Advanced energy management and frequency control of distributed microgrid using multi-agent systems-Reference-Cited by-同舟云学术

Advanced energy management and frequency control of distributed microgrid using multi-agent systems

Published:2021-12-28 Issue:0 Volume:0 Page:
ISSN:2194-5756
Container-title:International Journal of Emerging Electric Power Systems
language:en
Short-container-title:

Author:

Azeroual Mohamed¹^ORCID,Boujoudar Younes¹,Aljarbouh Ayman²,Fayaz Muhammad²,Qureshi Muhammad Shuaib²,El Moussaoui Hassan¹,El Markhi Hassane¹

Affiliation:

1. Electrical Engineering Department , Sidi Mohamed Ben Abdellah University, FST , Fez , Morocco

2. University of Central Asia , 310 Lenin Street , Naryn 722918 , Kyrgyzsta

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Energy Engineering and Power Technology

Link

https://www.degruyter.com/document/doi/10.1515/ijeeps-2021-0298/pdf

Reference29 articles.

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.

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.

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.

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.

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.

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