Title :
Economic scheduling based on multi-objective optimization considering wind output
Author :
Gao, Yajing ; Chang, Peng ; Liang, Haifeng
Author_Institution :
Dept. of Electr. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
As an important renewable energy form, wind power obtains rapid development recently. A more accurate method of wind power prediction and a new multi-objective economic scheduling of power system are required. In this paper, in order to improve the low accuracy of wind power prediction, the EMD-ARMA model is used to predict the wind farm output, then the multi-objective economic scheduling model considering wind output is proposed, and the Particle Swarm Optimization Algorithm is used to optimize the above model. The programming of prediction and optimization is development by MATLAB 2009b, and IEEE standard example is adopted to test the validity of the model and the effectiveness of the algorithm.
Keywords :
particle swarm optimisation; power system economics; wind power; EMD-ARMA model; IEEE standard; MATLAB 2009b; economic scheduling; multiobjective optimization; particle swarm optimization algorithm; renewable energy form; wind output; wind power; Economics; Mathematical model; Optimization; Power systems; Predictive models; Wind forecasting; Wind power generation; ARMA; EMD; Economic Scheduling; Multi-Objective Optimization; prediction;
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
Conference_Location :
Weihai, Shandong
Print_ISBN :
978-1-4577-0364-5
DOI :
10.1109/DRPT.2011.5994115