Every industrial solar project begins the same way.
A contractor or consultant presents a feasibility study. It contains yield simulations, financial projections, a performance guarantee framework, and a conclusion that invariably says the same thing — this project makes financial sense.
The plant manager reviews the executive summary. The financial director checks the payback period and the IRR. The board approves the investment. The contract is signed.
And almost nobody — in the entire decision-making chain — actually reads the assumptions behind the numbers.
I work on the ground — managing a solar PV autoconsumption system at a cement plant in Morocco. Over the past few years, I have also been asked to independently review feasibility studies for other industrial solar projects in this market — including one project representing an investment of more than 5 million euros.
Across all of them, I have seen the same pattern repeat with remarkable consistency.
The assumptions that determine whether the project delivers its promised returns for 25 years — the irradiation dataset, the soiling figure, the temperature derating model — are presented with the same confidence as the project name and the installation date. They are almost never questioned.
The most expensive mistake in industrial energy is not a technical error. It is the decision to accept a feasibility study without understanding what it actually says — and what it deliberately leaves unsaid.
This article will change that.
Disclosure: This article contains affiliate links. If you purchase through these links, I may earn a small commission at no extra cost to you. I only recommend technical resources that I consider genuinely useful for industrial solar professionals working in Africa and the MENA region.
Why feasibility studies are systematically optimistic
I want to be precise here — because this is not a criticism of individual consultants or contractors. Most feasibility studies I have reviewed were prepared by competent professionals who genuinely believed their methodology was sound.
The problem is structural.
A feasibility study is prepared by someone who wants the project to proceed — either because they will build it, because they are paid to advise on it, or because their client wants to see a positive result. In this environment, the natural human tendency is to select assumptions that make the numbers work — not assumptions that reflect the most probable operating reality.
This is not dishonesty. It is the predictable consequence of incentive structures that nobody talks about honestly.
The result is a feasibility study that represents the best plausible scenario — presented as if it were the most probable one.
For a 2 MWp industrial solar project in Morocco — a feasibility study that overestimates annual yield by 10% creates a financial gap of approximately 36,000 USD per year. Over 25 years — that is 900,000 USD of returns that were promised in the document and never delivered in reality.
On larger projects the numbers scale proportionally — and the damage compounds accordingly.
The single biggest error I have seen on real projects in Morocco
Before going through all five critical assumptions — I want to start with the one that has caused the most financial damage on real projects I have observed.
Irradiation data that is too optimistic.
On a project I was asked to review independently — representing more than 5 million euros of investment in Morocco — the feasibility study showed exactly this pattern.
The consultant used a single satellite dataset — a common and widely accepted approach — and applied the P50 median value directly as the production guarantee baseline. No second source was cross-referenced. No uncertainty buffer was applied.
What this means in practice is that the financial model was built on a number that — by statistical definition — will be exceeded only 50% of years. In the other 50% of years, actual production will fall below this figure. And in years where irradiation is meaningfully below the P50 value — the financial shortfall is real, immediate, and entirely consistent with the assumptions in the document.
Nobody had explained this to the investor before they committed capital.
On a project above 5 million euros — the difference between a P50 and a P90 production estimate can represent 200,000 to 400,000 USD per year in electricity savings. That gap is not an engineering error. It is a communication failure — and it is entirely preventable if the right questions are asked before the contract is signed.
The five assumptions that matter most
Assumption 1 — The irradiation dataset
As I described above — this is the assumption that has caused the most financial damage on real projects I have observed in Morocco.
What to do : Request that the feasibility study cross-references irradiation data from at least two independent satellite sources — PVGIS at pvgis.ec.europa.eu and NASA POWER at power.larc.nasa.gov as a minimum.
Request both P50 and P90 production estimates. Ask specifically :
“What does this project look like financially at P90?”
If the answer changes the investment decision materially — the project is more marginal than the headline numbers suggest.
Apply a 5% uncertainty buffer to the P90 estimate before presenting any production figure to investors or management.
Assumption 2 — The soiling loss figure
This is the assumption I scrutinize on every feasibility study I review — and the one where I consistently find the largest gap between the model and the field reality.
The feasibility studies I have reviewed for industrial projects in Morocco — including the project above 5 million euros — typically apply soiling assumptions of 3 to 5% annually. Even on heavy industrial sites where real losses are significantly higher.
At the cement plant where I work — we clean every panel three times per month. And soiling still returns visibly within days of each cleaning cycle near the clinker handling areas.
The honest soiling figure for heavy industrial environments in North Africa is 8 to 15% without a systematic and intensive cleaning program — not 3 to 5%.
The financial consequence of this gap on a 2 MWp project in Morocco :
A 5% soiling underestimate = approximately 60,000 kWh per year in unmodeled production loss = approximately 6,600 USD per year in lost savings = 165,000 USD over 25 years — from a single incorrect assumption
On larger projects — the numbers scale proportionally and the damage is correspondingly more significant.
What to do : Ask your feasibility consultant to justify their soiling assumption in writing — with reference to measured soiling data from comparable industrial sites in similar climates. If they cannot provide this justification — the assumption should be treated as a risk factor, not a validated input.
Assumption 3 — The temperature derating model
Most feasibility studies apply a temperature correction to module output — standard and generally applied correctly.
What is frequently missing is the inverter temperature derating model.
At the industrial site where I work in Morocco — ambient temperatures in the inverter room regularly reach 50 to 55 degrees Celsius during peak summer afternoon hours. Most industrial inverters begin thermal derating above 40 to 45 degrees Celsius. At 52 degrees — output reduction of 6 to 12% during peak production hours is entirely normal — and entirely invisible on a standard monitoring dashboard.
