A multi-objective stochastic tri-level programming for highlighting the role of the pumped-storage power plant on electric grid defense budget

Document Type : Original Article


Imam hossein university


This paper attempted to highlight the impact of a pumped-storage hydro plant on the electricity grid defense budget, which is spent to increase the power system resilience against terrorist attacks. A stochastic tri-level programming approach known as the defender-attacker-defender technique was applied to detect the defense plan by considering the pumped-storage hydro plant. The stochastic parameter was related to the water volume of the upper reservoir during the disruptive attack. In the stochastic tri-level programming model, the upper level was formulated to identify the components that should be defended for mitigating the system vulnerability against disruptive agent attacks. A terrorist agent seeks to find a set of components for maximizing power system damage. Therefore, the middle level was used to model the disruptive behavior. Finally, the lower level modeled the system operator behavior during the attack. The system operator generally applied flexible sources such as storage to reduce the effects of the attack. Thus, the role of the pump-storage hydro plant was evident at this level. The proposed tri-level problem was solved by transforming it into an equivalent bi-level program, which was solved by using an enumeration algorithm. Simulation results illustrate the effectiveness of the pump-storage hydro plant in reducing the power system defender budget


Main Subjects

1. Watson, D., Rebello, E., Kii, N., Fincker, T., Rodgers, M. “Demand and
energy avoidance by a 2 MWh energy storage system in a 10 MW wind
farm,” Journal of Energy Storage, vol. 20, pp. 371-379,2018.
2. Robert, Fabien Chidanand, Gyanendra Singh Sisodia, and Sundararaman Gopalan. "A critical review on the utilization of storage and demand
response for the implementation of renewable energy microgrids." Sustainable cities and society vol. 40 , PP: 735-745, 2018.
3. Kusakana, Kanzumba. "Optimal operation scheduling of grid-connected
PV with ground pumped hydro storage system for cost reduction in
small farming activities." Journal of Energy Storage vol.16, PP. 133-138,
4. Ta¸scıkaraoglu, Akın. "Economic and operational benefits of energy ˘
storage sharing for a neighborhood of prosumers in a dynamic pricing
environment." Sustainable cities and society vol. 38,PP. 219-229,2018.
5. Madadi, S., B. Mohammadi-Ivatloo, and S. Tohidi. "Decentralized optimal multi-area generation scheduling considering renewable resources
mix and dynamic tie line rating." Journal of cleaner production vol.
223,PP. 883-896, 2019.
6. Tan, Xiao-fei, et al. "Biochar as potential sustainable precursors for
activated carbon production: multiple applications in environmental
protection and energy storage." Bioresource technology vol.227, pp.
359-372, 2017.
7. Nazari-Heris, Morteza, et al. "Optimal stochastic scheduling of virtual
power plant considering NaS battery storage and combined heat and
power units." Journal of Energy Management and Technology vol.2,
no.3,pp.1-7, 2018.
8. Jadidbonab, Mohammad, Sajad Madadi, and Behnam Mohammadiivatloo. "Hybrid Strategy for Optimal Scheduling of Renewable Integrated Energy Hub Based on Stochastic/Robust Approach." Journal of
Energy Management and Technology vol.2, no.4, pp.29-38, 2018.
9. Karimi, Ali, et al. "Scheduling and value of pumped storage hydropower
plant in Iran power grid based on fuel-saving in thermal units." Journal
of Energy Storage vol.24.pp.100753, 2019.
10. Jiang, Ruiwei, Jianhui Wang, and Yongpei Guan. "Robust unit commitment with wind power and pumped storage hydro." IEEE Transactions
on Power Systems vol.27, no.2, pp.800-810, 2011.
11. Khodayar, Mohammad E., Lisias Abreu, and Mohammad Shahidehpour. "Transmission-constrained intrahour coordination of wind and
pumped-storage hydro units." IET Generation, Transmission & Distribution vol.7.no.7,pp.755-765, 2013.
12. Khodayar, Mohammad E., Mohammad Shahidehpour, and Lei Wu. "Enhancing the dispatchability of variable wind generation by coordination
