Enhanced Grey Prediction Model (IGM (1,1)) for Accurate Geothermal Heat Pump Stations Output Temperature Forecasting

Recently, many developed countries have turned to the use of Geothermal Heat Pump Systems (GHPS), an alternative source of renewable energy that is essentially clean, flexible, and freely available. GHPS is environmentally friendly and once installed, either vertically or horizontally, it does not require additional gas for operation. This chapter presents the Improved Grey Prediction Model, also called IGM (1,1) model, to increase the prediction accuracy of the Grey Prediction Model (GM) model that performs the GHPS output temperature prediction. This was based on correcting the current predicted value by subtracting the error between the previous predicted value and the previous immediate mean of the measured value. Subsequently, the IGM (1,1) model was applied to predict the output temperature of the GHPSs at Oklahoma University, the University Politècnica de València, and Oakland University, respectively. For each GHPS, the model uses a small dataset of 24 data points (i.e., 24 h) for training to predict the output temperature eight hours in advance. To evaluate the prediction performance of the improved model, the Root Mean Square Error (RSME), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) were used to measure the prediction accuracy of the IGM (1,1) model. The proposed model was verified using three different output temperature datasets; these datasets were also used to validate the power efficiency of the proposed model. In addition, the empirical results show that the proposed IGM (1,1) model significantly improves the simulation (in-sample) and the prediction (out-of-sample) of the output temperature of the GHPS through error reduction, thereby enhancing the GM (1,1) model’s overall accuracy. As a result, the prediction accuracies were compared, and the improved model was found to be more accurate than the GM (1,1) model in both simulation and prediction results for all datasets used. In the future, improvements are anticipated for the IGM (1,1) to make it even more accurate for geothermal heat pump systems for longer than just the short term.