The uncertainties involved in measuring national solar photovoltaic electricity generation

O.T. Huxley, J. Taylor, A. Everard, J. Briggs, K. Tilley, J. Harwood and A. Buckley

Renewable and Sustainable Energy Reviews, 2022, vol. 156, issue C

Abstract: The measurement of near real-time national solar PV electricity output is an increasingly important component for managing electricity systems. PV systems embedded in the distribution network are problematic for system operators since their output is not directly visible through existing transmission system metering. Typically, national solar PV output is measured indirectly by upscaling the output from a sample of reference PV systems using an estimate of the national capacity. National PV output is then used, along with similar measurements for other embedded technologies such as wind, to train and validate electricity forecasts which ensure efficient electricity market operation. For the first time and using Great Britain as a case study, we investigate the accuracy of this general approach by characterising different sources of uncertainty in national PV output measurements. We find that the capacity error, at ±5%, dominates the yield calculation error, at < ±1% and leads to an overall error in GB solar PV output estimates of ±5.1%. We conclude that solar PV measurements, and consequently national electricity demand forecasts, are currently limited by the state of national PV capacity registers. To make PV output measurements more accurate nations must develop a coherent and comprehensive approach to PV system registration, and output measurement methods must move away from using static solar PV capacity registers towards estimating an operational grid-connected solar PV capacity. This could involve moving away from capacity registers altogether and instead estimating capacity from other sources, for example, from network power flows, satellite imagery, or more likely, a combination of complementary datasets.

Keywords: Solar photovoltaic power; Solar photovoltaic capacity; Reference PV systems; PV fleet Estimates; Upscaling method; Yield prediction (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.rser.2021.112000

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