This paper presents a framework to analyze the problem of real-time management of Smart Grids. For this purpose, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems (MAS) leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. With this framework it was possible to evaluate the design of the energy management and the impact of the algorithm developed in the MAS. In the same way, the data sent from the power system to be used for energy management have a direct impact on his behavior. The proposed framework is tested with the help of a microgrid, so the results may be replicated.
This paper deals with the problem of real-time management of Smart Grids. For this sake, 1 the energy management is integrated with the power system through a telecommunication system.
2The use of Multiagent Systems leads the proposed algorithm to find the best-integrated solution, 3 taking into consideration the operating scenario and the system characteristics. The proposed 4 technique is tested with the help of an academic microgrid, so the results may be replicated.
This paper aims the planning, construction and modeling of a low-cost multivariable level plant for didactic purposes. The developed model has two pumps that feed four tanks coupled to each other. Between the tanks and the pumps, there are inlet and outlet valves that can change the system dynamics according to its opening configuration. To automate the pumps and read the instrumentation used, the Arduino microcontroller was chosen because it is a model of great use in the academic environment and of easy parameterization. For sensing, the HC-SR04 ultrasonic sensor was chosen, which already has native compatibility with the microcontroller. In order to validate the constructed plant, it was necessary to identify its model, using the empirical step response method for this purpose. In this way, this work has both qualitative and quantitative characteristics, since the planning and construction of the didactic plant involved an exploratory research of the problem, and then the modeling and simulation method was applied to obtain the mathematical model of the plant. Finally, an experimental research was conducted, comparing the data obtained in the real plant with the model data for validation. Having completed all research stages, the work result is a didactic plant with good linearity, able to provide implementation of level control strategies of coupled tanks and to assist in teaching and learning subjects that involve concepts of dynamic systems, besides multivariable systems identification and control.
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