1. C. M. Colson and M. H. Nehrir, “A review of challenges to real-time
power management of microgrids,” in 2009 IEEE Power & Energy
Society General Meeting, pp. 1–8, IEEE, 2009.
2. I. Series, “Microgrids and active distribution networks,” The institution
of Engineering and Technology, 2009.
3. G. Pepermans, J. Driesen, D. Haeseldonckx, R. Belmans, and
W. D’haeseleer, “Distributed generation: definition, benefits and issues,” Energy policy, vol. 33, no. 6, pp. 787–798, 2005.
4. J. Ning, Y. Zhou, F. Long, and X. Tao, “A synergistic energy-efficient
planning approach for urban rail transit operations,” Energy, vol. 151,
pp. 854–863, 2018.
5. Y. Lu, Y. Zhao, X. Zhao, G. Li, and C. Zhang, “Status analysis of
regenerative braking energy utilization equipments in urban rail transit,”
in 2017 IEEE transportation electrification conference and expo, AsiaPacific (ITEC Asia-Pacific), pp. 1–6, IEEE, 2017.
6. X. Yang, A. Chen, X. Li, B. Ning, and T. Tang, “An energy-efficient
scheduling approach to improve the utilization of regenerative energy
for metro systems,” Transportation Research Part C: Emerging Technologies, vol. 57, pp. 13–29, 2015.
7. C. Gouveia, J. Moreira, C. Moreira, and J. P. Lopes, “Coordinating
storage and demand response for microgrid emergency operation,”
IEEE transactions on smart grid, vol. 4, no. 4, pp. 1898–1908, 2013.
8. X. Xu, J. Mitra, N. Cai, and L. Mou, “Planning of reliable microgrids in
the presence of random and catastrophic events,” International Transactions on Electrical Energy Systems, vol. 24, no. 8, pp. 1151–1167,
9. J. Driesen and F. Katiraei, “Design for distributed energy resources,”
IEEE power and energy magazine, vol. 6, no. 3, pp. 30–40, 2008.
10. K. Buayai, W. Ongsakul, and N. Mithulananthan, “Multi-objective microgrid planning by nsga-ii in primary distribution system,” European Transactions on Electrical Power, vol. 22, no. 2, pp. 170–187, 2012.
11. X. Yang and W. Tian, “Microgrid’s generation expansion planning considering lower carbon economy,” in 2012 Asia-Pacific Power and Energy
Engineering Conference, pp. 1–6, IEEE, 2012.
12. M. R. Vallem and J. Mitra, “Siting and sizing of distributed generation
for optimal microgrid architecture,” in Proceedings of the 37th Annual
North American Power Symposium, 2005., pp. 611–616, IEEE, 2005.
13. W. Su, Z. Yuan, and M.-Y. Chow, “Microgrid planning and operation:
Solar energy and wind energy,” in IEEE PES General Meeting, pp. 1–7,
14. A. Khodaei and M. Shahidehpour, “Microgrid-based co-optimization
of generation and transmission planning in power systems,” IEEE
transactions on power systems, vol. 28, no. 2, pp. 1582–1590, 2012.
15. O. Hafez and K. Bhattacharya, “Optimal planning and design of a
renewable energy based supply system for microgrids,” Renewable
Energy, vol. 45, pp. 7–15, 2012.
16. A. K. Basu, S. Chowdhury, and S. Chowdhury, “Impact of strategic deployment of chp-based ders on microgrid reliability,” IEEE Transactions
on Power Delivery, vol. 25, no. 3, pp. 1697–1705, 2010.
17. L. Guo, W. Liu, J. Cai, B. Hong, and C. Wang, “A two-stage optimal
planning and design method for combined cooling, heat and power microgrid system,” Energy Conversion and Management, vol. 74, pp. 433–
18. O. Nadjemi, T. Nacer, A. Hamidat, and H. Salhi, “Optimal hybrid pv/wind
energy system sizing: Application of cuckoo search algorithm for algerian dairy farms,” Renewable and Sustainable Energy Reviews, vol. 70,
pp. 1352–1365, 2017.
19. M. Farrokhifar, F. H. Aghdam, A. Alahyari, A. Monavari, and A. Safari,
“Optimal energy management and sizing of renewable energy and
battery systems in residential sectors via a stochastic milp model,”
Electric Power Systems Research, vol. 187, p. 106483, 2020.
20. S. Hasanvand, M. Nayeripour, E. Waffenschmidt, and H. FallahzadehAbarghouei, “A new approach to transform an existing distribution network into a set of micro-grids for enhancing reliability and sustainability,”
Applied Soft Computing, vol. 52, pp. 120–134, 2017.
