A reliability approach to transmission expansion planning using minimal cut theory

Chanda, Rupsa; Bhattacharjee, Prasun

doi:10.1016/0378-7796(95)00937-d

“…Where, In this work, the objective function is different from those which are mentioned in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16], [19][20][21][22], [24,25] and in part of the problem constraints, ij f has been considered as an addition constraint. In addition to above-mentioned changes, also Line_Loading constraint has been considered as a new constraint in order to ensure adequacy of the network after expansion.…”

Section: Mathematical Model (Objective Function) Of the Stnep Promentioning

confidence: 99%

“…Some of this research such as [1]- [3], [5]- [19] is related to problem solution method. Some others, irrespective of solution method, proposed different approach for solution this problem considering various parameters such as reliability criteria [20], [21] and economic factors [22]. Also, some of them investigated this problem and generation expansion planning together [23], [24].…”

Section: Introductionmentioning

confidence: 99%

TNEP considering voltage level, network losses and number of bundle lines using GA

Jalilzadeh

¹

,

Kazemi

²

,

Mahdavi

³

et al. 2008

2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies

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Up to now, various methods have been presented for solution of the static transmission network expansion planning (STNEP) problem. However, in all of these methods, STNEP problem has been solved regardless to voltage level of transmission lines and role of voltage level in reducing annual losses of the network. In this paper, STNEP has been studied considering voltage level, network losses and number of bundle lines (which cause different network annual losses) using decimal codification based genetic algorithm (DCGA). Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, integer-mixed optimization problems, like the TNEP problem, better than a number of mathematical methodologies. The proposed method is tested on an actual transmission network of the Azerbaijan regional electric company, Iran to illustrate its robust performance. The results show that considering the network losses in a power system with different voltage levels, decreases the operational costs considerably and the network satisfies the requirement of delivering electric power more safely and reliably to load centers.

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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%

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.

show abstract

“…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%

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

Jalilzadeh¹,

Shayeghi²,

Mahdavi³

et al. 2009

American J. 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.

show abstract

A reliability approach to transmission expansion planning using minimal cut theory

Cited by 15 publications

References 9 publications

TNEP considering voltage level, network losses and number of bundle lines using GA

TNEP considering voltage level, network losses and number of bundle lines using GA

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

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