Short-term modeling of hybrid geothermal systems for Model Predictive Control

Abstract

Model Predictive Control (MPC) has shown significant energy savings potential in the operation of building energy systems, yet it needs accurate and simple models for optimization. In hybrid geothermal systems the source-side temperatures affect the system efficiency and its operational feasibility. Since the ground dynamics are rather slow, simplifications such as considering a constant coefficient of performance (COP) are made. We evaluate the added value of including a short-term dynamic borefield model to the controller. Simulations are performed in a heating-dominated building equipped with a hybrid geothermal system for two winter weeks. We consider 4 different modeling strategies where the formulation of the COP and the return fluid temperature from the borefield is varied in complexity. Results show that using a constant COP results in a bang-bang behavior of the heat pump, while with an accurate prediction of the COP the operation is smoother, saving 0.46%, 1.86% and 2.71% for low, average and high electricity-to-gas price ratios respectively. Including a short-term borefield model avoids shutting down the heat pump due to safety constraints which saves up to 8.12% more money while the use of the ground-source is quintupled. Despite reducing the optimization iteration number by almost 18%, simulation time is increased.