DOI QR코드

DOI QR Code

Optimal ESS Investment Strategies for Energy Arbitrage by Market Structures and Participants

  • Lee, Ho Chul ;
  • Kim, Hyeongig ;
  • Yoon, Yong Tae
  • Received : 2017.05.15
  • Accepted : 2017.08.09
  • Published : 2018.01.01

Abstract

Despite the advantages of energy arbitrage using energy storage systems (ESSs), the high cost of ESSs has not attracted storage owners for the arbitrage. However, as the costs of ESS have decreased and the price volatility of the electricity market has increased, many studies have been conducted on energy arbitrage using ESSs. In this study, the existing two-period model is modified in consideration of the ESS cost and risk-free contracts. Optimal investment strategies that maximize the sum of external effects caused by price changes and arbitrage profits are formulated by market participants. The optimal amounts of ESS investment for three types of investors in three different market structures are determined with game theory, and strategies in the form of the mixed-complementarity problem are solved by using the PATH solver of GAMS. Results show that when all market participants can participate in investment simultaneously, only customers invest in ESSs, which means that customers can obtain market power by operating their ESSs. Attracting other types of ESS investors, such as merchant storage owners and producers, to mitigate market power can be achieved by increasing risk-free contracts.

Keywords

Energy arbitrage;Energy storage system;Investment strategy;Nash equilibrium;Social welfare

References

  1. J. G. Kassakian, R. Schmalensee, G. Desgroseilliers, T. D. Heidel, K. Afridi, A. Farid, ..., and I. Perez- Arriaga, The future of the electric grid, Cambridge, MA:MIT, 2011, pp.143-167.
  2. Pierluigi Siano, "Demand response and smart grids - A survey," Renewable and Sustainable Energy Reviews, vol. 30, pp. 461-478, Nov. 2014. https://doi.org/10.1016/j.rser.2013.10.022
  3. Q. Qdr, "Benefits of demand response in electricity markets and recommendations for achieving them," US department of energy, Feb. 2006.
  4. Lee Tsung-Ying, "Operating schedule of battery energy storage system in a time-of-use rate industrial user with wind turbine generators: a multipass iteration particle swarm optimization approach," IEEE Trans. Energy Conversion, vol. 22, no. 3, pp. 774-782, Sep. 2007. https://doi.org/10.1109/TEC.2006.878239
  5. H. Kim, J. H. Heo, J. Y. Park, and Y. T. Yoon, "Impact of Battery Energy Storage System Operation Strategy on Power System: An Urban Railway Load Case under a Time-of-Use Tariff," Energies, vol. 10, no. 1, Jan. 2017.
  6. W. F. Su, S. J. Huang, and C. E. Lin, "Economic analysis for demand-side hybrid photovoltaic and battery energy storage system," IEEE Trans. Industry Applications, vol. 37, no. 1, pp. 171-177, Jan./Feb. 2001. https://doi.org/10.1109/28.903143
  7. R. Sioshansi, P. Denholm, T. Jenkin, and J. Weiss, "Estimating the value of electricity storage in PJM: Arbitrage and some welfare effects," Energy economics, vol. 31, no. 2, pp. 269-277, Mar. 2009. https://doi.org/10.1016/j.eneco.2008.10.005
  8. K. Bradbury, L. Pratson, and D. Patino-Echeverri, "Economic viability of energy storage systems based on price arbitrage potential in real-time US electricity markets," Applied Energy, vol. 114, pp. 512-519, Feb. 2014. https://doi.org/10.1016/j.apenergy.2013.10.010
  9. F. C. Figueiredo, P. C. Flynn, and E. A. Cabral, "The economics of energy storage in 14 deregulated power markets," Energy Studies Review, vol. 14, no. 2, pp. 131-152, 2006.
  10. R. Sioshansi, "Welfare impacts of electricity storage and the implications of ownership structure," The Energy Journal, vol. 31, no. 2, pp. 173-198, 2010.
  11. N. Gast, J. Y. L. Boudec, A. Proutiere, and D. C. Tomozei, "Impact of storage on the efficiency and prices in real-time electricity markets," in Proceedings of the fourth international conference on Future energy systems, Berkeley, USA, Jan. 2013.
  12. K. Bradbury, L. Pratson, and D. Patino-Echeverri, "Economic viability of energy storage systems based on price arbitrage potential in real-time US electricity markets," Applied Energy, vol. 114, pp. 512-519, Feb. 2014. https://doi.org/10.1016/j.apenergy.2013.10.010
  13. S. P. Dirkse, and M. C. Ferris, "The path solver: a nommonotone stabilization scheme for mixed complementarity problems," Optimization Methods and Software, vol. 5, no. 2, pp. 123-156, 1995. https://doi.org/10.1080/10556789508805606
  14. M. C. Ferris, and T. S. Munson, "Complementarity problems in GAMS and the PATH solver," Journal of Economic Dynamics and Control, vol. 24, no. 2, pp. 165-188, Feb. 2000. https://doi.org/10.1016/S0165-1889(98)00092-X

Acknowledgement

Supported by : Seoul National University Electric Power Research Institute