Master's Thesis Juan Moreno
Implementation of an exergy-based control strategy in a building automation system
Regarding the final energy consumption, the buildings sector represents the largest energy consuming sector, being responsible for more than 40% of the worldwide consumption. The efficiency improvement of current control algorithms plays an important role in shifting the consumption into a more sustainable path. The main objective of this Master’s thesis is the implementation of an existing model predictive exergy based control algorithm (BExMoC - Building Exergy-based Model Predictive Control Algorithm) in the automation system of a real building. I consider the E.ON ERC main building, which is equipped with a complex energy supply system and a Monitoring, Control and Interface System (MCIS).
Given the complexity of the building’s energy system, one out of twelve supply chains is selected for the implementation. Initially, existing Modelica models of the low temperature heating and cooling circuits within the ERC main building are improved. In this stage of the thesis, I use an optimization tool to estimate the model parameters that are not available or cannot be measured. With this approach, reliable parameters are determined. I validate these models against measurement data recorded by the MCIS.
The BExMoC algorithm was developed and tested at the Institute for Energy Efficient Buildings and Indoor Climate for a specific case study, before the beginning of this thesis. Therefore, in the next step, I further develop and generalize the algorithm. Before the implementation, I test the algorithm and the developed Modelica models of the selected supply chain using Software-in-the-Loop experiments. I compare the performance of the BExMoC algorithm with a reference model with conventional controllers. In these experiments, the algorithm’s high potential regarding energy consumption savings is evident. Savings over 20% can be achieved. However, the BExMoC control quality does not exceed the reference case.
After the theoretical testing, I perform the implementation of the control algorithm in the selected closed supply chain in the low temperature heating circuit of the E.ON ERC main building. Two different case studies are considered during the implementation. Results show that the algorithm is able to select plausible actuator set points by minimizing the exergy destruction and losses of the entire system.