Learn · Governance

🧭 Voting scenarios: diversify or concentrate?

5 min read · Used in Race to Zero

Key takeaway

Four realistic votes — diversify vs concentrate, big vs small, growth vs income, merchant vs contracted — with the trade-off spelled out rather than the answer.

The best way to understand governance is through concrete examples. These hypothetical scenarios illustrate common decision-making situations token holders face, with realistic trade-offs based on current industry economics. Each scenario presents options with pros and cons, allowing you to practice evaluating proposals.

📖 How to Use These Scenarios

These are teaching examples based on realistic renewable energy economics (2024 data). Project parameters like LCOE ($29-92/MWh for solar, $27-73/MWh for wind[3]), capacity factors (solar 21-34%, wind 33-47%[4]), and IRR ranges (8-13%[8]) reflect actual industry standards. Consider each scenario, decide how you'd vote, then read the analysis.

Scenario 1: Technology Diversification vs. Concentration

Situation:

The DAO has $25M to deploy. Two proposals emerge:

Option Project A Project B
Technology 50MW Solar (Arizona) 30MW Wind (Texas)
Capital Cost $25M ($0.50/W) $25M ($0.83/W)
LCOE $32/MWh $38/MWh
Capacity Factor 28% 42%
Expected IRR 11.5% 9.8%
Risk Profile Low (mature tech, strong sun) Medium (equipment complexity)
PPA Status 15-year signed 12-year signed

Key Trade-offs:

Stakeholder Perspectives:

Decision Framework:

Consider the DAO's current portfolio. If this is the first project, solar's lower risk makes sense. If the DAO already has solar projects, wind diversification becomes more attractive despite slightly lower IRR. The 2-3% IRR difference may be worth the risk reduction from diversification.

Scenario 2: Project Size and Economies of Scale

Situation:

The DAO has $40M available. Should we fund one large project or multiple smaller ones?

Aspect Option A: Single Large Project Option B: Three Smaller Projects
Configuration 100MW solar farm (California) 25MW solar (AZ) + 30MW wind (TX) + 15MW solar (NV)
Total Cost $40M $41M (2.5% premium)
Avg LCOE $30/MWh $34/MWh
Expected IRR 12.2% 10.5%
Development Risk High (single point of failure) Lower (risk spread across projects)
Timeline 18 months to operation 12-20 months (staggered)
Geographic Risk Concentrated in CA (regulatory risk) Spread across 3 states

Key Trade-offs:

Analysis:

Research shows economies of scale in renewables are more complex than traditional industries[9]. While a 100MW project enjoys cost advantages in equipment and construction through bulk purchasing and larger-scale operations, it faces higher development risks, more complex permitting, and concentration risk. Industry experience suggests large projects often face greater permitting challenges than smaller projects, though specific failure rates vary by jurisdiction and project type.

Suggested approach: If this is the DAO's first major deployment, the diversified option (Option B) reduces risk despite lower IRR. Once the DAO has operational experience and proven processes, larger projects become more attractive.

Scenario 3: Distribution Policy - Growth vs. Income

Situation:

Three projects are now operational, generating $3.2M annually after expenses. How should revenue be allocated?

Approach Option A: Reinvest Option B: Distribute Option C: Hybrid
Distribution to Token Holders $0 (0%) $3.2M (100%) $1.6M (50%)
Reinvestment for New Projects $3.2M $0 $1.6M
Immediate Yield (on $50M portfolio) 0% 6.4% 3.2%
Projected 5-Year Portfolio Growth $50M → $100M $50M (no growth) $50M → $70M
5-Year Total Distributions $0 for 5 years, then $6.4M/yr $16M over 5 years $8M over 5 years, $4.5M/yr after

Stakeholder Perspectives:

Analysis:

This classic growth vs. income trade-off has no universally correct answer—it depends on investor base and market conditions. However, many successful renewable energy funds use a tiered approach:

For a young DAO, Option A or C makes strategic sense to build portfolio scale. Once the portfolio reaches critical mass ($100M+), shifting toward distributions rewards early supporters.

Scenario 4: Risk vs. Return - Merchant vs. Contracted

Situation:

A developer offers two versions of the same 40MW wind project:

Aspect Option A: PPA Contracted Option B: Merchant
Revenue Model 15-year PPA at $45/MWh Sell into market (avg $52/MWh)
Expected IRR 9.2% 14.5%
Revenue Certainty 100% for 15 years Fluctuates with market prices
Downside Scenario (low prices) 9.2% IRR (unchanged) 4.2% IRR (if prices drop to $35/MWh)
Upside Scenario (high prices) 9.2% IRR (unchanged) 22.8% IRR (if prices rise to $65/MWh)
Financing 70% debt available (due to PPA) 50% debt available (higher risk)

Key Considerations:

Analysis:

Industry observations suggest merchant renewable projects can potentially achieve higher IRR than PPA projects during periods of rising electricity prices, but with significantly higher volatility (2-3x). The key question: does the DAO's token holder base prefer stable distributions or higher expected returns with volatility?

Recommended approach: For a DAO's first few projects, PPA contracts provide stability and allow higher leverage. Once portfolio reaches 100+ MW with stable cash flows, adding 20-30% merchant exposure can boost returns without excessive risk.

Try it in Race to Zero →

Figures marked […] above are sourced on the references page.