Advertisement

Robust Optimization-Based Energy Procurement

  • Mahdi Mir
  • Noradin GhadimiEmail author
  • Oveis Abedinia
  • Sayed Ahmad Reza Shokrani
Chapter

Abstract

In this chapter, the robust optimization approach (ROA), which is one of the most popular uncertainty modeling methods, is used to solve the power procurement problem of a large consumer under the power price uncertainty considering 30% variation in the price. In contrast to stochastic optimization, ROA is rather a deterministic and set-based method. In addition, the robust optimization method investigates the effect of an uncertain parameter on the optimal result, which aims to reduce the sensitivity of the optimal result to the uncertain parameter. To solve the problem, the standard MILP formulation of proposed model based on deterministic formulation is provided and solved under CLPX solver in GAMS optimization program. The comparing obtained results with the deterministic case show that by increasing the power price in the pool market, the large consumer seeks to procure its required demand using other sources as self-generating units, which makes the consumer robust against the price volatility of the market.

Keywords

Robust optimization approach Uncertainty modeling Pool price uncertainty Risk-averse strategy Large consumer power procurement 

References

  1. 1.
    H.A. Bagal, Y.N. Soltanabad, M. Dadjuo, K. Wakil, N. Ghadimi, Risk-assessment of photovoltaic-wind-battery-grid based large industrial consumer using information gap decision theory. Sol. Energy 169, 343–352 (2018)CrossRefGoogle Scholar
  2. 2.
    N. Ghadimi, A new hybrid algorithm based on optimal fuzzy controller in multimachine power system. Complexity 21(1), 78–93 (2015)MathSciNetCrossRefGoogle Scholar
  3. 3.
    D. Bertsimas, M. Sim, The price of robustness. Oper. Res. 52(1), 35–53 (2004)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    D. Bertsimas, D.B. Brown, C. Caramanis, Theory and applications of robust optimization. SIAM Rev. 53(3), 464–501 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  5. 5.
    S. Nojavan, B. Mohammadi-Ivatloo, K. Zare, Robust optimization based price-taker retailer bidding strategy under pool market price uncertainty. Int. J. Electr. Power Energy Syst. 73, 955–963 (2015)CrossRefGoogle Scholar
  6. 6.
    I. Ahmadian, O. Abedinia, N. Ghadimi, Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization. Front. Energy 8(4), 412–425 (2014)CrossRefGoogle Scholar
  7. 7.
    Z. Haider, H. Charkhgard, C. Kwon, A robust optimization approach for solving problems in conservation planning. Ecol. Model. 368, 288–297 (2018)CrossRefGoogle Scholar
  8. 8.
    A. Noruzi, T. Banki, O. Abedinia, N. Ghadimi, A new method for probabilistic assessments in power systems, combining Monte Carlo and stochastic-algebraic methods. Complexity 21(2), 100–110 (2015)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Y. Zhang, J. Tang, A robust optimization approach for itinerary planning with deadline. Transp. Res. E Logist. Transp. Rev. 113, 56–74 (2018)CrossRefGoogle Scholar
  10. 10.
    R.M. Lima, A.Q. Novais, A.J. Conejo, Weekly self-scheduling, forward contracting, and pool involvement for an electricity producer. An adaptive robust optimization approach. Eur. J. Oper. Res. 240(2), 457–475 (2015)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Z. Geng, A.J. Conejo, Q. Chen, C. Kang, Power generation scheduling considering stochastic emission limits. Int. J. Electr. Power Energy Syst. 95, 374–383 (2018)CrossRefGoogle Scholar
  12. 12.
    S. Nojavan, H. Allah Aalami, Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program. Energy Convers. Manag. 103, 1008–1018 (2015)CrossRefGoogle Scholar
  13. 13.
    N. Sayyad, B. Mohammadi-Ivatloo, K. Zare, Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties. IET Gener. Transm. Distrib. 9(4), 328–338 (2015)CrossRefGoogle Scholar
  14. 14.
    A.J. Conejo, M. Carrión, J.M. Morales, Decision Making Under Uncertainty in Electricity Markets, vol 153 (Springer, Boston, 2010)zbMATHGoogle Scholar
