Level 4 · Energy Technologies & Economics · Module 11
Solar & Wind Economics
Why can two 100 MW projects have completely different values?
- 4
- connected lessons
- 8
- guided learning steps
- 180
- estimated minutes
The central idea
Why can two 100 MW projects have completely different values?
Installed MW do not determine value. Actual MWh multiplied by the achieved capture price creates revenue.
Installed MW do not determine value. Actual MWh multiplied by the achieved capture price creates revenue. The public preview explains the operating logic, professional relevance and boundaries before the complete guided application.
Professional relevance
Why this matters beyond the classroom.
Developers optimise site and design engineers defend resource and loss assumptions grid teams quantify export and curtailment
What you will learn
Four lessons that build one working mental model.
- 01
From Resource to Gross Energy
Installed MW, irradiation, wind distributions, power curves, yield studies and hourly profiles.
A 100 MW solar park and a 100 MW wind farm can never be compared by capacity alone. MW describe the maximum instantaneous active power under defined conditions. Investors are paid mainly for energy delivered over intervals, expressed in MWh, and for any additional contracted attributes or services. The route from nameplate to revenue passes through resource, equipment, losses, timing, network access and market prices. Even two solar projects with identical modules can differ because irradiation, horizon, temperature, orientation, DC/AC ratio, soiling, snow, electrical design and grid constraints differ. Two wind projects can differ because the entire wind-speed distribution, shear, turbulence, air density, terrain, wakes, turbine selection and availability differ. A project with fewer annual MWh may still earn more if its output occurs in higher-price hours or enjoys stronger contractual protection. The correct central equation is not MW times hours times an optimistic resource assumption. It is actual settled MWh multiplied interval by interval by achieved prices, plus eligible additional revenues, less market and contractual deductions. Every step must have a boundary, source and uncertainty. Solar projects may quote module DC capacity in MWp and inverter/export AC capacity in.
- 02
From Gross to Net Sold MWh
Availability, electrical and environmental losses, degradation, wake effects, clipping and curtailment.
PV modules generally experience output degradation over time, but the model should distinguish warranted limits, expected central estimates and actual measured behaviour. Inverters and transformers may require replacement or refurbishment rather than a smooth degradation rate. Potential-induced degradation, light-induced effects, soiling trends and weather damage are not identical phenomena. Wind farms may experience performance changes from blade erosion, component ageing, control optimisation, environmental changes and availability evolution. Modelling every effect as a single annual percentage is convenient but may be inaccurate. Major component replacement can restore capability while creating downtime and CAPEX. Apply degradation to the correct energy stage and timing. A 0.4% annual assumption may mean year two equals year one times 99.6%, compounding thereafter; clarify whether degradation begins immediately or after the first operating year. Because LCOE divides discounted lifetime cost by discounted lifetime MWh, degradation raises LCOE and reduces later revenue, with larger impact on longer-lived projects. Curtailment reduces otherwise available generation. Its causes can include local connection limits, planned grid works, congestion management, system security, negative-price or subsidy rules, balancing instructions, environmental constraints, shared-connection controls and commercial optimisation. The party bearing the lost-volume and lost-price consequences.
- 03
Probability and Production Risk
Interannual variability, modelling uncertainty, P50/P75/P90, exceedance probability and portfolio effects.
As more similar generation enters a market, it tends to produce simultaneously under the same weather conditions. The added low-marginal-cost supply can reduce prices precisely when that technology generates most, eroding its capture rate. This is called cannibalisation. It does not imply that every new solar or wind MWh has zero value; the result depends on demand, interconnection, storage, flexible load, thermal retirements and market design. Historical capture rates should not be projected unchanged through 25 years. Forward baseload curves also do not provide technology-specific shape. Long-term price modelling needs scenarios for generation mix, commodity and carbon prices, demand electrification, flexibility, grid build-out and policy. Because these assumptions are uncertain, use several internally consistent scenarios. Design can respond. East-west solar, tracking, wind/solar diversification, storage, hybrid controls and flexible offtake can shift or preserve value. Their economics must include incremental CAPEX, efficiency losses, shared-grid constraints and contract terms. Volume risk is uncertainty in how many MWh are produced. Profile or shape risk concerns when those MWh occur relative to a contracted delivery shape or prices. Basis risk arises when the project settles at one price or node while its hedge references.
- 04
From MWh to Revenue and Value
Capture price, cannibalisation, grid constraints, merchant exposure, LCOE and integrated sensitivities.
