Journal of Modeling in Engineering

Journal of Modeling in Engineering

Optimal Scheduling of Energy Storage Systems with Private Ownership Based on a Stochastic-Robust Hybrid Optimization Model in Energy and Ancillary Services Markets

Document Type : Research Paper

Authors
Mohammad Farahani 1
Abouzar Samimi 2
Hossein Shateri 2
1 MSc, Department of Electrical Engineering, Arak University of Technology, Arak, Iran
2 Assistant Professor, Department of Electrical Engineering, Arak University of Technology, Arak, Iran
10.22075/jme.2023.26339.2226
Abstract
In this paper, the problem of participation of a Battery Energy Storage (BES) in the Day-Ahead Market (DAM) and Real-Time Market (RTM) in three cases including Joint Energy and Reactive Power Market (JERPM), Energy Market (EM) and Energy and Reserve Market (ERM) is modeled based on a hybrid Stochastic Robust Optimization (SRO) model and it tries to maximize the profit of the BES owner in the face of uncertainty pertaining to the market prices. In the proposed model, in the first step, the decision maker or BES owner predicts energy, reserve and reactive power prices in each market according to historical network information. In the second step, by determining the uncertainty interval of prices for DAM and RTM, robust optimization is implemented aiming at maximizing the profit of the BES owner using a model of forming a robust counterpart of the objective function and dual theory. In the next step, by defining some different scenarios for the robust budget, Stochastic Programming (SP) assigns a probability to each scenario. Then, the final profit of each market is calculated through probabilistic weighting, and finally the market with more profit is opted as considered participation market. The proposed formulation based on the Mixed Integer Nonlinear Programming (MINLP) model is implemented in the GAMS software environment and the results demonstrate the maximum profitability of BES in EM (21% more) and also show participation in providing ancillary services, such as reserve to provide security in incidents and reactive power to maintain stability and reduce cost and losses, despite the decrease in profit, leads to neutralizing the negative impact of uncertainties in the BES profit.
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Keywords
Electricity market
Stochastic-robust hybrid optimization
Energy-storage system
Uncertainty
Ancillary services markets
Subjects
  1. N. Amjady, A. Rabiee, and H.A. Shayanfar. "Pay-as-bid based reactive power market." Energy Conversion and Management51, no. 2 (2010): 376-381.
  2. O. Gandhi, W. Zhang, C.D. Rodríguez-Gallegos, H. Verbois, H. Sun, T. Reindl, and D. Srinivasan. "Local reactive power dispatch optimisation minimising global objectives." Applied energy262 (2020): 114529.
  3. H. Ahmadi, and A. Akbari Foroud. "Improvement of the simultaneous active and reactive power markets pricing and structure." IET Generation, Transmission & Distribution10, no. 1 (2016): 81-92.
  4. K. Afshar, M. Ehsan, M. Fotuhi-Firuzabad, and N. Amjady. "Cost-benefit analysis and MILP for optimal reserve capacity determination in power system." Applied Mathematics and Computation196, no. 2 (2008): 752-761.
  5. M. Shahidehpour, H. Yamin, and Z. Li. Market operations in electric power systems: forecasting, scheduling, and risk management. John Wiley & Sons, 2002.
  6. M. Khaji, M. Amiri, and M.T. Taghavifard. "Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties." Journal of Modeling in Engineering21, no. 75 (2023): 29-51.
  7. A. Ebrahimi, A. Dideban, and R. Keypour. "A novel control strategy for solar-wind hybrid energy systems based on optimal battery charge and discharge limits in various time domain." (2019): 163-173.
