This research project aims to develop a strategy to manage the energy consumption and comfort in smart buildings equipped with renewable resources such as photovoltaic generation (PV), and energy storage system (ESS). The approach considers the management of the heating, ventilation and air conditioning (HVAC) units and lighting appliances, since they represent the two largest loads in a typical building, and coordinates PV, ESS and the energy traded with the main grid. The goal is to reduce the electrical bill of the building by managing the loads, as well as scheduling of ESS, meanwhile suitable indoor conditions are ensured to guarantee the comfort of the users. In the literature there are different strategies to solve the building operation problem. Approaches based on building analysis tools can capture well the dynamics of the building but have the disadvantage of requiring a design phase to develop the model and high processing time. Some strategies are based on non-linear models that require the use of iterative methods. On the other hand, the strategies that use simpler models allow analytical optimal solution with a lower processing time but it can compromise the accuracy of the analysis. Thus, the present project combines approximated models with the accuracy of a building analysis tool, in this case EnergyPlus, in order to obtain a new mixed integer linear programing (MILP) model that can be solved using commercial solvers, which guarantee the optimality. This approach reduce the processing time since it does not use several simulations such as the co-simulation strategies, and improve the accuracy of the modeling by executing a pre-processing stage by EnergyPlus. The main objective of the project is to study the impacts of the management strategy in the indoor conditions, the energy consumption of the building and the distribution grid.
News published in Agência FAPESP Newsletter about the scholarship: