Interactive modeling of supply restoration procedures in distribution system operation

Dialynas, E.N.; Michos, D.

doi:10.1109/61.32681

Cited by 27 publications

(8 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reference [6] shows the to compute the NSE indexes, though it does not show how to calculate it. Reference [11] presents a statistical calculation approach, stating as well that there are many factors affecting this time, e.g., time (date and hour) of fault occurrence, number of affected phases, number of activated protection devices, meteorological conditions, and fault causes (fortuitous causes, accidents, fall of tree branches, winds, lightning strokes, transformer faults, etc.).…”

Section: B Fis To Estimate Thementioning

confidence: 99%

“…The addition of and allows computing the associated penalization for the zones to be restored through the load transference to nonfaulted feeders for each restoration configuration alternative. The restoration time for each alternative is computed as (6) In the methodology proposed in [1], computes the maximum feasible penalization, rendering an approximate view on the amount of penalization when there are load losses for more than one zone. Then, when there occurs a load loss, becomes equal to (7) IV.…”

Section: Times Involved In the Restoration Processmentioning

confidence: 99%

“…One of these criteria advises to assign economical costs to the operation of switches for each alternative considered, trying as well to reduce the restoration time in order to obtain lower NSE levels. On the other hand, [6] proposes to use indexes to choose the alternative that offers the greatest level for reducing the NSE. The problem of both approaches, from the NSE viewpoint, is that they assign specific times, or costs, to the switches, without considering the possibility of a variation from one restoration alternative to another.…”

Section: Introductionmentioning

confidence: 99%

“…The NSE used as an indicator to choose the restoration of operative configuration has been proposed in [4] and [6]. In [4], several criteria are employed to pick an appropriate restoration alternative.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fuzzy-Heuristic Methodology to Estimate the Load Restoration Time in MV Networks

Rodríguez¹,

Vargas

2005

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

A marked feature of electrical markets in Latin America is the high level of penalizations imposed on the utilities on account of nonsupplied energy (NSE). These economical sanctions are intended as a preventive measure to keep the Electric Service Quality (ESQ) as high as possible. NSE is computed and controlled during a fixed period individually for each group of clients (INSE). When the INSE is violated, the utilities must pay a cost of penalization for the entire INSE. The total cost of penalizations will depend on the NSE allocation between different groups of clients. In case of a fault or simultaneous faults in MV networks, there are several alternatives for radial configuration operation to restore the service. They can be classified according to the switches that have to be operated for such an end, and each alternative has an associated INSE penalty cost that depends mainly on the restoration time implied. This work develops a fuzzy-heuristic methodology to estimate the times involved in the restoration times, and it is a part of a larger optimization method for solving the load restoration problem. The results from testing the methodology in a real 290-node network have proven the feasibility of this proposed tool.

show abstract

Section: B Fis To Estimate Thementioning

confidence: 99%

Section: Times Involved In the Restoration Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy-Heuristic Methodology to Estimate the Load Restoration Time in MV Networks

Rodríguez¹,

Vargas

2005

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

show abstract

“…et al (1989) [12], a heuristic was implemented to minimize the number of switch operations. Two other works (Kim et al [13], Fujii et al [14]) addressed the reconfiguration problem also minimizing the number of switch operations.…”

mentioning

confidence: 99%

Switch and Tap-Changer Reconfiguration of Distribution Networks Using Evolutionary Algorithms

Mendes

Boland

Guiney

et al. 2013

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

The reconfiguration of distribution networks is an important combinatorial problem. This work addresses the particular case of reconfiguration after an outage caused by the loss of a single branch of the network. The reconfiguration is carried out over two domains simultaneously: re-switching strategies and transformer tap-changer adjustments. The approach was tested using a real large-scale network within the concession area of Energy Australia. The model considers four operational elements: an AC power flow model, the network's radial topology when operating, voltage limits and load limits. Two evolutionary algorithms were implemented and tested. The first was a genetic algorithm, applied over the space of possible re-switching strategies, and for both re-switching and tap-changer adjustments, simultaneously. The second was a memetic algorithm, applied over the same two variations of the reconfiguration problem. Computational tests consider the evaluation of the loss of every branch, reporting the number of buses affected, and the number of overloaded branches after the reconfiguration.

show abstract

Multi-objective Optimisation of Power Restoration in Electricity Distribution Systems

Mendes

Boland

2011

AI 2011: Advances in Artificial Intelligence

View full text Add to dashboard Cite

Interactive modeling of supply restoration procedures in distribution system operation

Cited by 27 publications

References 8 publications

Fuzzy-Heuristic Methodology to Estimate the Load Restoration Time in MV Networks

Fuzzy-Heuristic Methodology to Estimate the Load Restoration Time in MV Networks

Switch and Tap-Changer Reconfiguration of Distribution Networks Using Evolutionary Algorithms

Multi-objective Optimisation of Power Restoration in Electricity Distribution Systems

Contact Info

Product

Resources

About