lev-os 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
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)
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
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
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
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]