with pumped-storage hydro units in stochastic power systems." IEEE
Transactions on Power Systems vol.28, no.3, pp.2808-2818, 2013.
13. Li, Jinghua, et al. "A coordinated dispatch method with pumped-storage
and battery-storage for compensating the variation of wind power."
Protection and control of modern power Systems vol.3, no.1 pp.2,
14. Brijs, Tom, et al. "Evaluating the role of electricity storage by considering
short-term operation in long-term planning." Sustainable Energy, Grids
and Networks vol.10, pp.104-117, 2017.
15. Vieira, Bruno, et al. "A multiple criteria utility-based approach for unit
commitment with wind power and pumped storage hydro." Electric
Power Systems Research vol.131,pp.244-254, 2016.
16. Kiran, B. Durga Hari, and M. Sailaja Kumari. "Demand response and
pumped hydro storage scheduling for balancing wind power uncertainties: A probabilistic unit commitment approach." International Journal
of Electrical Power & Energy Systems vol.81, pp.114-122, 2016.
17. Cheng, Chun-Tian, et al. "Short-term peak shaving operation for multiple power grids with pumped storage power plants." International
Journal of Electrical Power & Energy Systems vol.67, pp. 570-581,
18. Petrakopoulou, Fontina, Alexander Robinson, and Maria Loizidou. "Simulation and analysis of a stand-alone solar-wind and pumped-storage
hydropower plant." Energy vol.96, pp. 676-683, 2016.
19. Fernández-Muñoz, Daniel, and Juan I. Pérez-Díaz. "Contribution of
non-conventional pumped-storage hydropower plant configurations
in an isolated power system with an increasing share of renewable
energy." IET Renewable Power Generation vol.14, no.4 , pp. 658-670,
20. J. Salmeron, K. Wood, and R. Baldick, “Analysis of electric grid security
under terrorist threat,” IEEE Transactions on Power Systems, vol. 19,
no. 2, pp. 905-912, 2004.
21. J. Salmeron, K. Wood, and R. Baldick, “Worst-case interdiction analysis of large-scale electric power grids,” IEEE Transactions on Power
Systems, vol. 24, no. 1, pp. 96-104, 2009.
22. G. Brown, M. Carlyle, J. Salmerón, and K. Wood, “Defending critical
infrastructure,” Interfaces, vol. 36, no. 6, pp. 530-544, 2006.
23. V. M. Bier, E. R. Gratz, N. J. Haphuriwat, W. Magua, and K. R.
Wierzbicki, “Methodology for identifying near-optimal interdiction strategies for a power transmission system,” Reliability Engineering and
System Safety, vol. 92, pp. 1155-1161, 2007.
24. A. J. Holmgren, E. Jenelius, and J. Westin, “Evaluating strategies for
defending electric power networks against antagonistic attacks,” IEEE
Transactions on Power Systems, vol. 22, no. 1, pp. 76-84, 2007.
25. Wu, Xuan, and Antonio J. Conejo. "An efficient tri-level optimization
model for electric grid defense planning." IEEE Transactions on Power
Systems vol.32.no.4, pp. 2984-2994, 2016.
26. H. Nemati, M. A. Latify and G. R. Yousefi, "Optimal Coordinated Expansion Planning of Transmission and Electrical Energy Storage Systems
Under Physical Intentional Attacks," in IEEE Systems Journal, vol. 14,
no. 1, pp. 793-802, 2020.
27. C. Wang et al., "Robust Defense Strategy for Gas–Electric Systems
Against Malicious Attacks," in IEEE Transactions on Power Systems,
vol. 32, no. 4, pp. 2953-2965,2017.
28. Brown, Gerald, et al. "Defending critical infrastructure." Interfaces
vol.36, no.6, pp.530-544, 2006.
29. Alguacil, Natalia, Andrés Delgadillo, and José M. Arroyo. "A trilevel
programming approach for electric grid defense planning." Computers
& Operations Research vol.41pp.282-290, 2014.
30. Alvarez, Rogelio E. Interdicting electrical power grids. NAVAL POSTGRADUATE SCHOOL MONTEREY CA, 2004.
31. Ordoudis, Christos, et al. "An Updated Version of the IEEE RTS 24-Bus
System for Electricity Market and Power System Operation Studies."
32. Nazari-Heris, Morteza, Sajad Madadi, and Behnam MohammadiIvatloo. "Optimal management of hydrothermal-based micro-grids employing robust optimization method." Classical and recent aspects of
power system optimization. Academic Press, pp.407-420,2018..
  • Receive Date: 09 August 2020
  • Revise Date: 05 October 2020
  • Accept Date: 10 October 2020
  • First Publish Date: 19 October 2020