Case Study with Comparison of Home Energy Optimization and Control Algorithms

To ensure an optimal use of energy on household level, the interaction of multiple household components has to
be optimized. Therefore, different algorithms like control loops and model predictive control methods (MPC) are implemented and tested at the real-world research environment Energy Smart Home Lab (ESHL). In an additional simulation environment, the coordination of further components is shown in theory. The purpose lies in finding an optimal battery operation considering actual photovoltaic and load changes driven by weather conditions and the behaviour of the residents. As objectives, the power exchange with the connected distribution grid is to be reduced in order to relief the grid and the economic costs are to be reduced. The rolling horizon in the real-time optimization includes the next 24 hours segmented in a time step delta of five minutes. In a case study during a residential period in the Energy Smart Home Lab, the algorithms are executed and compared. Additionally, it can be seen that the potential for flexibility is highly dependent on accurate forecasts of future generation and consumption.