[article] inIEEE transactions on energy conversion > Vol. 23 N°1 (Mars 2008) . - pp. 294 - 301
Titre : |
Pumped-storage scheduling using evolutionary particle swarm optimization |
Type de document : |
texte imprimé |
Auteurs : |
Po-Hung Chen, Auteur |
Année de publication : |
2008 |
Article en page(s) : |
pp. 294 - 301 |
Note générale : |
Energy conversion |
Langues : |
Anglais (eng) |
Mots-clés : |
Decoding encoding evolutionary computation hydrothermal power systems particle swarm optimisation pumped-storage stations scheduling |
Résumé : |
This paper presents new solution algorithms based on an evolutionary particle swarm optimization (EPSO) for solving the pumped-storage (P/S) scheduling problem. The proposed EPSO approach combines a basic particle swarm optimization (PSO) with binary encoding/decoding techniques as well as a mutation operation. The binary encoding/decoding techniques are adopted to model the discrete characteristics of a P/S plant. The mutation operation is applied to accelerate convergence and escape local optimums. The optimal generation schedules for both P/S and thermal units are concurrently obtained within the evolutionary process of a scoring function. Therefore, hydrothermal iteration is no longer needed. The proposed approach is applied with great success to an actual utility system consisting of four P/S units and 34 thermal units. Experimental results indicate the attractive properties of the EPSO approach in a practical application, namely, a highly optimal solution and robust convergence behavior. |
En ligne : |
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4453979&sortType%3Das [...] |
[article] Pumped-storage scheduling using evolutionary particle swarm optimization [texte imprimé] / Po-Hung Chen, Auteur . - 2008 . - pp. 294 - 301. Energy conversion Langues : Anglais ( eng) in IEEE transactions on energy conversion > Vol. 23 N°1 (Mars 2008) . - pp. 294 - 301
Mots-clés : |
Decoding encoding evolutionary computation hydrothermal power systems particle swarm optimisation pumped-storage stations scheduling |
Résumé : |
This paper presents new solution algorithms based on an evolutionary particle swarm optimization (EPSO) for solving the pumped-storage (P/S) scheduling problem. The proposed EPSO approach combines a basic particle swarm optimization (PSO) with binary encoding/decoding techniques as well as a mutation operation. The binary encoding/decoding techniques are adopted to model the discrete characteristics of a P/S plant. The mutation operation is applied to accelerate convergence and escape local optimums. The optimal generation schedules for both P/S and thermal units are concurrently obtained within the evolutionary process of a scoring function. Therefore, hydrothermal iteration is no longer needed. The proposed approach is applied with great success to an actual utility system consisting of four P/S units and 34 thermal units. Experimental results indicate the attractive properties of the EPSO approach in a practical application, namely, a highly optimal solution and robust convergence behavior. |
En ligne : |
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4453979&sortType%3Das [...] |
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