Exhibit 99.1

 

Q3 ABS

Technical Due Diligence Report

Palmetto Clean Technology

 

Document No.: 10582434-HOU-R-01

Issue: C, Status: Final

Date: 15 September 2025

 

 

SAFER, SMARTER, GREENER

 

IMPORTANT NOTICE AND DISCLAIMER

 

1.

This document is intended for the sole use of the Customer as detailed on page iii of this document, to whom it is addressed and who has entered into a written agreement with the DNV entity issuing this document (“DNV”). No other person or entity is entitled to rely on this document for any purpose. To the maximum extent permitted by law, neither DNV nor any its group companies (collectively the “Group”) assumes any responsibility or liability whether in contract, tort (including without limitation negligence), or otherwise , to any Third Party (being any individual or entity other than the Customer). No company in the Group other than DNV shall be liable for any loss or damage whatsoever suffered by virtue of any act, omission or default (whether arising by negligence or otherwise) by DNV, the Group or any of its or their servants, subcontractors or agents. To the extent that any Third Party is deemed to have a right to rely on this document by operation of law, statute, or otherwise, such reliance is subject to DNV’s standard reliance letter terms, including without limitation, the limitation of liability, which limits DNV’s total liability to 5x the contract value.

 

2.

This document must be read in its entirety and is subject to any assumptions, limitations and qualifications expressed herein as well as in any other relevant communications in connection with it. This document may contain detailed technical data intended solely for use by individuals possessing requisite expertise in its subject matter.

 

3.

This document is protected by copyright and may only be reproduced and circulated in accordance with the confidentiality conditions stipulated and/or in DNV’s written agreement with the Customer. No part of this document may be disclosed in any public offering memorandum, prospectus or stock exchange listing, circular or announcement without the express and prior written consent of DNV. Distribution of this document to any Third Party (including by consent) does not confer any rights of reliance unless such Third Party has executed a reliance letter with DNV. Any unauthorized distribution or use of this document shall not create any duty of care or liability on the part of DNV or the Group. The Customer shall not alter or modify this document in any way without DNV’s prior written consent.

 

4.

This document has been produced from information relating to dates and periods referred to in this document. This document does not imply that any information is not subject to change. Except and to the extent that checking or verification of information or data is expressly agreed within the written scope of its services, DNV shall not be responsible in any way in connection with erroneous information or data provided to it by the Customer or any third party, or for the effects of any such erroneous information or data whether or not contained or referred to in this document.

 

5.

Any estimates or predictions are subject to factors not all of which are within the scope of this document and nothing in this document guarantees any particular performance or output.

 

 

DNV Document No.: 10582434-HOU-R-01, Issue: C, Status: Final – www.dnv.com		Page i

 

 

 

Project name:		Q3 ABS		DNV Energy Systems
Report title:		Technical Due Diligence Report		Renewables & Power Grids
Customer:		Palmetto Clean Technology		1999 Harrison Street,
		155 Grand Ave. Suite 600, Oakland, CA		Oakland, CA, 94612 USA
Contact person:		David Fairbank		Tel: +1 510-891-0446
Date of issue:		15 September 2025
Proposal reference:		OPP-00429093-HOU-P-01-A Palmetto Q3 2025 ABS
Document No.:		10582434-HOU-R-01-C

 

Task and objective:

The Report describes DNV’s technical due diligence review, in its capacity as Independent Engineer, for a residential, third-party owned portfolio.

 

Prepared by:		Approved by:
Rebecca Ambresh		Sarah Heller
Project Manager		Senior Project Manager

 

 

Distribution outside of DNV:
☐ PUBLISHED		Available for information only to the general public
		(subject to the above Important Notice and Disclaimer).
☒ CUSTOMER’S		Distribution for information only at the discretion of the
DISCRETION		Customer (subject to the above Important Notice and
		Disclaimer and the terms of DNV’s written agreement
		with the Customer).
☐ CONFIDENTIAL		Not to be disclosed outside the Customer’s organization.
☐ NONE		Not to be disclosed outside of DNV.

 

© 2025 DNV Energy USA Inc. All rights reserved.

Reference to part of this report which may lead to misinterpretation is not permissible.

 

Issue

Date

Status

Reason for Issue

Prepared by

Verified by

Approved by

A

21 August 2025

DRAFT

Preliminary Report

Various

S. Heller

C. Vadakkan

B

12 September

DRAFT

Updates to equipment replacement modeling

R. Ambresh

S. Heller

C

15 September

FINAL

Updates to equipment replacement modeling

R. Ambresh

S. Heller

(meter costs)

 

 

DNV Document No.: 10582434-HOU-R-01, Issue: C, Status: Final – www.dnv.com		Page ii

 

 

 

Table of contents
1		ENERGY ANALYSIS AND PERFORMANCE GUARANTEE FORECASTING					3
		1.1		Description of the data set			3
		1.2		Weather correction			3
		1.3		Accuracy of Sponsor’s energy production forecasts			4
		1.4		Forecasting			5
		1.5		Degradation			7
		1.6		Performance guarantee payout modeling			8
2		TECHNICAL INPUTS TO FINANCIAL MODEL					12
		2.1		PV equipment replacement modeling			12
		2.2		BESS equipment replacement modeling			22
		2.3		Financial model conclusion			26
3		REFERENCES					27

