Storage technology is a key enabler for the integration of renewable energy resources into power systems because it provides the required flexibility to balance, the net load variability and forms a buffer for uncertainties. A solution for sizing of energy storage devices in electric power systems is presented. The considered planning problem is divided into two time perspectives: hourly and intra-hour intervals. For the intra-hour time horizon, the algorithm determines the optimal size of the energy storage devices to provide the adequate ramping capability for the system. This ramping capability guarantees the system ability to follow the load in the intra-hour intervals, as well as to alleviate short-term wind generation and load fluctuations. In the hourly time scale, the optimal size of the storage is determined with respect to having a sufficient generation capacity to support the loads. A 6-bus test power system is studied to show the effectiveness of the proposed algorithm.

References

1. 1)
  - 13. Abedi, S., Alimardani, A., Gharehpetian, G., Riahy, G., Hosseinian, S.: ‘A comprehensive method for optimal power management and design of hybrid res-based autonomous energy systems’, Renew. Sustain. Energy Rev., 2012, 16, pp. 1577–1587 (doi: 10.1016/j.rser.2011.11.030).
2. 2)
  - 9. Mohammadi, S., Mozafari, B., Solymani, S., Niknam, T.: ‘Stochastic scenario-based model and investigating size of energy storages for pem-fuel cell unit commitment of micro-grid considering profitable strategies’, IET Gener. Transm. Distrib., 2014, 8, (7), pp. 1228–1243 (doi: 10.1049/iet-gtd.2013.0026).
3. 3)
  - 4. Ernst, B., Oakleaf, B., Ahlstrom, M., et al: ‘Predicting the wind’, IEEE Power Energy Mag., 2007, 5, (6), pp. 78–89 (doi: 10.1109/MPE.2007.906306).
4. 4)
  - 8. Chakraborty, S., Senjyu, T., Toyama, H., Saber, A., Funabashi, T.: ‘Determination methodology for optimising the energy storage size for power system’, IET Gener. Transm. Distrib., 2009, 3, (11), pp. 987–999 (doi: 10.1049/iet-gtd.2008.0300).
5. 5)
  - 15. Yang, P., Nehorai, A.: ‘Joint optimization of hybrid energy storage and generation capacity with renewable energy’, IEEE Trans. Smart Grid, 2014, 5, (4), pp. 1566–1574 (doi: 10.1109/TSG.2014.2313724).
6. 6)
  - 20. CaliforniaISO, Integration of Renewable Resources: Technical Appendices for California ISO Renewable Integration Studies Version 1. Available at: http://www.caiso.com/282d/282d85c9391b0.pdf.
7. 7)
  - 1. Mai, T., Wiser, R., Sandor, D., et al.: ‘Exploration of high-penetration renewable electricity futures’. Tech. Rep., National Renewable Energy Lab., 2012.
8. 8)
  - 18. Cardell, J., Anderson, C.: ‘A flexible dispatch margin for wind integration’, IEEE Trans. Power Syst., 2015, 30, (3), pp. 1501–1510 (doi: 10.1109/TPWRS.2014.2337662).
9. 9)
  - 19. Negnevitsky, M., Nguyen, D., Piekutowski, M.: ‘Risk assessment for power system operation planning with high wind power penetration’, IEEE Transactions on Power Systems, 2015, 30, (3), pp. 1359–1368 (doi: 10.1109/TPWRS.2014.2339358).
10. 10)
  - 22. Ernst, B., Wan, Y., Kirby, B.: ‘Short-term power fluctuation of wind turbines: looking at data from the German 250-mw measurement program from the ancillary services viewpoint, windpower’. Windpower 99 Conf., American Wind Energy Association, 1999.
11. 11)
  - 12. Awad, A., EL-Fouly, T., Salama, M.: ‘Optimal ess allocation for load management application’, IEEE Trans. Power Syst., 2015, 30, (1), pp. 327–336 (doi: 10.1109/TPWRS.2014.2326044).
12. 12)
  - 14. Zheng, Y., Dong, Z., Luo, F., Meng, K., Qiu, J., Wong, K.: ‘Optimal allocation of energy storage system for risk mitigation of discos with high renewable penetrations’, IEEE Trans. Power Syst., 2014, 29, (1), pp. 212–220 (doi: 10.1109/TPWRS.2013.2278850).
13. 13)
  - 2. Stiebler, M.: ‘Wind energy systems for electric power generation’ (Springer, 2008).
14. 14)
  - 11. Wen, S., Lan, H., Fu, Q., Yu, D., Zhang, L.: ‘Economic allocation for energy storage system considering wind power distribution’, IEEE Trans. Power Syst., 2015, 30, (2), pp. 644–652 (doi: 10.1109/TPWRS.2014.2337936).
15. 15)
  - 7. Khodayar, M., Shahidehpour, M., Wu, L.: ‘Enhancing the dispatchability of variable wind generation by coordination with pumped-storage hydro units in stochastic power systems’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 2808–2818 (doi: 10.1109/TPWRS.2013.2242099).
16. 16)
  - 24. Löfberg, J.: ‘Yalmip: a toolbox for modeling and optimization in matlab’. Proc. of the CACSD Conf., Taipei, Taiwan, 2004, pp. 284–289.
17. 17)
  - 16. Zhang, F., Hu, Z., Song, Y.: ‘Stochastic scenario-based model and investigating size of energy storages for pem-fuel cell unit commitment of micro-grid considering profitable strategies’, IET Gener. Transm. Distrib., 2013, 7, (8), pp. 919–928 (doi: 10.1049/iet-gtd.2012.0666).
18. 18)
  - 10. Ghofrani, M., Arabali, A., Etezadi-Amoli, M., Fadali, M.: ‘Energy storage application for performance enhancement of wind integration’, IEEE Trans. Power Syst., 2013, 28, (4), pp. 4803–4811 (doi: 10.1109/TPWRS.2013.2274076).
19. 19)
  - 3. Kargarian, A., Raoofat, M.: ‘Stochastic reactive power market with volatility of wind power considering voltage security’, Energy, 2011, 36, (5), pp. 2565–2571 (doi: 10.1016/j.energy.2011.01.051).
20. 20)
  - 6. ‘http://www.sandia.gov/ess/’.
21. 21)
  - 5. Banakar, H., Luo, C., Ooi, B.T.: ‘Impacts of wind power minute-to-minute variations on power system operation’, IEEE Trans. Power Syst., 2008, 23, (1), pp. 150–160 (doi: 10.1109/TPWRS.2007.913298).
22. 22)
  - 17. Bahramirad, S., Reder, W., Khodaei, A.: ‘Reliability-constrained optimal sizing of energy storage system in a microgrid’, IEEE Trans. Smart Grid, 2012, 3, (4), pp. 2056–2062 (doi: 10.1109/TSG.2012.2217991).
23. 23)
  - 21. Makarov, Y., Loutan, C., Ma, J., Mello, P.: ‘Operational impacts of wind generation on California power systems’, IEEE Trans. Power Syst., 2009, 24, (2), pp. 1039–1050 (doi: 10.1109/TPWRS.2009.2016364).
24. 24)
  - 23. EPRI: ‘Electricity energy storage technology options: a white paper primer on applications, costs, and benefits’. Tech. Rep., EPRI, Palo Alto, CA, USA, 2010.

Optimal sizing of energy storage systems: a combination of hourly and intra-hour time perspectives

References

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