Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm
Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computati...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
|
| Online Access: | https://hdl.handle.net/10356/96755 http://hdl.handle.net/10220/13078 |
| _version_ | 1826116988325330944 |
|---|---|
| author | Suganthan, P. N. Zhang, Xuexia Chen, Weirong |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Suganthan, P. N. Zhang, Xuexia Chen, Weirong |
| author_sort | Suganthan, P. N. |
| collection | NTU |
| description | Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (GAs), differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem. |
| first_indexed | 2024-10-01T04:20:25Z |
| format | Conference Paper |
| id | ntu-10356/96755 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:20:25Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/967552020-03-07T13:24:47Z Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm Suganthan, P. N. Zhang, Xuexia Chen, Weirong School of Electrical and Electronic Engineering International Conference on Intelligent System Design and Engineering Application (2nd : 2012 : Sanya, China) Optimizing multi-objective reactive power dispatch in power systems is an effective way of improving voltage quality, decreasing active power losses and increasing voltage stability margin. This is a non-linear, constrained, non-convex, mixed discrete-continuous variable problem. Recently, computational intelligence-based methods such as genetic algorithms (GAs), differential evolution (DE) algorithms, particle swarm optimization (PSO) algorithms and immune algorithms (IAs) have been applied to solve this problem. This paper employs dynamic multi-group self-adaptive differential evolution (DMSDE) algorithm to solve multi-objective reactive power optimization problem. In DMSDE, the population is divided into multiple groups which exchange information dynamically. Further, in the mutation phase, the best vector among the three randomly vectors is used as the base vector while the difference vector is determined by the remaining two vectors. Moreover, two parameters, F and CR, are self-adapted. The presented method is tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus power systems. The numerical results, when compared with other algorithms, show that DMSDE is an efficient tool to solve dispatch reactive power flow problem. 2013-08-12T08:28:04Z 2019-12-06T19:34:35Z 2013-08-12T08:28:04Z 2019-12-06T19:34:35Z 2012 2012 Conference Paper https://hdl.handle.net/10356/96755 http://hdl.handle.net/10220/13078 10.1109/ISdea.2012.412 en |
| spellingShingle | Suganthan, P. N. Zhang, Xuexia Chen, Weirong Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title | Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title_full | Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title_fullStr | Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title_full_unstemmed | Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title_short | Optimal multi-objective reactive power dispatch considering static voltage stability based on dynamic multi-group self-adaptive differential evolution algorithm |
| title_sort | optimal multi objective reactive power dispatch considering static voltage stability based on dynamic multi group self adaptive differential evolution algorithm |
| url | https://hdl.handle.net/10356/96755 http://hdl.handle.net/10220/13078 |
| work_keys_str_mv | AT suganthanpn optimalmultiobjectivereactivepowerdispatchconsideringstaticvoltagestabilitybasedondynamicmultigroupselfadaptivedifferentialevolutionalgorithm AT zhangxuexia optimalmultiobjectivereactivepowerdispatchconsideringstaticvoltagestabilitybasedondynamicmultigroupselfadaptivedifferentialevolutionalgorithm AT chenweirong optimalmultiobjectivereactivepowerdispatchconsideringstaticvoltagestabilitybasedondynamicmultigroupselfadaptivedifferentialevolutionalgorithm |