Improved PSO based automatic generation control of multi-source nonlinear power systems interconnected by AC/DC links. Issue 1 (1st January 2018)
- Record Type:
- Journal Article
- Title:
- Improved PSO based automatic generation control of multi-source nonlinear power systems interconnected by AC/DC links. Issue 1 (1st January 2018)
- Main Title:
- Improved PSO based automatic generation control of multi-source nonlinear power systems interconnected by AC/DC links
- Authors:
- Barisal, A.K.
Mishra, Somanath - Editors:
- Chitti Babu, B.
- Abstract:
- Abstract: This paper presents the automatic generation control of two unequal areas with diverse power generation sources like thermal, hydro, wind and diesel power plants. Three evolutionary optimization techniques named Bacteria Foraging algorithm, Particle swarm optimization (PSO) and Improved PSO (IPSO) have been applied to tune the PID controller for the power system under study. In this paper an improved PSO technique with a constraint treatment mechanism called dynamic search space squeezing strategy is devised to accelerate the optimization process in the PSO algorithm. The dynamic performance of two unequal areas with diverse sources is investigated by the proposed IPSO optimized PID controller and with the cost function integral of time multiplied absolute error (ITAE) considering 1% step load perturbation in either one of the control areas and all of the control areas. It is found that significant improvement in the system dynamic performance is achieved by considering parallel AC/DC lines in comparison to only AC tie lines between control areas. The parameters obtained with proposed approach at nominal condition need not be required to reset while performing sensitivity analysis. Also, satisfactory system performance is obtained when subjected to random load perturbation. Furthermore, the wind and diesel sources are major contributor of power generations in load disturbances and considered as ultimate participating sources to meet the peak load for improvement ofAbstract: This paper presents the automatic generation control of two unequal areas with diverse power generation sources like thermal, hydro, wind and diesel power plants. Three evolutionary optimization techniques named Bacteria Foraging algorithm, Particle swarm optimization (PSO) and Improved PSO (IPSO) have been applied to tune the PID controller for the power system under study. In this paper an improved PSO technique with a constraint treatment mechanism called dynamic search space squeezing strategy is devised to accelerate the optimization process in the PSO algorithm. The dynamic performance of two unequal areas with diverse sources is investigated by the proposed IPSO optimized PID controller and with the cost function integral of time multiplied absolute error (ITAE) considering 1% step load perturbation in either one of the control areas and all of the control areas. It is found that significant improvement in the system dynamic performance is achieved by considering parallel AC/DC lines in comparison to only AC tie lines between control areas. The parameters obtained with proposed approach at nominal condition need not be required to reset while performing sensitivity analysis. Also, satisfactory system performance is obtained when subjected to random load perturbation. Furthermore, the wind and diesel sources are major contributor of power generations in load disturbances and considered as ultimate participating sources to meet the peak load for improvement of dynamics of power system. … (more)
- Is Part Of:
- Cogent engineering. Volume 5:Issue 1(2018)
- Journal:
- Cogent engineering
- Issue:
- Volume 5:Issue 1(2018)
- Issue Display:
- Volume 5, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 5
- Issue:
- 1
- Issue Sort Value:
- 2018-0005-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-01-01
- Subjects:
- automatic generation control -- dynamic performance -- multi source power system -- HVDC link -- renewable energy sources -- dynamic search space squeezing strategy
Engineering -- Periodicals
Technology -- Periodicals
Engineering
Technology
Periodicals
620 - Journal URLs:
- http://bibpurl.oclc.org/web/73324 ↗
http://cogentoa.tandfonline.com/journal/oaen20 ↗
http://www.tandfonline.com/toc/oaen20/1/1 ↗
http://www.tandfonline.com/ ↗
http://cogentoa.tandfonline.com/journal/oaps20 ↗ - DOI:
- 10.1080/23311916.2017.1422228 ↗
- Languages:
- English
- ISSNs:
- 2331-1916
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21686.xml