1. [1] Z. Yi, Y. Xu, W. Gu, and W. Wu, "A Multi-time-scale Economic Scheduling Strategy for Virtual Power Plant Based on Deferrable Loads Aggregation and Disaggregation," IEEE Trans. Sustain. Energy, 2019. [DOI:10.1109/TSTE.2019.2924936]

2. [2] R.-A. Hooshmand, S. M. Nosratabadi, and E. Gholipour, "Event-based scheduling of industrial technical virtual power plant considering wind and market prices stochastic behaviors-A case study in Iran," J. Clean. Prod., vol. 172, pp. 1748-1764, 2018. [DOI:10.1016/j.jclepro.2017.12.017]

3. [3] Q. Zhao, Y. Shen, and M. Li, "Control and bidding strategy for virtual power plants with renewable generation and inelastic demand in electricity markets," IEEE Trans. Sustain. Energy, vol. 7, no. 2, pp. 562-575, 2016. [DOI:10.1109/TSTE.2015.2504561]

4. [4] J. Hu, Y. Liu, and C. Jiang, "An optimum bidding strategy of CVPP by interval optimization," IEEJ Trans. Electr. Electron. Eng., 2018. [DOI:10.1002/tee.22721]

5. [5] M. Zajc, M. Kolenc, and N. Suljanović, "Virtual power plant communication system architecture," in Smart Power Distribution Systems, Elsevier, 2019, pp. 231-250. [DOI:10.1016/B978-0-12-812154-2.00011-0]

6. [6] M. J. Kasaei, M. Gandomkar, and J. Nikoukar, "Optimal management of renewable energy sources by virtual power plant," Renew. Energy, vol. 114, pp. 1180-1188, 2017. [DOI:10.1016/j.renene.2017.08.010]

7. [7] L. Ju, Q. Tan, Y. Lu, Z. Tan, Y. Zhang, and Q. Tan, "A CVaR-robust-based multi-objective optimization model and three-stage solution algorithm for a virtual power plant considering uncertainties and carbon emission allowances," Int. J. Electr. Power Energy Syst., vol. 107, pp. 628-643, 2019. [DOI:10.1016/j.ijepes.2018.12.012]

8. [8] G. Chen and J. Li, "A fully distributed ADMM-based dispatch approach for virtual power plant problems," Appl. Math. Model., vol. 58, pp. 300-312, 2018. [DOI:10.1016/j.apm.2017.06.010]

9. [9] H. Barati and F. Ashir, "Managing and Minimizing Cost of Energy in Virtual Power Plants in the Presence of Plug-in Hybrid Electric Vehicles Considering Demand Response Program," J. Electr. Eng. Technol., vol. 13, no. 2, pp. 568-579, 2018.

10. [10] S. Hadayeghparast, A. S. Farsangi, and H. Shayanfar, "Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant," Energy, vol. 172, pp. 630-646, 2019. [DOI:10.1016/j.energy.2019.01.143]

11. [11] A. G. Zamani, A. Zakariazadeh, S. Jadid, and A. Kazemi, "Stochastic operational scheduling of distributed energy resources in a large scale virtual power plant," Int. J. Electr. Power Energy Syst., vol. 82, pp. 608-620, 2016. [DOI:10.1016/j.ijepes.2016.04.024]

12. [12] P. Karimyan, M. Abedi, S. H. Hosseinian, and R. Khatami, "Stochastic approach to represent distributed energy resources in the form of a virtual power plant in energy and reserve markets," IET Gener. Transm. Distrib., vol. 10, no. 8, pp. 1792-1804, 2016. [DOI:10.1049/iet-gtd.2015.0715]

13. [13] E. Mashhour and S. M. Moghaddas-Tafreshi, "Bidding strategy of virtual power plant for participating in energy and spinning reserve markets-Part I: Problem formulation," IEEE Trans. Power Syst., vol. 26, no. 2, pp. 949-956, 2011. [DOI:10.1109/TPWRS.2010.2070884]