  8. J. Aghaei, A. Rahimi Rezaei, and M. Karimi. "Coordination of Wind Power Plants and Energy Storage Devices in Security-Constrained Unit Commitment Problem Using Robust Optimization." Journal of Modeling in Engineering16, no. 53 (2018): 207-220.
  9. S. Maiz, L. Baringo, and R. García-Bertrand. "Expansion planning of a price-maker virtual power plant in energy and reserve markets." Sustainable Energy, Grids and Networks32 (2022): 100832
  10. G. Sun, S. Shen, S. Chen, Y. Zhou, and Z. Wei. "Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets." Renewable Energy191 (2022): 278-290.
  11. R. Khalili, A. Khaledi, M. Marzband, A. Foroughi Nematollahi, B. Vahidi, and P. Siano. "Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs." Applied Energy334 (2023): 120737.
  12. A. Samimi, "Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems." Journal of Modern Power Systems and Clean Energy7, no. 6 (2019): 1596-1607.
  13. M. Kazemi, H. Zareipour, N. Amjady, W.D. Rosehart, and M. Ehsan. "Operation scheduling of battery storage systems in joint energy and ancillary services markets." IEEE Transactions on Sustainable Energy8, no. 4 (2017): 1726-1735.
  14. H. Mehrjerdi, R. Hemmati, and E. Farrokhi. "Nonlinear stochastic modeling for optimal dispatch of distributed energy resources in active distribution grids including reactive power." Simulation Modelling Practice and Theory94 (2019): 1-13.
  15. A. Barbry, M.F. Anjos, E. Delage, and K.R. Schell. "Robust self-scheduling of a price-maker energy storage facility in the New York electricity market." Energy Economics78 (2019): 629-646.
  16. Z. Wang, A. Negash, and D.S. Kirschen. "Optimal scheduling of energy storage under forecast uncertainties." IET Generation, Transmission & Distribution11, no. 17 (2017): 4220-4226.
  17. M. Zugno, Marco, and Antonio J. Conejo. "A robust optimization approach to energy and reserve dispatch in electricity markets." European Journal of Operational Research247, no. 2 (2015): 659-671.
  18. A. Akbari-Dibavar, K. Zare, and S. Nojavan. "A hybrid stochastic-robust optimization approach for energy storage arbitrage in day-ahead and real-time markets." Sustainable Cities and Society49 (2019): 101600.
  19. E. Abedini, and M. Jafari Nokandi. "Clearing for Coordinated Electricity and Gas Markets." Journal of Modeling in Engineering19, no. 64 (2021): 53-66.
  20. N. Amjady, B. Vatani, and H. Sharifzadeh. "OPTIMUM STOCHASTIC SELF-SCHEDULING FOR GENCOS CONSIDERING POOL AUCTION AND BILATERAL CONTRACTS." (2011): 21-29.
  21. A. Hosseini, A. Sadeghi Yazdan, M. Hemmati, and M. Abapour. "Hybrid Robust Stochastic Bidding Strategy for Wind Farms Integrated with Compressed Air Energy Storage and Power to Gas Technology." Journal of Modeling in Engineering19, no. 65 (2021): 137-148.
  22. M. Farahani, A. Samimi, and H. Shateri. "Robust bidding strategy of battery energy storage system (BESS) in joint active and reactive power of day-ahead and real-time markets." Journal of Energy Storage59 (2023): 106520.
  23. H. Mehrjerdi, and R. Hemmati. "Modeling and optimal scheduling of battery energy storage systems in electric power distribution networks." Journal of Cleaner Production234 (2019): 810-821.
  24. A. Zakariazadeh, S. Jadid, and P. Siano. "Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach." Energy Conversion and Management78 (2014): 151-164.
  25. C. Opathella, A. Elkasrawy, A.A. Mohamed, and B. Venkatesh. "Optimal scheduling of merchant-owned energy storage systems with multiple ancillary services." IEEE Open Access Journal of Power and Energy7 (2019): 31-40.
  26. M. Bussieck, J.H. Jagla, and L. Westermann. "GAMs General Algebraic Modeling System." 2010.

 

Journal of Modeling in Engineering
Volume 22, Issue 76
Spring 2024
Pages 1-12

  • Receive Date 21 February 2022
  • Revise Date 22 July 2023
  • Accept Date 20 August 2023