Design Tools for the bankability of PV plantsperfplus.eu/frontend/files/userfiles/files/1...

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Design Tools

for the bankability of PV plants

Luis Narvarte

Solar Energy Institute – Polytechnical University of Madrid

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Bankability Bankability:

• Project Finance

• Contract

• Due Diligence

Requirements for Design Tools: • Same model for simulation+TS+QCP to assure coherence

• Model with just parameters guaranteed by manufacturers

• Low uncertainty

• TS linked to QC to be included in contracts

• QC to assign responsibilities

PV plant production

Energy yield estimation

Financing P90

SIMULATION

Reduce UNCERTAINTY

Technical annex TECHNICAL SPECIFICATIONS (TS)

Quality control

Assign responsibilities

QUALITY CONTROL PROCEDURE (QCP)

TESTING KITS

Just parameters GUARANTEED

Input variables: G, Tc, datasheet

Quality control: measurements

Performance of components and PV plant

Known by manufacturers and promoters

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Guaranteed by manufacturers

With low uncertainty

Model for Simulation + TS + QCP

+ Scenarios for expected losses (thermal, shades, cables,…) validated in > 70 PV plants

Objective of Simulation + TS + QCP: -Determine the actual production capability -Dealing with defective components

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STEPS in TS + QC STEP CURRENT

PROCEDURE

OBJECTION PROPOSAL

Design:

Energy yield forecast

Commercial software

Based on non-guaranteed

information

SISIFO

SISIFO

• Open source tool

• Free available

• Just inputs guaranteed by manufacturers

• and of course:

• models tested in more than 70 PV plants

• Shadowing models

• trackers

• uncertainty calculation, …

Available at: www.sisifo.info

http://www.sisifo.info/

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PROCEDURE

OBJECTION PROPOSAL

Design:


Commercial software


information

SISIFO

G and Tc from available

databases +

Transportation models

High uncertainty Available databases corrected with PV

modules as sensors

PRPYR

PRREF

Mean Maximum Minimum Range

PRPYR 0.775 0.824 0.726 ± 4%

PRREF 0.801 0.819 0.784 ± 2%

c-Si PV array, Madrid 2014

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PROCEDURE

OBJECTION PROPOSAL

Design:


Commercial software


information

SISIFO


databases + Transportation

models

High uncertainty Available databases corrected with PV modules as

sensors

Procurement:

PV module sample

peak power testing

Prior to the installation, at

qualified laboratories

Neither LID nor

Irradiance and

temperature behaviour

are addressed

γ, a, b, c, from tests at real Sun

P*/PNOM reviewed at the lights of LID test

New estimation with SISIFO

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PROCEDURE

OBJECTION PROPOSAL

Design:


Commercial software


information

SISIFO



models


sensors

Procurement:

PV module sample peak

power testing



Neither LID nor

Irradiance and temperature

behaviour are addressed




Commissioning:

PV plant production

testing

PR during a week

(Often pass criteria

PR ≥ 80%)

Time-dependence

disturbs technical quality

qualification

PRSTC

G and TC with PV modules

Weekly PR and PRSTC evolution along the year Same spectral, angular, thermal and dirt response than the tested PV array Stabilized according to IEC 61215. Measured according to IEC 60904

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PROCEDURE

OBJECTION PROPOSAL

Design:


Commercial software


information

SISIFO



models


sensors

Procurement:


power testing



Neither LID nor






Commissioning:

PV plant production

testing

PR during a week


PR ≥ 80%)

Time-dependence

disturbs technical quality

qualification

Detailed characterization

of real PV plant

behaviour not addressed

PRSTC


Detailed characterization of real PV plant

behaviour with on-site measurements

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STEPS in TS + QC G

TC PDC PAC

Power limitation dueto DC/AC ratio > 1

Clouds affecting theirradiance sensor but notthe whole PV array

Efficiency dependenceon irradiance

Power limitation dueto DC/AC ratio > 1

Clouds affecting theirradiance sensor but notthe whole PV array

Efficiency dependenceon irradiance

CloudEnhancement

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PROCEDURE

OBJECTION PROPOSAL

Design:


Commercial software


information

SISIFO



models


sensors

Procurement:


power testing



Neither LID nor






Commissioning: PV plant production

testing

PR during a week


PR ≥ 80%)

Time-dependence disturbs

technical quality qualification

PRSTC


Detailed characterization of real PV plant behaviour

not addressed

Infrared inspection Hot-spot detection Acceptance criteria

scarcely addressed

Rejection criteria for hot spots and PID

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∆PARRAY >> ∆PALONE

Operation current

∆PARRAY >> ∆PALONE

Operation current

Defective PV module at a string

with others non-defective ones

Real power reduction is high

The PV module satisfies standard

guaranties but it does not properly performs

Proposal PV module rejection criteria:

-∆THS ≥ 20o C because lifetime threat

-10o C ≤ ∆THS < 20o C and ∆V > 20% because

real power is out of guarantee

Hot- Spots

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PID

ΔPm = - 10%

ΔVop = -16%

- +

1 12 13 24

- +

1 12 13 24

V- V+ ΔV > 5% → Probable PID

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Reduction of Uncertainty

Project phase Model parameters σ (%)

Design:

Yield prediction

γ, a, b, c, k0, k1 and k2 from datasheets

P*/PNOM from the agree losses scenario

SISIFO without PV module sensors

> 5%

Procurement:

PV module sample

Lab-testing

γ, a, b, c, from tests


Again SISIFO

4 %

Commissioning

In-deep checking

a, b, c, k0, k1 and k2 from test

P*/PNOM from test

PV module sensors

< 2 %

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Results and Impact RESULTS

• Documents of TS + QC for contracts

• SISIFO Toolbox

Increase of PR and reduction of LCeE

• without increase of PV system cost

Scenario of

improvement

Increase of PR

due to our Design Tools

Current P50

(PR= 76.5)

1.7%

Current P90

(PR= 83.8)

6.81%

Design Tools for the bankability of PV plantsperfplus.eu/frontend/files/userfiles/files/1...

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