Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2012, Article ID 784389, 12 pages
http://dx.doi.org/10.1155/2012/784389
Research Article

A Novel Evaluation Model for Hybrid Power System Based on Vague Set and Dempster-Shafer Evidence Theory

1School of Economics and Management, North China Electric Power University, Beijing 102206, China
2School of Industrial Engineering, Tokai University, Kumamoto 862-8652, Japan
3Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway

Received 27 August 2012; Accepted 4 October 2012

Academic Editor: Peng Shi

Copyright © 2012 Dongxiao Niu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. J. Wai and C. Y. Lin, “Active low-frequency ripple control for clean-energy power-conditioning mechanism,” IEEE Transactions on Industrial Electronics, vol. 57, no. 11, pp. 3780–3792, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. P. D. C. Wijayatunga and D. Prasad, “Clean energy technology and regulatory interventions for Greenhouse Gas emission mitigation: Sri Lankan power sector,” Energy Conversion and Management, vol. 50, no. 6, pp. 1595–1603, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Esmin and G. Lambert-Torres, “Application of particle swarm optimization to optimal power systems,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 3A, pp. 1705–1716, 2012. View at Google Scholar
  4. J. Park, T. Oh, K. Cho et al., “Reliability evaluation of interconnected power systems including wind turbine generators,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 8, pp. 5797–5808, 2012. View at Google Scholar
  5. A. Abro and J. Mohamad-Saleh, “Control of power system stability-reviewed solutions based on intelligent systems,” International Journal of Innovative Computing, Information and Control, vol. 8, no. 10A, pp. 6643–6666, 2012. View at Google Scholar
  6. P. Tavner, “Wind power as a clean-energy contributor,” Energy Policy, vol. 36, no. 12, pp. 4397–4400, 2008. View at Publisher · View at Google Scholar · View at Scopus
  7. K. Kaygusuz, “Wind power for a clean and sustainable energy future,” Energy Sources, Part B, vol. 4, no. 1, pp. 122–133, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Nishimura, Y. Hayashi, K. Tanaka et al., “Life cycle assessment and evaluation of energy payback time on high-concentration photovoltaic power generation system,” Applied Energy, vol. 87, no. 9, pp. 2797–2807, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. K. Morison, L. Wang, and P. Kundur, “Power system security assessment,” IEEE Power and Energy Magazine, vol. 2, no. 5, pp. 30–39, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. Y. Wei, D. Niu, and G. Wang, “Comprehensive benefit evaluation of thermal-wind-hydraulic power joint operation based on combined weight,” East China Electric Power, vol. 4, pp. 1–5, 2012. View at Google Scholar
  11. C. He, F. Kai, and Z. Quan, “et al. Investment evaluation system development based on unified information platform for future smart grid,” Energy Procedia, vol. 12, pp. 10–17, 2011. View at Publisher · View at Google Scholar
  12. Y. Jing, H. Bai, and J. Wang, “A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources,” Energy Policy, vol. 42, pp. 286–296, 2012. View at Publisher · View at Google Scholar
  13. S. Hu and L. Wang, “A comprehensive analysis of the cogeneration units to the thermal system transformation,” Energy Procedia, vol. 17, no. B, pp. 1169–1176, 2012. View at Publisher · View at Google Scholar
  14. Q. Sun, X. Ge, L. Liu et al., “Review of smart grid comprehensive assessment systems,” Energy Procedia, vol. 12, pp. 219–229, 2011. View at Publisher · View at Google Scholar
  15. A. Hepbasli, “A key review on exergetic analysis and assessment of renewable energy resources for a sustainable future,” Renewable and Sustainable Energy Reviews, vol. 12, no. 3, pp. 593–661, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. R. Laleman, J. Albrecht, and J. Dewulf, “Life cycle analysis to estimate the environmental impact of residential photovoltaic systems in regions with a low solar irradiation,” Renewable and Sustainable Energy Reviews, vol. 15, no. 1, pp. 267–281, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, Princeton, NJ, USA, 1976. View at Zentralblatt MATH
