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Analysis of Data Generated by an Automated Platform for Aggregation of Distributed Energy Resources

  • Juan AguilarEmail author
  • Alicia Arce
Conference paper
  • 5 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1173)

Abstract

The irruption of Distributed Energy Resources (DER) in the power system involves new scenarios where domestic consumers (end-users) would participate aggregated in energy markets, acting as prosumers. Amongst the different possible scenarios, this work is focused on the analysis of the results of a case study which is composed by 40 homes equipped with energy generation units including Li-Ion batteries, HESS systems and second life vehicle batteries to hydrogen storages. Software tools have been developed and deployed in the pilot to allow the domestic prosumers to participate into wholesale energy markets so that operations would be aggregated (all DERs acting as single instance), optimal (optimizing profit and reducing penalties) and smart managed (helping operators in the decision making process). Participating in energy markets is not trivial due to different technical requirements that every participant must comply. Amongst the different existent markets, this paper is focused on the participation in the day-ahead market and the grid operation during the following day to reduce penalties and comply with the energy profile committed. This paper presents an analysis of the data generated during the pilot operation deployed in a real environment. This valuable analysis will be developed in Sect. 4 Results, which raises important conclusions that will be presented. Netfficient is a project funded by the European Union’s Horizon 2020 research and innovation program, with the main objective of the deployment and testing of heterogeneous storages at different levels of the grid on the German Island of Borkum.

Keywords

Energy Intelligent system Optimization Mathematical programming 

Notes

Acknowledgment

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 646463.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Systems Engineering and Automatic ControlUniversity of SevilleSevilleSpain
  2. 2.Control Systems LaboratoryAyesaSevilleSpain

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