 

List of tables
Table 1-1 Palmetto Portfolio Summary					1
Table 1-1 Regional PI of the Production Sample					4
Table 1-2 PTO PI of the Production Sample					5
Table 1-3 Forecast Sample distribution					5
Table 1-4 Future uncertainty by region					6
Table 1-5 Portfolio exceedance values considering IAV only					7
Table 1-6 Portfolio degradation rates					8
Table 1-7 Performance guarantee Correction Factors and standard deviation					9
Table 1-8 Performance guarantee payout forecasts for the Portfolio, 25 years with a 3-year payout schedule					10
Table 1-9 Performance guarantee payout forecasts for the Portfolio, 20 years with a 3-year payout schedule					10
Table 1-10 Performance guarantee payout forecasts for the Portfolio, 20 years with a 2-year payout schedule					11
Table 2-1 Portfolio inverter OEM					12
Table 2-2 Portfolio module OEM					12
Table 2-3 Labor costs by failure type					13
Table 2-4 Inverter equipment replacement costs					15
Table 2-5 Module equipment replacement costs					17
Table 2-6 Meter replacement costs					19
Table 2-7 Annual equipment replacement cost forecast for the Portfolio					21
Table 2-8 Annual equipment replacement cost forecast for the Portfolio					22
Table 2-9 Portfolio BESS Breakdown					22
Table 2-10 Portfolio BESS Breakdown					23
Table 2-11 DNV generic BESS failure curve					23
Table 2-12 Annual BESS equipment replacement cost forecast for the Portfolio					24
Table 2-13 Annual BESS equipment replacement cost forecast for the Portfolio per unit					24
Table 2-14 Portfolio equipment replacement model summary					26
List of figures
Figure 2-1 Total Portfolio O&M cost					15
Figure 2-2 DNV primary residential inverter and optimizer failure rates					17
Figure 2-3 DNV primary module failure rates					18
Figure 2-4 Meter failure rates					20

 

 

DNV Document No.: 10582434-HOU-R-01, Issue: C, Status: Final – www.dnv.com		Page iii

 

 

INTRODUCTION

At the request of Palmetto Clean Technology (“Palmetto”, the “Customer” or the “Sponsor”), DNV has performed a technical due diligence review of the Sponsor’s portfolio of residential PV and PV + battery energy storage systems (BESS) projects (the “Portfolio”) in support of an anticipated securitization.

The purpose of this Report is to summarize DNV’s review of the Sponsor’s capabilities and the documentation received; to evaluate technical risks and mitigation measures relative to typical industry practice; and to advise on the status of any issues that appear technically incorrect and inconsistent with documentation or that remain unresolved at the time of the preparation of this Report.

Per the datatape DNV received, a summary of the Portfolio attributes is provided in Table 1-1.

Table 1-1 Palmetto Portfolio Summary

 

		Region		Number of systems		Capacity (MWdc)
		AZ		3,403		32,147
		CA		4,444		31,767
		CO		949		6,833
		CT		1,103		11,850
		FL		4,481		50,412
		GA		388		3,674
		IL		2,137		23,501
		KS		55		468
		MA		763		7,315
		MD		348		3,605
		ME		38		336
		MI		317		2,301
		MO		2		17
		NC		27		236
		NH		29		275
		NJ		288		3,056
		NM		75		473
		NV		711		6,692
		NY		65		717
		OH		264		2,351
		OK		57		507
		PA		631		5,617
		RI		67		559
		TX		1,545		14,953
		VA		1		16
		Grand Total		22,188		209,677

 

 

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Scope of work

The DNV scope of work is defined in the Short Form Agreement (“Agreement”) OPP-00429093-HOU-P-01-A Palmetto Q3 2025 ABS, dated 14 August 2025 and between Palmetto and DNV Energy USA Inc. This technical due diligence report (the “Report”) is provided pursuant to the terms and conditions of the Agreement, and disclosure of the Report to other potential investors and/or lenders is subject to provisions of the referenced terms and conditions and the disclaimer at the front of this Report.

The DNV scope of work includes the following:

 

●

Energy and performance guarantee forecasting

 

●

Technical inputs to the financial model

 

○

Equipment replacement modeling

Result tables presented herein are also presented in the attached spreadsheet deliverable 10582434-HOU-XL-01-C Palmetto Q3 2025 ABS TDD_15 Septmeber 2025.xlsm.

Methodology and assumptions

This Independent Engineering (IE) Report is a high-level technical due diligence review intended for financial institutions, customers, and project developers. DNV is well qualified to conduct this study, with extensive experience in solar independent engineering and technology due diligence work.

This Report summarizes DNV’s assessment of the Portfolio and relies on the accuracy of the information provided. All those supplying product information have been open and forthcoming in providing the data that DNV has requested. This Report is based on some information not within the control of DNV. DNV believes that the information provided by others is true and correct and reasonable for the purposes of this Report. DNV has not been requested to make an independent analysis or verification of the validity of such information. DNV does not guarantee the accuracy of the data, information, or opinions provided by others. In preparing this Report and the opinions presented herein, DNV has made certain assumptions with respect to conditions that may exist or events that may occur in the future. DNV believes that these assumptions are reasonable for purposes of this Report, but actual events or conditions may cause results to differ materially from forward-looking statements.

