The integration of renewable energy sources (RES) was amplified, during the past decades, in order to tackle the challenges related to energy demands and CO₂ increases. Recently, many initiatives have been taken by promoting the deployment and the usage of micro-grids (MG) in buildings, as decentralized systems, for energy production. However, the variable nature of RESs and the limited size of energy storage systems require the deployment of adaptive control strategies for efficient energy balance. In this paper, a generalized predictive control (GPC) strategy is introduced for energy management (EM) in MG systems. Its main objective is to efficiently connect the electricity generators and consumers in order to predict the most suitable actions for energy flow management. In fact, based on energy production and consumption profiles as well as the availability of energy storage systems, the proposed EM will be able to select the best suitable energy source for supplying the building’s loads. It will efficiently manage the usage of energy storage and the utility grid while maximizing RESs power generation. Simulations have been conducted, using real-sitting scenarios, and results are presented to validate the proposed predictive control approach by showing its effectiveness for MG systems control.

Despite its advantages over its AC counterparts, DC microgrids present a lot of challenges. One of these challenges is the instability issues caused by constant power loads (CPLs). CPLs deteriorate the system’s performance due to their incremental negative impedance characteristics. In this paper, a DC microgrid composed of a PV/battery system feeding a pure CPL was considered. A continuous-time model predictive control combined with a disturbance observer was applied to the DC–DC bidirectional converter. The purpose of the composite controller is to address the nonlinearity of the CPL and to maintain the stability of the system in a large operating region under load and PV generation variations. To show the performance of the system, several tests were performed under PV power and CPL power variations. Simulation results show good performance in terms of transient response, optimal tracking, and stability in a large operating region.