Cloud-Based Optimal Control of Individual Borehole Heat Exchangers in a Geothermal Field

Abstract

Integrating renewable energy sources is a crucial component in reducing CO2 emissions in the building sector. In particular, shallow geothermal energy is expected to play a significant role in the regenerative energy supply of buildings. An effective control strategy for the geothermal field is crucial to reduce the overall energy consumption. This paper analyzes the benefits of controlling an existing field’s individual borehole heat exchangers (BHE) using nonlinear model predictive control (NMPC) and moving horizon estimation. The considered geothermal field consists of 41 BHEs and is used for heating and cooling. Each BHE is equipped with temperature sensors for in- and outflow and has individually controllable valves, while a central hydraulic pump feeds all BHEs. The sensor measurements are accessed through a cloud platform, enabling also set point writing for the pump speed and the valve positions. To control the BHEs individually, we propose a two-stage process. In the calibration stage, a moving horizon estimator estimates the actual borehole and ground temperatures for each BHE. In the second stage, first, a nonlinear model predictive controller optimizes the number of active BHEs necessary to meet the buildings’ energy demand. With the estimated ground temperatures as a basis, it is determined which BHEs shall be (de)-activated. The active BHEs are fed with a fixed volume flow of 24 L/min to ensure turbulent heat transfer. To reduce the power usage of the pumps, an optimal control problem based on a simple hydraulic model of the geothermal field is used. The methodology is analyzed through simulations first and then validated experimentally. The results show that half or more of the BHEs could be deactivated most of the time, leading to 67% savings in electricity consumption by the hydraulic pump.The experimental validation confirms the high energy saving potential of the proposed methodology, reducing the consumption of electrical energy by 71%. Additionally, the deactivated BHEs regenerate faster and improve the field’s long-term behavior. In conclusion, the proposed strategy improves the short and long-term performance of the geothermal field.