An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration

Ahuja, Ashish; Das, Sanjoy; Pahwa, Anil

doi:10.1007/978-3-642-14013-6_2

Cited by 63 publications

(49 citation statements)

References 36 publications

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“…For instance, in [9] Different from previous works, we note that in the practical implementation of network reconfiguration, the control signal is distributed from the control center to each switcher respectively, via power line communication or wireless communication. The delay occurring in the communication, as well as the response delay in the reconfiguration process will cause disturbances in the local power grid.…”

Section: A Related Workmentioning

confidence: 99%

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Power distribution network reconfiguration for bounded transient power loss

Chen

et al. 2012

IEEE PES Innovative Smart Grid Technologies

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We revisit the loss reduction problem for network reconfiguration in power distribution systems in this paper. Besides the conventional line power loss (LPL), in our model, we introduce a new concept -the transient power loss (TPL), which is mainly induced by the communication asynchronization and response delay. TPL is often overlooked in previous works because it's hard to measure in the conventional power networks. However, we can tackle this challenge in smart grid especially with the help of smart meter. In this paper, we propose a new heuristic greedy algorithm to achieve the minimal LPL with bounded TPL and we assess its performance via simulation based on the IEEE-33 nodes system.

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Section: A Related Workmentioning

confidence: 99%

“…However, in previous works for network reconfiguration, e.g. [3][4][5][6][7][8][9][10][11], the researchers often overlooked TPL and only considered LPL in their model. In order to achieve the transient stability and the bounded disturbances, we propose a new approach to achieve the LPL reduction with bounded TPL.…”

Section: A Related Workmentioning

confidence: 99%

Power distribution network reconfiguration for bounded transient power loss

Chen

et al. 2012

IEEE PES Innovative Smart Grid Technologies

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“…As renewable distributed generation (RDG) sources increase in the system, benefits from redesigning radial systems into partially meshed systems are expected to increase [12]. Many researchers have explored the redesign of radial distribution systems: approaches to reconfiguration have objectives such as minimizing losses [13][14][15][16][17][18][19][20]; increasing reliability [21,22]; and achieving load balance [23,25].…”

Section: System Reliability Measuresmentioning

confidence: 99%

Some elements of design and operation of a smart distribution system

et al. 2010

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this paper relates to several specific aspects of design and operation of a 'smart' power distribution system. The emphasis is on automation in design, reliability enhancement, operations, and reconfiguration after a disturbance. The use of network incidence or connectivity matrices is shown and examples indicate the potential operational capabilities of a 'smart distribution system'. An algorithm described as a sequential feeder approach is illustrated.

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“…References [1]- [26] propose algorithms to locate faults in distribution networks. These algorithms are based on one or more of seven main techniques: impedance measurement, automated outage mapping (AOM), voltage sag estimation, traveling waves, direct three-phase circuit analysis, superimposed components, and artificial intelligence (AI).…”

Section: Introductionmentioning

confidence: 99%

“…In [21]- [23], the behavior of traveling wave produced due to a fault is evaluated in terms of the time difference between sequential recorded waves. In [24]- [26], extensive scenarios covering all fault conditions are simulated, and some features are extracted from system variables such as voltage and current waveforms. The extracted features are used to train neural networks to locate the fault.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Single and Simultaneous Fault Location in Distribution Networks

Majidi

Etezadi-Amoli

Fadali

2015

IEEE Trans. Power Syst.

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This paper introduces a novel method for single and simultaneous fault location in distribution networks by means of a sparse representation (SR) vector, Fuzzy-clustering, and machinelearning. The method requires few smart meters along the primary feeders to measure the pre-and during-fault voltages. The voltage sag values for the measured buses produce a vector whose dimension is less than the number of buses in the system. By concatenating the corresponding rows of the bus impedance matrix, an underdetermined set of equation is formed and is used to recover the fault current vector. Since the current vector ideally contains few nonzero values corresponding to fault currents at the faulted points, it is a sparse vector which can be determined by -norm minimization. Because the number of nonzero values in the estimated current vector often exceeds the number of fault points, we analyze the nonzero values by Fuzzy-c mean to estimate four possible faults. Furthermore, the nonzero values are processed by a new machine learning method based on the k-nearest neighborhood technique to estimate a single fault location. The performance of our algorithms is validated by their implementation on a real distribution network with noisy and noise-free measurement.Index Terms-Compressive sensing, distribution networks, fault location, Fuzzy-c mean, k-nearest neighborhood, and stable -norm minimization, smart meters.

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An AIS-ACO Hybrid Approach for Multi-Objective Distribution System Reconfiguration

Cited by 63 publications

References 36 publications

Power distribution network reconfiguration for bounded transient power loss

Power distribution network reconfiguration for bounded transient power loss

Some elements of design and operation of a smart distribution system

A Novel Method for Single and Simultaneous Fault Location in Distribution Networks

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