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The place beyond the lines - efficient storage allocation in a spatially unbalanced power system with a high share of renewables

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  • Czock, Berit Hanna
  • Sitzmann, Amelie
  • Zinke, Jonas

Abstract

Increasing shares of wind and solar generation serve to decarbonize electricity generation; however, their temporal and spatial variability poses challenges in grid operation. While grid expansion is restricted in the medium term, storage technologies can potentially increase the power system’s efficiency by temporally aligning generation and demand and increasing network utilization. This paper uses a theoretical and a numerical model to evaluate the optimal allocation of battery storage. In a case study for Germany, we find that batteries can reduce system costs when placed behind the north–south grid bottleneck and near solar power. The supply costs in a setting with uniform prices and a random battery distribution are 9.3% higher than in the theoretical first-best benchmark with nodal prices. An optimal allocation of batteries can reduce this efficiency gap by 0.7 percentage points to 8.6% - the remainder of the efficiency gap can be explained by the suboptimal allocation of wind and solar power under uniform pricing. Although the efficiency gains achieved by batteries seem small, in relation to the cost of battery investments, this corresponds to almost a doubling of the supply cost savings per euro spent. Due to the lack of spatially differentiated investment incentives under Germany’s uniform pricing scheme, battery allocation requires additional policy measures. Simple allocation rules such as tying battery siting to solar capacity or explicitly identifying a limited number of suitable sites for capacity auctions can approximate an optimal allocation and can serve as the foundation for such a policy instrument.

Suggested Citation

  • Czock, Berit Hanna & Sitzmann, Amelie & Zinke, Jonas, 2025. "The place beyond the lines - efficient storage allocation in a spatially unbalanced power system with a high share of renewables," Energy Economics, Elsevier, vol. 149(C).
  • Handle: RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325005298
    DOI: 10.1016/j.eneco.2025.108702
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    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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