 

 

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1	ENERGY ANALYSIS AND PERFORMANCE GUARANTEE FORECASTING

DNV analyzed production data from Palmetto’s Fleet of deployed systems to assess the accuracy of Palmetto’s energy production estimates with the goal of establishing expectations for future production risks going forward for the Portfolio. DNV notes that many of the systems for which DNV was provided production data are cash and loan systems, not TPO systems, which is a distinction worth mentioning as cash and loan systems and TPO systems typically have different levels of operational oversight.

 

1.1	Description of the data set

DNV received a production data file in August 2024 (“H2 2024 data set”) with production estimates, actual production, and metadata for 19,946 systems through the end of July 2024 [1]. DNV used this production data for energy and performance guarantee payout forecasting for the Portfolio. DNV receive a separate datatape of system attributes [2] which was used to create Portfolio concentrations in this energy analysis and the equipment replacement forecasting analysis.

DNV analyzed Palmetto’s operational data from the Production Data File using the following steps:

 

●

Clean the data to remove erroneous and excludable values;

 

●

Adjust the production data to long-term average behavior with regard to irradiance;

 

●

Calculate system performance indices based on the accuracy of Palmetto’s forecasts;

 

●

Apply uncertainties to the future Portfolio;

 

●

Forecast future production.

Of the 19,946 systems, 17,006 systems had sufficient production and metadata with which to perform a historical production analysis (the Production Sample). These systems represent systems with data until July 2024. DNV notes that systems with lifetime historical performance indices below 50% and greater than 150% are not included in the Production Sample.

 

1.2	Weather correction

DNV calculated the extent to which over/under production in a region can be attributed to differences between the irradiance during the operational period relative to the reference irradiation for that region. The analysis compared monthly global horizontal irradiation (GHI) over the operational period to the long-term reference GHI. DNV procured monthly GHI data from DNV Solcast, a web-based service that provides gridded satellite-based irradiance data with global coverage. Solcast’s global solar dataset is based on over a decade of high-resolution visible satellite imagery via the broadband visible wavelength channel. This data has been processed using a combination of peer-reviewed, industry standard techniques and processing algorithms developed in-house, including a cloud-index algorithm that produces consistent results when used with the large number of satellites that must be combined to construct a global dataset. The resulting time series of cloudiness (or cloud index) is then combined with other information to model the amount of solar radiation at the Earth’s surface. The outcome is a 17+ year dataset that provides hourly and sub-hourly estimates of surface irradiance (GHI, DNI, and DIF) for all the Earth’s land mass at a spatial resolution of approximately 3 km (2 arc minutes).

DNV mapped each system in the Residential Production Sample in order to run a clustering algorithm that selects irradiance tile locations based on the geographic distribution and climactic regime of each of the systems in the Residential Production Sample. A total of 79 tile locations were selected. The actual production of each system in the Residential Production Sample is adjusted according to the irradiance adjustment factor during the measurement period from the nearest irradiance tile. The irradiance adjustment factor is the ratio of the annual long-term average compared to the period of record of each system.

 

 

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1.3 Accuracy of Sponsor’s energy production forecasts

For each system, DNV computed the mean actual and expected monthly production for each of the twelve (12) calendar months. A Performance Index (PI) was then computed for each system by dividing the sum of monthly means for the actual production by the sum of monthly means for the expected production.

The Production Sample consists of 17,006 systems and the distribution of the performance indices in the Production Sample by region is displayed in the table below.

Table 1-1 Regional PI of the Production Sample

 

Region		System count		Total capacity (kWdc)		Irradiance adjusted  PI
AZ		170		1,609		1.04
CA		417		2,913		0.98
CO		158		1,127		0.94
CT		207		1,741		0.96
DC		11		83		0.92
FL		1,939		20,695		0.95
GA		1,173		10,296		0.96
IL		956		7,221		0.92
MA		2,033		17,420		0.95
MD		205		1,826		0.95
MI		422		3,004		0.90
MO		40		329		0.95
NC		1,545		12,717		0.96
NJ		304		2,417		0.95
NM		59		386		1.01
NV		856		7,180		0.98
NY		1		14		0.97
OH		523		4,572		0.95
PA		2,798		25,543		0.94
RI		508		3,575		0.95
SC		1,329		10,892		0.94
TX		1,077		10,717		0.93
UT		18		130		0.98
VA		233		2,295		0.92
WI		24		182		0.95
Total		17,006		148,884		0.95

 

 

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The distribution of the performance indices in the Production Sample by PTO is displayed in the table below.

Table 1-2 PTO PI of the Production Sample

 

PTO year		System count		Total capacity (kWdc)		Irradiance adjusted  PI
2017		2		11		0.90
2018		386		2,967		0.93
2019		1,126		8,771		0.93
2020		1,952		16,211		0.96
2021		3,524		31,271		0.95
2022		6,739		60,967		0.95
2023		3,277		28,687		0.95
Total		17,006		148,884		0.95

Forecasting

A representative sample of systems from the Production Sample were used to forecast for the Portfolio with a total capacity of 209,790 kWdc as shown in the table below (the “Forecast Sample”) which is intended to mirror the geographic and capacity distribution of the Portfolio. Systems in the Production Sample were randomly selected from the corresponding regions to achieve the capacity for each region in the Forecast Sample. As shown in the Forecast Sample, the capacity of the Forecast Sample is 209,790 kWdc and the target capacity of the Portfolio is 209,677 kWdc.

