Assumptions

Assumptions are the foundation of any techno-economic model. Aire helps you document, track, and manage assumptions explicitly—making models more transparent, defensible, and easier to evolve.

Assumptions in Aire

Every model is built on assumptions—about prices, performance, timelines, market conditions, and countless other variables. Unlike static spreadsheets where assumptions are often buried in cells or institutional knowledge, Aire treats assumptions as first-class objects that can be documented, sourced, and updated systematically.

When assumptions are explicit and traceable, models become more credible, collaboration improves, and updating models as conditions change becomes straightforward rather than risky.

What is an Assumption?

An assumption is any input, constant, or premise that underpins your model’s logic. It might represent:

• A projected cost or price (e.g., electricity price = $0.08/kWh)
• A performance parameter (e.g., solar panel efficiency = 22%)
• A timeline or schedule input (e.g., construction duration = 18 months)
• A financial or policy expectation (e.g., ITC rate = 30%)

Assumptions flow through your model as terms, but they’re distinguished by their nature—they’re givens rather than derived calculations.

Why Track Assumptions?

Making assumptions explicit delivers several benefits:

• Transparency: Anyone reviewing the model can see what’s assumed and why
• Traceability: Each assumption can be linked to a source—user input, research, prior projects
• Flexibility: Assumptions can be swapped across cases to explore uncertainty
• Quality: Teams can review, challenge, and validate assumptions collaboratively
• Updates: When conditions change, you can update assumptions in one place rather than hunting through formulas

Assumptions and Cases

Aire’s case system is designed specifically to handle assumption uncertainty. Rather than committing to a single value, you can define multiple cases for any assumption:

• Electricity price: low ($0.06/kWh), base ($0.08/kWh), high ($0.10/kWh)
• Capacity factor: conservative (32%), base (35%), aggressive (38%)
• Policy incentive: no_ITC, ITC_30, ITC_50

Each case represents a different assumption set, and you can build scenarios by selecting specific cases across your model. This lets you reason through what you know, what you don’t, and what the range of outcomes might be.

Documenting Assumptions

In Aire, every assumption-based term carries structured metadata to make it clear and defensible:

• Label: What the assumption represents
• Value: The numerical or categorical input (with units)
• Source: Where the value came from—research, user input, test data, past projects
• Description: Context on what the assumption means and why it matters
• Cases: Alternate values reflecting different possible futures

This metadata travels with the assumption throughout the platform—in views, exports, QA workflows, and scenario comparisons.

Where Assumptions Live

Assumptions are embedded in the model as terms within blocks. For example:

• A solar block might include assumptions about panel efficiency, degradation rate, and installation costs
• A financing block might include assumptions about interest rates, loan terms, and equity requirements
• A market block might include assumptions about electricity prices, REC values, or demand profiles

By organizing assumptions into blocks, you create clear scope boundaries and make it easier to update or swap entire assumption sets when modeling different configurations.

Reviewing Assumptions in Views

Aire provides specialized views designed to help you review and manage assumptions efficiently based on your project data. These views present assumptions in an easy-to-comprehend format, making quality control and stakeholder review straightforward:

Key Assumptions View The Key Assumptions view surfaces the most critical assumptions that drive your model’s outcomes. This curated view helps you focus on the inputs that matter most—the ones that have the greatest impact on key metrics like NPV, IRR, or LCOE. It’s ideal for:

• Executive reviews and investment committee presentations
• Quick sanity checks before running scenarios
• Identifying which assumptions need the most rigorous validation

All Assumptions View The All Assumptions view provides a comprehensive table of every assumption in your model, organized by block and annotated with metadata (units, sources, descriptions, cases). This view is useful for:

• Comprehensive model audits
• Detailed technical reviews with engineering or finance teams
• Documentation and record-keeping
• Ensuring no assumption is overlooked during QA

Both views are dynamically generated from your project data, ensuring they stay current as your model evolves. You can filter, sort, and export these views to support different workflows—from internal reviews to external deliverables.

Common Assumption Categories

While every project is different, assumptions typically fall into a few categories:

Technical Assumptions

• Equipment performance and efficiency
• Capacity factors and availability
• Degradation rates and lifetimes
• Resource quality (wind speed, solar irradiance, feedstock composition)

Cost Assumptions

• Capital costs (CapEx) by component or phase
• Operating costs (OpEx) including energy, labor, maintenance
• Escalation rates for costs over time

Market Assumptions

• Commodity prices (electricity, hydrogen, carbon credits)
• Demand profiles or offtake agreements
• Price escalation and volatility

Financial Assumptions

• Discount rates and WACC
• Loan terms, interest rates, and equity returns
• Tax rates, depreciation schedules, and incentives

Timeline Assumptions

• Development and permitting durations
• Construction schedules
• Commercial operation dates

Validating Assumptions

Aire helps you validate and quality-check assumptions through:

• Source tracking: Every assumption can cite its origin, making it easy to review credibility
• Team collaboration: Multiple stakeholders can review, comment on, or flag assumptions that need attention
• Comparison views: See how different assumption sets (cases) affect key outputs side by side
• Audit trails: Track when assumptions were updated, by whom, and why

This makes models more defensible when presenting to investors, partners, or internal stakeholders.

Evolving Assumptions Over Time

Project development is iterative. Early-stage models rely on rough assumptions; later stages incorporate real quotes, test data, and contractual terms. Aire makes this evolution manageable:

• Update assumption values in place as better data becomes available
• Add new cases to reflect refined understanding of uncertainty
• Document assumption changes in descriptions or sources
• Compare current assumptions against past versions to understand how the model evolved

Assumptions vs. Outputs

It’s important to distinguish assumptions from outputs:

• Assumptions are inputs you set or estimate
• Outputs are results calculated from assumptions and model logic

For example:

• Assumption: electricity price = $0.08/kWh
• Output: annual revenue = $2.4M (calculated from price × generation)

Aire’s structure keeps this distinction clear, making it easy to trace how assumptions flow through formulas to produce results.

Working with Assumptions in Scenarios

When building scenarios, you’re effectively selecting which assumptions to use across different parts of your model:

• A conservative scenario might select low revenue cases and high cost cases
• A base scenario might select mid-range assumptions across the board
• An aggressive scenario might select optimistic values to model upside potential

This structured approach to assumption management lets you build defensible narratives, explore risk, and communicate uncertainty clearly to decision-makers.

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Questions about managing assumptions in your model? Reach out to the Aire Labs team or explore related documentation on Terms, Cases, and Blocks.