Abstract

A key strategy for the transition towards a low-carbon economy is the electrification of industrial heat. Heat pumps can recover and upgrade excess or waste heat. They present a highly efficient component to decarbonize process heating. In Pinch Analysis, most approaches to design the heat recovery system as well as the utility system are based on a single operating point or a couple of operating point. In the past, this was due to the lack of temporally detailed process data. However, the available process data is expected to increase drastically by the use of transient process simulation models. Thus, a method is needed which interprets the data correctly and assists with design choices.This study proposes a methodology for the design and sizing of a heat pump based on the simulated annual process data of an industrial process. Three approaches are explored: (1) the conventional approach for heat pump integration by application of the Time Average Model (TAM), (2) an approach that investigates the optimal heat pump parameters for each data point by the principles of Pinch Analysis and mathematical optimization and (3) an optimization method, which considers the entire annual process data as well as thermo-economic objectives such as net present value (NPV) and internal rate of return (IRR).The new methodology compared to the conventional TAM approach is able to design a 33 % smaller heat pump, which reduces the annual operating cost by an additional 2.2 %. The NPV and IRR are more than tripled.

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