Tackling the uncertainty in solar energy yield calculations
3E, as a member of different European funded projects (Performance Plus project, Solar Bankability project,…) is working intensively within international teams to reduce the risks related to photovoltaic (PV) investments and to enhance the performance, reliability and lifetime of PV systems.
Within the Performance Plus consortium, 3E has worked to develop best practice guidelines on uncertainty in PV modelling and monitoring. The results of this work are documented in the report of the project, to be presented to the public on 06/10/2015 in Brussels (more info HERE). The developed guidelines will help developers, investors and plant operators to manage the financial risks and improve the operational performance of the PV plants during their lifetime.
As a first taste, 3E’s Mauricio Richter wrote a first introductory paper on the matter. This paper focuses on long term PV yield assessments, and how the uncertainties in PV modelling affect this process.
The uncertainty quantification of solar energy yield calculations is important for managing the financial risks of an investment in a photovoltaic system. Quantifying the energy yield is subject to several uncertainties introduced by the different elements in the PV energy conversion chain. The most important element in the contribution to the total combined uncertainty is the measurement and/or estimation of the solar resource. When estimating the energy output of a grid-connected PV system (up-front calculations), in addition to the uncertainty on the estimation of the solar resource, the uncertainty depends on the different models used and on external variables that are specific to the site.
The combined uncertainty is calculated using the rule of propagation of uncertainty and is in the order of ±6% to ±8% when using state-of-the-art models and considering a climate variability in the order of 4% to 6% which is representative for central European sites.
Get in touch to receive the full article on uncertainties in PV modelling.