Refrences:
1.Fotuhi-Friuzabad, M., Safdarian, A., and Moeini- Aghtaie, M., et al. Upcoming challenges of future electric power systems: sustainability and resiliency", Scientia Iranica, 23(4), pp. 1565-1577 (2016).
2. Shahidehpour, M. and Fotuhi-Friuzabad, M. Grid modernization for enhancing the resilience, reliability, economics, sustainability, and security of electricity grid in an uncertain environment", Scientia Iranica, 23(16), pp. 2862-2873 (2016).
3. Lu, W., Liu, M., Lin S., et al. Incremental-oriented ADMM for distributed optimal power ow with discrete variables in distribution networks", IEEE Trans. Smart Grid, 10(6), pp. 6320-6331 (Nov. 2019). DOI: 10.1109/TSG.2019.2902255
4. Ross, M., Abbey, C., Bou_ard, F., et al. Multiobjective optimization dispatch for microgrids with a high penetration of renewable generation" , IEEE Trans. Sustain. Energy, 6(4), pp. 1306-1314 (2015). 5. Fathi M. and Bevrani, H. Statistical cooperative power dispatching in interconnected microgrids", IEEE Trans. Sustain. Energy, 4(3), pp. 586-593 (2013). 6. Ouammi, A., Dagdougui, H., Dessaint L., et al. Coordinated model predictive-based power ows control 3620 M. Doostizadeh et al./Scientia Iranica, Transactions D: Computer Science & ... 26 (2019) 3606{3621 in a cooperative network of smart microgrids", IEEE Trans. Smart Grid, 6(5), pp. 2233-2244 (2015). 7. Haddadian, H. and Noroozian, R. Multi-microgrids approach for design and operation of future distribution networks based on novel technical indices", Appl. Energy, 185, pp. 650-663 (2017). 8. Haddadian, H. and Noroozian, R. Multi-Microgridbased operation of active distribution networks considering demand response programs", IEEE Trans. Sustain. Energy, 10(4), pp. 1804-1812 (Oct. 2019). DOI:10.1109/TSTE.2018.2873206 9. Zhang, B., Li Q., Wang, L., and Feng, W. Robust optimization for energy transactions in multi-microgrids under uncertainty" , Appl. Energy, 217, pp. 346-360 (2018). 10. Alam, M.N., Chakrabarti, S., and Ghosh, A. Networked microgrids: State-of-the-art and future perspectives", IEEE Trans. Ind. Inform., 15(3), pp. 1238- 1250 (2019). 11. Toutounchi, A.N., Seyedshenava, S., Contreras J., et al. A stochastic bilevel model to manage active distribution networks with multi-microgrids", IEEE Syst. J., 13(4), pp. 4190-4199 (Dec. 2019). DOI: 10.1109/JSYST.2018.2890062 12. Wang, Z., Chen, B., Wang, J., et al. Coordinated energy management of networked microgrids in distribution systems", IEEE Trans. Smart Grid, 6(1), pp. 45-53 (2015). 13. Minciardiand, R. and Robba, M. A bilevel approach for the stochastic optimal operation of interconnected microgrids", IEEE Trans. Autom. Sci. Eng., 14(2), pp. 482-493 (2017). 14. Wang, H. and Huang, J. Incentivizing energy trading for interconnected microgrids" , IEEE Trans. Smart Grid, 9(4), pp. 2647-2657 (2018). 15. Park, S., Lee, J., Bae, S., et al. Contribution-based energy-trading mechanism in microgrids for future smart grid: A game theoretic approach", IEEE Trans. Ind. Electron., 63(7), pp. 4255-4265 (2016). 16. Jadhav, A.M. and Patne, N.R. Priority-based energy scheduling in a smart distributed network with multiple microgrids", IEEE Trans. Ind. Inform., 13(6), pp. 3134-3143 (2017). 17. Du, Y., Wang, Z., Liu, G., et al. A cooperative game approach for coordinating multi-microgrid operation within distribution systems", Appl. Energy, 222, pp. 383-395 (2018). 18. Mei, J., Chen, C., Wang, J., et al. Coalitional game theory based local power exchange algorithm for networked microgrids", Appl. Energy, 239, pp. 133-141 (2019). 19. Liu, Y., Guo, L., and Wang, C. A robust operationbased scheduling optimization for smart distribution networks with multi-microgrids", Appl. Energy, 228, pp. 130-140 (2018). 20. Nunna, H. and Doolla, S. Multiagent-based distributed-energy-resource management for intelligent microgrids", IEEE Trans. Industr. Electron., 60(4), pp. 1678-1687 (2013). 