Advanced energy management and frequency control of distributed microgrid using multi-agent systems
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Mohamed Azeroual
, Younes Boujoudar
Abstract
One of the main objectives of the Energy Management System (EMS) is to achieve a very high level of flexibility, stability, and the system must be able to adapt to most changes in the distribution network. This paper proposes a multi-agent system-based microgrid energy management to balance the energy supply and demand by feasibly integrating the energy storage system and demand response. An overall power management strategy is necessary to manage power flows among all interconnected elements of the microgrid. The principal contribution of this paper is an energy management system based on intelligent agents; each agent uses the microgrid data to manage the power flow in the microgrid. The interaction between agents proposed is simulated using JADE (Java Agent Development Environment) and the microgrid model is simulated using MATLAB/Simulink, both platforms are connected through the MACSimJX middleware for a dynamic simulation.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Yin, C, Wu, H, Sechilariu, M, Locment, F. Power management strategy for an autonomous DC microgrid. Appl Sci 2018;8:2202. https://doi.org/10.3390/app8112202.Search in Google Scholar
2. Azeroual, M, Lamhamdi, T, El Moussaoui, H, El Markhi, H. Simulation tools for a smart grid and energy management for a microgrid with wind power using multi-agent system. Wind Eng 2020;44:661–72. https://doi.org/10.1177/0309524x19862755.Search in Google Scholar
3. Azeroual, M, El Makrini, A, El Moussaoui, H, El Markhi, H. Renewable energy potential and available capacity for wind and solar power in Morocco towards 2030. J Eng Sci Technol Rev 2018;11:189–98. https://doi.org/10.25103/jestr.111.23.Search in Google Scholar
4. Meng, L, Sanseverino, ER, Luna, A, Dragicevic, T, Vasquez, JC, Guerrero, JM. Microgrid supervisory controllers and energy management systems: a literature review. Renew Sustain Energy Rev 2016;60:1263–73. https://doi.org/10.1016/j.rser.2016.03.003.Search in Google Scholar
5. Gomez-Sanz, JJ, Garcia-Rodriguez, S, Cuartero-Soler, N, Hernandez-Callejo, L. Reviewing microgrids from a multi-agent systems perspective. Energies 2014;7:3355–82. https://doi.org/10.3390/en7053355.Search in Google Scholar
6. Colson, CM, Nehrir, MH. Comprehensive real-time microgrid power management and control with distributed agents. IEEE Trans Smart Grid 2013;4:617–27. https://doi.org/10.1109/tsg.2012.2236368.Search in Google Scholar
7. Kantamneni, A, Brown, LE, Parker, G, Weaver, WW. Survey of multi-agent systems for microgrid control. Eng Appl Artif Intell 2015;45:192–203. https://doi.org/10.1016/j.engappai.2015.07.005.Search in Google Scholar
8. Dragicevic, T, Wu, D, Shafiee, Q, Meng, L. Distributed and decentralized control architectures for converter-interfaced microgrids. Chin J Electr Eng 2017;3:41–52.10.23919/CJEE.2017.8048411Search in Google Scholar
9. Shafiee, Q, Stefanovic, C, Dragicevic, T, Popovski, P, Vasquez, JC, Guerrero, JM. Robust networked control scheme for distributed secondary control of islanded microgrids. IEEE Trans Ind Electron 2014;61:5363–74. https://doi.org/10.1109/tie.2013.2293711.Search in Google Scholar
10. Dehkordi, NM, Sadati, N, Hamzeh, M. Fully distributed cooperative secondary frequency and voltage control of islanded microgrids. IEEE Trans Energy Convers 2017;32:675–85. https://doi.org/10.1109/tec.2016.2638858.Search in Google Scholar
11. Albarakati, AJ, Boujoudar, Y, Azeroual, M, Jabeur, R, Aljarbouh, A, El Moussaoui, H, Ouaaline, N. Real-time energy management for DC microgrids using artificial intelligence. Energies 2021;14:5307.10.3390/en14175307Search in Google Scholar
12. Zhang, G, Li, C, Qi, D, Xin, H. Distributed estimation and secondary control of autonomous microgrid. IEEE Trans Power Syst 2017;32:989–98.10.1109/TPWRS.2016.2590431Search in Google Scholar
13. Dehkordi, NM, Sadati, N, Hamzeh, M. Distributed robust finite-time secondary voltage and frequency control of islanded microgrids. IEEE Trans Power Syst 2017;32:3648–59. https://doi.org/10.1109/tpwrs.2016.2634085.Search in Google Scholar
14. Azeroual, M, Lamhamdi, T, El Moussaoui, H, El Markhi, H. The intelligent energy management system of a smart microgrid using multiagent systems. Arch Electr Eng 2020;69:23–38. https://doi.org/10.24425/aee.2020.131756.Search in Google Scholar
15. Logenthiran, T, Naayagi, RT, Woo, WL, Phan, VT, Abidi, K. Intelligent control system for microgrids using multiagent system. IEEE J Emerg Sel Top Power Electron 2015;3:1036–45. https://doi.org/10.1109/jestpe.2015.2443187.Search in Google Scholar
