DocumentCode :
1629769
Title :
Simulated Annealing metaheuristic to solve the optimal power flow
Author :
Sousa, T. ; Soares, J. ; Vale, Z.A. ; Morais, H. ; Faria, P.
Author_Institution :
GECAD - Knowledge Eng. & Decision-Support Res. Group, Polytech. Inst. of Porto, Porto, Portugal
fYear :
2011
Firstpage :
1
Lastpage :
8
Abstract :
The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other well-known methodologies presented in the literature, showing the effectiveness of the proposed method.
Keywords :
artificial intelligence; combinatorial mathematics; heuristic programming; load dispatching; load flow; nonlinear programming; power system planning; simulated annealing; IEEE bus networks; artificial intelligence techniques; biological processes; cooling temperature process; economic dispatch; large combinatorial problem; mathematical methods; metallurgy; nonlinear programming; optimal power flow problem; power system planning; simulated annealing metaheuristic; Artificial intelligence; Economics; Generators; Load flow; Power generation; Reactive power; Simulated annealing; Artificial Intelligence; Economic Dispatch; Optimal Power Flow; Optimization Method; Simulated Annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2011 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4577-1000-1
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PES.2011.6039543
Filename :
6039543
Link To Document :
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