Table 1-3 Forecast Sample distribution

 

Region		Anticipated number of systems		Anticipated capacity (kWdc)		Forecast Sample systems		Forecast  Sample  capacity  (kWdc)
AZ		3,403		32,147		3,337		32,149
CA		4,444		31,767		4,488		31,772
CO		949		6,833		954		6,833
CT		1,103		11,850		1,410		11,854
FL		4,481		50,412		4,721		50,414
GA		388		3,674		419		3,682
IL		2,137		23,501		3,094		23,508
KS		55		468		66		468
MA		763		7,315		851		7,318
MD		348		3,605		416		3,612
ME		38		336		36		340
MI		317		2,301		328		2,304
MO		2		17		4		29
NC		27		236		27		242
NH		29		275		30		279

 

 

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Region		Anticipated number of systems		Anticipated capacity (kWdc)		Forecast Sample systems		Forecast  Sample  capacity  (kWdc)
NJ		288		3,056		384		3,059
NM		75		473		74		479
NV		711		6,692		863		6,698
NY		65		717		50		720
OH		264		2,351		278		2,352
OK		57		507		57		510
PA		631		5,617		623		5,624
RI		67		559		83		560
TX		1,545		14,953		1,507		14,962
VA		1		16		2		20
Totals / Average		22,188		209,677		24,102		209,790

 

1.4.1

Irradiance uncertainty

DNV calculated the uncertainty or the interannual variability (IAV) of the solar resource for each region in the Portfolio as shown in Table 1-4. The Portfolio level IAV, which is influenced by each regional IAV value, is used to forecast portfolio level uncertainty in Table 1-5 below.

Table 1-4 Future uncertainty by region

 

Region		Inter-Annual   Variability
AZ		1.58%
CA		2.82%
CO		2.40%
CT		3.10%
FL		2.31%
GA		3.63%
IL		2.58%
KS		2.40%
MA		2.89%
MD		2.88%
ME		2.87%
MI		2.40%
MO		3.33%
NC		3.03%
NH		2.88%

 

 

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Region		Inter-Annual Variability
NJ		3.02%
NM		2.01%
NV		2.27%
NY		2.55%
OH		2.52%
OK		3.52%
PA		2.86%
RI		3.05%
TX		3.81%
VA		2.83%
Portfolio		2.10%

1.4.2  Annual forecasts inclusive of irradiance uncertainty only

Table 1-5 shows probability of exceedance values for the Portfolio for any given year when the only source of uncertainty considered is IAV. Availability losses or historical performance of the systems in the forecast sample and degradation are not considered in Table 1-5 below. Values are not specific to Year 1 of the Portfolio, but represent the probability of exceedance of the IAV for any 1-year period given the historical IAV of the regions represented in the Portfolio.

Table 1-5 Portfolio exceedance values considering IAV only

 

Exceedance value		1- year
P50		1.0000
P75		0.9858
P90		0.9730
P95		0.9654
P99		0.9511

1.5  Degradation

For an individual system utilizing standard crystalline modules, DNV utilizes an asymmetric system-level degradation distribution with a mean of 0.81%. This system-level degradation rate distribution is based on a peer-reviewed study published by NREL and DNV. The study analyzed a quality-controlled performance data from numerous PV installations to isolate the effect of degradation from other performance factors. For Maxeon systems, DNV utilizes an annual system-level P50 degradation factor of 0.25%.

DNV notes that the study was primarily based on performance data from larger-capacity PV systems, rather than residential-scale systems study.

 

 

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There are notable differences between long-term module level degradation rates, such as the rates detailed in manufacturers warranties, and system level degradation. This difference is often attributed to BOS losses and system level degradation, which is the sum of the module level degradation and BOS degradation effects. It should be emphasized that a module can degrade at a rate independent of other modules. Over time the variation of these rates leads to system mismatch where the optimum operating current and voltages of modules may vary. For hardwired arrays this can lead to none of the degraded modules working as well in the array as they would individually, and this impact is expected to increase with time.

The Portfolio will utilize microinverters and module-level-power-electronic (MLPE) technology. The utilization of micro-inverters and module-level-power-electronics technology on residential sites can theoretically mitigate some of the electrical mismatch that can further degrade system performance; however, DNV currently lacks sufficient and statistically robust data to evaluate this behavior.

DNV performed a simulation on the Portfolio systems to estimate the uncertainty in Portfolio-level degradation. A key assumption is that each module model behaves independently. Other factors can create either correlation or independence in degradation; however, little data is available to inform how these factors behave. In each realization of the simulation, a degradation rate is randomly sampled from a distribution unique to each module model, and this degradation rate is assigned to all systems utilizing that same module make and model. The Portfolio-level degradation rate was calculated as an energy estimate-weighted average of the degradation rates for all systems within the Portfolio. The results of 1,000 simulations of the Portfolio are presented in the table below.

Table 1-6 Portfolio degradation rates

 

Percentile		Degradation rate
P50		0.80%
P75		0.92%
P90		1.04%
P95		1.11%
P99		1.26%

1.6 Performance guarantee payout modeling

DNV anticipates that in some cases the Customer’s performance guarantee under its customer agreements will result in reimbursements paid to homeowners. Performance guarantee payouts are observed throughout the residential solar industry.

