scholarly journals Microgrid energy management system for smart home using multi-agent system

2022 ◽  
Vol 12 (2) ◽  
pp. 1153
Author(s):  
Reda Jabeur ◽  
Youness Boujoudar ◽  
Mohamed Azeroual ◽  
Ayman Aljarbouh ◽  
Najat Ouaaline
Keyword(s):  
Energy Management ◽  
Management System ◽  
Smart Home ◽  
Energy Management System ◽  
Multi Agent System ◽  
Agent System ◽  
Development Framework ◽  
Multi Agent ◽  
Electrical Loads ◽  
Battery Energy

This paper proposes a multi-agent system for energy management in a microgrid for smart home applications, the microgrid comprises a photovoltaic source, battery energy storage, electrical loads, and an energy management system (EMS) based on smart agents. The microgrid can be connected to the grid or operating in island mode. All distributed sources are implemented using MATLAB/Simulink to simulate a dynamic model of each electrical component. The agent proposed can interact with each other to find the best strategy for energy management using the java agent development framework (JADE) simulator. Furthermore, the proposed agent framework is also validated through a different case study, the efficiency of the proposed approach to schedule local resources and energy management for microgrid is analyzed. The simulation results verify the efficacy of the proposed approach using Simulink/JADE co-simulation.

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

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3655 ◽  
Author(s):  
Aryuanto Soetedjo ◽  
Yusuf Ismail Nakhoda ◽  
Choirul Saleh
Keyword(s):  
Energy Management ◽  
Management System ◽  
Fuzzy Logic Controller ◽  
Optimization Technique ◽  
Building Energy ◽  
Energy Management System ◽  
Multi Agent System ◽  
Agent System ◽  
Building Energy Management ◽  
Multi Agent

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.

Sign in / Sign up

Export Citation Format

Share Document