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Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations

Author

Listed:
  • Philippe Voinov

    (iHomeLab—Lucerne University of Applied Sciences and Arts, 6048 Horw, Switzerland)

  • Patrick Huber

    (iHomeLab—Lucerne University of Applied Sciences and Arts, 6048 Horw, Switzerland)

  • Alberto Calatroni

    (iHomeLab—Lucerne University of Applied Sciences and Arts, 6048 Horw, Switzerland)

  • Andreas Rumsch

    (iHomeLab—Lucerne University of Applied Sciences and Arts, 6048 Horw, Switzerland)

  • Andrew Paice

    (iHomeLab—Lucerne University of Applied Sciences and Arts, 6048 Horw, Switzerland)

Abstract

Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance fluctuating PV power is to incentivize self-consumption by shifting certain loads. The potential improvement in the amount of self-consumption is usually estimated using smart meter and PV production data. Smart meter data are usually available only at sampling frequences far below the Nyquist limit. In this paper we investigate how this insufficient sampling rate affects the estimated self-consumption potential of shiftable household appliances (washing machines, tumble dryers and dishwashers). We base our analyses on measured consumption data from 16 households in the UK and corresponding PV data. We found that the simulated results have a marked dependence on the data sampling rate. The amount of self-consumed energy estimated with data sampled every 10 min was overestimated by 30–40% compared to estimations using data with 1 min sampling rate. We therefore recommend to take this factor into account when making predictions on the impact of appliance load shifting on the rate of self-consumption.

Suggested Citation

  • Philippe Voinov & Patrick Huber & Alberto Calatroni & Andreas Rumsch & Andrew Paice, 2020. "Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations," Energies, MDPI, vol. 13(20), pages 1-16, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5393-:d:428809
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    References listed on IDEAS

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    1. McKenna, Eoghan & Pless, Jacquelyn & Darby, Sarah J., 2018. "Solar photovoltaic self-consumption in the UK residential sector: New estimates from a smart grid demonstration project," Energy Policy, Elsevier, vol. 118(C), pages 482-491.
    2. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
    3. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2016. "Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems," Applied Energy, Elsevier, vol. 173(C), pages 331-342.
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