Short-term wind power output forecasting model for economic dispatch of power system incorporating large-scale wind farm

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 30, Issue 13, 2010, Pages 23-27

  Yuan, Tie Jiang ^a   Chao, Qin ^a   Li, Yi Yan ^a   Toerxun, Yibulayin ^a  

^a XINJIANG UNIVERSITY   (China)

Author keywords

Back propagation artificial neural network (BP ANN); Error; Prediction; Short term; Wind power

Indexed keywords

BACKPROPAGATION; COMPUTER SIMULATION; ELECTRIC LOAD FORECASTING; ELECTRIC UTILITIES; FARMS; MATHEMATICAL MODELS; SCHEDULING; WIND POWER;

ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; ECONOMIC DISPATCH; ERROR FORECASTING; ERROR PREDICTION; FORECASTING MODELS; MODIFICATION MODEL; OUTPUT POWER; POWER OUT PUT; POWER SYSTEMS; PREDICTION ACCURACY; PREDICTION ERRORS; PREDICTION MODEL; SIMULATION RESULT; WIND FARM; WIND POWER FORECASTING;

NEURAL NETWORKS;

EID: 77953280101     PISSN: 02588013     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Chao Qin, Josef T, Suonan Jiale, et al. Windhydro-hybrid power system stability analysis and simulation[J]. Acta Technica CSAV, 2005, 50(3): 263-277.
2. Chao Qin, Yuan Hai, Tuerxun. Dynamic simulation for stability of wind power system simulation[J]. Proceedings of the CSEE, 2005, 25(supplement): 277-279(in Chinese).
3. Zheng Guoqiang, Bao Hai, Chen Shuyong. Amending algorithm for wind farm penetration optimization based on approximate linear programming method[J]. Proceedings of the CSEE, 2004, 24(10): 68-71(in Chinese).
4. Chen C L, Lee T Y. Impact analysis of transmission capacity constraints on wind power penetration and production cost in generation dispatch[C]. IEEE International Conference on Intelligent Systems Applications to Power Systems, Taibei, China, 2007.
5. Yuan Tiejiang, Chao Qin, Tuerxun Yibulayin, et al. An environmental/economic dispatch model for power grid containing wind power generation units and its simulation in electricity market environment[J]. Power System Technology, 2009, 33(6): 67-71(in Chinese).
6. Lei Yazhou, Wang Weisheng, Yin Yonghua, et al. An optimization method for determining wind power penetration limit power system under static security constraints[J]. Proceedings of the CSEE, 2001, 21(6): 25-29(in Chinese).
7. Coppin P, Katzfey J. The feasibility of wind power production forecasting in the australian context[R]. Aspendale, Australia: CSIRO Atmospheric Research Centre, 2003.
8. Kariniotakis G. Next generation short-term forecasting of wind power-overview of the anemos project[C]. European Wind Energy Conference, Athens, 2006.
9. Giebel G, Landberg L, Kariniotakis G, et al. State-of-the-art on methods and software tools of short-term prediction of wind energy production[C]. European Wind Energy Conference and Exhibition EWEC, Marid, Spain, 2003.
10. Parkes J, Munoz L, Wasey J, et al. Wind energy trading benefits through short term forecasting[R/OL]. 2009-03[2009-12-20]. http://www.garradhassan.com.
11. Pinson P, Kariniotakis G N. Wind power forecasting using fuzzy neural networks enhanced with on-line prediction risk assessment[C]. IEEE Bologna Power Tech Conference, Bologna, Italy, 2003.
12. Garrad Hassan and Partners Ltd. Forecasting short-term wind farm production[R/OL]. 2009-03[2009-11-30]. http://www.garradhassan.com.
13. Liu Yongqian, Han Shuang, Hu Yongsheng. Review on short term wind power prediction[J]. Modern Electric Power, 2007, 24(5): 5-11(in Chinese).
14. Yang Y P, Han S, Liu Y Q. Genetic algorithm and tabu search based artificial neural networkfor wind speed prediction[C]. The 3rd International Green Energy Conference, Vasteras, Sweden, 2007.
15. Han S, Liu Y Q, Yang Y P. Wind speed predictionmodel of neural network based on tabu search algorithm[C]. The 2nd IEEE Conference on Industrial Electronics and Applications, Harbin, China, 2007.
16. Zhou Shuangxi, Wang Haichao, Chen Shousun. Analysis on operation value of wind power resources[J]. Power System Technology, 2006, 30(14): 99-104(in Chinese).