DNV understands that the Customer guarantees 90% of expected production for both PPA and lease systems. Actual production in a given true-up period below 90% results in a refund to the customer, while actual production above 90% will be used to offset future underperformance. The true-up period for systems in the Portfolio is three years or two years depending on the contract.

When forecasting performance guarantee payouts DNV considers the historical performance of assets in the portfolio (defined as Correction Factor or Regional Correction Factor), IAV, and degradation. In the performance guarantee model, DNV calculates Correction Factor by averaging the annual Performance Index values for all systems in the Production Sample for that region that have more than two years of production data. The Correction Factor standard deviation for a given region is calculated by taking a standard deviation of annual Performance Index values for each system in a region.

 

 

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Then all system level standard deviations are averaged to determine a regional standard deviation for modeling purposes. The table below shows the performance guarantee Correction Factor and Correction Factor standard deviation for the performance guarantee calculations.

Table 1-7 Performance guarantee Correction Factors and standard deviation

 

Region		Systems with 2+ yrs data in Production Sample		Correction Factor		Standard deviation
US		12,860		0.96		0.040

DNV has forecast performance guarantee payouts for the Portfolio based on each system having either:

 

•

25 year agreement with a 3-year pay schedule, with the last year being a 1-year true-up

 

•

20 year agreement with a 3-year pay schedule, with the last year being a 2-year true up

 

•

20 year agreement with a 2-year pay schedule

The model was run at a 90% guarantee level via Monte Carlo simulation for the Forecast Sample of 24,102 systems, which were sampled from the 12,860 systems with sufficient data. The methodology employed for these calculations for both the lease and PPA systems is as follows:

 

1)

The calculations were performed on the 24,102 systems in the Forecast Sample. Each asset was assigned a first- year generation estimate in units of kWh/year by multiplying its kWdc size by the average yield factor of each state.

 

2)

For each system, production was simulated for each year of the customer agreement according to the following process:

 

a.

A Regional Correction Factor was sampled from the system’s Regional Correction Factor distribution for each year of each system realization.

 

b.

A degradation rate was sampled for each system for each realization. DNV’s degradation distribution for PV systems has a median of 0.64% and a mean of 0.81%.

 

c.

For each year of each system realization, inter-annual variability values were sampled from the Portfolio variability distributions for each year. These variability values were applied to the simulated production from (b).

 

3)

If production for any year was below either 90% of the estimate for that year, the difference was considered reimbursable energy, and a refund is issued to the homeowner. If production exceeded the guaranteed production, that amount is banked against future underproduction.

 

4)

For each system, the annual reimbursement rates were calculated as the ratio of the reimbursable energy to the estimated production in that year. The system’s total reimbursement rate was calculated as the ratio of the total reimbursable energy to the total energy produced. The average reimbursement rate was calculated for each region for both the annual and the lifetime results.

 

5)

The model was run with 1,000 realizations and the P50, P75, P90, and P99 reimbursement rates were calculated.

 

 

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Results are presented in Table 1-8 below as the ratio of reimbursable energy to the forecast energy for that three-year period (one year period for the last year of contract term). DNV’s forecast assumes that each system starts on the same date. The forecasts can be applied proportionally across different start years.

Table 1-8 Performance guarantee payout forecasts for the Portfolio, 25 years with a 3-year payout schedule

 

Year		P50		P75		P90		P95		P99
1
2
3		0.04%		0.10%		0.21%		0.29%		0.42%
4
5
6		0.20%		0.26%		0.32%		0.36%		0.44%
7
8
9		0.63%		0.72%		0.80%		0.85%		0.92%
10
11
12		1.17%		1.28%		1.38%		1.43%		1.52%
13
14
15		1.81%		1.92%		2.03%		2.08%		2.18%
16
17
18		2.49%		2.63%		2.73%		2.79%		2.91%
19
20
21		3.27%		3.40%		3.51%		3.58%		3.69%
22
23
24		4.08%		4.22%		4.34%		4.41%		4.51%
25		4.58%		4.75%		4.89%		4.97%		5.11%

Table 1-9 Performance guarantee payout forecasts for the Portfolio, 20 years with a 3-year payout schedule

 

Year		P50		P75		P90		P95		P99
1
2
3		0.04%		0.10%		0.21%		0.29%		0.42%
4
5
6		0.20%		0.26%		0.32%		0.36%		0.44%

 

 

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7
8
9		0.63%		0.72%		0.80%		0.85%		0.92%
10
11
12		1.17%		1.28%		1.38%		1.43%		1.52%
13
14
15		1.81%		1.92%		2.03%		2.08%		2.18%
16
17
18		2.49%		2.63%		2.73%		2.79%		2.91%
19
20		3.13%		3.27%		3.38%		3.45%		3.56%

Table 1-10 Performance guarantee payout forecasts for the Portfolio, 20 years with a 2-year payout schedule

 

Year		P50		P75		P90		P95		P99
1
2		0.04%		0.11%		0.25%		0.35%		0.50%
3
4		0.08%		0.12%		0.17%		0.20%		0.29%
5
6		0.25%		0.31%		0.37%		0.41%		0.50%
7
8		0.54%		0.63%		0.71%		0.76%		0.81%
9
10		0.89%		0.99%		1.08%		1.14%		1.22%
11
12		1.27%		1.38%		1.48%		1.53%		1.63%
13
14		1.69%		1.80%		1.91%		1.96%		2.07%
15
16		2.15%		2.26%		2.37%		2.43%		2.55%
17
18		2.61%		2.75%		2.85%		2.91%		3.02%
19
20		3.13%		3.27%		3.38%		3.45%		3.56%

 

 

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2  TECHNICAL INPUTS TO FINANCIAL MODEL

2.1  PV equipment replacement modeling

DNV modelled expected equipment replacement costs for inverters, modules, monitoring equipment for the Portfolio as provided in the Portfolio characteristics provided by Palmetto [2].

