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Friedrich-Alexander-Universität Digital Transformation: Bits to Energy Lab Nuremberg WiSo
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    1. Friedrich-Alexander-Universität
    2. Fachbereich Wirtschafts- und Sozialwissenschaften
    Friedrich-Alexander-Universität Digital Transformation: Bits to Energy Lab Nuremberg WiSo
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    4. Solar energy community design: How many members, how many prosumers, what PV system sizes?

    Solar energy community design: How many members, how many prosumers, what PV system sizes?

    Bereichsnavigation: Forschung_alt
    • Technoökonomische Analysen von Energiesystemen und -technologien
      • Demand-response with electric vehicles: charge later, support the grid now
      • Local grid vs. global emissions: electric vehicle charging
      • Quantifizierung des Potenzials von Elektrofahrzeugen für nachfrageseitige Flexibilität
      • Solar energy community design: How many members, how many prosumers, what PV system sizes?
      • Gemeinsame Nutzung von Solaranlagen in städtischen Energiegemeinschaften
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    Solar energy community design: How many members, how many prosumers, what PV system sizes?

    Prakhar Mehta

    Prakhar Mehta

    Ehemaliger Mitarbeiter

    Fachbereich Wirtschafts- und Sozialwissenschaften
    Tenure-Track-Professur für Digitale Transformation

    Nürnberg
    • E-Mail: prakhar.mehta@fau.de
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    Challenge

    Local energy communities (ECs) are social and organisational structures, typically networks of households and businesses, designed to meet specific goals of members such as collectively owning or participating in energy-related projects, or sharing energy within local networks for economic or energy autonomy purposes. ECs therefore help promote the uptake of local renewable generation and accelerate the energy transition. However, not all energy community designs can satisfy all stakeholder expectations. Prosumers may want better profitability and energy autonomy, while grid operators may want to limit infrastructure upgrades. It is therefore important to understand how the EC design impacts performance metrics relevant to different stakeholders.

    Approach

    To evaluate and quantify EC performance, we perform a deterministic techno-economic simulation based on high-resolution real-world demand data from 3,594 households. We systematically vary three key energy community design dimensions, namely size of the community, prosumer ratio, and the installed PV system capacity, and analyse their impact on three key performance indicators: profitability of individual prosumers, achievement of community self-sufficiency targets, and avoidance of upgrades to the existing grid infrastructure.

    Key Results

    Community size (number of households in the community) is irrelevant for prosumer profitability and community self-sufficiency. When analyzing the impact of the EC on the local electricity infrastructure (the distribution transformer), the community size, installed PV capacity and penetration level of PV systems are all relevant. In ECs with more than 30% households with PV systems, less than one-in-four of those households end up being profitable. If all households have PV systems, then a maximum of 37.8% of the EC’s energy needs can be satisfied. However, to avoid unnecessary grid upgrades, the study shows that, limits of 30-100% on the share of prosumer households may be necessary, in-turn limiting the achievable energy self-sufficiency to 33.3%.

    The results therefore help establish clear configurations that strike a good balance between different performance metrics of an EC. EC planners, policymakers, and grid operators can build on these results as rules of thumb to incentivize EC formation while maximizing welfare for all stakeholders.

    Selected Publications

    Mehta, P., & Tiefenbeck, V. (2022). Solar PV sharing in urban energy communities: Impact of community configurations on profitability, autonomy and the electric grid. Sustainable Cities and Society, 87, 104178.

    Funding

    This research was funded by the Bavarian State Ministry of Science and the Arts, in a program coordinated by the Bavarian Research Institute for Digital Transformation (bidt).

    Team

    Prakhar Mehta, Verena Tiefenbeck

    Friedrich-Alexander-Universität
    Lehrstuhl für Digitale Transformation

    Lange Gasse 20
    90403 Nürnberg
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