14. [14] S. R. Dabbagh and M. K. Sheikh-El-Eslami, "Risk assessment of virtual power plants offering in energy and reserve markets," IEEE Trans. Power Syst., vol. 31, no. 5, pp. 3572-3582, 2016. [DOI:10.1109/TPWRS.2015.2493182]

15. [15] A. Shayegan Rad, A. Badri, A. Zangeneh, and M. Kaltschmitt, "Risk‐based optimal energy management of virtual power plant with uncertainties considering responsive loads," Int. J. Energy Res., 2019. [DOI:10.1002/er.4418]

16. [16] M. Shabanzadeh, M.-K. Sheikh-El-Eslami, and M.-R. Haghifam, "The design of a risk-hedging tool for virtual power plants via robust optimization approach," Appl. Energy, vol. 155, pp. 766-777, 2015. [DOI:10.1016/j.apenergy.2015.06.059]

17. [17] A. Shayegan-Rad, A. Badri, and A. Zangeneh, "Day-ahead scheduling of virtual power plant in joint energy and regulation reserve markets under uncertainties," Energy, vol. 121, pp. 114-125, 2017. [DOI:10.1016/j.energy.2017.01.006]

18. [18] A. Soroudi, Power System Optimization Modeling in GAMS. Springer, 2017. [DOI:10.1007/978-3-319-62350-4]

19. [19] N. Norouzi, R. Tavakkoli-Moghaddam, M. Ghazanfari, M. Alinaghian, and A. Salamatbakhsh, "A new multi-objective competitive open vehicle routing problem solved by particle swarm optimization," Networks Spat. Econ., vol. 12, no. 4, pp. 609-633, 2012. [DOI:10.1007/s11067-011-9169-4]

20. [20] F. A. Mohamed and H. N. Koivo, "System modelling and online optimal management of microgrid using mesh adaptive direct search," Int. J. Electr. Power Energy Syst., vol. 32, no. 5, pp. 398-407, 2010. [DOI:10.1016/j.ijepes.2009.11.003]

21. [21] H. Shayan and T. Amraee, "Network Constrained Unit Commitment Under Cyber Attacks Driven Overloads," IEEE Trans. Smart Grid, 2019. [DOI:10.1109/TSG.2019.2904873]

22. [22] Z. Liang, Q. Alsafasfeh, T. Jin, H. Pourbabak, and W. Su, "Risk-Constrained Optimal Energy Management for Virtual Power Plants Considering Correlated Demand Response," IEEE Trans. Smart Grid, 2017.

23. [23] S. You, C. Træholt, and B. Poulsen, "Developing virtual power plant for optimized distributed energy resources operation and integration," 2010.

24. [24] B. Vatandoust, A. Ahmadian, M. A. Golkar, A. Elkamel, A. Almansoori, and M. Ghaljehei, "Risk-Averse Optimal Bidding of Electric Vehicles and Energy Storage Aggregator in Day-ahead Frequency Regulation Market," IEEE Trans. Power Syst., 2018. [DOI:10.1109/TPWRS.2018.2888942]

25. [25] H. Jahangir et al., "A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks," IEEE Trans. Ind. Informatics, p. 1, 2019.

26. [26] M. Sedghi, A. Ahmadian, E. Pashajavid, and M. Aliakbar-Golkar, "Storage scheduling for optimal energy management in active distribution network considering load, wind, and plug-in electric vehicles uncertainties," J. Renew. Sustain. Energy, vol. 7, no. 3, p. 33120, 2015. [DOI:10.1063/1.4922004]

27. [27] H. Jahangir et al., "Charging Demand of Plug-in Electric Vehicles: Forecasting Travel Behavior Based on a Novel Rough Artificial Neural Network Approach," J. Clean. Prod., 2019. [DOI:10.1016/j.jclepro.2019.04.345]

28. [28] "CAISO Open Access Same-Time Information System (OASIS). Accessed on May 2016. [Online]. Available: http://oasis.caiso.com/mrioasis/logon.do." .