A reliability approach to transmission expansion planning using fuzzy fault-tree model

Chanda, Rupsa; Bhattacharjee, Prasun

doi:10.1016/s0378-7796(97)01226-1

Cited by 58 publications

(29 citation statements)

References 8 publications

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“…Line_Loading ≤ LL max (8) Where (i, j) ∈ Ω and: S = Branch-node incidence matrix In this study, the objective function was different from those which were considered in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][23][24][25][26][27]29,30] and in part of the problem constraints, ij f is considered as an additional constraint. In addition to the abovementioned changes, also Line_Loading constraint was considered as a new constraint in order to ensure adequacy of the network after expansion.…”

Section: Methodsmentioning

confidence: 99%

“…Some of this researches such as [1][2][3]6,[8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] were related to problem solution method. Some others proposed different approaches for solution of this problem considered various parameters such as uncertainty in demand [5] , reliability criteria [4,25,26] and economic factors [27] . Also, some of them investigated this problem and generation expansion planning together [28,29] .…”

Section: Introductionmentioning

confidence: 99%

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A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines

Jalilzadeh¹

2009

American Journal of Applied Sciences

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Transmission Network Expansion Planning (TNEP) was studied considering voltage level, network losses and number of bundle lines using decimal codification based genetic algorithm (DCGA). TNEP determines the characteristic and performance of the future electric power network and directly influences the operation of power system. Up till now, various methods have been presented for the solution of the Static Transmission Network Expansion Planning (STNEP) problem. However, in all of these methods, STNEP problem has been solved regardless of voltage level of transmission lines. For this reason and according to various voltage levels and different number of bundle lines used in real transmission network which caused different annual losses, STNEP was studied considering voltage level, network losses and number of bundle lines using genetic algorithm. Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, mixedinteger optimization problems, like the TNEP problem, better than a number of mathematical methodologies. The proposed method was tested on an actual transmission network of the Azerbaijan regional electric company, Iran, to illustrate its robust performance. The results were shown that considering the network losses in a network with different voltage levels and the number of bundle lines considerably decreased the operational costs and the network can be satisfied the requirement of delivering electric power more safely and reliably to load centers.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines

Jalilzadeh¹

2009

American Journal of Applied Sciences

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“…This tumble and swim make one chemo tactic step. If the concentration is greater at next location then they take another step in that direction [10][11] [12]. When concentration at next location is lesser that of previous location they tumble to find another direction and swim in this new direction.…”

Section: Bacterial Foragingmentioning

confidence: 99%

“…Papers that consider only investment/construction cost as an objective are: The simulated annealing (SA) [10], method has been successfully applied to large-scale TNEP problem. The SA [12] tries to avoid local optima by allowing temporary, limited deterioration of actual solutions.…”

Section: Introductionmentioning

confidence: 99%

Multi Objective Optimization for Transmission Network Expansion Planning using Modified Bacterial Foraging Technique

Jaganathan¹,

Palaniswami²,

Kumar³

2010

IJCA

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Multi-objective optimisation is a proven well known parameter tuning technique in complex power system problems. It is especially suited to solve complex transmission network expansion planning. This paper proposes a practical method for transmission network expansion planning by bacterial foraging technique. The electricity industry has always been interested in expanding investment in the transmission sector of the industry. As load demand increases and generation expands to meet the need, transmission expansion becomes important in order to increase social welfare by reducing total system operating cost, and to make the system more reliable. In this context, two objectives: investment cost and network adequacy restrictions are considered to overcome the drawbacks of conventional mathematical optimization method in arriving at local optimum and dimension disasters, we introduced the bacterial foraging technique into transmission network optimal planning for the first time, from which the optimal scheme is generated. The bacterial foraging is used as the optimization tool to obtain the Pareto approximation set solutions. The proposed algorithm is implemented on typical IEEE 6 bus systems and performance is assessed by statistical test.

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“…Most commonly used reliability study methods for power system include Reliability Block Diagram (RBD) [2], Markov chain [3], Monte Carlo simulation [4] and Fault Tree Analysis (FTA) [5]. Considering the feature of industrial grids, for example, multi-input and multi-output, large quantity of components, known electrification scheme, desiring to identify key component(s) with biggest impact on the entire system reliability, as well as for the purpose of reflecting reliability trend after introducing VFDs, FTA is chosen in this paper to develop a generic evaluation algorithm.…”

Section: Introductionmentioning

confidence: 99%

Generic Reliability Evaluation Method for Industrial Grids with Variable Frequency Drives

Yu¹,

Chen²,

Pan³

et al. 2013

EPE

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The paper presents a reliability evaluation method based on fault tree analysis with set theory and minimal cut set as core algorithm, which can be used to evaluate the reliability for industrial grids with wide application of variable frequency drives. The working principle is introduced firstly, based on which the method development considering different system topology designs, backup solutions and redundancy mechanisms are analyzed in details. In the end the proposed method is applied to two cases to show the reliability performance of system with variable frequency drives. The proposed method is also suitable for analyzing the reliability performance of industrial grids with other types of power electronic converter technology.

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A reliability approach to transmission expansion planning using fuzzy fault-tree model

Cited by 58 publications

References 8 publications

A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines

A GA Based Transmission Network Expansion Planning Considering Voltage Level, Network Losses and Number of Bundle Lines

Multi Objective Optimization for Transmission Network Expansion Planning using Modified Bacterial Foraging Technique

Generic Reliability Evaluation Method for Industrial Grids with Variable Frequency Drives

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