Collection of data from GHP systems is one challenge and significant strides have been made with the increased availability of data from the increased use of IoT devices and the availability of low-cost web hosting and data storage services. However, as the availability of data increases, analysis of these data can be challenging as the measurement methods vary considerably, accompanied by differences in measurement error, as do the objectives of the analysis and tolerance for uncertainty.
Most common measures of GHP performance rely on measures of both the thermal and electrical energy flows. Thermal energy measurements in GHP systems are particularly challenging because temperature differences can be small and when calculating metrics that rely on multiple measurement points, measurement error can result in signficant uncertainty. Options for measuring electrical energy span a wide range of accuracies and costs. Our research has focused on developing a suite of Python scripts that can satisfy a range of objectives, including methods to quantify uncertainty.
For example, the performance of ground loop serving a GHP system can be characterized by the temperatures that the loop experiences over the course of a year. A closed-loop system that drops below 32 ℉ may indicate under performance (though antifreeze prevents loop fluid from freezing). In the image to the right, the ground loop for site 03561 experiences temperatures as low as 30 ℉ which is largely due to heat not being injected into the ground in summer when air-conditioning. Analysis of ground loop temperature requires only a single measurement and is not significantly impacted by typical measurement errors.
Another example is when utilities are interested in the load that GHP systems place on the electric grid, the magnitude and timing of electricity usage can be quantified for different times of day and for different seasons. will be gaining electric customers In the figure to the left, the average hourly electricity demand is summarized for each season showing that heating has the highest demand in the morning hours while air-conditioning the highest in the afternoon and evening. The 90th percentile for the winter season shows that GHP technology can provide steady baseload demand. This illustrates how utilities can benefit from the transition to GHP systems. First, the transition of heating from fossil fuels to electrically driven heat pumps will increase sales and, second, because heating demand is greatest in off-peak hours, existing electric infrastructure will not require modifications.