Maximizing the Yield of Large PV Power Plants: What Can We Learn from Monitoring and Simulation?

In this paper, we describe a number of quality assurance procedures for PV performance evaluations using data that has been acquired with commercially operating PV power plants. Summarized under the term "performance verification", these procedures aim to make reliable use of data gathered by PV operators, despite inaccuracies in such data. To this end, shortterm measurements with independent equipment and/or data sources are factored in. This ensures both meteorological and PV performance data gathered by operators have sufficient quality. Given a sufficient quality, site-adaptation of satellite based solar irradiation time series and optimizations of PV models may allow for significantly reduced uncertainties of yield predictions. This we anticipate to be of great interest to a broad range of PV stakeholders. The prerequisite for this, however, are appropriate quality of on-site sensors and strict maintenance of the PV performance monitoring systems in place.

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On-site performance verification to reduce yield prediction uncertainties

Reich

Zenke

Müller

et al. 2015

2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC)

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Application of Dynamic Multi-Step Performance Loss Algorithm

Lindig

Moser

Müller

et al. 2020

2020 47th IEEE Photovoltaic Specialists Conference (PVSC)

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Maximizing the Yield of Large PV Power Plants: What Can We Learn from Monitoring and Simulation?

Cited by 2 publications

References 8 publications

On-site performance verification to reduce yield prediction uncertainties

On-site performance verification to reduce yield prediction uncertainties

Application of Dynamic Multi-Step Performance Loss Algorithm

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