Hierarchical model predictive control for energy management of power-to-X systems

Conference Paper (2020)
Author(s)

Oguzhan Kaya (Student TU Delft)

Els van der Roest (KWR Water Research Institute)

Dirk Vries (KWR Water Research Institute)

T. Keviczky (TU Delft - Team Tamas Keviczky)

Research Group
Team Tamas Keviczky
Copyright
© 2020 Oguzhan Kaya, Els Van Der Roest, Dirk Vries, T. Keviczky
DOI related publication
https://doi.org/10.1109/ISGT-Europe47291.2020.9248892
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Oguzhan Kaya, Els Van Der Roest, Dirk Vries, T. Keviczky
Research Group
Team Tamas Keviczky
Pages (from-to)
1094-1098
ISBN (electronic)
978-1-7281-7100-5
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Abstract

This paper presents the application of Hierarchical Model Predictive Control (HMPC) as an energy management framework for a multi-timescale mixed-energy system, i.e., Power-to-X (PtX). The goal of the energy managing controller is to minimize an economic objective by determining the energy flows within the system. HMPC enables a long-term scheduling solution to anticipate ahead of the seasonal energy mismatches occurring in PtX systems. This paper presents a novel approach to couple the separate control layers in the hierarchy by heuristic assignment to fully employ the PtX fundamentals in the controller design. Simulation results based on historical data of the Dutch energy sector show the suitability of HMPC and its superiority over a rule-based control approach. The proposed controller may, however, also be used for any configuration of multi-timescale mixed-energy systems dealing with temporal energy mismatches.

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