21. L. Zhang, W. Tang, Y. Liu, and T. Lv, “Multiobjective optimization and
decision-making for dg planning considering benefits between distribution company and dgs owner,” International Journal of Electrical Power
& Energy Systems, vol. 73, pp. 465–474, 2015.
22. K. Zou, A. P. Agalgaonkar, K. M. Muttaqi, and S. Perera, “Distribution
system planning with incorporating dg reactive capability and system
uncertainties,” IEEE Transactions on Sustainable Energy, vol. 3, no. 1,
pp. 112–123, 2011.
23. R. Hemmati, R.-A. Hooshmand, and N. Taheri, “Distribution network
expansion planning and dg placement in the presence of uncertainties,”
International Journal of Electrical Power & Energy Systems, vol. 73,
pp. 665–673, 2015.
24. C. Liu, X. Wang, J. Guo, M. Huang, and X. Wu, “Chance-constrained
scheduling model of grid-connected microgrid based on probabilistic
and robust optimisation,” IET Generation, Transmission & Distribution,
vol. 12, no. 11, pp. 2499–2509, 2018.
25. L. Wang, G. Huang, X. Wang, and H. Zhu, “Risk-based electric power
system planning for climate change mitigation through multi-stage jointprobabilistic left-hand-side chance-constrained fractional programming:
A canadian case study,” Renewable and Sustainable Energy Reviews,
vol. 82, pp. 1056–1067, 2018.
26. J. Liu, H. Chen, W. Zhang, B. Yurkovich, and G. Rizzoni, “Energy management problems under uncertainties for grid-connected microgrids:
A chance constrained programming approach,” IEEE Transactions on
Smart Grid, vol. 8, no. 6, pp. 2585–2596, 2016.
27. J. Wu, B. Zhang, Y. Jiang, P. Bie, and H. Li, “Chance-constrained
stochastic congestion management of power systems considering
uncertainty of wind power and demand side response,” International
Journal of Electrical Power & Energy Systems, vol. 107, pp. 703–714,
28. Z. Shi, H. Liang, S. Huang, and V. Dinavahi, “Distributionally robust
chance-constrained energy management for islanded microgrids,” IEEE
Transactions on Smart Grid, vol. 10, no. 2, pp. 2234–2244, 2018.
29. C. A. Marino and M. Marufuzzaman, “A microgrid energy management system based on chance-constrained stochastic optimization
and big data analytics,” Computers & Industrial Engineering, vol. 143,
p. 106392, 2020.
30. M. Daneshvar, B. Mohammadi-Ivatloo, M. Abapour, S. Asadi, and
R. Khanjani, “Distributionally robust chance-constrained transactive
energy framework for coupled electrical and gas microgrids,” IEEE
Transactions on Industrial Electronics, vol. 68, no. 1, pp. 347–357,
31. Y. Xu, T. Zhao, S. Zhao, J. Zhang, and Y. Wang, “Multi-objective chanceconstrained optimal day-ahead scheduling considering bess degradation,” CSEE Journal of Power and Energy Systems, vol. 4, no. 3,
pp. 316–325, 2018.
32. B. Zhou, G. Chen, Q. Song, and Z. Y. Dong, “Robust chanceconstrained programming approach for the planning of fast-charging
stations in electrified transportation networks,” Applied Energy, vol. 262,
p. 114480, 2020.
33. M. Daneshvar, B. Mohammadi-Ivatloo, S. Asadi, A. Anvari-Moghaddam,
M. Rasouli, M. Abapour, and G. B. Gharehpetian, “Chance-constrained
models for transactive energy management of interconnected microgrid
clusters,” Journal of Cleaner Production, vol. 271, p. 122177, 2020.
34. M. Hemmati, B. Mohammadi-Ivatloo, M. Abapour, and A. AnvariMoghaddam, “Optimal chance-constrained scheduling of reconfigurable microgrids considering islanding operation constraints,” IEEE
Systems Journal, vol. 14, no. 4, pp. 5340–5349, 2020.
35. W. Li et al., Reliability assessment of electric power systems using
Monte Carlo methods. Springer Science & Business Media, 2013.
36. B. Odetayo, M. Kazemi, J. MacCormack, W. D. Rosehart, H. Zareipour,
and A. R. Seifi, “A chance constrained programming approach to the
integrated planning of electric power generation, natural gas network
and storage,” IEEE Transactions on Power Systems, vol. 33, no. 6,
pp. 6883–6893, 2018.
37. M. Hajian, M. Glavic, W. D. Rosehart, and H. Zareipour, “A chanceconstrained optimization approach for control of transmission voltages,”
IEEE Transactions on Power Systems, vol. 27, no. 3, pp. 1568–1576,