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Renewable energy communities, digitalization and information

Author

Listed:
  • Bergemann, Dirk
  • Bertolini, Marina
  • Castellini, Marta
  • Moretto, Michele
  • Vergalli, Sergio

Abstract

In this work we study the case of agents willing to engage in a Renewable Energy Community (REC). The municipality – being the promoter of the REC – burdens all the investment costs (RE plants, storage, local grid interventions) and entrusts an aggregator of its operation paying a fixed tariff. The latter, acting as a monopolist, is also the sole supplier of energy for the REC’s members. The management of the REC requires the collection of energy data from the members to assure its efficient operation on the side of the self-consumption and exchange of energy within it. Such data allow also the identification of the agents’ preferences across energy devices and are an additional source of revenues for the aggregator thanks to their sell to third parts. This behaviour translates into a dis-utility the agents, which we call privacy cost. In such a framework, we consider also uncertainty on the side of the investment cost. On the basis of the outcomes of our model, we are able to study the effect of data collection policy performed by the aggregator on the size of the REC, while also accounting for agents’ valuation and the role of uncertainty on the investment cost side.

Suggested Citation

  • Bergemann, Dirk & Bertolini, Marina & Castellini, Marta & Moretto, Michele & Vergalli, Sergio, 2022. "Renewable energy communities, digitalization and information," FEEM Working Papers 329581, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemwp:329581
    DOI: 10.22004/ag.econ.329581
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    Keywords

    Demand and Price Analysis; Research and Development/Tech Change/Emerging Technologies; Resource /Energy Economics and Policy;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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