  15. 15.
    A. Najafi-Ghalelou, S. Nojavan, K. Zare, Heating and power hub models for robust performance of smart building using information gap decision theory. Int. J. Electr. Power Energy Syst. 98, 23–35 (2018)CrossRefGoogle Scholar
  16. 16.
    R. Wang, P. Wang, G. Xiao, A robust optimization approach for energy generation scheduling in microgrids. Energy Convers. Manag. 106, 597–607 (2015)CrossRefGoogle Scholar
  17. 17.
    Y. Zhang, N. Gatsis, G.B. Giannakis, Robust energy management for microgrids with high-penetration renewables. IEEE Trans. Sustain. Energy 4(4), 944–953 (2013)CrossRefGoogle Scholar
  18. 18.
    W. Wu, J. Chen, B. Zhang, H. Sun, A robust wind power optimization method for look-ahead power dispatch. IEEE Trans. Sustain. Energy 5(2), 507–515 (2014)CrossRefGoogle Scholar
  19. 19.
    E. Craparo, M. Karatas, D.I. Singham, A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts. Appl. Energy 201, 135–147 (2017)CrossRefGoogle Scholar
  20. 20.
    L. Baringo, A.J. Conejo, Offering strategy via robust optimization. IEEE Trans. Power Syst. 26(3), 1418–1425 (2011)CrossRefGoogle Scholar
  21. 21.
    M. Rahimiyan, L. Baringo, Strategic bidding for a virtual power plant in the day-ahead and real-time markets: a price-taker robust optimization approach. IEEE Trans. Power Syst. 31(4), 2676–2687 (2016)CrossRefGoogle Scholar
  22. 22.
    S. Nojavan, K. Zare, B. Mohammadi-Ivatloo, Robust bidding and offering strategies of electricity retailer under multi-tariff pricing. Energy Econ. 68, 359–372 (2017)CrossRefGoogle Scholar
  23. 23.
    R. Jiang, J. Wang, Y. Guan, Robust unit commitment with wind power and pumped storage hydro. IEEE Trans. Power Syst. 27(2), 800–810 (2012)CrossRefGoogle Scholar
  24. 24.
    P. Xiong, P. Jirutitijaroen, C. Singh, A distributionally robust optimization model for unit commitment considering uncertain wind power generation. IEEE Trans. Power Syst. 32(1), 39–49 (2017)CrossRefGoogle Scholar
  25. 25.
    A. Street, F. Oliveira, J.M. Arroyo, Contingency-constrained unit commitment with $n - K$ security criterion: a robust optimization approach. IEEE Trans. Power Syst. 26(3), 1581–1590 (2011)CrossRefGoogle Scholar
  26. 26.
    H. Ye, Y. Ge, M. Shahidehpour, Z. Li, Uncertainty marginal price, transmission reserve, and day-ahead market clearing with robust unit commitment. IEEE Trans. Power Syst. 32(3), 1782–1795 (2017)CrossRefGoogle Scholar
  27. 27.
    C. Wang, B. Jiao, L. Guo, Z. Tian, J. Niu, S. Li, Robust scheduling of building energy system under uncertainty. Appl. Energy 167, 366–376 (2016)CrossRefGoogle Scholar
  28. 28.
    M. Mazidi, H. Monsef, P. Siano, Robust day-ahead scheduling of smart distribution networks considering demand response programs. Appl. Energy 178, 929–942 (2016)CrossRefGoogle Scholar
  29. 29.
    R.A. Jabr, Robust transmission network expansion planning with uncertain renewable generation and loads. IEEE Trans. Power Syst. 28(4), 4558–4567 (2013)CrossRefGoogle Scholar
  30. 30.
    H. Yu, C.Y. Chung, K.P. Wong, Robust transmission network expansion planning method with Taguchi’s orthogonal array testing. IEEE Trans. Power Syst. 26(3), 1573–1580 (2011)CrossRefGoogle Scholar
  31. 31.
    CPLEX 12. [Online]. Available: https://www.gams.com/latest/docs/S_CPLEX.html. Accessed 15 Jul 2018
  32. 32.
    A. Brooke, D. Kendrick, A. Meeraus, R. Raman, R.E. Rosenthal, GAMS A User’s Guide Introduction 1 (GAMS Development Corporation, Washington, DC, 1998)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mahdi Mir
    • 1
  • Noradin Ghadimi
    • 2
    Email author
  • Oveis Abedinia
    • 3
  • Sayed Ahmad Reza Shokrani
    • 4
  1. 1.Department of Electrical EngineeringFerdowsi University of MashhadMashhadIran
  2. 2.Young Researchers and Elite Club, Ardabil BranchIslamic Azad UniversityArdabilIran
  3. 3.Department of Electrical EngineeringBudapest University of Technology and EconomicsBudapestHungary
  4. 4.Department of Industrial Management, Faculty of ManagementUniversity of TehranTehranIran

Personalised recommendations