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Maximum Return on Investment for a Domestic Photovoltaic Installation

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  • Tom Nonnenmacher
  • Jenny Nelson
  • Benedict Winchester

Abstract

The rising energy prices in Europe and the urgent need to address global warming have sparked a significant increase in the installation of domestic photovoltaic systems to harness solar energy. However, since solar energy is available only during daytime hours and its availability varies daily, effectively shifting energy use becomes crucial. Whilst batteries can assist in storing excess energy, their high prices hinder their widespread adoption. In this study, we explore the importance of load to maximise return on investment. We propose an incremental approach to fitting load profiles into the production envelope, allowing for practical implementation. We compare different meter resolutions: 1 second, 5 minutes, 15 minutes, and 1 hour. Our analysis reveals that making real-time decisions (per second) leads to significant energy savings of 16\% compared to hourly decisions. Furthermore, we explore three types of device management strategies: ON/OFF management independent of PV production, ON/OFF management based on the current PV production, ON/OFF management based on both current and forecasted PV production, utilising an optimal fit algorithm. Through our study, we demonstrate that our implementation of the third approach outperforms a standard management approach, resulting in more than 17% cost savings. This study provides insights into the optimisation of load-shifting strategies in domestic photovoltaic installations, highlighting the importance of load control and the potential benefits in maximising the utilisation of solar energy while minimising energy costs and environmental impact.

Suggested Citation

  • Tom Nonnenmacher & Jenny Nelson & Benedict Winchester, 2023. "Maximum Return on Investment for a Domestic Photovoltaic Installation," Papers 2310.09323, arXiv.org.
  • Handle: RePEc:arx:papers:2310.09323
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    File URL: http://arxiv.org/pdf/2310.09323
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