Modelling study to assess the potential benefits of trading in and between local energy communities in Germany

In collaboration with Bündnis Bürgerenergie e.V. (BBEn), Grid Singularity conducted a study, using its open source energy exchange simulation tool and the dataset provided by the EWS Elektrizitätswerke Schönau eG, to assess the feasibility of local energy markets in Germany, reducing overall grid usage while maximising economic and social benefits of distributed renewable resources for citizens. This article, co-authored by BBEn and Grid Singularity, presents the study approach and the main findings.

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The Approach

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Figure 1: Hierarchical structure of bottom-up markets in Grid Singularity’s energy exchange engine, d3a.io, as modelled for the EWS Schönau community

Discussion of Results

a. Reduced energy bills with LEM implementation

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Table 1 : Cumulative electricity bills and cost reduction of the simulated EWS Schönau community for the weeks in November and May, with and without LEM (note: negative value indicates revenue)

b. Enhanced storage usage and improved self-consumption and self-sufficiency with LEM implementation

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Figure 2: Community import and export in a week in November; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Figure 3: Storage use improvements with LEMs in a week in November; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Figure 4: Storage use improvements with LEMs in a week in May; Grid Singularity’s simulation of EWS Schönau community dataset.
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Table 2: Self-consumption and self-sufficiency with and without enabled LEMs; Grid Singularity’s simulation based on EWS Schönau community dataset.

c. Community resource optimisation

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Table 3: Self-consumption and self-sufficiency baseline LEM compared to LEM with an additional 100 kW PV; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Figure 5: Self-sufficiency and self-consumption values with added storage capacity; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Figure 6. SOC of the large agricultural unit storage (150 kWh) during the week of November; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Figures 7: SOC of the large agricultural unit storage (150 kWh) during the week of May; Grid Singularity’s simulation based on EWS Schönau community dataset.
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Table 4: Cumulative electricity bills with and without additional wind turbine; Grid Singularity’s simulation based on EWS Schönau community dataset.

d. Inter-community trading benefits

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Figure 8: Maximum, minimum and average price of energy in an exclusively consumer community, comparing the baseline scenario (above) and the scenario with inter-community trade (below); Grid Singularity’s simulation based on EWS Schönau community dataset.
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Table 5: EWS Schönau and consumer community electricity bills with and without inter-community trading for the weeks in November and May; Grid Singularity simulation
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Written by

Engineering d3a.io, open source software that simulates and operates custom energy exchanges, creating local marketplaces that interconnect to form a smart grid

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