  18. M. Beynon, D. Cosker, and D. Marshall, “An expert system for multi-criteria decision making using Dempster Shafer theory,” Expert Systems with Applications, vol. 20, no. 4, pp. 357–367, 2001. View at Publisher · View at Google Scholar · View at Scopus
  19. S. Le Hégarat-Mascle, D. Richard, and C. Ottlé, “Multi-scale data fusion using Dempster-Shafer evidence theory,” Integrated Computer-Aided Engineering, vol. 10, no. 1, pp. 9–22, 2003. View at Google Scholar · View at Scopus
  20. V. Kaftandjian, O. Dupuis, D. Babot, and Y. M. Zhu, “Uncertainty modelling using Dempster-Shafer theory for improving detection of weld defects,” Pattern Recognition Letters, vol. 24, no. 1–3, pp. 547–564, 2003. View at Publisher · View at Google Scholar · View at Scopus
  21. S. Fabre, A. Appriou, and X. Briottet, “Presentation and description of two classification methods using data fusion based on sensor management,” Information Fusion, vol. 2, no. 1, pp. 49–71, 2001. View at Publisher · View at Google Scholar · View at Scopus
  22. C. R. Parikh, M. J. Pont, and N. Barrie Jones, “Application of Dempster-Shafer theory in condition monitoring applications: a case study,” Pattern Recognition Letters, vol. 22, no. 6-7, pp. 777–785, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  23. P. Wang, N. Propes, N. Khiripet, Y. Li, and G. Vachtsevanos, “Integrated approach to machine fault diagnosis,” in Proceedings of the IEEE Annual Textile, Fiber and Film Industry Technical Conference, pp. 59–65, Atlanta, Ga, USA, May 1999. View at Scopus
  24. R. W. Jones, A. Lowe, and M. J. Harrison, “A framework for intelligent medical diagnosis using the theory of evidence,” Knowledge-Based Systems, vol. 15, no. 1-2, pp. 77–84, 2002. View at Publisher · View at Google Scholar · View at Scopus
  25. X. Su, P. Shi, L. Wu et al., “A novel approach to filter design for T-S fuzzy discrete-time systems with time-varyingdelay,” IEEE Transactions on Fuzzy Systems. In press. View at Publisher · View at Google Scholar
  26. Q. Zhou, P. Shi, J. Lu et al., “Adaptive output feedback fuzzy tracking control for a class of nonlinear systems,” IEEE Transactions on Fuzzy Systems, vol. 19, no. 5, pp. 972–982, 2011. View at Publisher · View at Google Scholar
  27. L. Wu, X. Su, P. Shi, and J. Qiu, “Model approximation for discrete-time state-delay systems in the TS fuzzy framework,” IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, pp. 366–378, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. L. Wu, X. Su, P. Shi, and J. Qiu, “A new approach to stability analysis and stabilization of discrete-time T-S fuzzy time-varying delay systems,” IEEE Transactions on Systems, Man, and Cybernetics B, vol. 41, no. 1, pp. 273–286, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. J. Zhang, P. Shi, and Y. Xia, “Robust adaptive sliding-mode control for fuzzy systems with mismatched uncertainties,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 4, pp. 700–711, 2010. View at Publisher · View at Google Scholar · View at Scopus
  30. S. K. Nguang, P. Shi, and S. Ding, “Fault detection for uncertain fuzzy systems: an LMI approach,” IEEE Transactions on Fuzzy Systems, vol. 15, no. 6, pp. 1251–1262, 2007. View at Publisher · View at Google Scholar · View at Scopus
  31. W. L. Gau and D. J. Buehrer, “Vague sets,” IEEE Transactions on Systems, Man and Cybernetics, vol. 23, no. 2, pp. 610–614, 1993. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  32. X. Geng, X. Chu, and Z. Zhang, “A new integrated design concept evaluation approach based on vague sets,” Expert Systems with Applications, vol. 37, no. 9, pp. 6629–6638, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. D. Zhang, J. Zhang, K. K. Lai, and Y. Lu, “An novel approach to supplier selection based on vague sets group decision,” Expert Systems with Applications, vol. 36, no. 5, pp. 9557–9563, 2009. View at Publisher · View at Google Scholar · View at Scopus
  34. S. Wan, “Applying interval-value vague set for multi-sensor target recognition,” International Journal of Innovative Computing, Information and Control, vol. 7, no. 2, pp. 955–963, 2011. View at Google Scholar · View at Scopus