Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

Optimal Energy Shift Scheduling Algorithm for Energy Storage Considering Efficiency Model

  • Cho, Sung-Min (Energy New Business Laboratory, KEPCO Research Institute)
  • Received : 2017.09.13
  • Accepted : 2018.06.16
  • Published : 2018.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

Energy shifting is an innovative method used to obtain the highest profit from the operation of energy storage systems (ESS) by controlling the charge and discharge schedules according to the electricity prices in a given period. Therefore, in this study, we propose an optimal charge and discharge scheduling method that performs energy shift operations derived from an ESS efficiency model. The efficiency model reflects the construction of power conversion systems (PCSs) and lithium battery systems (LBSs) according to the rated discharge time of a MWh-scale ESS. The PCS model was based on measurement data from a real system, whereas for the LBS, we used a circuit model that is appropriate for the MWh scale. In addition, this paper presents the application of a genetic algorithm to obtain the optimal charge and discharge schedules. This development represents a novel evolutionary computation method and aims to find an optimal solution that does not modify the total energy volume for the scheduling process. This optimal charge and discharge scheduling method was verified by various case studies, while the model was used to realize a higher profit than that realized using other scheduling methods.

Keywords

References

  1. A. A. Akhil, G. Huff, A. B. Currier, B. C. Kaun, D. M. Rastler, and others, "DOE/EPRI Electricity Storage Handbook," no. February, 2015.
  2. H. Kim, J., Choi, Y., Ryu, S., and Kim, "Robust Operation of Energy Storage System with Uncertain Load Profiles," Energies, vol. 10, no. 4, p. 416, 2017. https://doi.org/10.3390/en10040416
  3. P.-I. Jeong, Mu-Gu; Moon, Seung-Il; Hwang, "Indirect Load Control for Energy Storage Systems Using Incentive Pricing under Time-of-Use Tariff - Semantic Scholar," 2016.
  4. K. Rahbar, C. C. Chai, and R. Zhang, "Energy Cooperation Optimization in Microgrids with Renewable Energy Integration," IEEE Transactions on Smart Grid, vol. 3053, no. c, pp. 1-1, 2016.
  5. K. Rahbar, J. Xu, and R. Zhang, "Real-time energy storage management for renewable integration in microgrid: An off-line optimization approach," IEEE Transactions on Smart Grid, vol. 6, no. 1, pp. 124-134, 2015. https://doi.org/10.1109/TSG.2014.2359004
  6. K. M. Chandy, S. H. Low, U. Topcu, X. Huan, and Huan Xu, "A simple optimal power flow model with energy storage," Decision and Control (CDC), 2010 49th IEEE Conference on, pp. 1051-1057, 2010.
  7. I. Koutsopoulos, V. Hatzi, and L. Tassiulas, "Optimal energy storage control policies for the smart power grid," Smart Grid Communications 2011 IEEE International Conference on, pp. 475-480, 2011.
  8. D. Gayme and U. Topcu, "Optimal power flow with distributed energy storage dynamics," American Control Conference (ACC), 2011, pp. 1536-1542, 2011.
  9. E. Samadani, S. Farhad, W. Scott, M. Mastali, L. E. Gimenez, and others, "Empirical modeling of lithiumion batteries based on electrochemical impedance spectroscopy tests," Electrochimica Acta, vol. 160, pp. 169-177, 2015. https://doi.org/10.1016/j.electacta.2015.02.021
  10. V. Agarwal, K. Uthaichana, R. A. Decarlo, and L. H. Tsoukalas, "Development and validation of a battery model useful for discharging and charging power control and lifetime estimation," IEEE Transactions on Energy Conversion, vol. 25, no. 3, pp. 821-835, 2010. https://doi.org/10.1109/TEC.2010.2043106
  11. X. Hu, F. Sun, and Y. Zou, "Estimation of state of charge of a Lithium-Ion battery pack for electric vehicles using an adaptive luenberger observer," Energies, vol. 3, no. 9, pp. 1586-1603, 2010. https://doi.org/10.3390/en3091586
  12. Z. Chen, B. Xia, C. C. Mi, and R. Xiong, "Loss-Minimization-Based Charging Strategy for Lithium-Ion Battery," IEEE Transactions on Industry Applications, vol. 51, no. 5, pp. 4121-4129, 2015. https://doi.org/10.1109/TIA.2015.2417118
  13. K. Li and K. J. Tseng, "Energy efficiency of lithiumion battery used as energy storage devices in microgrid," IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, pp. 5235-5240, 2015.
  14. X. Tang, X. Mao, J. Lin, and B. Koch, "Li-ion battery parameter estimation for state of charge," American Control Conference (ACC), 2011, pp. 941-946, 2011.
  15. S. Lemofouet and A. Rufer, "A Hybrid Energy Storage System Based on Compressed Air and Supercapacitors With Maximum Efficiency Point Tracking (MEPT)," IEEE Transactions on Industrial Electronics, vol. 53, no. 4, pp. 1105-1115, 2006. https://doi.org/10.1109/TIE.2006.878323
  16. J. Kim, "Fuzzy Logic-Controlled Online State-of-Health (SOH) Prediction in Large Format $LiMn_2O_4$ Cell for Energy Storage System (ESS) Applications," 2014 Ieee International Conference on Industrial Technology (Icit), pp. 474-479, 2014.
  17. S.-M. Cho, H.-S. Shin, J.-H. Park, and J.-C. Kim, "Distribution System Reconfiguration Considering Customer and DG Reliability Cost," Journal of Electrical Engineering and Technology, vol. 7, no. 4, pp. 486-492, Jul. 2012. https://doi.org/10.5370/JEET.2012.7.4.486