribution networks raises fresh issues with how such electrical systems function. These networks have some characteristics that indicate the need for better monitoring and control capabilities, including dispersed generation employing renewable resources, changing load profiles, and rising reliability requirements. Phasor measurement units (PMUs) offer simultaneous voltage and current phasor measurements at various places and offer a variety of options for gauging the condition and health of the power distribution network. In this regard, a cost‐optimized PMU with some unique features for distribution systems is presented in this work. These features include a fuzzy inference system to determine the root cause of potential electrical disturbances and methods to estimate electrical parameters through measured field data, which are necessities. This study takes into account the modelling of PMUs, utilizing a process for fault detection and classification with a fuzzy inference network. The 9‐bus distribution network's dependability model is built once the components and their functions are first outlined. The proposed model is then used to calculate the availability of the presented model, which has been examined to provide an analogous reliability model for PMUs. Depending on the specific manufacturer, the PMU's design and specs will change. To extract phase and size measurement features for the proposed model adaptive neural‐fuzzy inference system network's training, two PMU structures and associated reliability models are described here. When merging input data for fuzzy neural network prediction using MATLAB software, fuzzy sets are taken into account for error classification analysis.

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Section: Related Workmentioning

confidence: 99%

“…The capabilities of both neural networks and fuzzy logic can be utilized in this system. It learns to approximate hitting and has nonlinear functions thanks to its inference system, which is based on a collection of fuzzy if-then rules [14]. Since then, the universal estimator ANFIS has been presented [15,35].…”

Section: Established Neural Fuzzy Networkmentioning

confidence: 99%

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Khosravi,

Trik,

Ansari

2024

The Journal of Engineering

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“…With the development of distribution automation systems and monitoring devices, DTU and FTU are gradually popularized, which can monitor the electrical status and alarm state during the operation of the distribution network and will timely upload the electrical information to the data center (SCADA) after fault detection. On this basis, some fault location methods are proposed for the active distribution network, such as expert system (ES) [3], artificial neural network (ANN) [4,5], Petri nets [6], the rough set method [7], linked-list method [8,9], matrix algorithm [10][11][12][13][14][15], and optimization algorithm [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. Among them, the matrix algorithm and the optimization algorithm, are widely used in the practical distribution network.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], a layered fault location algorithm for the problem of low accuracy and efficiency in the case of multiple faults is designed, which improves the solving efficiency. In addition, genetic algorithm (GA) [20], pseudoelectromagnetism algorithm [21], particle swarm optimization (PSO) [22], imperial competition algorithm (ICA) [23], cuckoo search (CS) [24], harmony search (HS) [25], and many other artificial intelligence algorithms have been introduced into this field in recent years. e principle of the optimization algorithm is to construct the objective function based on the indicator states, which can fully excavate the redundant correlation between the alarm information and the fault section.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Method for Fault Location of Active Distribution Network Based on Improved Matrix Algorithm and Optimization Algorithm

Qiao

Wang

et al. 2022

International Transactions on Electrical Energy Systems

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The traditional fault location methods are not effective for the multisource active distribution network and are difficult to meet both requirements of timeliness and fault tolerance simultaneously. In this paper, a fault location method for active distribution networks which combines both improved matrix algorithm and optimization algorithm is proposed. The improved matrix algorithm is constructed to determine the fault section hypothesis by using the causal relationship between the alarm information and the fault section. Subsequently, network splitting is used for causal verification to check whether the alarm information is distorted. If the alarm information is normal, the fault sections can be quickly located by the above matrix algorithm. If the alarm information is distorted, the optimization model is constructed by using the fault section hypothesis selected by the matrix algorithm. The discrete particle swarm optimization (DPSO) algorithm is used to solve this optimization model, which can accurately locate the real fault sections. Hence, the advantages of both matrix algorithm and optimization algorithm are complementary. Simulation results show that the proposed method has the advantages of both high timeliness and fault tolerance in a complex active distribution network.

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The energy, water supply, and ecology coordination for middle-long-term reservoirs scheduling with different connection modes using an elite mutation strategy-based NMOSFLA

Yang

Wang

Yang

et al. 2022

Journal of Hydroinformatics

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Conventional reservoir operation emphasizes power generation (PG) with ignoring downstream river ecosystem and water supply benefits for sustainable development. Compared with the model defining water supply and ecological flow requirements as constraints, a novel long-term multi-objective scheduling model in complex parallel reservoir system (LTMOSCPRS) is developed to assess and achieve win–win and sustainable development for energy, water supply, and ecological benefits. The suitable and ideal ecological water requirements are calculated based on the requirement level index. Afterward, the novel multi-objective shuffled frog leaping algorithm (NMOSFLA) including renewed frog grouping, local search, and external elite frog set mutation strategies is proposed. Results indicate that three optimization objectives expose a mutual competing relationship. The benefit of the river ecosystem will increase at a loss of PG and water supply guarantee rate (WSGR). Therefore, the parallel reservoir system should be adjusted to improve the benefits of WSGR and ecological water spill and shortage (EWSS) with minimizing the loss of PG, simultaneously. Finally, the NMOSFLA is verified to outperform other compared methods at the solution diversity and convergence which is evaluated by multiple indicators. Overall, the NMOSFLA provides efficient reservoir operation schemes for decision-makers to select optimal trade-off schemes and feasible ways to solve the LTMOSCPRS.

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Application of BICA-NM hybrid algorithm for optimal locating of fault indicators in distribution networks

Cited by 3 publications

References 12 publications

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

Diagnosis and classification of disturbances in the power distribution network by phasor measurement unit based on fuzzy intelligent system

A Comprehensive Method for Fault Location of Active Distribution Network Based on Improved Matrix Algorithm and Optimization Algorithm

The energy, water supply, and ecology coordination for middle-long-term reservoirs scheduling with different connection modes using an elite mutation strategy-based NMOSFLA

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