arXiv subjects

Eckhard A. Groll

Publications and source records attributed to Eckhard A. Groll.

4 recordsLinked to original sources

arXiv2026

Laboratory and field testing of a residential heat pump retrofit for a DC solar nanogrid

Residential buildings are increasingly integrating large devices that run natively on direct current (DC), such as solar photovoltaics, electric vehicles, stationary batteries, and DC motors that drive heat pumps and other major appliances. Today, these natively-DC devices typically connect within buildings through alternating current (AC) distribution systems, entailing significant energy losses due to conversions between AC and DC. This paper investigates the alternative of connecting DC devices through DC distribution. Specifically, this paper shows through laboratory and field experiments that an off-the-shelf residential heat pump designed for conventional AC systems can be powered directly on DC with few hardware modifications and little change in performance. Supporting simulations of a DC nanogrid including {historical heat pump and rest-of-house load measurements,} a solar photovoltaic array, and a stationary battery suggest that connecting these devices through DC distribution could decrease annual electricity bills by 12.5% with an after-market AC-to-DC heat pump retrofit and by 16.7% with a heat pump designed to run on DC. The associated savings in gross nanogrid energy are 8% and 9.2%, respectively.

eess.SY↗

arXiv2025

Asymptotic Behavior of a Buoyant Jet Regime inside a Carbon-dioxide Ejector

Ejectors are used in various engineering systems, including steam and vapor compression cycles. Optimizing the performance of ejectors requires understanding and analysis of multiphase and turbulent flow structures associated with their internal flow fields. This approach yields higher fidelity but at a high computational cost. Lower-fidelity one-dimensional (1D) models offer lower computational costs; however, 1D models are often empirical and provide limited understanding of the internal flow fields, overlooking possibilities of optimization. Ejector flows can be categorized into four regimes: Regime 1 (R1), which is compressibility dominated; Regime 2 (R2), which is interface instability driven; Regime 3 (R3), which is buoyancy dominated; and Regime 4 (R4), which is a wall-bounded turbulent jet expansion. Among these, the buoyancy-dominated regime is the most complex and least understood. This work discusses an approach to develop a reduced-order model utilizing a self-similarity framework to capture the internal flow field of the jet within the buoyancy-dominated regime under quasi-steady, compressible, and isothermal flow conditions, where density variations arise only from mixing. The density variation is captured through the Favre-averaging approach. The model captures the expansion of a central jet influenced by momentum diffusivity and a constant streamwise pressure gradient. Interaction of the central jet with the cylindrical wall induces a counterflow annular wall jet due to the combined effects of negative radial density gradients and shear stress imposed by the wall. Initially, the discussion focuses on flow topology inside the ejector, followed by the self-similarity methodology and implementation of asymptotic analysis. Finally, the resemblance...

physics.flu-dyn↗

arXiv2025

Protecting residential electrical panels and service through model predictive control: A field study

Residential electrification - replacing fossil-fueled appliances and vehicles with electric machines - can significantly reduce greenhouse gas emissions and air pollution. However, installing electric appliances or vehicle charging in a residential building can sharply increase its current draws. In older housing, high current draws can jeopardize electrical infrastructure, such as circuit breaker panels or electrical service (the wires that connect a building to the distribution grid). Upgrading electrical infrastructure can entail long delays and high costs, so poses a significant barrier to electrification. This paper develops and field-tests a control system that avoids the need for electrical upgrades by keeping an electrified home's total current draw within the safe limits of its panel and service. In the proposed control architecture, a high-level controller plans device set-points over a rolling prediction horizon. A low-level controller monitors real-time conditions and ramps down devices if necessary. The control system was tested in an occupied, electrified single-family house with code-minimum insulation, an air-to-air heat pump and backup resistance heat, a resistance water heater, and a plug-in hybrid electric vehicle with Level I charging. The field tests spanned 31 winter days with outdoor temperatures as low as -20 C. The control system maintained the whole-home current within the safe limits of electrical panels and service rated at 100 A, a common rating for older houses in North America, by adjusting only the temperature set-points of the heat pump and water heater. Simulations suggest that the same 100 A limit could accommodate a second electric vehicle with Level II charging. The proposed control system could allow older homes to safely electrify without upgrading electrical panels or service, saving a typical household on the order of $2,000 to $10,000.

eess.SY↗

arXiv2024

Field demonstration of predictive heating control for an all-electric house in a cold climate

Efficient electric heat pumps that replace fossil-fueled heating systems could significantly reduce greenhouse gas emissions. However, electric heat pumps can sharply increase electricity demand, causing high utility bills and stressing the power grid. Residential neighborhoods could see particularly high electricity demand during cold weather, when heat demand rises and heat pump efficiencies fall. This paper presents the development and field demonstration of a predictive control system for an air-to-air heat pump with backup electric resistance heat. The control system adjusts indoor temperature set-points based on weather forecasts, occupancy conditions, and data-driven models of the building and heating equipment. Field tests from January to March of 2023 in an occupied, all-electric, 208 m^2 detached single-family house in Indiana, USA, included outdoor temperatures as low as -15 C. On average over these tests, the control system reduced daily heating energy use by 19% (95% confidence interval: 13--24%), energy used for backup heat by 38%, and the frequency of using the highest stage (19 kW) of backup heat by 83%. Concurrent surveys of residents showed that the control system maintained satisfactory thermal comfort. The control system could reduce the house's total annual heating costs by about $300 (95% confidence interval: 23--34%). These real-world results could strengthen the case for deploying predictive home heating control, bringing the technology one step closer to reducing emissions, utility bills, and power grid impacts at scale.

eess.SY↗