Decentralized energy trading framework for active distribution networks with multiple microgrids under uncertainty

Document Type : Article

Authors

Faculty of Engineering, Lorestan University, 5 km Tehran Road, Khorramabad, P.O. Box 68151-44316, Lorestan, Iran.

Abstract

The ever-increasing need for more reliable power supply, cost-effective and environmental-friendly utilization of distributed energy resources will result in formation of multiple microgrids (MMGs) in the near future of distribution system. To achieve this prospective, a coordination among MMGs is necessary. Accordingly, this paper proposes a new non-hierarchical multilevel architecture for the optimal scheduling of active distribution network (ADN) with MMGs. The proposed model is a decentralized decision making algorithm to optimally coordinate the mutual interaction between local optimization problems of ADN and MMGs. A non-hierarchical analytical target cascading (ATC) method is presented to solve the local optimization problems in parallel. Also, underlying risks of the energy trading caused by renewable generation uncertainty are reflected in both the objective functions and the constraints of local optimization problem. The numerical results on modified IEEE 33-bus distribution test system containing two microgrids demonstrate the effectiveness and merits of proposed model.

Keywords

References

References:
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  flow 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., Bouffard, 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  flows control 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  flexible 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).
34. Kargarian, A., Mohammadi, J., Guo, J., et al. "Toward distributed/decentralized DC optimal power  flow 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 flow model: Relaxations and convexification-Part I", IEEE Trans. Power Syst., 28(3), pp. 2554-2564 (2013).
37. Kargarian, A., Fu, Y., and Li, Z. "Distributed security constrained 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 reconfiguration 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.
Scientia Iranica
Volume 26, Special Issue on machine learning, data analytics, and advanced optimization techniques...
Transactions on Computer Science & Engineering and Electrical Engineering (D)
November and December 2019
Pages 3606-3621

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History

  • Receive Date: 17 July 2019
  • Accept Date: 14 September 2019

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