Optimal selection and sizing of hybrid energy storage systems for wind power dispatching

Document Type : Original Article


1 School of Electrical and Computer Engineering, College of Engineering, University of Tehran,Tehran, Iran

2 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran


Wind power uncertainty is one of the problems in large-scale wind farms integration to the network. The use of Energy Storage Systems (ESSs) is a practical solution to enhance availability and power dispatching possibility of renewable energy sources (RESs). RESs need an ESS with high power and energy capacity while none of ESSs has this feature at the same time. The accepted solution for this problem is using the hybrid energy storage system (HESS). In this paper, HESS optimal sizing and power dispatching of wind-HESS system are considered, simultaneously, and the problem of high storage capacity in the modified min-max wind power dispatching method is resolved by utilizing the limited min-max wind power dispatching method. The optimal types and capacity of HESS are determined based on multi-objective optimization function with objectives of maximizing the net present value and storage lifetime. Furthermore, in short-term power management control, the wind-HESS performance and delivering the prescheduled and constant power to the network are investigated and HESS charge-discharge cycles are controlled to work in safety range. Finally, the proposed method and short-term power management are evaluated by a wind farm real data, which is scaled down to 3 MW power level for better comparison with other studies.


Main Subjects

1. C.A. Sepulveda Rangel, L. Canha, M. Sperandio, R. Severiano,
“Methodology for ESS-type selection and optimal energy management
in distribution system with DG considering reverse flow limitations and
cost penalties,” IET Generation, Transmission and Distribution, vol. 12,
no. 5, pp. 1164-1170, 2018.
2. F. Islam, A. Al-Durra, S. M. Muyeen, “Smoothing of wind farm output
by prediction and supervisory-control-unit-based FESS,” IEEE Trans.
Sustainable Energy, vol. 4, no. 4, pp. 925-933, 2013.
3. M.R. Jannesar, A. Sedighi, M. Savaghebi, A. Anvari-Moghadam, J.
M. Guerrero, “Optimal multi-objective integration of photovoltaic, wind
turbine, and battery energy storage in distribution networks,” Journal of
Energy Management and Technology, vol. 4, no. 4, pp. 76-83, 2020.
4. M. McPherson, S. Tahseen, “Deploying storage assets to facilitate
variable renewable energy integration: The impacts of grid flexibility,
renewable penetration, and market structure,” Energy, vol. 145, pp.
856-870, 2018.
5. D.L. Yao, S.S. Choi, K.J. Tseng, T.T. Lie, “A statistical approach to the
design of a dispatchable wind power-battery ESS,” IEEE Trans. Energy
Conversation, vol. 24, no. 4, pp. 916–925, 2009.
6. A. Kargarian, G. Hug, “Optimal sizing of energy storage systems: a
combination of hourly and intra-hour time perspectives,” IET Generation,
Transmission and Distribution, vol. 10, no. 3, pp. 594-600, 2016.
7. Sh. Sharma, S. Bhattacharjee, A. Bhattacharya, “Swine Influenza
model based optimization for operation management of micro-grid,” In
EESCO, Jan. 2015, Visakhapatnam, India , pp. 1-6.
8. X. Zhang, S. Ch. Tan, G. Li, J. Li, Zh. Feng, “Components sizing of hybrid energy systems via the optimization of power dispatch simulations,”
Energy, vol. 52, pp. 165-172, Apr. 2013.
9. M. Gitizadeh, H. Fakharzadegan, “Battery capacity determination with
respect to optimized energy dispatch schedule in grid-connected photovoltaic (PV) systems,” Energy, vol. 65, pp. 665-674, 2014.
10. L. Liang, L. Jianlin, H. Dong, “An optimal energy storage capacity
calculation method for 100 MW wind farm,” In POWERCON, Oct. 2010,
Hangzhou, China, pp. 1-4.
11. S. Teleke, M. Baran, S. Bhattacharya, A.Q. Huang, “Optimal control of
battery energy storage for wind farm dispatching,” IEEE Trans. Energy
