Determination of critical switches in distribution system

Chen, C.S.; Cho, M.Y.

doi:10.1109/61.141863

Cited by 53 publications

(12 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and can be obtained using item 4) in method A. c) Normalization: A normalization procedure is required such that all objectives can be compared when calculating grey correlation grade. The superior, , and inferior, , solutions are used in the normalization (18) to (20) are rewritten as • Upper-bound effectiveness measuring (24) • Lower-bound effectiveness measuring (25) • Moderate effectiveness measuring (26) d) Determine the grey correlation grade: In (21), and correspond to 1 and 0 when superior and inferior solutions are used. Equation (21) is rewritten as (27) can be calculated as (28): (28) where is the measure between the solution represented by the th chromosome applying to the th objective and the superior or inferior solution.…”

Section: Gcra For Multi-objectivementioning

confidence: 99%

“…Equation (21) is rewritten as (27) can be calculated as (28): (28) where is the measure between the solution represented by the th chromosome applying to the th objective and the superior or inferior solution. Since the scale of the grey relational grade can be determined by in (21), the scale of each generation is fixed. In (28), is the weight for the th objective.…”

Section: Gcra For Multi-objectivementioning

confidence: 99%

“…During reconfiguration of distribution feeders, several objectives are considered by the distribution system operators. These objectives include: 1) line losses [1], [4], [6]- [11], [13], [18]- [20], [22], [24]; 2) load balancing [4], [5], [11], [20], [21], [23], [24]; 3) voltage drop [2], [3], [5], [8], [9], [24]; 4) number of switching actions [2], [3], [8], [9]; etc. Single objective optimization was considered in the past.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

Tsai

Hsu²

2010

IEEE Trans. Power Syst.

118

View full text Add to dashboard Cite

Feeder reconfiguration is a common technique that is used by distribution system operators during normal or emergency operational planning. By changing the status of switches on the distribution systems, the feeders can be reconfigured. During a feeder reconfiguration, more than one objective is considered by the distribution system operators. Due to the complexity of the reconfiguration problems, the system operators are looking for assistance from computer program that can provide adequate switching plans to reconfigure the feeders such that the desired goal can be achieved. Thus, the feeder reconfiguration is a type of discrete multi-objective optimization problems. Evolutionary programming (EP) technique is a method that can be applied to identify an optimal switching plan for feeder reconfiguration. A fitness function is required in EP for chromosome selection during reproduction process. The fitness function needs to integrate the objectives to provide a measure for each chromosome. Normalizing the objectives is a typical method for multi-objective optimizations such that these objectives are comparable. In this paper, Gray CoRrelation Analysis (GCRA) method is proposed. The proposed method is used to integrate the objectives and provide a relative measure to a particular switching plan associated with a chromosome without any prior knowledge of the system under reconfiguration. Two different distribution systems are used in this paper to demonstrate how the proposed GCRA is applied during the selection process of EP. Several simulations show that the EP can identify the solution more accurately when GCRA is applied than other methods.

show abstract

Section: Gcra For Multi-objectivementioning

confidence: 99%

Section: Gcra For Multi-objectivementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

Tsai

Hsu²

2010

IEEE Trans. Power Syst.

118

View full text Add to dashboard Cite

show abstract

“…The method is applicable to bwh constant as well aswhanging load conditions. Chen and Cho [5] evaluated the optimal switching operations based on the hourly load patterns. The critical switches are identified by investigating the optimal switching patterns.…”

Section: Introductionmentioning

confidence: 99%

A new fuzzy reasoning approach for load balancing in distribution system

Raj

Rao

1995

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

-Transformer and feeder load balancing in a distribution system reduces the risk of overloads due to load changes.The possible out of service area following the occurrence of a fault is also reduced. However, keeping in view the life expectancy of the switches, it is desirable that the number of switching operations is kept to a minimum. A new algorithm for load balancing based on fuzzy set decision theory is presented in this paper. The decision regarding switching operations is arrived at by considering transformer and feeder load balancing together. The proposed method is illustrated through an example.

show abstract

“…

Distribution system reconfiguration is performed during normal or emergency operations by changing the status of switches. The objectives considered by the aforementioned research include: system loss [1,4,[6][7][8]10,[13][14][15]17], load balancing [4,5,8,16,18], number of switch operations [2,3,5,7,8], and so on. For emergency operations, de-energized loads can be transferred to adjacent energized feeders through system reconfiguration.

…”

mentioning

confidence: 99%

A non-dominated sorting evolutionary programming algorithm for multi-objectives power distribution system feeder reconfiguration problems

Hsu

Tsai

2011

Int. Trans. Electr. Energ. Syst.

View full text Add to dashboard Cite

SUMMARY Distribution system reconfiguration is performed during normal or emergency operations by changing the status of switches. System reconfiguration can be used for system loss reduction or voltage profile improvement during normal operations. For emergency operations, de‐energized loads can be transferred to adjacent energized feeders through system reconfiguration. Several objectives, for example, system real power loss reduction and transformer load balancing improvement, are considered simultaneously during system reconfiguration. In order to consider the objectives simultaneously, weighted sum method was commonly used. Only one solution may be obtained when weighted sum method was applied. However, several compromise solutions were preferred for the distribution system operators. Multi‐objective approach was one of the methods that can be used to provide multiple compromise solutions. In this paper, the fitness function in non‐dominated sorting genetic algorithm and the reproduction procedure in evolutionary programming were integrated. The proposed non‐dominated sorting evolutionary programming was applied to the multi‐objective problems in distribution systems in order to provide system operators with different compromise solutions. The results of this study indicated that the proposed non‐dominated sorting evolutionary programming was capable of identifying better solutions than that of non‐dominated sorting genetic algorithm for distribution system reconfiguration problems. Copyright © 2011 John Wiley & Sons, Ltd.

show abstract

Determination of critical switches in distribution system

Cited by 53 publications

References 15 publications

Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

A new fuzzy reasoning approach for load balancing in distribution system

A non-dominated sorting evolutionary programming algorithm for multi-objectives power distribution system feeder reconfiguration problems

Contact Info

Product

Resources

About