Integration of Heat Pump Storage Systems in Manufacturing Systems via Data Farming and Monte Carlo Simulation
Seevers, Jan-Peter
Schlosser, Florian
Download PDF

How to Cite

Seevers J.-P., Schlosser F., 2019, Integration of Heat Pump Storage Systems in Manufacturing Systems via Data Farming and Monte Carlo Simulation, Chemical Engineering Transactions, 76, 373-378.
Download PDF

Abstract

The electrification of industrial energy demand is essential for effective climate protection and a successful energy transition. In production systems with fluctuating heating and cooling demands, heat pumps can make a significant contribution to electrification and increased efficiency in a demand-oriented production with automated standby operation. In order to dimension a suitable heat pump storage system, well-founded statistical information about the production system is required. For the creation of stochastic heating and cooling demand profiles, numerous material flow simulations were therefore carried out as part of a case study, whereby the simulated time is always a production week in seconds resolution with shutdown at the weekend. Input data for the simulation are real energy measurement data from an energy monitoring system. The results of the Monte Carlo simulation show that relatively small heat pumps and storages can ensure the reliable heat and cold supply of the manufacturing system thanks to the superposition and mutual compensation of numerous sources of uncertainty in the manufacturing system. In the case study presented in this paper, covering a constantly running HP in only 95 % of all possible cases instead of the entire 100 % leads to a drastic reduction in storage volume by a factor of about 25.
Download PDF