Yield assessment experience, 2019 Yield analysis experience, 2019

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What was the aim of the project?

In 2019, Natural Power increased its energy yield analysis experience. Using our in-house team of over 20 energy analysts, we delivered over 380 analyses for our clients. This covered both pre-construction and operational assets in over 25 countries.


What was the outcome?

Natural Power collaborated with its client base to deliver the analyses, and the results were used to inform several decisions.

For pre-construction projects, our clients used the bankable results to progress project finance. The results also supported the definition of the final turbine or PV technology and layout at construction phase.

The results associated with operational assets allowed our client base to review and compare the results with pre-construction assumptions. The results also showed potential performance issues and informed both proactive and reactive maintenance planning.

In cases where we delivered the energy yield analyses on behalf of banks and financial institutions, the results informed wider investment and divestment decision making.


What did Natural Power do to get this result?

Pre-construction assessments (wind)

For each analysis, our analysts used on-site data collected from masts or remote sensing devices to determine the local wind regime within the given site boundary. We then adjusted the data to a selected reference dataset to define the long-term wind climate in the region.

We conducted shear and turbulence intensity calculations before performing wind flow modelling. We did this using either a linear flow model, CFD model or mesoscale product. This informed gross energy yield calculations for the specific turbine configurations.

We then performed a full losses and uncertainties assessment, including consideration of the blockage effect, to inform net production figures.

Post construction assessments (wind)

The team used SCADA data recorded by all turbines on a per site basis for each assessment, and monthly production reports were also reviewed.

We undertook a detailed review of alarm logs and associated categorisations to determine any significant downtime events, and operational power curves were generated following a filtering process accounting for downtime and unrepresentative performance. We quantified site electrical losses and reapplied them as a secondary loss.

An operational site performance model was then created to inform the calculation of the net P50 figure, with any further appropriate secondary losses applied, ahead of a full uncertainty assessment.

Pre-construction assessment (solar)

Each solar analysis used PVsyst software combined with bespoke in-house tools to inform yield estimates. It included a survey of commonly used solar resource databases to determine the most appropriate long-term dataset to be considered.

A monthly breakdown of the P50 forecast was finalised to consider seasonality, and the defined energy yield model considered the relevant nearby and horizon shading and, where relevant, complex terrain effects.

We undertook a full assessment of losses and degradation to define net production figures, with any additional risks or areas for further investigation highlighted on a per project basis.

The projects assessed by Natural Power ranged from commercial rooftop sites to 100MW+ ground-mounted projects. A significant number of these featured bifacial modules.

Post construction assessments (solar)

Natural Power assessed the long-term performance of operational solar assets on the basis of historic production, correlated with long-term solar reference data.

We derived an operational site performance model to inform the calculation of the revised P50 figure, including an assessment of future losses, degradation and uncertainties.

Project stats

80+ GW

80+ GW of analysis services delivered globally, spanning over 40 countries and six continents.

25 years’

Over 25 years’ experience delivering marking leading analysis services to inform project development, finance and operational management.

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