Project S is 100 MWac solar with 130 MWp DC, 210 GWh P50 net production and a 24.0% AC capacity factor. Its baseload price scenario is EUR80/MWh, but hourly weighting produces a EUR64/MWh capture price. Before other revenue, value is EUR13.44 million. Project W is 100 MW wind with 300 GWh P50 and a 34.2% factor. At a EUR72/MWh capture price, value is EUR21.60 million. This does not prove W is superior. Suppose S costs EUR75 million and W EUR155 million; OPEX, degradation, P90 spreads, construction timing and contracts differ. If S has a EUR75/MWh pay-as-produced PPA while W is merchant with material congestion, S may offer more stable debt service. If grid curtailment removes 12% of S's midday output but only 2% of W's, the opposite may follow. The example shows the correct sequence: production, temporal value, costs, contracts and risk. EUR/MW or capacity factor alone cannot answer the investment question. Single-variable sensitivities identify arithmetic exposure: CAPEX plus or minus 10%, P50 energy plus or minus 5%, capture price plus or minus EUR10/MWh, curtailment, availability, degradation and COD delay. Combined scenarios test plausible stories. A congested-renewables case might combine.
Key takeaways
What should remain after the details.
- Maximum power under defined conditions, not annual output or value.
- Resource and conversion must be modelled, not multiplied by a single generic factor.
- The authored source identifies “wind-speed distribution and power curve” as the correct interpretation.
- P90 moves lower; it never means 90% of P50.
- The authored source identifies “level exceeded with 90% probability under stated assumptions” as the correct interpretation.
- Midday prices and solar capture rate can fall through cannibalisation.
- Headline PPA price is not automatically realised revenue.
- The authored source identifies “correlated renewable output depresses prices in its producing hours” as the correct interpretation.
Correct the shortcut
Common misconceptions
- Equal MW means equal output
- This shortcut is incomplete; apply the module’s definitions, system boundary and operating constraints before drawing a conclusion.
- irradiation equals PV energy
- This shortcut is incomplete; apply the module’s definitions, system boundary and operating constraints before drawing a conclusion.
- average wind speed determines wind energy
- This shortcut is incomplete; apply the module’s definitions, system boundary and operating constraints before drawing a conclusion.
- time availability equals energy availability
- This shortcut is incomplete; apply the module’s definitions, system boundary and operating constraints before drawing a conclusion.
- P90 is 90% of P50
- This shortcut is incomplete; apply the module’s definitions, system boundary and operating constraints before drawing a conclusion.
Worked reasoning
Correlation must survive scenarios
Resource, price and curtailment are not independent. High regional solar output may lower solar prices and increase congestion. Strong wind may create similar effects. Low hydro or thermal outages can change the same relationship. Combining P90 volume with a low-price scenario may be conservative, but its coherence depends on weather-price correlation and the decision purpose. Create scenario years or chronological simulations that retain hourly relationships. If using separate weather and market models, document how years are paired and whether climate trends are considered. Test a high-renewables/slow-grid case, a flexible-demand/storage case and a commodity-driven price case rather than only parallel percentage shocks. Portfolio diversification depends on correlation too. Two geographically separated wind farms reduce risk only to the extent that their outputs and constraints differ. Solar and wind can complement one another seasonally or intraday, but evidence must quantify it.
Concept map
The vocabulary this module connects.
- Installed MW
- irradiation
- wind distributions
- power curves
- yield studies and hourly profiles.
- Availability
- electrical and environmental losses
- degradation
- wake effects
- clipping and curtailment.
- Interannual variability
- modelling uncertainty
- P50/P75/P90
- exceedance probability and portfolio effects.
- Capture price
- cannibalisation
- grid constraints
- merchant exposure
- LCOE and integrated sensitivities.
Evidence boundary
Selected authoritative sources
Research reviewed 2026-08-13. The complete learning package contains the full reference trail and explains where simplified beginner models stop.
- European Commission Joint Research Centre, PVGIS online toolResearch source used in the Solar & Wind Economics learning package
- European Commission JRC, PVGIS data sources and calculation methodsResearch source used in the Solar & Wind Economics learning package
- European Commission JRC, PVGIS user manualResearch source used in the Solar & Wind Economics learning package
- IRENA, Renewable Power Generation Costs in 2024Research source used in the Solar & Wind Economics learning package
- IEA, Renewables 2024Research source used in the Solar & Wind Economics learning package
Questions answered
Solar & Wind Economics FAQ
Why can two 100 MW projects have completely different values?
Installed MW do not determine value. Actual MWh multiplied by the achieved capture price creates revenue.
Why does solar & wind economics matter to energy professionals?
Developers optimise site and design engineers defend resource and loss assumptions grid teams quantify export and curtailment
What will I learn in this Solar & Wind Economics module?
You will connect Installed MW, irradiation, wind distributions, power curves, yield studies and hourly profiles.; Availability, electrical and environmental losses, degradation, wake effects, clipping and curtailment.; Interannual variability, modelling uncertainty, P50/P75/P90, exceedance probability and portfolio effects.; Capture price, cannibalisation, grid constraints, merchant exposure, LCOE and integrated sensitivities..
What remains inside the complete learning module?
The complete module contains the full readings, guided decisions, feedback, mastery assessment and professional challenge, with progress recorded in the learner experience.
Learn, apply, test
Reading is only the beginning.
The complete module adds guided decisions, feedback, a mastery assessment and a professional challenge. Your progress remains in your learner dashboard.