Effects of non-industrial decentralized demand-side-management on energy costs and battery storage requirement in Germany's power grid

As the share of volatile renewable energy sources in the electrical power grid continues to grow, needed additional system flexibility can be provided by energy storages, power transmission, and demand-side-management. The interplay between these three elements has recently gained interest in the field of energy system modeling. This study aims to determine the impact of potential non-industrial demand-side-management technologies, including heat pumps, controlled charging of battery electric vehicles, refrigeration, and air conditioning, on energy costs and battery storage requirements in Germany's future electrical power system. The model is analyzed using a novel modeling approach that enables a comparison of flexible loads responding to different market conditions: centralized market conditions with uniform market prices and decentralized market conditions with nodal prices, considering the congestion management potential of demand-side-management. The results show that non-industrial flexible loads can significantly affect the need for battery storage if high residual load peaks can be reduced by the specific technology. However, energy costs may only be reduced by up to 10 %. The study emphasizes the potential of demand-side-management for mitigating grid congestions, demonstrating that investment in battery storages may be lowered by up to 40 % when comparing centralized and decentralized market conditions. • Analysis of four non-industrial DSM technologies in national energy system model. • Modelling method compares DSM response to uniform vs. nodal electricity prices. • DSM may reduce operational energy costs and investment in battery storages. • Grid congestion may limit the cost reduction impact of DSM for electricity market. • Nodal pricing for DSM may support grid management and reduce grid congestion costs.

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Publication Details

Journal
Energy
Published
2025-03-30
DOI
https://doi.org/10.1016/j.energy.2025.135892
Citations
4
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
2.92

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article

Effects of non-industrial decentralized demand-side-management on energy costs and battery storage requirement in Germany's power grid

Ingo Stadler, Arjuna Nebel, Bennet Köppchen
4 citations
Energy
Integrated Energy Systems Optimization
2.92
article

Effects of non-industrial decentralized demand-side-management on energy costs and battery storage requirement in Germany's power grid

Ingo Stadler, Arjuna Nebel, Bennet Köppchen
article en
4 citations

Abstract

As the share of volatile renewable energy sources in the electrical power grid continues to grow, needed additional system flexibility can be provided by energy storages, power transmission, and demand-side-management. The interplay between these three elements has recently gained interest in the field of energy system modeling. This study aims to determine the impact of potential non-industrial demand-side-management technologies, including heat pumps, controlled charging of battery electric vehicles, refrigeration, and air conditioning, on energy costs and battery storage requirements in Germany's future electrical power system. The model is analyzed using a novel modeling approach that enables a comparison of flexible loads responding to different market conditions: centralized market conditions with uniform market prices and decentralized market conditions with nodal prices, considering the congestion management potential of demand-side-management. The results show that non-industrial flexible loads can significantly affect the need for battery storage if high residual load peaks can be reduced by the specific technology. However, energy costs may only be reduced by up to 10 %. The study emphasizes the potential of demand-side-management for mitigating grid congestions, demonstrating that investment in battery storages may be lowered by up to 40 % when comparing centralized and decentralized market conditions. • Analysis of four non-industrial DSM technologies in national energy system model. • Modelling method compares DSM response to uniform vs. nodal electricity prices. • DSM may reduce operational energy costs and investment in battery storages. • Grid congestion may limit the cost reduction impact of DSM for electricity market. • Nodal pricing for DSM may support grid management and reduce grid congestion costs.

EnergyVol. 323
TH Köln - University of Applied Sciences (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung
Affordable and clean energy
Openalex Percentile: Top 10%
Integrated Energy Systems Optimization
2.92
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