16. Feilat, EA, Azzam, S, Al-Salaymeh, A. Impact of large PV and wind power plants on voltage and frequency stability of Jordan’s national grid. Sustain Cities Soc 2018;36:257–71. https://doi.org/10.1016/j.scs.2017.10.035.Search in Google Scholar
17. Hanada, K, Wada, T, Masubuchi, I, Asai, T, Fujisaki, Y. Multi‐agent consensus for distributed power dispatch with load balancing. Asian J Control 2021;23:611–9. https://doi.org/10.1002/asjc.2257.Search in Google Scholar
18. Khan, MW, Wang, J. The research on multi-agent system for microgrid control and optimization. Renew Sust Energ Rev 2017;80:1399–411.10.1016/j.rser.2017.05.279Search in Google Scholar
19. Metihalli, BK, Sabhahit, JN. Disturbance observer based distributed consensus control strategy of multi-agent system with external disturbance in a Standalone DC microgrid. Asian J Control 2020;23:920–36. https://doi.org/10.1002/asjc.2287.Search in Google Scholar
20. Pitt, J, Mamdani, A. A protocol-based semantics for an agent communication language. IJCAI 1999;99:486–91.Search in Google Scholar
21. Bellifemine, F, Bergenti, F, Caire, G, Poggi, A. JADE—a java agent development framework. In: Multi-agent programming. Boston, MA: Springer; 2005:125–47 pp.10.1007/0-387-26350-0_5Search in Google Scholar
22. Robinson, CR, Mendham, P, Clarke, T. MACSimJX: a tool for enabling agent modelling with Simulink using JADE. J Phys Agents; 2010, 4.10.14198/JoPha.2010.4.3.01Search in Google Scholar
23. Harmouch, FZ, Krami, N, Hmina, N. A multiagent based decentralized energy management system for power exchange minimization in microgrid cluster. Sustain Cities Soc 2018;40:416–27.10.1016/j.scs.2018.04.001Search in Google Scholar
24. El Iysaouy, L, Lahbabi, M, Oumnad, A. Enhancing the performances of PV array configurations under partially shaded conditions: a comparative study. Int J Renew Energy Res 2018;8:1779–90.Search in Google Scholar
25. Abdel-Salam, M, El-Mohandes, MT, Goda, M. An improved perturb-and-observe based MPPT method for PV systems under varying irradiation levels. Solar Energy 2018;171:547–61.10.1016/j.solener.2018.06.080Search in Google Scholar
26. El Karkri, Y, Rey-Boué, AB, El Moussaoui, H, Stöckl, J, Strasser, TI. Improved control of grid-connected DFIG-based wind turbine using proportional-resonant regulators during unbalanced grid. Energies 2019;12:4041. https://doi.org/10.3390/en12214041.Search in Google Scholar
27. Kumar, D, Chatterjee, K. A review of conventional and advanced MPPT algorithms for wind energy systems. Renew Sustain Energy Rev 2016;55:957–70. https://doi.org/10.1016/j.rser.2015.11.013.Search in Google Scholar
28. Boujoudar, Y, Elmoussaoui, H, Lamhamdi, T. Lithium-ion batteries modeling and state of charge estimation using artificial neural network. Int J Electr Comput E 2019;9:3415.10.11591/ijece.v9i5.pp3415-3422Search in Google Scholar
29. Mohamed, A, Lamhamdi, T, El Moussaoui, H, El Markhi, H. A multi-agent system for fault location and service restoration in power distribution systems. Multiagent Grid Syst 2019;15:343–58.10.3233/MGS-190316Search in Google Scholar
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Articles in the same Issue
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- Power quality improvement using model predictive control based shunt connected custom power device in a single phase system
- A reliable islanding identification mechanism for DC microgrid using PCC transient signal
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- Advanced energy management and frequency control of distributed microgrid using multi-agent systems
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Articles in the same Issue
- Frontmatter
- Research Articles
- Torque ripple minimization of multi-level inverter fed PMSM drive using modified MPTC
- Blockchain insisted resilience enhancement of power electricity markets using distributed energy trading
- A novel Confidential Consortium Blockchain framework for peer to peer energy trading
- Experimental verification of DSTATCOM for various non-linear load
- Grid integration of hybrid renewable energy source using Aligned Multilevel Inverter
- Frequency regulation of wind energy integrated power system using a novel optimized type II fuzzy tilted integral derivative controller
- Power quality improvement using model predictive control based shunt connected custom power device in a single phase system
- A reliable islanding identification mechanism for DC microgrid using PCC transient signal
- Intrinsic time decomposition based differential protection with adaptive threshold for UPFC compensated transmission line
- Advanced energy management and frequency control of distributed microgrid using multi-agent systems
- Accurate estimation of modern power system harmonics using a novel LSA hybridized recursive least square technique