TY - JOUR
T1 - Enhancement of hydroelectric generation scheduling using ant colony system based optimization approaches
AU - Huang, Shyh Jier
N1 - Funding Information:
Manuscript received February 23, 2000. This work was partially supported by the National Science Council of Republic of China under Contract NSC88-TPC-E-006-013. The author is with the Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan. Publisher Item Identifier S 0885-8969(01)07339-9.
PY - 2001/9
Y1 - 2001/9
N2 - In this paper, an Ant Colony System (ACS) based optimization approach is proposed for the enhancement of hydroelectric generation scheduling. To apply the method to solve this problem, the search space of multi-stage scheduling is first determined. Through a collection of cooperative agents called ants, the near-optimal solution to the scheduling problem can be effectively achieved. In the algorithm, the state transition rule, local pheromone-updating rule, and global pheromone-updating rule are all added to facilitate the computation. Because this method can operate the population of agents simultaneously, the process stagnation can be better prevented. The optimization capability can be thus significantly enhanced. The proposed approach has been tested on Taiwan Power System (Taipower) through the utility data. Test results demonstrated the feasibility and effectiveness of the method for the application considered.
AB - In this paper, an Ant Colony System (ACS) based optimization approach is proposed for the enhancement of hydroelectric generation scheduling. To apply the method to solve this problem, the search space of multi-stage scheduling is first determined. Through a collection of cooperative agents called ants, the near-optimal solution to the scheduling problem can be effectively achieved. In the algorithm, the state transition rule, local pheromone-updating rule, and global pheromone-updating rule are all added to facilitate the computation. Because this method can operate the population of agents simultaneously, the process stagnation can be better prevented. The optimization capability can be thus significantly enhanced. The proposed approach has been tested on Taiwan Power System (Taipower) through the utility data. Test results demonstrated the feasibility and effectiveness of the method for the application considered.
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U2 - 10.1109/60.937211
DO - 10.1109/60.937211
M3 - Article
AN - SCOPUS:0035451122
VL - 16
SP - 296
EP - 301
JO - IEEE Transactions on Energy Conversion
JF - IEEE Transactions on Energy Conversion
SN - 0885-8969
IS - 3
ER -