Investigation of synergies between solar energy and high-temperature heat pumps for process heat applications in Germany using nonlinear techno-economic optimization

The combination of solar energy and high-temperature heat pumps shows promising potential for supplying low to medium temperature process heat, even in countries with moderate available irradiation. To date, combinations of solar thermal collectors, high-temperature heat pumps, and thermal energy storage have been investigated for process heat applications. This study additionally considers hybridization with solar power from photovoltaics and battery energy storage, enabling the continuous supply of a representative process heat demand at 200 °C in Germany. To assess the synergies in various complex system configurations combining solar thermal, solar power, heat pump, and storage, a novel optimization algorithm is introduced. The optimization considers design and operational aspects by utilizing nonlinear component models to capture the complex dependencies between temperatures, mass flows, and power flows with the aim to minimize costs and emissions. Because the techno-economic optimization leads to a large-scale nonlinear multi-objective optimization problem that is computationally intensive, the algorithm applies different decomposition techniques while maintaining a high level of model detail. The results show that the investigated systems can reduce operating emissions by 48% on average while remaining cost-competitive with fossil burners. A configuration with parabolic trough collectors and heat pump in parallel, coupled with thermal energy storage in series and supported by photovoltaics, performs best at all three German sites investigated. Additionally, the results highlight the importance of nonlinear models for optimizing system design and operational strategies to identify non-obvious synergies.