access icon free Flexibility of controllable power transformers for managing wind uncertainty using robust adjustable linearised optimal power flow

© The Institution of Engineering and Technology
Received 19/04/2018, Accepted 23/10/2018, Revised 12/08/2018, Published 23/10/2018

As renewable energy sources (RESs) penetration increases in the power system, the transmission system operators face new challenges to ensure system reliability and flexibility while ensuring high utilisation of uncertain RES generation. Controllable transformers with on-load tap changers and phase shifting capability are the promising flexibility tools to keep the system acceptable security and flexibility levels by controlling the voltage levels and energy flow. The AC optimal power flow (AC OPF) with detailed modelling considerations such as the bus voltage magnitude by including these devices is challenging. This study develops the AC OPF model to propose a robust flexibility optimisation framework for daily scheduling problem with uncertain wind energy sources. Nevertheless, the proposed formulation representation is an intractable mixed integer nonlinear programming (MINLP) while it includes AC grid constraints and the augmented modelling of the mentioned transformers. Accordingly, the proposed MINLP problem has been converted into a mixed-integer linear program where a certain level of solution accuracy can be achieved for the available time budget. The effectiveness of the proposed method is demonstrated using a modified 6-bus and IEEE 118-bus test systems.

Inspec keywords: power system security; optimal control; on load tap changers; nonlinear programming; power control; wind power; power generation reliability; voltage control; power grids; robust control; wind power plants; integer programming; load flow control; power generation control; power generation scheduling

Other keywords: on-load tap changers; energy flow control; uncertain wind energy sources; MINLP problem; modified 6-bus test system; transmission system operators; robust flexibility optimisation framework; AC optimal power flow model; voltage level control; intractable mixed integer nonlinear programming; AC OPF model; uncertain RES generation; renewable energy sources penetration; AC grid constraints; modified IEEE 118-bus test system; phase shifting capability; system reliability; bus voltage magnitude; system acceptable security level; daily scheduling problem; controllable power transformers; wind uncertainty management; system acceptable flexibility level; robust adjustable linearised optimal power flow; power system; system flexibility

Subjects: Reliability; Optimisation techniques; Optimisation techniques; Control of electric power systems; Voltage control; Power system control; Transformers and reactors; Energy resources; Wind power plants; Power and energy control; Power system protection; Stability in control theory; Optimal control