The model is designed to simulate an ownership model in which Palmetto is responsible for all O&M costs. DNV’s model considers equipment failure rates, projected equipment costs, equipment warranties, system size, likelihood of multiple non-critical failures on a single system, and labor costs.

2.1.1  PV equipment replacement assumptions

2.1.1.1  Portfolio PV equipment replacement assumptions

 

•

The lease/PPA for all systems is 25 years; no lease renewals or defaults are considered.

 

•

No equipment replacement costs past lease expiration date.

 

•

Systems in the Portfolio were installed in 2023-2025.

DNV modeled the inverter capacities in Table 2-1.

Table 2-1 Portfolio inverter OEM

 

Inverter OEM		Capacity (kWdc)		% of total capacity
Enphase		130,714		62.39%
Tesla		51,605		24.26%
SolarEdge		27,351		13.35%
Schneider		7		0.00%
Total		209,677		100%

DNV modeled module capacities and quality classifications in Table 2-2.

Table 2-2 Portfolio module OEM

 

Module OEM		Capacity (kWdc)		% of total capacity		Quality classification
QCells		71,117		33.92%		High
Jinko		42,832		20.43%		High
Trina		24,233		11.56%		High
Hyundai		19,989		9.53%		Typical
Longi		13,466		6.42%		High
JA Solar		11,798		5.63%		High
REC		7,713		3.68%		High
Canadian Solar		6,816		3.25%		High
Silfab		6,561		3.13%		Typical
VSUN		1,726		0.82%		Typical

 

 

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Module OEM		Capacity (kWdc)		% of total capacity		Quality classification
Maxeon		1,698		0.81%		High
SEG		828		0.39%		Unknown
Mission		458		0.22%		Unknown
Ureco		390		0.19%		Unknown
Sunpower		52		0.02%		High
Total		209,677		100%

2.1.1.2  Labor PV equipment replacement assumptions

DNV modeled the anticipated costs to replace all PV equipment (modules, string inverters, optimizers, microinverters, and monitoring and communications equipment) in the Portfolio. DNV assumed the labor costs are fully born by Palmetto for the entire Portfolio.

 

•

Truck roll costs are synonymous with labor costs and are exclusive of equipment costs.

•

Palmetto provided DNV with average historical truck roll costs by equipment type as well as the average number of truck rolls required for each type of failure to fully remedy [3]. The table below presents the average truck roll costs presented to DNV and the average number of truck rolls required for each type of failure.

Table 2-3 Labor costs by failure type

 

Equipment type		Truck roll cost range		Average number of truck rolls required		Total replacement labor cost per failure
Microinverter		$430		1.11		$478
Optimizer		$398		1.11		$442
String		$366		1.11		$407

 

•

Labor costs per failure have been modeled at a blended rate of $456, which considers the distribution of microinverter, optimizer, and string inverter systems in the Portfolio.

•

The failure of one module, optimizer, or microinverter, all considered non-critical components, only decreases system production incrementally by the proportion of energy represented by that part in the system. DNV’s model requires that at least five (5) non-critical components fail before a truck roll is allowed on a given system.

•

In order to model the number of truck-rolls required, DNV used the binomial distribution to calculate the number of sites which had a minimum threshold of failed non-critical components. For example, a minimum threshold could be one (1) failed microinverter and one (1) failed module on an Enphase system. The binomial distribution can be used to calculate how many sites have two (2) non-critical component failures necessitating a truck roll.

•

Labor cost escalation has not been modeled.

•

DNV did not model reimbursement from manufacturers for warranty replacement labor.

2.1.1.3  Equipment PV equipment replacement assumptions

DNV’s O&M cost forecasting assumes the Sponsor possesses mature logistics capabilities and is able to exercise and enforce all relevant equipment warranties to their fullest extent. Under successful warranty claims, the equipment and shipping costs to replace failed components are fully covered by the original equipment manufacturer. Each equipment

 

 

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manufacturer provides distinct warranty terms, after which all replacement equipment costs are fully borne by the system Owner.

 

•

Equipment is modeled considering the following warranties:

•

Modules:

 

◾

High Durability: 30 years

◾

Typical Quality: 25 years

◾

Unknown Quality: 25 years

○

Inverters:

◾

Enphase microinverters: 25 years

◾

Schneider inverters: 13 years

◾

SolarEdge inverters: 25 years

◾

SolarEdge optimizers: 25 years

◾

Telsa inverters: 12.5 years

○

Monitoring hardware: 5 years for all manufacturers

•

DNV assumes monitoring hardware count is the same as the number of string inverters, and for systems with microinverters 1 monitoring system is used per project

•

DNV assumes 1.2 string inverters per system.

