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Robust allocation of reserves considering different reserve types and the flexibility from HVDC

Robust allocation of reserves considering different reserve types and the flexibility from HVDC

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Since the production of electric power from renewable resources is intrinsically variable and uncertain, it creates difficulties in balancing demand and generation. On the one hand, the ensemble of dispatchable resources is being required to provide larger and more frequent ramping capabilities. On the other hand, the transmission grid is operated closer to its limits on a more frequent basis. These two factors require a reassessment of the techniques used to provide and ensure the deliverability of reserves and flexibility. In this study the authors present an adjustable robust approach for the procurement of reserve, as well as for the repartition of this reserve between manual and policy-based automatic reserves. This approach takes into consideration the location and temporal evolution of the uncertainty on the generation sources and the flexibility offered by high voltage direct current (HVDC) interconnections. The resulting problem is solved iteratively. Case studies compare policy and non-policy based reserves, the allocation of ramping capacity and the resulting operational cost.

References

    1. 1)
      • 1. Dvorkin, Y., Kirschen, D., Ortega-Vazquez, M.: ‘Assessing flexibility requirements in power systems’, IET Gener. Transm. Distrib., 2014, 8, pp. 18201830(10). Available at: http://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2013.0720.
    2. 2)
      • 2. Wood, A., Wollenberg, B.: ‘Power generation, operation and control’ (Wiley, New York, 1996).
    3. 3)
      • 3. UCTE OpHB-Team: ‘UCTE Operation Handbook Policy 1: Load-Frequency Control and Performance’, 2009.
    4. 4)
      • 4. Ela, E., Milligan, M., Kirby, B.: ‘Operating reserves and variable generation’. Technical Report, NREL, 08 2011.
    5. 5)
      • 5. Lin, X., Tretheway, D.: ‘Flexible ramping products’. Technical Report, CAISO, 12 2014.
    6. 6)
      • 6. Al-Abdullah, Y., Abdi-Khorsand, M., Hedman, K.: ‘The role of out-of-market corrections in day-ahead scheduling’, IEEE Trans. Power Syst., 2015, 30, (4), pp. 19371946.
    7. 7)
      • 7. Doorman, G., Jaehnert, S.: ‘Reservation of transmission capacity for the exchange of regulating resources in Northern Europe: Is there a benefit?Energy Economy, Policies and Supply Security: Surviving the Global Economic Crisis. IAEE, 2010, first publication by IAEE in the 11th IAEE European Conf. Proc..
    8. 8)
      • 8. Farahmand, H., Hosseini, S., Doorman, G., et al: ‘Flow based activation of reserves in the nordic power system’. Power and Energy Society General Meeting, 2010 IEEE, 2010, pp. 18.
    9. 9)
      • 9. Morales, J., Conejo, A., Perez-Ruiz, J.: ‘Economic valuation of reserves in power systems with high penetration of wind power’, IEEE Trans. Power Syst., 2009, 24, (2), pp. 900910.
    10. 10)
      • 10. Ortega-Vazquez, M., Kirschen, D.: ‘Estimating the spinning reserve requirements in systems with significant wind power generation penetration’, IEEE Trans. Power Syst., 2009, 24, (1), pp. 114124.
    11. 11)
      • 11. Pandzic, H., Dvorkin, Y., Qiu, T., et al: ‘Toward cost-efficient and reliable unit commitment under uncertainty’, IEEE Trans. Power Syst., 2016, 31, (2), pp. 970982.
    12. 12)
      • 12. Jiang, R., Wang, J., Guan, Y.: ‘Robust unit commitment with wind power and pumped storage hydro’, IEEE Trans. Power Syst., 2012, 27, (2), pp. 800810.
    13. 13)
      • 13. Zhao, C., Wang, J., Watson, J.-P., et al: ‘Multi-stage robust unit commitment considering wind and demand response uncertainties’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 27082717.
    14. 14)
      • 14. Zhao, C., Guan, Y.: ‘Unified stochastic and robust unit commitment’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 33533361.
    15. 15)
      • 15. Lee, C., Liu, C., Mehrotra, S., et al: ‘Modeling transmission line constraints in two-stage robust unit commitment problem’, IEEE Trans. Power Syst., 2014, 29, (3), pp. 12211231.
    16. 16)
      • 16. An, Y., Zeng, B.: ‘Exploring the modeling capacity of two-stage robust optimization: Variants of robust unit commitment model’, IEEE Trans. Power Syst., 2015, 30, (1), pp. 109122.
    17. 17)
      • 17. Wei, W., Liu, F., Mei, S., et al: ‘Robust energy and reserve dispatch under variable renewable generation’, IEEE Trans. Smart Grid, 2015, 6, (1), pp. 369380.
