Technical Program
Paper Detail
| Paper: | POSTER-A.46 |
| Session: | Power System Operations A |
| Time: | Monday, October 11, 14:00 - 16:00 |
| Presentation: |
Poster
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| Title: |
Application Meta-Heuristics Method for Short-Term Unit Commitment Problem |
| Authors: |
Gwo-Ching Liao, Fortune Institute of Technology |
| Abstract: |
This paper presents a Hybrid Chaos Search Genetic Algorithm and Simulated Annealing method (CGA-SA) for solving short-term thermal generatingUnit Commitment (UC) problems. The UC problem involves determining the start-up and shutdown schedules for generating units to meet theforecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve and individual units. We combined a genetic algorithm with the chaos search. First, it generates a set of feasible unit commitment schedules, and then puts the solution to the SA. The CGA has good global optima search capabilities, but poor local optima search capabilities. The SA method on the other hand, has good local optima search capabilities. Through this combined approach an optimal solution can be found. |
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