This loss does not appear in most feasibility studies because the designer assumed adequate ventilation — or because the thermal derating curve was simply not applied to the specific inverter models proposed.
What to do : Ask specifically whether inverter thermal derating has been modeled — and at what ambient temperature. Request the thermal derating curve for the proposed inverter models. If inverter room temperature assumptions are not documented — treat summer production figures as potentially optimistic.
Assumption 4 — The DC/AC ratio
For MENA and African industrial sites — a DC/AC ratio of 1.20 to 1.35 is appropriate. Many feasibility studies for industrial projects in this region propose ratios of 1.10 to 1.15 — lower ratios that reduce apparent inverter clipping in the simulation output but leave real annual production on the table.
On larger projects in Morocco — the difference between a DC/AC ratio of 1.15 and 1.30 can represent 3 to 5% in additional annual yield. At any scale — that is a financially significant decision that deserves explicit justification in the feasibility document.
What to do : Check the DC/AC ratio explicitly in the simulation parameters. If it is below 1.20 for a MENA industrial site — ask why. A well-justified answer is acceptable. The absence of a justification suggests the ratio was selected for presentation purposes rather than engineering optimization.
Assumption 5 — The O&M cost model
Standard O&M cost assumptions in feasibility studies for industrial solar in MENA range from 0.5 to 1% of installed cost per year.
For a 2 MWp system in Morocco — that is 11,000 to 22,000 USD annually at 0.5 to 1%.
For a heavy industrial site with the intensive cleaning program that real operating conditions require — realistic O&M costs are 1.25 to 1.5% of installed cost — 27,500 to 33,000 USD annually for a 2 MWp system.
The gap between the optimistic assumption and the realistic one compounds into a significant difference in actual net returns over 25 years.
What to do : Ask specifically what the O&M cost assumption includes — and what cleaning frequency is assumed. For industrial sites — request that the O&M budget is validated against actual cleaning costs for your specific facility type and environment.
What a rigorous feasibility study actually looks like
A feasibility study that deserves your signature contains :
A yield simulation that includes
P90 production estimate with documented uncertainty analysis. Soiling assumption validated against real data from comparable industrial sites — not a generic 3 to 5% applied uniformly regardless of facility type. Inverter thermal derating applied using manufacturer curves for the specific models proposed. Irradiation data cross-referenced from two independent sources.
A financial model that includes
O&M costs calibrated to the actual facility type and environment. A sensitivity analysis showing project economics under pessimistic irradiation — P90 rather than P50 — high soiling, and elevated O&M scenarios. A clear statement of which assumptions, if wrong, would change the investment decision.
A risk section that actually identifies risks
Not a boilerplate list of generic renewable energy risks — but a specific identification of the risks relevant to your facility, your location, and your grid connection. Soiling risk for your industrial environment. Grid curtailment risk for your specific utility connection. Substation capacity risk given your existing electrical infrastructure.
The book that changed how I read feasibility studies
Understanding how yield simulations are built — and where the assumptions are embedded — requires a level of technical literacy that most decision-makers do not have simply from reviewing project documents.
The reference that gave me the foundation to read these studies critically — and ask the right questions — is Photovoltaic Systems Engineering by Roger Messenger and Amir Abtahi. Chapter 8 on system performance analysis is particularly relevant for anyone who wants to understand what a yield simulation actually calculates — and what it does not.
It is the book I recommend most consistently to engineers and project developers who want to move from accepting feasibility assumptions to genuinely understanding them.
The question that reveals everything
After reviewing any feasibility study — ask the consultant one final question :
“Under what circumstances would this project not meet its financial projections — and how likely are those circumstances at this specific site in Morocco?”
A consultant who answers honestly — identifying specific risk factors for your facility type, quantifying their potential impact, and explaining what mitigation measures are proposed — is a consultant who has done the analysis rigorously.
A consultant who responds with reassurances about simulation software quality or general methodology conservatism — without addressing the specific risks at your site — has not given you the analysis you need to make a sound investment decision.
Field experience teaches you things that no feasibility document ever shows.
Working daily on a real industrial solar system in Morocco — and having been asked to independently review feasibility studies for larger projects in this market, including one above 5 million euros — the pattern becomes impossible to ignore.
The most consistently dangerous assumption across every study I have reviewed was irradiation data that was too optimistic, applied without uncertainty analysis, presented as a production guarantee when it was statistically only a median estimate.
This single assumption — on a project of any size — can represent tens of thousands of dollars per year in the gap between projected and actual returns. On larger projects, that gap scales accordingly.
A solar PV feasibility study is not a guarantee. It is a model built on assumptions that describe one possible future for your investment. The assumptions that matter most are rarely the ones that appear most prominently in the document.
Questioning these assumptions is not a sign of distrust. It is the basic due diligence that any serious capital investment deserves — particularly one that will determine your facility’s energy economics for the next 25 years.
The plant manager who asks the right questions before signing protects millions of euros of returns over the lifetime of the project. The one who accepts the feasibility study without scrutiny discovers the gap — one monthly production report at a time, for 25 years.
If you are evaluating a feasibility study for an industrial solar project in Africa or the MENA region and want an independent technical review of the key assumptions — the contact form is open.
More articles coming soon — a two-year operational review of a real industrial solar system in Morocco, and what your monitoring data is actually telling you.
Publié par :
Solar PV MENA Expert
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Disclosure: This article contains affiliate links. If you purchase through these links, I may earn a small commission at no extra cost to you. I only recommend technical resources that I consider genuinely useful for industrial solar professionals working in Africa and the MENA region.