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An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

Author

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  • Aryuanto Soetedjo

    (Department of Electrical Engineering, National Institute of Technology (ITN), Malang 65145, Indonesia)

  • Yusuf Ismail Nakhoda

    (Department of Electrical Engineering, National Institute of Technology (ITN), Malang 65145, Indonesia)

  • Choirul Saleh

    (Department of Electrical Engineering, National Institute of Technology (ITN), Malang 65145, Indonesia)

Abstract

This paper presents a hardware testbed for testing the building energy management system (BEMS) based-on the multi agent system (MAS). The objective of BEMS is to maximize user comfort while minimizing the energy extracted from the grid. The proposed system implements a multi-objective optimization technique using a genetic algorithm (GA) and the fuzzy logic controller (FLC) to control the room temperature and illumination setpoints. The agents are implemented on the low cost embedded systems equipped with the WiFi communication for communicating between the agents. The photovoltaic (PV)-battery system, the air conditioning system, the lighting system, and the electrical loads are modeled and simulated on the embedded hardware. The popular communication protocols such as Message Queuing Telemetry Transport (MQTT) and Modbus TCP/IP are adopted for integrating the proposed MAS with the existing infrastructures and devices. The experimental results show that the sampling time of the proposed system is 16.50 s. Therefore it is suitable for implementing the BEMS in a real-time where the data are updated in an hourly or minutely basis. Further, the proposed optimization technique shows better results in optimizing the comfort index and the energy extracted from the grid compared to the existing methods.

Suggested Citation

  • Aryuanto Soetedjo & Yusuf Ismail Nakhoda & Choirul Saleh, 2019. "An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System," Energies, MDPI, vol. 12(19), pages 1-29, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3655-:d:270386
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    References listed on IDEAS

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    1. Anvari-Moghaddam, Amjad & Rahimi-Kian, Ashkan & Mirian, Maryam S. & Guerrero, Josep M., 2017. "A multi-agent based energy management solution for integrated buildings and microgrid system," Applied Energy, Elsevier, vol. 203(C), pages 41-56.
    2. Esther, B. Priya & Kumar, K. Sathish, 2016. "A survey on residential Demand Side Management architecture, approaches, optimization models and methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 342-351.
    3. Antimo Barbato & Antonio Capone, 2014. "Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey," Energies, MDPI, vol. 7(9), pages 1-38, September.
    4. Israr Ullah & DoHyeun Kim, 2017. "An Improved Optimization Function for Maximizing User Comfort with Minimum Energy Consumption in Smart Homes," Energies, MDPI, vol. 10(11), pages 1-21, November.
    5. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
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    Cited by:

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    2. Isaías González & Antonio José Calderón & José María Portalo, 2021. "Innovative Multi-Layered Architecture for Heterogeneous Automation and Monitoring Systems: Application Case of a Photovoltaic Smart Microgrid," Sustainability, MDPI, vol. 13(4), pages 1-24, February.

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