Multi-objective feeder reconfiguration in different tariff structures

Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II

“…Additionally, this approach alters the essence of the original technical problem. On the other hand, some authors have studied this problem using aggregation functions, converting the multi-objective problem into a single objective one that assumes a (weighted or not) sum of the selected objective functions [23][24][25][26][27][28][29][30]. The major difficulty in this kind of problem consists in the incompatibility of different criteria.…”

“…In order to avoid the evaluation of the entire space of the candidate solutions and to minimize the computation burden, several algorithms have been developed. Most authors have used different well known heuristics (branch exchange [2,3,21], branch and bound [1,4], simulated annealing [5]), other heuristic rules or meta-heuristics [7][8][9][11][12][13]15,17,22,23,25,27,28] or multi-agent technologies [20]. On the other hand, some authors have developed methods based on evolutionary computation techniques [6,14,16,18,19,24,26,29,30].…”

Sensitivity and functionally oriented models for power system planning, operation, and control

“…These problems are solved in long-and short-term planning, operation, and can be applied in design studies to achieve different objectives, discussed, for example, in [19][20][21]. An increased interest to network reconfiguration is associated with wide automation of distribution systems whose switches are remotely monitored and controlled.…”

“…It permits one to solve the problems as on-line, real time problems. Many works have been dedicated to their solution in a monocriteria as well as multicriteria statements on the basis of diverse approaches (for example, [2,[19][20][21][22][23][24][25][26][27][28][29][30]). These works ''compete'' in aspiration for obtaining ''more optimal'' solutions.…”

“…However, this aspiration, considering that the combination of the information uncertainty and relative stability of optimal solutions produces decision uncertainty regions [19,31], is not convincing. At the same time, the results of [2,[19][20][21][22][23][24][25][26][27][28][29][30] as well as other works in this field do not permit one to consider a power system reaction when optimizing distribution system configuration.…”