Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
1. R. H. Lasseter and P. Paigi, “ Microgrid: A conceptual solution,” in IEEE 35th Annual Power Electronics Specialists Conference, 2004 (PESC 04), 2004, Vol. 6, pp. 42854290.
2. G. Venkataramanan and C. Marnay, “ A larger role for microgrids,” IEEE Power Energy Mag. 6, 7882 (2008).
3. J. P. Barton and D. G. Infield, “ Energy storage and its use with intermittent renewable energy,” IEEE Trans. Energy Convers. 19, 441448 (2004).
4. X. Wang, D. Mahinda Vilathgamuwa, and S. Choi, “ Determination of battery storage capacity in energy buffer for wind farm,” IEEE Trans. Energy Convers. 23, 868878 (2008).
5. C. L. T. Borges, “ An overview of reliability models and methods for distribution systems with renewable energy distributed generation,” Renewable Sustainable Energy Rev. 16, 40084015 (2012).
6. J. Li, W. Wei, and J. Xiang, “ A simple sizing algorithm for stand-alone pv/wind/battery hybrid microgrids,” Energies 5, 53075323 (2012).
7. C. W. Tan, T. C. Green, and C. A. Hernandez-Aramburo, “ A stochastic method for battery sizing with uninterruptible-power and demand shift capabilities in PV (photovoltaic) systems,” Energy 35, 50825092 (2010).
8. P. Hu, R. Karki, and R. Billinton, “ Reliability evaluation of generating systems containing wind power and energy storage,” IET Gener. Transm. Distrib. 3, 783791 (2009).
9. R. Karki, P. Hu, and R. Billinton, “ A simplified wind power generation model for reliability evaluation,” IEEE Trans. Energy Convers. 21, 533540 (2006).
10. R. Billinton and Bagen, “ Generating capacity adequacy evaluation of small stand-alone power systems containing solar energy,” Reliab. Eng. Syst. Saf. 91, 438443 (2006).
11. R. Billinton, Bagen, and Y. Cui, “ Reliability evaluation of small stand-alone wind energy conversion systems using a time series simulation model,” IEE Proc. Gener. Transm. Distrib. 150, 96100 (2003).
12. E. K. Hart, E. D. Stoutenburg, and M. Z. Jacobson, “ The potential of intermittent renewables to meet electric power demand: Current methods and emerging analytical techniques,” Proc. IEEE 100, 322334 (2012).
13. Y. Atwa, E. El-Saadany, and A.-C. Guise, “ Supply adequacy assessment of distribution system including wind-based dg during different modes of operation,” IEEE Trans. Power Syst. 25, 7886 (2010).
14. Y. Atwa, E. El-Saadany, M. M. A. Salama, R. Seethapathy, M. Assam, and S. Conti, “ Adequacy evaluation of distribution system including wind/solar dg during different modes of operation,” IEEE Trans. Power Syst. 26, 19451952 (2011).
15. R. S. Weissbach and J. M. Cheers, “ Markov based estimation of energy storage requirements accounting for seasonal variations,” in 2010 IEEE Power and Energy Society General Meeting, 2010, pp. 15.
16. J. Song, M. C. Bozchalui, A. Kwasinski, and R. Sharma, “ Microgrids availability evaluation using a Markov chain energy storage model: a comparison study in system architectures,” in 2012 IEEE PES Transmission and Distribution Conference and Exposition (T&D), 2012, pp. 16.
17. J. Song, V. Krishnamurthy, A. Kwasinski, and R. Sharma, “ Development of a Markov-chain-based energy storage model for power supply availability assessment of photovoltaic generation plants,” IEEE Trans. Sustainable Energy 4, 491500 (2013).
18. S. Piller, M. Perrin, and A. Jossen, “ Methods for state-of-charge determination and their applications,” J. Power Sources 96, 113120 (2001).
19. Z. Yanhui, S. Wenji, L. Shili, F. Ziping et al., “ A critical review on state of charge of batteries,” J. Renewable Sustainable Energy 5, 021403 (2013).
20. A. N. Celik, “ On the distributional parameters used in assessment of the suitability of wind speed probability density functions,” Energy Convers. Manage. 45, 17351747 (2004).
21. P. Tavner, C. Edwards, A. Brinkman, and F. Spinato, “ Influence of wind speed on wind turbine reliability,” Wind Eng. 30, 5572 (2006).
22. D. Villanueva, J. Pazos, and A. Feijoo, “ Probabilistic load flow including wind power generation,” IEEE Trans. Power Syst. 26, 16591667 (2011).
23. A. P. Leite, C. L. Borges, and D. M. Falcao, “ Probabilistic wind farms generation model for reliability studies applied to Brazilian sites,” IEEE Trans. Power Syst. 21, 14931501 (2006).
24. S. Drouilhet, B. L. Johnson et al., “A battery life prediction method for hybrid power applications,” US Department of Energy, Chicago, IL, Contract No. DE-AC36-83CH10093, 1997.

Data & Media loading...


Article metrics loading...



A major drawback of renewable power sources is their fluctuant characteristics. To overcome this drawback, a battery storage system is the prevalent way to smooth the fluctuation of renewable power sources. It is a critical problem whether such a smooth can lead to a constant output power for a renewable generator consisting of renewable power source and the associated battery storage system. This paper provides a probabilistic answer for this problem by making use of Markov Chain method. The obtained results are analytic and their efficacy is verified by a comparison with that the Monte Carlo simulation technique.


Full text loading...


Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd