Title :
A PSO algorithm for economic scheduling of power system incorporating wind based generation
Author :
Benhamida, F. ; Salhi, Y. ; Souag, S. ; Graa, A. ; Ramdani, Y. ; Bendaoud, Abdelber
Author_Institution :
Dept. of Electrotechnics, UDL Univ. of Sidi Bel Abbes, Sidi Bel Abbes, Algeria
Abstract :
This paper presents a solution of economic scheduling incorporation wind based generation (WBG) using a particle swarm optimization algorithm (PSO). The effect of inclusion of wind-based generation (WBG) on economic load dispatch scheduling is investigated, while the WBG speed is subjected to short duration variations around a stable mean value. Analytical formulation of the economic load dispatch (ELD) problem including of WBG is presented. The short time duration wind speed variations effect is included as a static amount of power and not as stochastic models. The PSO algorithm is simple in concept, easy in implementation. PSO algorithm does not require any derivative information, sure and fast convergence, moreover; PSO needs less computational time compared to other heuristic methods. These features increase the applicability of the PSO, particularly in power system applications. A 20-unit test system is resolved using PSO to illustrate the variation in the optimal cost, losses, and system-λ with the variation of stable mean wind speed.
Keywords :
load dispatching; particle swarm optimisation; power generation scheduling; power system economics; wind power plants; 20 unit test system; ELD problem; PSO algorithm; WBG; economic load dispatch scheduling; economic scheduling incorporation; heuristic methods; particle swarm optimization; power system applications; short duration variations; stable mean value; wind based generation; wind speed variations effect; Biological system modeling; Cost function; Economics; Power systems; Propagation losses; Wind power generation; Wind speed; economic dispatch problem; particle swarm optimization; renewable energy; wind energy; wind power generation;
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2013 5th International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5812-5
DOI :
10.1109/ICMSAO.2013.6552630