DocumentCode :
666056
Title :
Generation expansion planning considering integrating large-scale wind generation
Author :
Chunyu Zhang ; Yi Ding ; Ostergaard, Jacob ; Qiuwei Wu
Author_Institution :
Center for Electr. Power & Energy, Tech. Univ. of Denmark, Copenhagen, Denmark
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
2051
Lastpage :
2056
Abstract :
Generation expansion planning (GEP) is the problem of finding the optimal strategy to plan the construction of new generation while satisfying technical and economical constraints. In the deregulated and competitive environment, large-scale integration of wind generation (WG) in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. A bi-level generation expansion planning approach considering large-scale wind generation was proposed in this paper. The first phase is investment decision, while the second phase is production optimization decision. A multi-objective PSO (MOPSO) algorithm was introduced to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of the proposed bi-level planning approach and the MOPSO algorithm have been verified by a numerical test system.
Keywords :
convergence of numerical methods; investment; particle swarm optimisation; power generation economics; power generation planning; wind power plants; GEP; MOPSO algorithm; Pareto-optimal front set convergence; Pareto-optimal front set diversity; bi-Ievel generation expansion planning approach; investment decision; large-scale wind generation integration; multiobjective PSO algorithm; numerical test system; power system investment planning; production optimization decision; Annealing; Planning; Generation expansion planning; Multi-objective PSO algorithm; large-scale wind generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6699447
Filename :
6699447
Link To Document :
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