Multi-agent Control System with Intelligent Optimization for Building Energy Management

Author(s):  
Ee May Kan ◽  
Khaing Yadanar ◽  
Ngee Hoo Ling ◽  
Yvonne Soh ◽  
Naing Lin
Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3655 ◽  
Author(s):  
Aryuanto Soetedjo ◽  
Yusuf Ismail Nakhoda ◽  
Choirul Saleh

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.


2018 ◽  
Vol 152 ◽  
pp. 1164-1169 ◽  
Author(s):  
Qiwen Jiang ◽  
Jianbo Chen ◽  
Jialin Hou ◽  
Yanhua Liu

2016 ◽  
Vol 2 (1/2) ◽  
pp. 60 ◽  
Author(s):  
Ee May Kan ◽  
Siew Leong Kan ◽  
Yvonne Soh ◽  
Dou Zi ◽  
Khaing Yadanar

Author(s):  
Zina Boussaada ◽  
Guillaume Terrasson ◽  
Alvaro Llaria ◽  
Christophe Merlo ◽  
Octavian Curea ◽  
...  

2017 ◽  
Vol 2 (2) ◽  
pp. 64 ◽  
Author(s):  
Weixian Li ◽  
Thillainathan Logenthiran ◽  
Van-Tung Phan ◽  
Wai Lok Woo

Smart Buildings is a modern building that allows residents to have sustainable comfort with high efficiency of electricity usage. These objectives could be achieved by applying appropriate, capable optimization algorithms and techniques. This paper presents a Housing Development Building Management System (HDBMS) strategy inspired by Building Energy Management System (BEMS) concept that will integrate with smart buildings using Supply Side Management (SSM) and Demand Side Management (DSM) System. HDBMS is a Multi-Agent System (MAS) based decentralized decision making system proposed by various authors. MAS based HDBMS was created using JAVA on a IEEE FIPA compliant multi-agent platform named JADE. It allows agents to communicate, interact and negotiate with energy supply and demand of the smart buildings to provide the optimal energy usage and minimal electricity costs.  This results in reducing the load of the power distribution system in smart buildings which simulation studies has shown the potential of proposed HDBMS strategy to provide the optimal solution for smart building energy management.


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