Hybrid Geothermal System Research Articles

A variable water flow rate control method of hybrid geothermal heat pump systems

In the long-term operation of a geothermal heat pump system, when the cooling load is high, the temperature rise in the ground due to heat accumulation occurs. Changes in ground temperature hinder recovery of the temperature on the heat source side of the heat pump, and the performance of the geothermal system deteriorates because the heat exchange efficiency of the circulating water decreases. This problem can be solved by operating a hybrid geothermal system composed of an additional heat source system to the geothermal system. Therefore, in this paper, a method for operating a hybrid geothermal heat pump system was proposed to solve the degradation of system performance due to the temperature rise in the ground due to heat accumulation. The operating conditions for starting the operation of the hybrid geothermal heat pump system were derived, and the coefficient of performance prediction model was proposed for flow rate control considering the energy of the pump and the heat pump system. In addition, the proposed control method was evaluated for energy saving and performance improvement through simulation, and was also evaluated in terms of economic feasibility.

A COP Prediction Model of Hybrid Geothermal Heat Pump Systems based on ANN and SVM with Hyper-Parameters Optimization

When the geothermal heat pump system is operated due to an imbalance in the heating and cooling load, the system performance is lowered due to the occurrence of a thermal environment problem in the ground. To solve the performance degradation, a hybrid geothermal heat pump system with an added auxiliary heat source is used. For the efficient operation of the system, it is necessary to check the performance coefficient of the hybrid geothermal system. The coefficient of performance can be monitored based on a mathematical model using a measuring instrument. However, in the case of mathematical models, there are a lot of input data required, and many measurement sensors are required for this. If there is an input factor that is omitted among the necessary input factors, the accuracy of the predicted performance coefficient is lowered or a problem occurs that it is impossible to predict. In this study, we intend to create a model that predicts the coefficient of performance (COP) by using ANNs and SVMs that can accurately predict at low cost using small input factors. Hyper-parameter optimization is performed to increase prediction accuracy in machine learning models. We compared the accuracy of ANN and SVM-based prediction models. In this study, the ANN model showed higher CvRMSE by 5.4% and SVM by 8%. It is expected that the predictive model will be able to be used in the operation of the hybrid geothermal system in the future.

Full-scale utilization of geothermal energy: A high-efficiency CO2 hybrid cogeneration system with low-temperature waste heat

The utilization of geothermal energy is becoming increasingly important in the current transition towards sustainable energy sources. Among the various methods of utilizing geothermal energy, the use of hybrid geothermal power plants that exploit CO2 fluid for preheating in electricity generation has been identified as an attractive approach. Additionally, the shallow ground source heat pump (SGSHP) has been proven to be superior in previous experimental studies. However, the full-scale utilization of geothermal energy, through generating electricity from geothermal power plants and applying waste heat with SGSHPs for auxiliary heating, needs further exploration. This study proposes a novel CO2 hybrid geothermal system that incorporates a GSHP heating system. The hybrid geothermal system uses CO2 as the underground working fluid, and the electricity and waste heat are used to assist the GSHP for heating, ventilation, and air conditioning. The proposed system can produce 11.41 MW of electricity, 80 °C of hot water, and 34.76 MW of cold energy by driving 50 MW of the geothermal heat. Through a comprehensive analysis of the economy, energy, exergy, and environment, the results demonstrate that the maximum exergy damage of the refrigeration power cycle is 37999.33 kW, which has the highest exergy losses. The exergy loss of the steam turbine heat power conversion in the geothermal power generation process is the highest, but this loss can be effectively reduced through heat integration. The optimal cooling temperature of the coupled system should be set at 8 °C, and it has a good investment prospect. In summary, the CO2 hybrid geothermal system can realize effective cogeneration and fully utilize geothermal energy. Therefore, it has great potential to contribute to the transition towards a sustainable energy future.

A Methodology for Long-Term Model Predictive Control of Hybrid Geothermal Systems: The Shadow-Cost Formulation

Model Predictive Control (MPC) predictive’s nature makes it attractive for controlling high-capacity structures such as thermally activated building systems (TABS). Using weather predictions in the order of days, the system is able to react in advance to changes in the building heating and cooling needs. However, this prediction horizon window may be sub-optimal when hybrid geothermal systems are used, since the ground dynamics are in the order of months and even years. This paper proposes a methodology that includes a shadow-cost in the objective function to take into account the long-term effects that appear in the borefield. The shadow-cost is computed for a given long-term horizon that is discretized over time using predictions of the building heating and cooling needs. The methodology is applied to a case with only heating and active regeneration of the ground thermal balance. Results show that the formulation with the shadow cost is able to optimally use the active regeneration, reducing the overall operational costs at the expenses of an increased computational time. The effects of the shadow cost long-term horizon and the predictions accuracy are also investigated.

Development of Changeover Operating Method Based on Performance Prediction of Hybrid Geothermal Heat Pump Systems through Field Test and Numerical Analysis

The installation and operation of geothermal systems increased due to the expectation of good cooling and heating performance due to stable heat source temperatures. In actual geothermal system operations, heat source temperature rises or falls due to an imbalance of heating and cooling energy usage. Problems of source side temperature result in reduced geothermal system performance. The purpose of this study is to develop hybrid geothermal system operation technology to stabilize temperature and improve system performance by utilizing auxiliary heat source system. The auxiliary heat source system is operated by comparing the performance when operating the geothermal heat pump system alone and the performance when operating the hybrid geothermal heat pump system. The performance of a hybrid geothermal system is determined by the circulating water temperature of the geothermal system and the circulating water temperature of the auxiliary heat source system. Hybrid geothermal heat pump system performance is predicted through numerical analysis and collection of hybrid geothermal system performance data at various temperature ranges through field test. An operating method was developed using the predicted performance as the changeover operating point of the hybrid geothermal heat pump system. When applying the development and operation technology, it handled about 11% more load than the existing geothermal system operation. The addition of an auxiliary heat source increases the initial investment cost compared to the existing geothermal system, but decreases energy consumption, confirming that the initial investment cost of 15.3 years is recovered.

Combining brine or CO2 geothermal preheating with low-temperature waste heat: A higher-efficiency hybrid geothermal power system

Abstract Hybrid geothermal power plants operate by using geothermal fluid to preheat the working fluid of a higher-temperature power cycle for electricity generation. This has been shown to yield higher electricity generation than the combination of a stand-alone geothermal power plant and the higher-temperature power cycle. Here, we test both a direct CO2 hybrid geothermal system and an indirect brine hybrid geothermal system. The direct CO2 hybrid geothermal system is a CO2 Plume Geothermal (CPG) system, which uses CO2 as the subsurface working fluid, but with auxiliary heat addition to the geologically produced CO2 at the surface. The indirect brine geothermal system uses the hot geologically produced brine to preheat the secondary working fluid (CO2) within a secondary power cycle. We find that the direct CPG-hybrid system and the indirect brine-hybrid system both can generate 20 % more electric power than the summed power of individual geothermal and auxiliary systems in some cases. Each hybrid system has an optimum turbine inlet temperature which maximizes the electric power generated, and is typically between 100 °C and 200 °C in the systems examined. The optimum turbine inlet temperature tends to occur where the geothermal heat contribution is between 50 % and 70 % of the total heat addition to the hybrid system. Lastly, the CO2 direct system has lower wellhead temperatures than indirect brine and therefore can utilize lower temperature resources.

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

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.