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Main Authors: Song, Wonsun, Harzer, Jakob, Jung, Christopher, Sander, Leon, Diehl, Moritz
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.07427
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author Song, Wonsun
Harzer, Jakob
Jung, Christopher
Sander, Leon
Diehl, Moritz
author_facet Song, Wonsun
Harzer, Jakob
Jung, Christopher
Sander, Leon
Diehl, Moritz
contents The transition to a carbon-neutral energy system requires widespread deployment of renewable energy sources and economically feasible energy storage solutions. This study presents a comprehensive optimization framework that jointly addresses the design and control of a nonlinear energy system supplying both heat and electricity to the Dietenbach district in Freiburg, Germany. The proposed system integrates solar and wind power with battery storage and seasonal thermal energy storage coupled via a heat pump, enhancing self-sufficiency and mitigating seasonal supply-demand mismatches. A multi-node lumped-parameter model captures heat transfer within the pit thermal energy storage, forming the basis of a periodic optimal control problem solved numerically. An averaging method reduces computation time by 80.5% while preserving fidelity for year-long optimization. A case study shows a projected total yearly energy cost of 5.93 EUR/m2 for combined heat and electricity, which is 73% lower than the German average. This study underscores the feasibility of designing economically viable, autonomous energy communities in real-world scenarios and provides an efficient, robust optimization framework for designing system components and operational control strategies.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07427
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Novel Numerical Method for Simultaneous Design and Control Optimization of Seasonal Thermal Energy Storage Systems
Song, Wonsun
Harzer, Jakob
Jung, Christopher
Sander, Leon
Diehl, Moritz
Optimization and Control
The transition to a carbon-neutral energy system requires widespread deployment of renewable energy sources and economically feasible energy storage solutions. This study presents a comprehensive optimization framework that jointly addresses the design and control of a nonlinear energy system supplying both heat and electricity to the Dietenbach district in Freiburg, Germany. The proposed system integrates solar and wind power with battery storage and seasonal thermal energy storage coupled via a heat pump, enhancing self-sufficiency and mitigating seasonal supply-demand mismatches. A multi-node lumped-parameter model captures heat transfer within the pit thermal energy storage, forming the basis of a periodic optimal control problem solved numerically. An averaging method reduces computation time by 80.5% while preserving fidelity for year-long optimization. A case study shows a projected total yearly energy cost of 5.93 EUR/m2 for combined heat and electricity, which is 73% lower than the German average. This study underscores the feasibility of designing economically viable, autonomous energy communities in real-world scenarios and provides an efficient, robust optimization framework for designing system components and operational control strategies.
title Novel Numerical Method for Simultaneous Design and Control Optimization of Seasonal Thermal Energy Storage Systems
topic Optimization and Control
url https://arxiv.org/abs/2501.07427