Synthetic wind speed scenarios including diurnal effects: Implications for wind power dimensioning

Energy

Volumn 37, Issue 1, 2012, Pages 41-50

  Suomalainen, K ^a   Silva, C A ^a   Ferrao P ^a   Connors, S ^b  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Isolated energy systems; Surplus wind power; Wind resource variability

Indexed keywords

INVESTMENTS; MARKOV PROCESSES; QUALITY CONTROL; WIND EFFECTS;

AUTO REGRESSIVE MODELS; DESIGN INFORMATION; DIURNAL PATTERN; DIURNAL WIND; ENERGY SYSTEM DESIGN; ENERGY SYSTEM MODELLING; ENERGY SYSTEMS; FUTURE ENERGIES; GENERATION INVESTMENT; HIGH WINDS; LOW FREQUENCY; MARKOV MODEL; PORTUGAL; SEASONAL DIFFERENCES; SMALL ENERGY; TEMPORAL SCALE; WIND GENERATION; WIND RESOURCES; WIND SPEED; WIND SPEED DATA;

WIND POWER;

DIURNAL VARIATION; ENERGY EFFICIENCY; FREQUENCY ANALYSIS; MAGNITUDE; NUMERICAL MODEL; RENEWABLE RESOURCE; TEMPORAL ANALYSIS; WIND POWER; WIND VELOCITY;

AZORES; PORTUGAL;

EID: 84855591185     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2011.08.001     Document Type: Article

References (21)

1. Billington R., Chen H., Ghajar R. Asequential simulation technique for adequacy evaluation of generating systems including wind energy. IEEE Transactions on Energy Conversion 1996, 11(4):728-734.
2. Castro Sayas F., Allan R.N. Generation availability assessment of wind farms. IEEE Proceedings - Generation, Transmission and Distribution 1996, 143(5):507-518.
3. Castellanos F., Ramesar V.I. Characterization and estimation of wind energy resources using autoregressive modelling and probability density functions. Wind Engineering 2006, 30(1):1-14.
4. MPP, Green Islands Project, Azores, MIT-Portugal Program and the University of the Azores, http://www.green-islands-azores.uac.pt.
5. Suomalainen K, Silva C, Connors S, Ferrão P. Wind speed dynamics in scenario generation for energy systems modelling. Proceedings of 23rd International Conference on Efficiency, Cost, Optimization & Environmental Impact of Energy Systems, June 14-17 2010, Lausanne, Switzerland, Editors: Daniel Favrat and François Maréchal, 2011;2:327-34.
6. Beyer H.G., Nottebaum K. Synthesis of long-term hourly wind speed time series on the basis of the European wind atlas data. Solar Energy 1995, 54(5):351-355.
7. Chang T.J., Tu Y.L. Evaluation of monthly capacity factor of wecs using chronological and probabilistic wind speed data: a case study of Taiwan. Renewable Energy 2007, 32:1999-2010.
8. Elmore A.C., Gallagher R. Using regional climate center data to predict small wind turbine performance. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management January 2009, 14-19.
9. Gallagher R., Elmore A.C. Monte Carlo simulations of wind speed data. Wind Engineering 2009, 33(6):661-673.
10. Kennedy Scott, Rogers Peter Aprobabilistic model for simulating long-term wind-power output. Wind Engineering 2003, 27(3):167-181.
11. Kirchhoff R.H., Kaminsky F.C., Syi C.Y. Synthetic of wind speed using a Markov process. Proceedings of the Eight ASME Wind Energy Symposium Jan. 1989, 17-22.
12. Sahin A.D., Sen Z. First-order Markov chain approach to wind speed modelling. Journal of Wind Engineering and Industrial Aerodynamics 2001, 89:263-269.
13. Nfaoui H., Essiarab H., Sayigh A.A.M. Astochastic Markov chain model for simulating wind speed time series at Tangiers, Morocco. Renewable Energy 2004, 29:1407-1418.
14. Shamshad A., Bawadi M.A., Wan Hussin W.M.A., Majid T.A., Sanusi S.A.M. First and second order Markov chain models for synthetic generation of wind speed time series. Energy 2005, 30:693-708.
15. Kaminsky F.C., Kirchhoff R.H., Syi C.Y., Manwell J.F. Acomparison of alternative approaches for the synthetic generation of a wind speed time series. Journal of Solar Energy Engineering 1991, 113:280-289.
16. Hocaoĝlu F.O., Gerek O.N., Kurban M. The effect of Markov chain state size for synthetic wind speed generation. Proceedings of the 10th International Conference on Probabilistic Methods Applied to Power Systems, 2008. PMAPS '08 2009, 1-4.
17. Negra N.B., Holmström O. Model of a synthetic wind speed time series generator. Wind Energy 2008, 11:193-209.
18. Donatelli M., Bellocchi G., Habyarimana E., Confaloniere R., Micale F. An extensive model library for generating wind speed data. Computers and Electronics in Agriculture 2009, 69:165-170.
19. Burton T., Sharpe D., Jenkins N., Bossanyi E. Wind Energy Handbook 2001, John Wiley & Sons, Ltd., Chichester, England. 2nd ed.
20. Enercon wind energy converters, product overview, [accessed June, 2011]. http://www.enercon.de/en-en/62.htm.
21. Dudhia J., Gill D., Manning K., Wang W., Bruvere C. PSU/NCAR Mesoscale Modeling System Tutorial Class Notes and User's Guide: MM5 Modeling System Version 3 2005, Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research.