21. Rahman, M.S. and Oo, A.M.T. Distributed multiagent based coordinated power management and control strategy for microgrids with distributed energy resources", Energy Convers. Manage., 139, pp. 20-32 (2017). 22. Ju, L., Zhang, Q., Tan, Z., et al. Multi-agentsystem- based coupling control optimization model for micro-grid group intelligent scheduling considering autonomy-cooperative operation strategy", Energy, 157, pp. 1035-1052 (2018). 23. Kou, P., Liang, D., and Gao L. Distributed EMPC of multiple microgrids for coordinated stochastic energy management", Appl. Energy, 185, pp. 939-952, (2017). 24. Holjevac, N., Capuder, T., Zhang, N., et al. Corrective receding horizon scheduling of exible distributed multi-energy microgrids", Appl. Energy, 207, pp. 176- 194 (2017). 25. Wang, H. and Huang, J. Incentivizing energy trading for interconnected microgrids", IEEE Trans. Smart Grid, 7(6), pp. 2647-2657 (2018). 26. Gao, H., Liu, J., Wang, L., et al. Decentralized energy management for networked microgrids in future distribution systems", IEEE Trans. Power Syst., 33(4), pp. 3599-3610 (2018). 27. Feng, C., Wen, F., Zhang, L., et al. Decentralized energy management of networked microgrid based on alternating-direction multiplier method", Energies, 11(10), p. 2555 (2018). 28. Mohiti, M., Monsef, H., Anvari-Moghaddam, A., et al. A decentralized robust model for optimal operation of distribution companies with private microgrids", Int. J. Elect. Power Energy Syst., 106, pp. 105-123 (2019). 29. Anjos, M.F., Lodi, A., and Tanneau, M. A decentralized framework for the optimal coordination of distributed energy resources" , IEEE Trans. Power Syst., 34(1), pp. 349-359 (2019). 30. Kraning, M., Chu, E., Lavaei, J., and Boyd, S. Dynamic network energy management via proximal message passing" , Foundations and Trendsrin Optimization, 1(2), pp. 73-126 (2014). 31. Kargarian, A., Fu, Y., DorMohammadi, S., et al. Optimal operation of active distribution grids: a system of systems framework", IEEE Trans. Smart Grid, 5, pp. 1228-1237 (2014). 32. Zhao, B., Wang, X., Lin, D., et al. Energy management of multiple microgrids based on a system of systems architecture", IEEE Trans. Power Syst., 33(6), pp. 6410-6421 (2018). 33. Xie, M., Ji, X., Hu, X., et al. Autonomous optimized economic dispatch of active distribution system with multi-microgrids", Energy, 153, pp. 479-489 (2018). M. Doostizadeh et al./Scientia Iranica, Transactions D: Computer Science & ... 26 (2019) 3606{3621 3621 34. Kargarian, A., Mohammadi, J., Guo, J., et al. Toward distributed/decentralized DC optimal power ow implementation in future electric power systems", IEEE Trans. Smart Grid, 9(4), pp. 2574-2594 (2018). 35. Zimmerman, R.D., Murillo-Sanchez, C.E., and Thomas, R.J. MATPOWER's extensible optimal power ow architecture", in Proc. 2009 Power & Energy Society General Meeting, Calgary, AB, Canada (2009). 36. Farivar, M. and Low, S.H. Branch ow model: Relaxations and convexi_cation-Part I", IEEE Trans. Power Syst., 28(3), pp. 2554-2564 (2013). 37. Kargarian, A., Fu, Y., and Li, Z. Distributed securityconstrained unit commitment for large-scale power systems" , IEEE Trans. Power Syst., 30(4), pp. 1925- 1936 (2015). 38. Kargarian, A., Mehrtash, M., and Falahati, B. Decentralized implementation of unit commitment with analytical target cascading: A parallel approach", IEEE Trans. Power Syst., 33(4), pp. 3981-3993 (2018). 39. Baran, M.E. and Wu, F.F. Network recon_guration in distribution systems for loss reduction and load balancing", IEEE Trans. Power del., 4(2), pp. 1401- 1407 (1989). 40. Lofberg, J. Yalmip : A toolbox for modeling and optimization in Matlab", In Proceedings of the CACSD Conference, Taipei, Taiwan, pp. 284-289 (2004). 41. IBM ILOG CPLEX (2019). [Online]. Available: https://www.ibm.com/analytics/cplex-optimizer.
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