modeling-energy-transition-infrastructure

Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.

11 stars

Best use case

modeling-energy-transition-infrastructure is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.

Teams using modeling-energy-transition-infrastructure should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/modeling-energy-transition-infrastructure/SKILL.md --create-dirs "https://raw.githubusercontent.com/CaseMark/skills/main/skills/capital/modeling-energy-transition-infrastructure/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/modeling-energy-transition-infrastructure/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How modeling-energy-transition-infrastructure Compares

Feature / Agentmodeling-energy-transition-infrastructureStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Modeling Energy Transition Infrastructure

Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis.

## When To Use

- Modeling project-financed battery energy storage systems (BESS) for merchant or contracted revenue structures
- Evaluating grid modernization capital programs (T&D upgrades, smart grid, DERMS platforms)
- Sizing and financing EV charging networks across depot, fleet, and public-access configurations
- Analyzing green/blue hydrogen production, storage, and offtake economics
- Structuring blended capital stacks with ITC/PTC, state incentives, and concessional finance layers
- Comparing energy transition assets on a risk-adjusted return basis for infrastructure fund deployment

## Inputs To Gather

- **Asset specification**: technology type, nameplate capacity (MW/MWh), degradation curves, round-trip efficiency (storage), utilization assumptions
- **Revenue structure**: PPA/tolling terms, capacity market clearing prices, energy arbitrage spreads, ancillary service revenue, demand charge savings, REC/carbon credit pricing [VERIFY market-specific pricing]
- **Capital costs**: EPC contract pricing or benchmark $/kW and $/kWh, interconnection costs, land/easement costs, development fees
- **Operating costs**: O&M contracts (fixed and variable $/kW-yr), augmentation capex schedule (BESS), insurance, property tax, land lease escalators
- **Financing terms**: senior debt tenor and pricing, debt service coverage ratios (DSCR), cash sweep mechanics, equity return hurdles (levered IRR, cash-on-cash), construction facility terms
- **Incentives and policy**: ITC/PTC eligibility and phase-down schedule [VERIFY current IRC provisions], state-level incentives, prevailing wage/apprenticeship bonus credit requirements, domestic content adder eligibility
- **Offtake/counterparty**: creditworthiness of offtaker, contract tenor, curtailment risk allocation, merchant tail exposure

## Workflow

1. **Classify the asset and revenue model**
   - Identify technology (BESS, T&D, EVCI, hydrogen electrolyzer, etc.) and primary revenue pathway (contracted vs. merchant vs. hybrid)
   - For BESS: determine use case stack (energy arbitrage, frequency regulation, capacity, resource adequacy, T&D deferral) and whether revenues are co-optimized or siloed
   - For hydrogen: classify by color (green/blue/pink), map electrolyzer technology (PEM vs. alkaline vs. SOEC), and define offtake structure (tolling, merchant, hub pricing)

2. **Build the operating model**
   - Construct hourly or sub-hourly dispatch profile for storage assets; use 8760 analysis where arbitrage is a material revenue source
   - Model degradation: capacity fade curves for lithium-ion (typically 2–3% annual with augmentation strategy), efficiency degradation for electrolyzers
   - For EV charging: model utilization ramp (typically 3–7 year curve to stabilization), energy throughput per charger, demand charge exposure, and network effects across sites
   - For grid modernization: model regulated rate-base treatment, allowed ROE, and capital deployment schedule across multi-year programs

3. **Structure the capital stack**
   - Layer ITC/PTC benefits — determine whether tax equity, transferability (post-IRA), or direct pay is optimal [VERIFY entity tax status and election availability]
   - Size senior debt to target DSCR (typically 1.30–1.50x for contracted BESS; higher for merchant exposure); model sculpted amortization where appropriate
   - For PPP structures: model availability-based payments, handback provisions, and lifecycle reserve funding
   - Calculate levered equity returns (IRR, MOIC, cash yield) with and without incentive scenarios

4. **Run revenue and risk scenarios**
   - Energy price scenarios: base, high, low, and stress cases using forward curves and fundamental supply/demand analysis
   - Technology risk: sensitivity on degradation rate, replacement capex timing, and efficiency assumptions
   - Policy risk: model returns with and without ITC/PTC, with and without state incentives; quantify breakeven incentive level
   - Counterparty risk: evaluate impact of offtaker default or contract termination on debt coverage and equity returns
   - For hydrogen: sensitivity on electrolyzer capex learning curve, electricity input cost, and offtake price indexation

5. **Produce output tables and investment memo inputs**
   - Summary returns table: unlevered IRR, levered IRR, MOIC, cash-on-cash by year, payback period
   - Debt metrics: DSCR profile, average DSCR, minimum DSCR, debt yield
   - Waterfall: sources and uses, construction draw schedule, annual cash flow waterfall (revenue → opex → debt service → cash sweep → equity distributions)
   - Sensitivity matrix: 2-way tables on key variables (e.g., capacity price vs. degradation rate; electricity cost vs. hydrogen offtake price)

## Output

- **Pro forma financial model** with annual (and sub-annual where needed) projections over asset life (typically 20–30 years for storage/grid; 15–20 for EV/hydrogen)
- **Returns summary** with base, upside, and downside scenarios clearly separated
- **Capital structure recommendation** with optimal debt sizing, tax equity or transfer pricing, and incentive monetization strategy
- **Risk register** mapping each key assumption to its sensitivity impact on levered IRR and DSCR
- **Investment committee memo inputs**: executive summary, asset description, market context, financial summary, risk factors, and recommendation

## Quality Checks

- Confirm DSCR never breaches lockup or default levels in base case; document minimum DSCR year and driver
- Verify balance sheet balances in every period (total assets = total liabilities + equity)
- Check that degradation and augmentation assumptions align with manufacturer warranties and independent engineer reports [VERIFY]
- Validate ITC/PTC calculations against current IRS guidance and bonus credit qualification requirements [VERIFY]
- Ensure merchant revenue assumptions are supportable by recent market data (ISO clearing prices, REC auction results, hydrogen hub pricing indices)
- Cross-check $/kW and $/kWh capital cost assumptions against recent comparable transactions and NREL/Lazard benchmarks
- Confirm discount rate and WACC assumptions reflect current market pricing for comparable risk-profile assets
- Flag any input where source data is older than 12 months or drawn from a different jurisdiction with [VERIFY]

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