A study on the energy management in domestic micro-grids based on Model Predictive Control strategies

Highlights: • Development of a domestic microgrid and house thermal model. • Model Predictive Control for simultaneous management of power flow and thermal comfort. • Modeling of summer and winter typical conditions. • Comparison with standard rule based controller results. • Fuel cell downsizing potential of output is up to 60%. - Abstract: In this paper a Model Predictive Control (MPC) logic, based on weather forecasts, has been applied to the analysis of power management in a domestic off-grid system. The system is laid out as the integration of renewable energy conversion devices (Photovoltaic, PV), a high efficiency energy conversion programmable system (a Fuel Cell, FC) and an electrochemical energy storage (batteries). The control strategy has the objective of minimizing energy costs, while maintaining the optimal environmental comfort in the house, thus optimizing the use of renewable sources. To that aim, a validated numerical model of the whole system has been developed, and simulations have been carried out for winter and summer periods. Performances attainable with a MPC-based logic have been evaluated in comparison with a standard Rule Based Control logic, by means of costs and efficiency parameters of the micro-grid. Temperature violations have been taken into account to represent the impact of the control on comfort. Results show an improvement of the house comfort conditions and a lower use (on average 14.5%) of primary fossil energy. This is due both to a reduction of required energy, and to an increased use of renewable energy sources. Moreover, the modulation of the HVAC load and of the FC operation gives a reduction of requested power by approximately 40%. Smoother battery pack charge and discharge processes are also obtained. As a main positive effect, a reduction of the FC powerplant size and an increase of its durability seems feasible, leading to an overall reduction of capital costs