Distribution Systems Reconfiguration Using Ant Colony Optimization and Harmony Search Algorithms

A Radial Path Building Algorithm for Optimal Feeder Planning of Primary Distribution Networks Considering Reliability Assessment

“…Therefore, to obtain maximum advantage from the principle of optimality theorem, optimal routing should be started with the terminal nodes that are farthest away from the substation. As per Figure 4, the terminal nodes to be considered are 13,10,14,25,15,11,22, and 21. The identified optimal paths of these terminal nodes are likely to cover most of the other nodes of the system on their paths.…”

“…In general, the planning problem of distribution networks may be stated as an optimization problem for a given geographical topology or region with a set of load demands, including the location of the transformation centers required for the load supply while minimizing the total installation and operational costs [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15], subject to the technical requirements for satisfactory operation of the system. Moreover, distribution system planning addresses a number of issues, such as determining the number of feeders and their routes and substation location, size, and service area, etc.…”

Adaptive Power System Stabilizer Design Using Optimal Support Vector Machines Based on Harmony Search Algorithm

“…HS is simple in concept, has fewer parameters, and is easy to implement [25]. It has been successfully applied to various optimization problems, such as optimal conductor size selection in distribution systems [26] and economic load dispatch [27], distribution system reconfiguration [28], and solving optimal power flow problems [29]. These works show that the HS algorithm is superior to other algorithms, and accordingly, the HS algorithm is used for the tuning of SVM parameters in this work.…”

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

“…The method was tested on both modified IEEE 33-bus and 69-bus distribution systems and compared with GA, Refined GA (RGA), Fuzzy, heuristic techniques, SA, and Plant Growth Search (PGS), returning the best results for the multi-variable function. Other works are developed in [67] and [84].…”