As Built Energy Yield Assesment - A Risk Mitigation Approach

Posted by SgurrEnergy on February 19th, 2020

1 Introduction – As-Built Energy Yield
With solar PV having emerged as the leading technology in the renewable energy sector,
with over 480GW global installations, the need for continual development and advancement
in the methodologies for assessing the long-term profitability of the technology play a
crucial role in the progress of the industry.
One of the primary mechanisms adopted to ensure the same is through accurately
predicting the power generation of a solar power plant through detail oriented energy yield
estimations. These estimations take into account various technical factors affecting a
project and thereby predict the resultant yield that can be expected for a particular time
period. It is therefore crucial that the energy assessment accurately represents the working
of a solar PV plant thereby incorporating precise losses incurred on site.
The current market trends indicate the use of the energy yield assessments conducted at the
feasibility study stage of a solar PV power project to be adopted within the financial model
employed by many lenders and financial institutions. These solar PV plant energy yield
assessments capture various aspects of the project that are envisaged during the inception
stages of the project. However, considerable variations arise in the project design subsequent
to the conceptual development of the PV plant i.e. during the detailed design and engineering,
and over the course of the construction phase of the project.
These variations are often overlooked by many solar power consultants and solar PV plant
developers in evaluating a precise energy yield model after the commissioning of the
project. Exclusion of these design deviations arising between the initial assessment and the
final project design implemented at the project site may have considerable impact on the
accuracy of the yield predictions for any given site. As a result of these deviations, the project
finance analysis may also be adversely affected, thereby posing as a risk to the lenders and in
turn the annual revenues of the project. The decision to proceed with the development of a
solar PV project rests upon the commercial viability of the project, as determined through a
financial assessment. SgurrEnergy India has described various such avenues that are the
prevailing factors, wherein the PV plant is not accurately modelled in the assessment.
Based on the cumulative experience of SgurrEnergy in conducting project planning and
solar PV power plant feasibility studies in the early stages of plant conceptualisation, in
conjunction with detailed engineering and designing of the PV projects for over 20GW, SEI
intends to initiate evaluating projects based on finalised design and conducting a
corresponding predictive yield modelling of the project, or in-short, an ‘As-Built Energy Yield
Assessment’.
The as-built assessments can cater to lenders and various financial institutions for them to
evaluate with higher confidence the financial aspects of a given project.
In the article, the loss assumptions that can vary over the course of the project design have
been enlisted in order to provide clarity on the extent of their impact on the yield estimations
and thereby the significance of considering them within an as-built energy yield estimation
of the project.

2 Investigating the Variations
In a typical energy yield for a solar PV project, several losses affect the annual power
generation. However, among these losses, the following are the common variations
observed in the project planning and the operational phase by SgurrEnergy. Thesedeviations are based on the observations made over the course of project planning up until commissioning.

2.1 Inter-Row Shading Effects
Inter-row shading loss essentially depends on the land terrain, slopes and topography. Often
neglected due to non-availability of topographic surveys in the feasibility / early stages of
project, this shading loss may pose a major hindrance in arriving at an optimum yield. If not
included in an energy prediction model, an overestimated figure is produced of the project’s
performance.
Analysis of inter-row shading impact typically requires the topography studies of the site,
and as per the final solar PV plant layout, PV arrays are manually modelled in the simulation.
Substantial energy loss can arise due to negligent levelling and grading of unwanted
elevated land parcels.

2.2 Shading due to Obstacles
It is a general practice during design and installation, to avoid shading on PV arrays due to
nearby obstructions that include PV plant equipment and environmental obstacles such as
hillocks, trees etc. The PV projects’ in situ structures include inverter stations, control
rooms, lightning arrestors, transmission towers, fencings etc., whereas environmental
obstacles include trees, minor hillocks and various other obstructions.
These obstacles are often not-considered within the modelling of the project and thereby
also resulting in the miscalculation of the respective PV arrays.

2.3 PV Module Performance
Subsequent to the shipment of the PV modules the manufacturers provide flash test
reports indicating the various parameters that affect the performance of the PV module.
These reports depict the deviation of the module performance with respect to its actual rated
capacity; and therefore, these values play a major role in characterising the PV performance
on a string and system level.
Modern modules tend to have a positive tolerance with respect to their rated capacities;
and the flash tests, once evaluated, give an accurate performance prediction of modules
with respect to module quality gain/loss corresponding to its nameplate capacity and
module mismatch occurring at site.

2.4 Angular Losses
The sun path varies over a day resulting in change in irradiation falling on the PV array. A
PV plant exhibits maximum yield when the sun is perpendicular to the plane of array;
however, during the course of the day when the sun is not perpendicular, there is a reduction
in total irradiation reaching the plane of PV array, specifically the direct beam irradiation.
Sunlight enters the module through the glass and encapsulant, which serve as an enclosure
to provide adhesion between solar cells and mechanical robustness to the modules. By
default, the properties of these materials should incorporate high light-transmissivity in
order to avoid losses in radiation transmission. This is primarily quantified by the Incidence
Angle Modifier (IAM) profile of the module, and is calculated based on the physical
parameters of the module materials.
This profile, is developed by the module manufacturer and verified by an independent
laboratory tests. Generally subsequent to the commissioning of the modules, the
manufacturer provides an independent laboratory test accurately predicting the angular
losses occurring in the module resulting in an un-biased loss value.

2.5 Ohmic Loss Evaluation
During the project-planning phase of a project, due to incomplete land acquisition, the
layouts of the proposed solar PV plant are not finalised, thereby leading to various
assumptions on array placement and consequently, rudimentary ohmic wiring loss
assumptions.
However, during the execution phase of the project, subsequent complete land acquisition
and finalised design, the cable routes are optimally developed thereby resulting in an ohmic
wiring loss calculation, deviating than the initially assumed value.
It is evident that with an increase in the length of a cable, a corresponding increase in loss
is observed, therefore it is essential to encompass the modified cable losses calculated
during the detail designing phase.The estimation obtained as a result of using the assumed loss values tends to lead to over
or underestimated values which is considered to be an improper engineering practise, and
must therefore be revised on inclusion in the as-built energy yield estimation.

3 Conclusion
Based on the discussions above, the variation in the estimation of the energy yield values can
be considerably large due to incorporation of the above mentioned assumptions of the losses
and thereby can have a significant impact on the accuracy of predictions. As stated earlier,
this can crucially affect the profitability of the solar PV power plant.