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The demand for electricity is increased due to the development of the industry, the electrification of transport, the rise of household demand, and the increase in demand for digitally connected devices and air conditioning systems. For that, solutions and actions should be developed for greater consumers of electricity. For instance, MG (Micro-grid) buildings are one of the main consumers of electricity, and if they are correctly constructed, controlled, and operated, a significant energy saving can be attained. As a solution, hybrid RES (renewable energy source) systems are proposed, offering the possibility for simple consumers to be producers of electricity. This hybrid system contains different renewable generators connected to energy storage systems, making it possible to locally produce a part of energy in order to minimize the consumption from the utility grid. This work gives a concise state-of-the-art overview of the main control approaches for energy management in MG systems. Principally, this study is carried out in order to define the suitable control approach for MGs for energy management in buildings. A classification of approaches is also given in order to shed more light on the need for predictive control for energy management in MGs.

Micro-Grid (MG) systems have been extensively studied and deployed to lower the power consumption while reducing the greenhouse gas emissions. Although, the challenge with Renewable Energy Sources (RES) is their uncertain and intermittent nature, things that led the researchers to think about integrating storage devices, especially batteries, into MG systems. The main aim is to store the excess of produced energy for further usage when not enough energy is available. Nevertheless, batteries modeling and characterization is mandatory to identify their parameters and study their performance within MG systems. Moreover, in order to continuously supply electricity to the building, it is required to figure out the optimum size of energy production systems and storage devices. This paper introduces a methodology for MG modeling and performance evaluation. Its main contribution is twofold, (i) battery’s parameters identification, and (ii) modeling and dimensioning method for both standalone and MG systems. An instrumentation platform, composed of recent sensing and actuating equipment, for MG energy management and battery characterization is developed. Simulation and experimental results show the effectiveness of the proposed methodology.