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Analysis and model-based predictions of solar PV and battery adoption in Germany: an agent-based approach

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Computer Science - Research and Development

Abstract

In order to tackle energy challenges faced in Germany, a Feed-in Tariff program was created in 2004 to aid the adoption of solar PhotoVoltaic (PV) systems where owners of such systems are paid a certain amount for each unit of electricity generated. Solar PV electricity generation is limited due to its intermittency but this can be managed using batteries. In this paper, we study the adoption of PV and battery (PV-battery) systems in Germany, and evaluate policies that could improve the adoption of these systems and their impact on the electric grid. To do this, we create an agent-based model that is simulated to estimate the impacts of different policies; this model is informed by an online survey with respondents from Germany. Simulating adoption over a period of 10 years, the results show that increasing electricity prices could result in improved PV-battery adoption in Germany better than reducing PV-battery system prices could. In addition, given the high level of affinity of people towards PV systems in Germany, disconnection from the grid would be a viable option within the next 10 years.

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Notes

  1. “EEG-Umlage”: According to §60 EEG electricity utilities have to pay an EEG apportionment to the transmission system operators (TSO) for each delivered kilowatt hour of electricity to final consumers. With these payments, the difference between the revenue and expenditure of the TSO will be covered in the EEG implementation.

  2. The payback period is the amount of time (typically, years) it takes for a system to pay for itself.

  3. Deflection is a measure of effectiveness based on ACT.

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Acknowledgments

This work has been partially carried out within both Internet-Kompetenzzentrum Ostbayern (IKZ_Ostbayern) project and the European project DC4Cities (FP7-ICT-2013.6.2). Furthermore, the authors of this paper would like to show their gratitude to Mr. Franz-Josef Feilmeier and Prof. S. Keshav, Univ. of Waterloo, for their significant contributions in this paper.

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Authors and Affiliations

  1. Computer Networks and Communications Group, University of Passau, Innstraße 43, 94032, Passau, Germany

    Ammar Alyousef & Hermann de Meer

  2. University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada

    Adedamola Adepetu

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  1. Ammar Alyousef
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Correspondence to Ammar Alyousef.

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Alyousef, A., Adepetu, A. & de Meer, H. Analysis and model-based predictions of solar PV and battery adoption in Germany: an agent-based approach. Comput Sci Res Dev 32, 211–223 (2017). https://doi.org/10.1007/s00450-016-0304-9

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