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Article type: Research Article
Authors: Rwegasira, Dianaa; b; * | Dhaou, Imed Benc; d | Ebrahimi, Masoumeha | Hallén, Andersa | Mvungi, Nereyb | Tenhunen, Hannua
Affiliations: [a] Royal Institute of Technology, Kista, Sweden | [b] University of Dar es Salaam, Dar es Salaam, Tanzania | [c] Hekma School of Engineering, Computing, and Informatics, Dar Al-Hekma University, Jeddah, Saudi Arabia | [d] University of Monastir, Monastir, Tunisia
Correspondence: [*] Corresponding author: Diana Rwegasira, %****␣mgs-17-mgs210345_temp.tex␣Line␣25␣**** Royal Institute of Technology, Box 229, Kista 16440, Sweden. E-mail: [email protected].
Abstract: The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.
Keywords: Architecture, energy management, load shedding, DC microgrid, multi-agent system
DOI: 10.3233/MGS-210345
Journal: Multiagent and Grid Systems, vol. 17, no. 2, pp. 113-128, 2021
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