Model-based energy performance analysis of high pressure processing systems

Mathematical models are developed to simulate the behaviour of high pressure processing systems (single- and multi-cycle processes of different pulse-shapes) and predict the effects of processing parameters on their energy consumption. The validity of the models is established by comparing simulation results with experimental measurements from published works and the present study. Specific energy consumption is shown to depend mainly on holding pressure, pressure medium compressibility, equipment scale and vessel filling efficiency. Inlet temperature, compression and decompression times show negligible effects as do cycle pressure shapes. Longer compression times, however, reduce power capacity requirements, if all other conditions remain constant. The holding time has negligible effects on energy consumption, save for leakages and standby power, hence, extending it does not incur significant energy penalties. On the other hand, a drop in holding pressure leads to a more than proportionate drop in energy consumption. Hence, lower-pressure, longer-time processes are more advantageous from an energy standpoint, provided they satisfy product quality, safety and throughput requirements. Lower-compressibility fluids enable higher pressures to be established with lower energy losses. Higher equipment scales and vessel filling efficiencies reduce the proportion of wasted energy. These conditions are therefore beneficial for energy-efficient operation. Industrial relevance: The production of clean-label, minimally-processed and microbial-safe food products with excellent nutritional, organoleptic properties and extended shelf life is becoming increasingly important. High-pressure processing HPP is a promising technology in this regard, increasingly being deployed at commercial scale. To reduce per-unit HPP product costs, which are currently higher than those of traditional thermal systems, it is important to reduce energy usage, which constitutes a significant proportion of operating costs. The modelling scheme developed in this work would help process designers and operators determine optimal processing conditions with respect to energy consumption, while satisfying product quality and safety constraints; providing a basis for improved process automation.