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access icon openaccess Bi-level optimised dispatch strategy of electric supply–demand balance considering risk–benefit coordination

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References

    1. 1)
      • 1. Siano, P.: ‘Demand response and smart grids – a survey’, Renew. Sustain. Energy Rev., 2014, 30, pp. 461478.
    2. 2)
      • 2. Zhao, D., Meliopoulos, A.P.S., Tan, Z., et al: ‘A market-based operation method for distribution system with distributed generation and demand response’. Int. Conf. NAPS, Manhattan, USA, 2013, pp. 16.
    3. 3)
      • 3. Farhangi, H.: ‘The path of the smart grid’, IEEE Power Energy Mag.., 2010, 8, (1), pp. 1828.
    4. 4)
      • 4. Zakariazadeh, A., Jadid, S., Siano, P.: ‘Stochastic operational scheduling of smart distribution system considering wind generation and demand response programs’, Int. J. Electr. Power Energy Syst., 2014, 63, pp. 218225.
    5. 5)
      • 5. Gungor, V.C., Sahin, D., Kocak, T.: ‘Smart grid technologies: communication technologies and standards’, IEEE Trans. Ind. Inf., 2011, 7, (4), pp. 529539.
    6. 6)
      • 6. Rahimi, F., Ipakchi, A.: ‘Demand response as a market resource under the smart grid paradigm’, IEEE Trans. Smart Grid, 2010, 1, (1), pp. 8288.
    7. 7)
      • 7. Chen, H., Li, Y., Louie, R.H.Y., et al: ‘Autonomous demand side management based on energy consumption scheduling and instantaneous load billing: an aggregative game approach’, IEEE Trans. Smart Grid, 2014, 5, (4), pp. 17441754.
    8. 8)
      • 8. Torriti, J.: ‘Price-based demand side management: assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in northern Italy’, Energy, 2012, 44, (1), pp. 576583.
    9. 9)
      • 9. Du, P., Lu, N.: ‘Appliance commitment for household load scheduling’, IEEE Trans. Smart Grid, 2011, 2, (2), pp. 411419.
    10. 10)
      • 10. Aghaei, J., Alizadeh, M.I.: ‘Demand response in smart electricity grids equipped with renewable energy sources: a review’, Renew. Sustain. Energy Rev., 2013, 18, pp. 6472.
    11. 11)
      • 11. Yang, S., Liu, J., Yao, J.: ‘Model and strategy for multi-time scale coordinated flexible load interactive scheduling’, Proc. CSEE, 2014, 34, (22), pp. 36643673.
    12. 12)
      • 12. Kwag, H.G., Kim, J.O.: ‘Optimal combined scheduling of generation and demand response with demand resource constraints’, Appl. Energy, 2012, 96, pp. 161170.
    13. 13)
      • 13. Paterakis, N.G., Erdinc, O., Bakirtzis, A.G., et al: ‘Load-following reserves procurement considering flexible demand-side resources under high wind power penetration’, IEEE Trans. Power Syst., 2015, 30, (3), pp. 13371350.
    14. 14)
      • 14. Mahdavi, N., Braslavsky, J.H., Seron, M.M., et al: ‘Model predictive control of distributed air-conditioning loads to compensate fluctuations in solar power’, IEEE Trans. Smart Grid, 2017, 8, (6), pp. 30553065.
    15. 15)
      • 15. Vrettos, E., Oldewurtel, F., Andersson, G.: ‘Robust energy-constrained frequency reserves from aggregations of commercial buildings’, IEEE Trans. Power Syst., 2016, 31, (6), pp. 42724285.
    16. 16)
      • 16. Liu, X., Wang, B., Li, Y., et al: ‘Stochastic unit commitment model for high wind power integration considering demand side resources’, Proc. CSEE, 2015, 35, (14), pp. 37143723.
    17. 17)
      • 17. Song, M., Amelin, M.: ‘Purchase bidding strategy for a retailer with flexible demands in day-ahead electricity market’, IEEE Trans. Power Syst., 2017, 32, (3), pp. 18391850.
    18. 18)
      • 18. Asensio, M., Contreras, J.: ‘Risk-constrained optimal bidding strategy for pairing of wind and demand response resources’, IEEE Trans. Smart Grid, 2017, 8, (1), pp. 200208.
    19. 19)
      • 19. Mathieu, S., Ernst, D., Louveaux, Q.: ‘An efficient algorithm for the provision of a day-ahead modulation service by a load aggregator’. Fourth IEEE PES ISGT Europe, Lyngby, Denmark, 2013, pp. 15.
    20. 20)
      • 20. Li, B., Shen, J., Wang, X., et al: ‘From controllable loads to generalized demand-side resources: a review on developments of demand-side resources’, Renew. Sustain. Energy Rev., 2016, 53, pp. 936944.
    21. 21)
      • 21. Kardakos, E.G., Simoglou, C.K., Bakirtzis, A.G.: ‘Optimal offering strategy of a virtual power plant: a stochastic bi-level approach’, IEEE Trans. Smart Grid, 2016, 7, (2), pp. 794806.
    22. 22)
      • 22. Cameron, L., Cramton, P.: ‘The role of the ISO in US electricity markets: a review of restructuring in California and PJM’, Electr. J., 1999, 12, (3), pp. 7181.
    23. 23)
      • 23. Shefrin, H., Statman, M.: ‘Behavioral portfolio theory’, J. Financ. Quant. Anal., 2000, 35, (2), pp. 127151.
    24. 24)
      • 24. Zare, K., Moghaddam, M.P., Sheikh-El-Eslami, M.K.: ‘Risk-based electricity procurement for large consumers’, IEEE Trans. Power Syst., 2011, 26, (4), pp. 18261835.
    25. 25)
      • 25. Tushar, W.: ‘Three-party energy management with distributed energy resources in smart grid’, IEEE Trans. Ind. Electron., 2015, 62, (4), pp. 24872498.
    26. 26)
      • 26. Zhu, J., Duan, P., Liu, M.: ‘Electric real-time dispatch via bi-level coordination of source-grid-load of power system with risk’, Proc. CSEE, 2015, 135, (13), pp. 32393247.
    27. 27)
      • 27. Kennedy, J.: ‘Particle swarm optimization’, in Sammut, C., Webb, G.I.Encyclopedia of machine learning’ (Springer, New York, 2011), pp. 760766.
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