Conversation, vol. 25, no. 3, pp. 787–794, 2010.
12. Q. Li, S.S. Choi, Y. Yuan, D.L. Yao, “On the determination of battery
energy storage capacity and short-term power dispatch of a wind farm,”
IEEE Trans. Sustainable Energy, vol. 2, no. 2, pp. 148–158, 2011.
13. C.L. Nguyen, H.H. Lee, T.W. Chun, “Cost optimized battery capacity
and short term power dispatch control for wind farm,” IEEE Trans.
Industry Applications, vol. 51, no. 1, pp. 595-606, 2015.
14. C.L. Nguyen, H.H. Lee, “A comparative analysis among power dispatching control strategies for hybrid wind and energy storage system,”
In 20th International Conference on Electrical Engineering, Jun. 2014,
Jeju, Korea, pp. 489-494.
15. C.L. Nguyen, T.W. Chun, H.H. Lee, “Determination of the optimal
battery capacity based on a life time cost function in wind farm,” IEEE
Energy Conversion Congress and Exposition, pp. 51–58, 2013.
16. M. Khosravi, S. Afsharnia, Sh. Farhangi, “Optimal sizing and technology
selection of hybrid energy storage system with novel dispatching power
for wind power integration,” International Journal of Electrical Power
and Energy Systems, vol. 127, May 2021, 106660.
17. X.Y. Wang, D.V. Mahinda, S.S. Choi, “Determination of battery storage
capacity in energy buffer for wind farm,” IEEE Trans. Energy Conversation, vol. 23, no. 3, pp. 868–878, 2008.
18. A. Berrada, Kh. Loudiyi, I. Zorkani, “Profitability, risk, and financial
modeling of energy storage in residential and large scale applications,”
Energy, vol. 119, pp. 94-109, 2017.
19. H. Ding, Z. Hu, Y. Song, “rolling optimization of wind farm and ESS
in electricity markets,” IEEE Trans. Power Systems, vol. 30, no. 5, pp.
2676–2684, 2015.
20. B. Zhao, X. Zhang, J. Chen, C. Wang, “Operation optimization of
standalone microgrids considering lifetime characteristics of BESS,”
IEEE Trans. Sustainable Energy, vol. 4, no. 4, pp. 934-943, 2013.
21. M. Moradzadeh, J.V. de Vyver, L. Vandevelde, “Optimal energy storage
sizing based on wind curtailment reduction,” In ICRERA, Oct. 2014,
Milwakuee, USA, pp. 331-335.
22. M. Daghi, M. Sedghi, A. Ahmadian, M. Aliakbar-Golkar, “Factor analysis based optimal storage planning in active distribution network considering different battery technologies,” Applied Energy, vol. 183, pp.
456–469, 2016.
23. D.O. Akinyele, R.K. Rayudu, “Review of energy storage technologies for
sustainable power networks,” Sustainable Energy Technology Assess.,
vol. 8, pp. 74–91, 2014.
24. B. Zakeri, S. Syri, “Electrical energy storage systems: A comparative
life cycle cost analysis,” Renewable Sustainable Energy Review, vol.
42, pp. 569–596, 2015.
25. M. Jannati, S.H. Hosseinian, B. Vahidi, G.J. Li, “ADALINE (ADAptive
Linear Neuron)-based coordinated control for wind power fluctuation
smoothing with reduced BESS (Battery Energy Storage System) capacity,” Energy, vol. 101, pp. 1-8, 2016.
26. Wind power Data [Online]. Available: https://www.ceps.cz/en/all-dataGenerationRES.
27. Z. Wang, A. Negash, D.S. Kirschen, “Optimal scheduling of energy
storage under forecast uncertainties,” IET Generation, Transmission
and Distribution, vol. 11, no. 17, pp. 4220-4226, 2017.
28. P.C. Butler, Ph. A. Eidler, P.G. Grimes, S.E. Klassen, R.C. Miles,
“Zinc/Bromine batteries,” Sandia National Laboratories (SNL), California, 2000 [Online]: www.sandia.gov/ess/publications/SAND2000-
29. M. Dadkhaha, M.J. Rezaee, A.Z. Chavoshi, “Short-term power output
forecasting of hourly operation in power plant based on climate factors
and effects of wind direction and wind speed,” Energy, vol. 148, pp.
775-788, 2018.
30. F. Dıaz-Gonzalez, F.D. Bianchi, A. Sumper, O.G. Bellmunt, “Control of
a flywheel energy storage system for power smoothing in wind power
plants,” IEEE Trans. Energy Conversation, vol. 29, no. 1, pp. 204-214,
Volume 5, Issue 4
December 2021
Pages 19-28
  • Receive Date: 08 December 2020
  • Revise Date: 18 February 2021
  • Accept Date: 18 February 2021
  • First Publish Date: 18 February 2021