•

For each Tesla inverter installed, Palmetto holds $600 back from each installer. This is put into a reserve to be allocated toward Tesla inverter failures after the Tesla 12.5-year inverter warranty expires. DNV modeled a reserve of $3,875,040 ($600 * 6,458 Tesla inverters) against which equipment costs of Tesla inverters are offset after the warranty expires. The reserve covers inverter equipment costs until 2048.

•

DNV assumes all warranties are honored for the full term and has not derated any warranty terms based on the financial strength of the OEMs.

•

DNV considers primary and secondary equipment failures, meaning equipment that is replaced can fail again.

•

DNV uses a DNV-modified version of Wood Mackenzie’s H1 2024 US solar PV system pricing data [4].

Figure 2-1 displays the forecast O&M costs for the Portfolio.

 

 

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2.1.2  Inverter replacement equipment costs

Table 2-4 below displays DNV’s modeled equipment replacement costs for inverters and optimizers in the Portfolio. Optimizers only apply to SolarEdge inverters for the Portfolio. DNV has assigned the costs below to respective components in the Portfolio. In all cases, the Wood Mackenzie forecast extends to 2034 [4]. Thereafter, DNV assumes a 2% annual cost reduction until 2044 where DNV assumes a flatline of costs.

Table 2-4 Inverter equipment replacement costs

 

Year		String [$/Wdc]		Microinverter [$/Wdc]		Optimizer [$/Wdc]
2025		$0.148		$0.347		$0.168
2026		$0.145		$0.340		$0.165
2027		$0.142		$0.333		$0.162
2028		$0.139		$0.327		$0.158
2029		$0.136		$0.320		$0.155
2030		$0.134		$0.314		$0.152
2031		$0.132		$0.307		$0.149

 

 

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Year		String [$/Wdc]		Microinverter [$/Wdc]		Optimizer [$/Wdc]
2032		$0.131		$0.301		$0.146
2033		$0.130		$0.295		$0.143
2034		$0.128		$0.289		$0.140
2035		$0.126		$0.284		$0.137
2036		$0.123		$0.278		$0.135
2037		$0.121		$0.272		$0.132
2038		$0.118		$0.267		$0.129
2039		$0.116		$0.262		$0.127
2040		$0.114		$0.256		$0.124
2041		$0.111		$0.251		$0.122
2042		$0.109		$0.246		$0.119
2043		$0.107		$0.241		$0.117
2044		$0.105		$0.236		$0.115
2045		$0.105		$0.236		$0.115
2046		$0.105		$0.236		$0.115
2047		$0.105		$0.236		$0.115
2048		$0.105		$0.236		$0.115
2049		$0.105		$0.236		$0.115
2050		$0.105		$0.236		$0.115

2.1.3  Inverter failure rates

DNV assumes the inverter and optimizer failure rates as shown in Figure 2-2. DNV’s projected failure rates are based on available data.

 

 

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2.1.4  Module replacement costs

Table 2-5 below displays DNV’s modeled equipment replacement costs for modules in the Portfolio. In all cases, the Wood Mackenzie forecast extends to 2034 [4]. Thereafter, DNV assumes a 3% annual cost reduction until 2045 where DNV assumes a flatline of costs.

Table 2-5 Module equipment replacement costs

 

Year		Module [$/Wdc]
2025		$0.284
2026		$0.268
2027		$0.263
2028		$0.260
2029		$0.256
2030		$0.251
2031		$0.247
2032		$0.243
2033		$0.239
2034		$0.242
2035		$0.234
2036		$0.227

 

 

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Year		Module [$/Wdc]
2037		$0.221
2038		$0.214
2039		$0.208
2040		$0.201
2041		$0.195
2042		$0.189
2043		$0.184
2044		$0.178
2045		$0.178
2046		$0.178
2047		$0.178
2048		$0.178
2049		$0.178
2050		$0.178

2.1.5  Module failure rates

DNV assumes the module failure rates as shown in Figure 2-3. DNV’s projected failure rates are based on available data.

 

 

 

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2.1.6  Meter replacement costs 

Table 2-6 below displays DNV’s modeled equipment replacement costs for meters in the Portfolio. DNV assumes a cost of $250/meter for all years forecasted. Palmetto confirmed their historical data supports this $250 blended rate for meter replacement costs. [5] 

Table 2-6 Meter replacement costs 

 

Year		Meter  [$/meter]
2025		$250.00
2026		$250.00
2027		$250.00
2028		$250.00
2029		$250.00
2030		$250.00
2031		$250.00
2032		$250.00
2033		$250.00
2034		$250.00
2035		$250.00
2036		$250.00
2037		$250.00
2038		$250.00
2039		$250.00
2040		$250.00
2041		$250.00
2042		$250.00
2043		$250.00
2044		$250.00
2045		$250.00
2046		$250.00
2047		$250.00
2048		$250.00
2049		$250.00
2050		$250.00

2.1.7  Meter failure rates

DNV assumes the meter failure rates as shown in Figure 2-4.

 

 

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2.1.8  Portfolio equipment replacement forecast

Table 2-7 below shows the equipment replacement forecast $/kWdc by year for the Portfolio. DNV also notes that these costs are exclusive of labor inflation.

