Implementation of an energy management algorithm in DC MGs using multi‐agent system

Abstract

Summary In this paper, an energy management strategy of direct current (DC) microgrids (MGs) is presented. The proposed MG consists of fuel cells, batteries, and supercapacitors, along with associated DC/DC and DC/AC converters. Coordination between different sources of MG is implemented using a multi‐agent system. Multi‐agent algorithm is implemented using an open source agent building toolkit, Java Agent Development framework (JADE). The energy source components are modeled and implemented using MatLab/Simulink (power system library). The proposed energy management strategy is designed using proportional‐integral (PI) controllers, which is implemented using the JADE. Interface between MatLab/Simulink and multi‐agent system (JADE) is done with the help of MACSimJX. The proposed multi‐agent framework is presented and the interface between the JADE and MatLab/Simulink is described in details. Then, the design and implementation steps of the PI controller using JADE are presented. Simulation work is carried out, and the results show that the proposed multi‐agent‐based controller effectively coordinated with variable loads in MG.

Development of a Mas Based Distributed Intelligent Control and Fault Control Strategy for Microgrid

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P‐type non‐isolated boost DC‐DC converter with high voltage gain and extensibility for DC microgrid applications

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“…Considering that the use of renewable energies has already accelerated and so that the main focus of the microgrids is renewable resources such as biomass, photovoltaics, and wind turbines. 1,2 In the DC and AC microgrids, the output of the microgrids, which includes solar panels, wind turbines, biomass, and so on, as shown in Figure 1, is connected to the load or utility by power electronic converters. The DC-DC converter is one of the important devices in the interface circuit to match the output microgrids to the desired value.…”

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