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Energies 2018, 11(12), 3461; https://doi.org/10.3390/en11123461

Economic Multiple Model Predictive Control for HVAC Systems—A Case Study for a Food Manufacturer in Germany

Department for Sustainable Products and Processes (upp), University of Kassel, 34125 Kassel, Germany
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Received: 31 October 2018 / Revised: 29 November 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
(This article belongs to the Collection Smart Grid)
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Abstract

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible Renewable Energies levy (EEG levy) was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering the electricity price and weather forecasts as well as an internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system. View Full-Text
Keywords: model predictive control; HVAC; climate control; flexible control technologies model predictive control; HVAC; climate control; flexible control technologies
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Heidrich, T.; Grobe, J.; Meschede, H.; Hesselbach, J. Economic Multiple Model Predictive Control for HVAC Systems—A Case Study for a Food Manufacturer in Germany. Energies 2018, 11, 3461.

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