Table 2-7 Annual equipment replacement cost forecast for the Portfolio

 

Year		Equipment $/kWdc		Labor $/kWdc		Total $/kWdc
2026		$0.00		$0.27		$0.27
2027		$0.00		$0.15		$0.15
2028		$0.00		$0.14		$0.14
2029		$0.00		$0.14		$0.14
2030		$0.00		$0.14		$0.14
2031		$0.00		$0.14		$0.14
2032		$0.00		$0.15		$0.15
2033		$0.01		$0.17		$0.18
2034		$0.05		$0.27		$0.32
2035		$0.19		$0.58		$0.76
2036		$0.55		$1.42		$1.98
2037		$1.33		$3.16		$4.48
2038		$2.39		$5.82		$8.22
2039		$3.52		$8.68		$12.20
2040		$4.10		$10.35		$14.46
2041		$3.79		$10.04		$13.83
2042		$2.77		$8.10		$10.87
2043		$1.60		$5.89		$7.48
2044		$0.73		$4.67		$5.40
2045		$0.26		$4.79		$5.05
2046		$0.08		$5.31		$5.39
2047		$0.04		$4.59		$4.63
2048		$1.72		$4.05		$5.77
2049		$2.64		$3.74		$6.39
2050		$2.05		$3.30		$5.35
Column total ($/kWdc)		$27.83		$86.05		$113.88

Table 2-8 below shows the equipment replacement forecast total spend by year for the Portfolio. DNV also notes that these costs are exclusive of labor inflation.

 

 

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Table 2-8 Annual equipment replacement cost forecast for the Portfolio

 

Year		Equipment $		Labor $		Total $
2026		$0		$56,077		$56,077
2027		$0		$30,545		$30,545
2028		$0		$29,634		$29,634
2029		$0		$29,634		$29,634
2030		$0		$29,634		$29,634
2031		$0		$29,634		$29,634
2032		$221		$30,545		$30,767
2033		$2,387		$36,016		$38,404
2034		$10,847		$55,617		$66,464
2035		$39,395		$120,783		$160,177
2036		$116,232		$297,967		$414,199
2037		$277,850		$662,490		$940,340
2038		$502,023		$1,221,011		$1,723,033
2039		$738,261		$1,819,577		$2,557,839
2040		$860,659		$2,170,844		$3,031,503
2041		$794,516		$2,104,621		$2,899,137
2042		$580,486		$1,698,286		$2,278,772
2043		$334,800		$1,234,615		$1,569,415
2044		$152,582		$978,877		$1,131,459
2045		$55,180		$1,003,333		$1,058,513
2046		$17,191		$1,113,880		$1,131,071
2047		$8,996		$961,682		$970,678
2048		$360,207		$849,506		$1,209,713
2049		$553,982		$784,810		$1,338,792
2050		$315,634		$508,312		$823,947
Column total		$5,721,450		$17,857,929		$23,579,379

 

2.2	BESS equipment replacement modeling

DNV modeled the cost of replacing BESS within the Portfolio. The Portfolio has been modeled with 4,787 BESS units according to the distribution in the table below.

Table 2-9 Portfolio BESS Breakdown

 

Supplier		Units		Concentration
Tesla		2,447		51%
Enphase		2,083		44%
SolarEdge		256		5%
Franklin		1		0%
Total		4,787		100%

 

 

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DNV made the following assumptions:

 

•

BESS units cost $6,250 in Year 1 and decline in cost at 3.5% annually for 20 years.

 

•

Secondary failures are also modeled, meaning that a replaced unit can fail again.

 

•

Each unit that fails is required to be replaced.

 

•

Palmetto confirmed that a BESS truck roll is $366 and the average number of truck rolls to replace a failed BESS is 1.11 [3]. Therefore, DNV modeled the cost of labor as $407 per BESS failure.

 

•

All units were modeled as installed in the same year. DNV notes that most assets in the Portfolio were installed in 2025 with a few in 2023 and 2024.

 

•

No labor escalation has been modeled.

Each BESS product follows manufacturer specific warranty and labor reimbursement terms as provided by Palmetto and shown in the table below. To the extent that manufacturer labor reimbursement does not cover the full modeled labor cost, DNV considers the difference to be payable by Palmetto, which has been considered in the model results.

Table 2-10 Portfolio BESS Breakdown

 

Supplier		Warranty term  (years)		Labor  reimbursement  term (years)		First labor  reimbursement		Second labor  reimbursement
Enphase		15		15		$350		$350
Franklin		12		0		$0		$0
SolarEdge		10		10		$250		$125
Tesla1		12		5		$450		$450

All products were modeled along DNV’s generic 70% BESS failure curve shown in Table 2-11.

Table 2-11 DNV generic BESS failure curve

 

Year		Failure Rate
1		6.40%
2		2.20%
3		1.60%
4		2.00%
5		1.80%
6		2.00%
7		1.50%
8		4.20%
9		17.10%
10		17.70%
11		1.80%
12		3.00%
13		5.60%

1	DNV notes that given Tesla’s first and second labor reimbursement is greater than the modeled cost of a truck roll ($407), DNV assumed that Tesla’s reimbursement would only be up to the truck roll cost of $407.

 

 

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