Model-based optimization of an ORC-based unit integrated in a Carnot Battery

The transition towards renewable energy sources requires proper energy storage capacity to balance energy demand and production. An emerging energy storage solution is represented by Carnot Batteries (CBs), which are based on the integration of a heat pump (HP) and a power unit (PU). Indeed, in a CB the unused electric energy is valorized to run the HP compressor, thus storing a high-temperature thermal energy in a thermal energy storage system. Subsequently, according to the demand, this energy is released through a PU. Among possible configurations, the integration of a HP with an ORC-based power unit gained a significant interest, due to the capability of the ORC to convert the thermal energy (usually at low-medium temperature according to HP characteristics) into electricity. The maturity level of HP components and the feasibility to consider hot water as thermal storage medium add a high interest to CBs. This latter aspect is particularly important, as it enables a low-cost thermal storage represented by hot water, to be scaled-up for a large-scale storage. Despite these benefits, ORC-based power units, especially for small scale applications (1-3 kW), present efficiency penalties under off design conditions, typical when the hot source temperature changes during electricity production. This calls for the development of reliable operating strategies, to maximize the power production of the unit when its operating conditions change. Despite this importance, in literature few analyses have been performed on this topic. To fill this gap, in this paper, a first contribution is presented on the modelling of the integrated HP-PU system during the ORC-based unit operation, i.e. when the thermal source is discharged. This situation is particularly critical considering the low temperature of the PU hot source during discharging (90-110 °C), which limits the efficiency at 4-5%. The developed PU model has been validated thanks to experimental data collected in literature. Once validated, the model has been used as software platform, which allowed to find the best PU operating parameters maximizing electricity production and efficiency.