A multi-objective evolutionary approach for planning and optimal condition restoration of secondary distribution networks

Optimal Network Reconfiguration to Reduce Power Loss Using an Initial Searching Point for Continuous Genetic Algorithm

“…e initial radial configuration causes the power loss of 1273.4509 kW and the minimum voltage amplitude of 0.8678 p.u corresponding to the fitness function value of 1355.6134. Meanwhile, using the proposed ISP method based on the heuristic technique, the ISP obtained is {43, 23,120,51,122,61,39,95,71,74,97,129,130,109, and 132} which causes the fitness value to be much lower than that of the initial radial configuration. is radial topology only causes power loss of 925.8662 kW and the minimum voltage amplitude of 0.9298 p.u.…”

“…Network reconfiguration (NR) is a method of changing the state of the switches on the distribution system in order to obtain the best radial structure to meet the goals such as reducing power loss, improving the load balance between branches or feeders, improving voltage quality, and improving power supply reliability. is is a nonlinear problem with constraints and has been solved by many different methods consisting of mathematical programming techniques such as linear, nonlinear, and dynamic programming [1][2][3][4][5][6][7][8], heuristic methods such as a discrete branch-andbound and branch exchange techniques [9][10][11][12], and metaheuristic methods such as firework algorithm (FW) [13], genetic algorithm (GA) [14,15], random-key GA [16], runner root algorithm [17,18], cuckoo search algorithm (CSA) [19][20][21], harmony search algorithm (HSA) [22], particle swarm optimization (PSO) [23,24], backtracking search algorithm (BSA) [25], symbiotic organisms search (SOS) [26], binary PSO [27,28], ant colony optimization [29], and flower pollination algorithm [30], combination of the wild goats and exchange market algorithms [31], and grey wolf optimizer (GWO) [32].…”

An Improved Beetle Swarm Algorithm Based on Social Learning for a Game Model of Multiobjective Distribution Network Reconfiguration

“…In summary, the players are Y1, {Y2, Y3}; the game strategy set is S1, S2, 3 = {S2, S3}; and the profit function is the profit function (25) and the profit function of the alliance income function (28).…”

“…This processing process is relatively rough and the three objectives cannot be optimized at the same time. Therefore, some scholars use the double-layer model to address multiobjectives [25]. Other scholars introduced game theory and constructed a multiobjective game model [26][27] to solve the multiobjective problem without subjectivity.…”

A Social Beetle Swarm Algorithm Based on Grey Target Decision-Making for a Multiobjective Distribution Network Reconfiguration Considering Partition of Time Intervals

“…This processing process is relatively rough, and the three objectives cannot be optimized at the same time. Therefore, some scholars use the doublelayer model to address multiobjectives [23]. Other scholars introduced the game theory and constructed a multiobjective game model [24] to solve the multiobjective problem.…”