Title :
Unit commitment of power systems integrated with wind farms based on cost-benefit analysis
Author :
Liudong Zhang ; Minghui Yin ; Kunlong Song ; Yun Zou
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
The traditional deterministic unit commitment cannot adequately address the safe and economic operation of power systems with large-scale volatile and uncontrollable wind power integration. By combining an uncertainty analysis of wind power based on confidence interval and cost-benefit analysis in economics, an improved unit commitment model considering the uncertainty risk of wind power predictions is proposed to appropriately apply wind power predictions into unit commitment. Cost-benefit analysis is utilized in the proposed model to obtain a single objective function consisting of the generation cost of units and loss-of-load risk of power systems. The proposed model remedies the defects of the existing models where the selection of confidence interval is not given, and realizes a scheduling decision compromising the economic efficiency and the risk of wind power. Using mixed integer linear programming method, simulation studies on the IEEE 26-generator reliability test system connected to a wind farm are presented to verify the effectiveness and advantage of the proposed model.
Keywords :
cost-benefit analysis; power generation economics; power generation scheduling; wind power plants; confidence interval; cost-benefit analysis; economic efficiency; loss-of-load risk; mixed integer linear programming method; power systems; scheduling decision; unit commitment; wind farms; wind power predictions; wind power risk; Analytical models; Generators; Linear programming; Predictive models; Reliability; Wind forecasting; Wind power generation; Confidence Interval; Cost-Benefit Analysis; Mixed Integer Linear Programming; Unit Commitment; Wind Power Forecast Uncertainty;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161780