In this paper, an energy coordination control method based on intelligent multi-agent systems (MAS) is proposed for energy management and voltage control of a DC microgrid. The structure of the DC microgrid is designed to realize the mathematical modeling of photovoltaic cells, fuel cells and batteries. A two-layer intelligent MAS is designed for energy coordination control: grid-connection and islanding of a DC microgrid is combined with energy management of PV cells, fuel cells, loads and batteries. In the hidden layer and the output layer of the proposed neural network there are 17 and 8 neurons, respectively, and the “logsig” activation function is used for the neurons in the network. Eight kinds of feature quantities and 13 different actions are taken as the input and output parameters of the neural network from the micro-source and the load, and the as the control center agent’s decision-makers. The feasibility of the proposed intelligent multi-agent energy coordination control strategy is verified by MATLAB/Simulink simulation, and three types of examples are analyzed after increasing the load. The simulation results show that the proposed scheme exhibits better performance than the traditional approaches.
This paper proposes the development of a formation control algorithm of multiple acoustic underwater vehicles by employing the behaviour of autonomous mobile agents under a proposed pursuit. A robust pursuit is developed using the distributed consensus coordinated algorithm ensuring the transfer of information among the AUVs. The development of robust pursuit based on characteristics of multi-agent system is for solving the incomplete information capabilities in each agent such as asynchronous computation, decentralized data and no system global control. In unreliable and narrow banded underwater acoustic medium, the formation of AUVs based distributed coordinated consensus tracking can be accomplished under the constant or varying virtual leader’s velocity. Further, the study to achieve tracking based on virtual leader AUV’s velocity is extended to fixed and switching network topologies. Again for mild connectivity, an adjacency matrix is defined in such a way that an adaptive connectivity is ensured between the AUVs. The constant virtual leader vehicle velocity method based on consensus tracking is more robust to reduce inaccuracy because no accurate position and velocity measurements are required. Results were obtained using MATLAB and acquired outcomes are analysed for efficient formation control in presence of the underwater communication constraints.
The smart grid concept is predicated upon the pervasive use of advanced digital communication, information techniques, and artificial intelligence for the current power system, to be more characteristics of the real-time monitoring and controlling of the supply/demand. Microgrids are modern types of power systems used for distributed energy resource (DER) integration. However, the microgrid energy management, the control, and protection of microgrid components (energy sources, loads, and local storage units) is an important challenge. In this paper, the distributed energy management algorithm and control strategy of a smart microgrid is proposed using an intelligent multi-agent system (MAS) approach to achieve multiple objectives in real-time. The MAS proposed is developed with co-simulation tools, which the microgrid model, simulated using MATLAB/Simulink, and the MAS algorithm implemented in JADE through a middleware MACSimJX. The main study is to develop a new approach, able to communicate a multi-task environment such as MAS inside the S-function block of Simulink, to achieve the optimal energy management objectives.
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