Abstract
The paper extends our pervious work on solving multi-contingency transient stability constrained optimal power flow problems (MC-TSCOPF) with the approach of particles swarm optimization (PSO). A hybrid PSO method that incorporates with a new wavelet theory based mutation operation, intends to improve the searching strategies on previously used PSO methods, is proposed to solve MC-TSCOPF problems. It employs wavelet theory in enhancing PSO methods in exploring solution spaces more effectively and robustly in reaching better solutions. A case study on the New England 39-bus system indicates that the proposed hybrid PSO outperforms significantly existing PSO methods in terms of solution quality and stability. As a result, reasonable solutions can be reached with faster convergence speeds and smaller computational efforts.
Original language | English |
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Pages (from-to) | 585-601 |
Number of pages | 17 |
Journal | International journal of information and systems sciences |
Volume | 4 |
Issue number | 4 |
Publication status | Published - 2008 |
Keywords
- Particles swarm optimization
- Genetic algorithm
- Wavelet theory
- Mutation
- Multi-contingency transient stability constrained optimal power flow problems