    18. 18)
      • 18. Ye, H., Li, Z.: ‘Robust security-constrained unit commitment and dispatch with recourse cost requirement’, IEEE Trans. Power Syst., 2015, PP, (99), pp. 110.
    19. 19)
      • 19. Bertsimas, D., Litvinov, E., Sun, X., et al: ‘Adaptive robust optimization for the security constrained unit commitment problem’, IEEE Trans. Power Syst., 2013, 28, (1), pp. 5263.
    20. 20)
      • 20. Hu, B., Wu, L., Marwali, M.: ‘On the robust solution to scuc with load and wind uncertainty correlations’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 29522964.
    21. 21)
      • 21. Zhao, J., Zheng, T., Litvinov, E.: ‘Variable resource dispatch through do-not-exceed limit’, IEEE Trans. Power Syst., 2015, 30, (2), pp. 820828.
    22. 22)
      • 22. Mohan, V., Singh, J.G., Ongsakul, W.: ‘An efficient two stage stochastic optimal energy and reserve management in a microgrid’, Appl. Energy, 2015, 160, pp. 2838.
    23. 23)
      • 23. Jiang, R., Wang, J., Zhang, M., et al: ‘Two-stage minimax regret robust unit commitment’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 22712282.
    24. 24)
      • 24. Li, Z., Wu, W., Zhang, B., et al: ‘Adjustable robust real-time power dispatch with large-scale wind power integration’, IEEE Trans. Sustain. Energy, 2015, 6, (2), pp. 357368.
    25. 25)
      • 25. Wang, Q., Watson, J.-P., Guan, Y.: ‘Two-stage robust optimization for n-k contingency-constrained unit commitment’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 23662375.
    26. 26)
      • 26. Dvorkin, Y., Fernandez-Blanco, R., Ortega-Vazquez, M.: ‘Probabilistic security-constrained unit commitment with generation and transmission contingencies’, IEEE Trans. Power Syst., 2017, 32, (1), pp. 228239.
    27. 27)
      • 27. Warrington, J., Goulart, P., Mariethoz, S., et al: ‘Policy-based reserves for power systems’, IEEE Trans. Power Syst., 2013, 28, (4), pp. 44274437.
    28. 28)
      • 28. Vrakopoulou, M., Margellos, K., Lygeros, J., et al: ‘Probabilistic guarantees for the N − 1 security of systems with wind power generation’. Proc. of Probabilistic Methods Applied to Power Systems Conf., 2012.
    29. 29)
      • 29. Margellos, K., Haring, T., Hohayem, P., et al: ‘A robust reserve scheduling technique for power systems with high wind penetration’. Int. Conf. on Probabilistic Methods Applied to Power Systems, 2012.
    30. 30)
      • 30. Bucher, M., Andersson, G.: ‘Balancing reserve procurement and operation in the presence of uncertainty and transmission limits’. Power Engineering Conf. (UPEC), 2013 48th Int. Universities’, September 2013, pp. 16.
    31. 31)
      • 31. Bucher, M., Wiget, R., Perez, G.-B., et al: ‘Optimal placement of multi-terminal hvdc interconnections for increased operational flexibility’. Innovative Smart Grid Technologies Conf. Europe (ISGT-Europe), 2014 IEEE PES, October 2014, pp. 16.
    32. 32)
      • 32. Wiget, R., Vrakopoulou, M., Andersson, G.: ‘Probabilistic security constrained optimal power flow for a mixed hvac and hvdc grid with stochastic infeed’. Power Systems Computation Conf. (PSCC), 2014, August 2014, pp. 17.
    33. 33)
      • 33. Rebours, Y., Kirschen, D., Trotignon, M., et al: ‘A survey of frequency and voltage control ancillary services - part i: Technical features’, IEEE Trans. Power Syst., 2007, 22, (1), pp. 350357.
    34. 34)
      • 34. Rebours, Y., Kirschen, D., Trotignon, M., et al: ‘A survey of frequency and voltage control ancillary services - part ii: Economic features’, IEEE Trans. Power Syst., 2007, 22, (1), pp. 358366.
    35. 35)
      • 35. Wiget, R., Andersson, G.: ‘DC optimal power flow including HVDC grids’. Electrical Power Energy Conf. (EPEC), 2013 IEEE, August 2013, pp. 16.
    36. 36)
      • 36. Zeng, B., Zhao, L.: ‘Solving two-stage robust optimization problems using a column-and-constraint generation method’, Oper. Res. Lett., 2013, 41, (5), pp. 457461. Available at http://www.sciencedirect.com/science/article/pii/S0167637713000618=0pt.
    37. 37)
      • 37. Bucher, M.A.: ‘On operational flexibility in transmission constrained electric power systems’. Ph.D. dissertation, ETH Zurich, 2016.
    38. 38)
      • 38. Platbrood, L., Capitanescu, F., Merckx, C., et al: ‘A generic approach for solving nonlinear-discrete security-constrained optimal power flow problems in large-scale systems’, IEEE Trans. Power Syst., 2014, 29, (3), pp. 11941203.
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