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Application of Pareto Optimization in an Economic Model Predictive Controlled Microgrid

Schmitt, Thomas and Engel, Jens and Rodemann, Tobias and Adamy, Jürgen (2020):
Application of Pareto Optimization in an Economic Model Predictive Controlled Microgrid.
Germany, 28th Mediteranean Conference on Control and Automation, MED'20, Saint-Raphaël, FRANCE, DOI: 10.25534/tuprints-00011706,
[Conference or Workshop Item]

Abstract

This paper presents an economic model predictive control approach for a linear microgrid model. The microgrid in grid-connected mode represents a medium-sized company building including storage systems, renewable energies and couplings between the electrical and heat energy system. Economic model predictive control together with Pareto optimization is applied to find suitable compromises between two competing objectives, i. e. monetary costs and thermal comfort. Using real-world data from 2018 and 2019, the model is simulated with auto-detection of the Pareto solution which is closest to the Utopia point. The results show that the Pareto optimization can either be used in real-time control of the microgrid, or to obtain suitable weights from long term simulations. Both approaches result in significant cost reductions.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Schmitt, Thomas and Engel, Jens and Rodemann, Tobias and Adamy, Jürgen
Title: Application of Pareto Optimization in an Economic Model Predictive Controlled Microgrid
Language: English
Abstract:

This paper presents an economic model predictive control approach for a linear microgrid model. The microgrid in grid-connected mode represents a medium-sized company building including storage systems, renewable energies and couplings between the electrical and heat energy system. Economic model predictive control together with Pareto optimization is applied to find suitable compromises between two competing objectives, i. e. monetary costs and thermal comfort. Using real-world data from 2018 and 2019, the model is simulated with auto-detection of the Pareto solution which is closest to the Utopia point. The results show that the Pareto optimization can either be used in real-time control of the microgrid, or to obtain suitable weights from long term simulations. Both approaches result in significant cost reductions.

Place of Publication: Germany
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics
Event Title: 28th Mediteranean Conference on Control and Automation, MED'20
Event Location: Saint-Raphaël, FRANCE
Date Deposited: 10 Jun 2020 12:33
DOI: 10.25534/tuprints-00011706
Official URL: https://tuprints.ulb.tu-darmstadt.de/11706
URN: urn:nbn:de:tuda-tuprints-117065
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