| Titre : | Pumped-storage scheduling using evolutionary particle swarm optimization (2008) |
| Auteurs : | Po-Hung Chen, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | IEEE transactions on energy conversion (Vol. 23 N°1, Mars 2008) |
| Article en page(s) : | pp. 294 - 301 |
| Note générale : | Energy conversion |
| Langues : | Anglais |
| Tags : | 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%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A4453975%29%26pageNumber%3D2 |
