Paper Info
Title
A network reconfiguration approach for power system restoration based on preference-based multiobjective optimization.
Abstract
Rapid load restoration after large-scale power system blackouts is of virtual importance to reduce economic losses. Network reconfiguration is an essential foundation of load restoration. Incorporating the preference for different objectives, a network reconfiguration approach based on preference-based multiobjective optimization is proposed for network reconfiguration schemes. On the one hand, considering the influences of generators, lines and loads, three evaluation indicators are proposed as objectives to establish a preference multiobjective optimization model. On the other hand, a preference-based discrete nondominated sorting genetic algorithm II (PD-NSGA-II) is designed considering the preference and high discreteness of the suggested model. For efficient decision making, the algorithm is equipped with two sorts of population and two dominance relations to obtain solutions with required quantity and high quality. The simulation results demonstrate that the preference-based multiobjective optimization can reasonably leverage the tradeoff among different factors about network reconfiguration. Furthermore, comparison with other algorithms indicates the efficiency of PD-NSGA-II in solving network reconfiguration optimization problems.
Year
DOI
Venue
2019
10.1016/j.asoc.2019.105656
Applied Soft Computing
Keywords
Field
DocType
Evolutionary computing,Network reconfiguration,Power system restoration,Preference-based multiobjective optimization
Population,Power system restoration,Mathematical optimization,Electric power system,Multi-objective optimization,Sorting,Network reconfiguration,Optimization problem,Mathematics,Genetic algorithm
Journal
Volume
ISSN
Citations 
83
1568-4946
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Runjia Sun100.34
Yutian Liu200.68
Hainan Zhu300.34
Rasoul Azizipanah-Abarghooee401.01
Vladimir V. Terzija58014.28