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Hybrid: Particle Swarm Optimization–Genetic Algorithm and Particle Swarm Optimization–Shuffled Frog Leaping Algorithm for long-term generator maintenance scheduling
- Source :
- International Journal of Electrical Power & Energy Systems. 65:432-442
- Publication Year :
- 2015
- Publisher :
- Elsevier BV, 2015.
-
Abstract
- This paper presents a Hybrid Particle Swarm Optimization based Genetic Algorithm and Hybrid Particle Swarm Optimization based Shuffled Frog Leaping Algorithm for solving long-term generation maintenance scheduling problem. In power system, maintenance scheduling is being done upon the technical requirements of power plants and preserving the grid reliability. The objective function is to sell electricity as much as possible according to the market clearing price forecast. While in power system, technical viewpoints and system reliability are taken into consideration in maintenance scheduling with respect to the economical viewpoint. It will consider security constrained model for preventive Maintenance scheduling such as generation capacity, duration of maintenance, maintenance continuity, spinning reserve and reliability index are being taken into account. The proposed hybrid methods are applied to an IEEE test system consist of 24 buses with 32 thermal generating units.
- Subjects :
- Mathematical optimization
Engineering
Job shop scheduling
business.industry
Market clearing
Energy Engineering and Power Technology
Particle swarm optimization
Grid
Preventive maintenance
Scheduling (computing)
Electric power system
Electrical and Electronic Engineering
Multi-swarm optimization
business
Subjects
Details
- ISSN :
- 01420615
- Volume :
- 65
- Database :
- OpenAIRE
- Journal :
- International Journal of Electrical Power & Energy Systems
- Accession number :
- edsair.doi...........c345fefa569f877917f14ba020937c5c