Transmission network expansion planning under an improved genetic algorithm

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

“…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.…”

“…In [10] , the network expansion costs and transmitted power through the lines have been included in objective function and the goal was optimization of both expansion costs and lines loading. In addition, the objective function was different from those which were considered in [6,11,12,[15][16][17]20,24,30] , but the voltage level of transmission lines, network losses and bundle of lines have not been investigated. In [31] , the voltage level of transmission lines has been considered as an additional factor, but the proposed objective function only includes expansion and generation costs and one of the reliability criteria i.e.…”

“…After Garver's paper that was published in 1970 [7] , much research has been done on the field of TNEP problem. 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] . Recently, different methods such as GRASP [3] , Bender decomposition [6] , HIPER [17] branch and bound algorithm [30] , sensitivity analysis [15] , genetic algorithm [1,11,20,24] , simulated annealing [16] and Tabu search [12] have been proposed for solution of the STNEP problem. In all of them, the problem has been solved regardless of voltage level of transmission lines and the role of voltage level in reducing network annual losses.…”

Time‐horizons in the planning and operation of transmission networks: an overview

“…In the recent period, Lattore et al [13] [32][33][34], disjunctive mixed integer programming [35], branch and bound algorithm [36], implicit enumeration [37,38], Benders decomposition [12, 39,40], maximum flow [12], hierarchical decomposition [41], sensitivity analysis [42,43], genetic algorithm (GA) [44][45][46][47][48][49], object-oriented programming [50], game-theory [51][52][53][54], simulated annealing [55,56], expert systems [57,58], fuzzy set [49,59,60], greedy randomised adaptive search [61], non-convex optimisation [62], tabu search [63], ant-colony [64], data-mining [65], particle swarm optimisation (PSO) [66][67][68][69], harmony search [70,71], artificial neural network (ANN) [72], game theory [73], and robust optimisation techniques [74][75]…”