References

    1. 1)
      • 26. Alliance for Sustainable Energy, Department of Energy (DOE), Nat. Renew. Renewable Energy Lab. (NREL): ‘System advisor model version 2014.1.14’.
    2. 2)
      • 5. Ohtsuki, H., Yokoyama, A., Sekine, Y.: ‘Reverse action of on-load tap changer in association with voltage collapse’, IEEE Trans. Power Syst., 1991, 6, (1), pp. 300–306.
    3. 3)
      • 24. Nikoobakht, A., Aghaei, J.: ‘IGDT-based robust optimal utilization of wind power generation using coordinated flexibility resources’, IET Renew. Power Gener., 2017, 11, (2), pp. 264–277.
    4. 4)
      • 4. Imhof, K., Oesch, F., Nordanlycke, I.: ‘Modelling of tap-changer transformers in an energy management system’, IEEE Trans. Power Syst., 1996, 11, (1), pp. 428–434.
    5. 5)
      • 10. Aghaei, J., Nikoobakht, A., Siano, P., et al: ‘Exploring the reliability effects on the short term AC security-constrained unit commitment: a stochastic evaluation’, Energy, 2016, 114, pp. 1016–1032.
    6. 6)
      • 27. Nikoobakht, A., Mardaneh, M., Aghaei, J., et al: ‘Flexible power system operation accommodating uncertain wind power generation using transmission topology control: an improved linearised AC SCUC model’, IET Gener. Transm. Distrib., 2017, 11, (1), pp. 142–153.
    7. 7)
      • 17. Ambriz-Perez, H., Acha, E., Fuerte-Esquivel, C.: ‘Advanced SVC models for Newton-Raphson load flow and newton optimal power flow studies’, IEEE Trans. Power Syst., 2000, 15, (1), pp. 129–136.
    8. 8)
      • 14. Heydarian-Forushani, E., Golshan, M., Moghaddam, M., et al: ‘Robust scheduling of variable wind generation by coordination of bulk energy storages and demand response’, Energy Convers. Manage., 2015, 106, pp. 941–950.
    9. 9)
      • 13. Dai, C., Wu, L., Wu, H.: ‘A multi-band uncertainty set based robust SCUC with spatial and temporal budget constraints’, IEEE Trans. Power Syst., 2016, 31, (6), pp. 4988–5000.
    10. 10)
      • 19. Belotti, P.: ‘Couenne: a user's manual’. Technical Report, Lehigh University, 2009.
    11. 11)
      • 1. Alizadeh, M., Moghaddam, M.P., Amjady, N., et al: ‘Flexibility in future power systems with high renewable penetration: a review’, Renew. Sust. Energy Rev., 2016, 57, pp. 1186–1193.
    12. 12)
      • 21. Nikoobakht, A., Aghaei, J., Parvania, M., et al: ‘Contribution of FACTS devices in power systems security using MILP-based OPF’, IET Gener. Transm. Distrib., 2018, 12, (15), pp. 3744–3755.
    13. 13)
      • 18. Nireekshana, T., Rao, G.K., Raju, S.S.N.: ‘Enhancement of ATC with FACTS devices using real-code genetic algorithm’, Int. J. Electr. Power Energy Syst., 2012, 43, (1), pp. 1276–1284.
    14. 14)
      • 2. Thakurta, P.G., Belmans, R., Van Hertem, D.: ‘Risk-based management of overloads caused by power injection uncertainties using power flow controlling devices’, IEEE Trans. Power Syst., 2015, 30, (6), pp. 3082–3092.
    15. 15)
      • 20. Drud, A.S.: ‘CONOPT – a large-scale GRG code’, ORSA J. Comput., 1994, 6, (2), pp. 207–216.
    16. 16)
      • 25. GAMS: ‘The solver manuals’. 1996. Available at: http://www.gams.com/.
    17. 17)
      • 22. Akbari, T., Bina, M.T.: ‘Linear approximated formulation of AC optimal power flow using binary discretisation’, IET Gener. Transm. Distrib., 2016, 10, (5), pp. 1117–1123.
    18. 18)
      • 7. Marinakis, A., Glavic, M., Van Cutsem, T.: ‘Minimal reduction of unscheduled flows for security restoration: application to phase shifter control’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 506–515.
    19. 19)
      • 8. Sidea, D.O., Toma, L., Eremia, M.: ‘Sizing a phase shifting transformer for congestion management in high wind generation areas’. IEEE 2017 PowerTech, Manchester, 2017, pp. 1–6.
    20. 20)
      • 6. Ding, T., Bo, R., Bie, Z., et al: ‘Optimal selection of phase shifting transformer adjustment in optimal power flow’, IEEE Trans. Power Syst., 2017, 32, (3), pp. 2464–2465.
    21. 21)
      • 9. Aien, M., Hajebrahimi, A., Fotuhi-Firuzabad, M.: ‘A comprehensive review on uncertainty modeling techniques in power system studies’, Renew. Sust. Energy Rev., 2016, 57, pp. 1077–1089.
    22. 22)
      • 3. Zarate-Minano, R., Conejo, A., Milano, F.: ‘OPF-based security redispatching including FACTS devices’, IET Gener. Transm. Distrib., 2008, 2, (6), pp. 821–833.
    23. 23)
      • 15. Nikoobakht, A., Aghaei, J.: ‘IGDT-based robust optimal utilisation of wind power generation using coordinated flexibility resources’, IET Renew. Power Gener., 2016, 11, (2), pp. 264–277.
    24. 24)
      • 11. Bertsimas, D., Litvinov, E., Sun, X.A., et al: ‘Adaptive robust optimization for the security constrained unit commitment problem’, IEEE Trans. Power Syst., 2013, 28, (1), pp. 52–63.
    25. 25)
      • 12. Hu, B., Wu, L.: ‘Robust SCUC considering continuous/discrete uncertainties and quick-start units: a two-stage robust optimization with mixed-integer recourse’, IEEE Trans. Power Syst., 2016, 31, (2), pp. 1407–1419.
    26. 26)
      • 23. Nikoobakht, A., Aghaei, J., Mardaneh, M.: ‘Managing the risk of uncertain wind power generation in flexible power systems using information gap decision theory’, Energy, 2016, 114, pp. 846–861.
    27. 27)
      • 16. Bussieck, M.R., Drud, A.: ‘SBB: a new solver for mixed integer nonlinear programming’ (Talk, OR, 2001).
    28. 28)
      • 28. Peschon, J., Piercy, D.S., Tinney, W.F., et al: ‘Sensitivity in power systems’, IEEE Trans. Power Appar. Syst., 1968, PAS-87, (8), pp. 1687–1696.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2018.5136
Loading

Related content

content/journals/10.1049/iet-rpg.2018.5136
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading