How We Built This Solar ROI Calculator
Most solar ROI calculators are either too simplistic (a single average payback number) or too complex (requiring you to input 15 variables you don't know). We wanted something in between: real data from authoritative government sources, presented in a way that gives homeowners actionable answers in under 60 seconds.
The Problem We Were Solving
When we researched the solar ROI space, we found two types of tools:
- Installer lead-gen forms: These collect your information to sell you to installers. The "calculator" is secondary to the sales funnel. Output is usually a vague "you could save $X per year!" designed to get you to submit your phone number.
- Overly complex tools: Some tools require inputs like your exact electricity rate, utility provider, roof pitch, shading percentage, and local incentive stacks. Useful if you already know all that — not useful for someone at the research stage.
We wanted to answer the first question homeowners actually ask: "Is solar worth it in my state at all?" Get the baseline answer right, and homeowners can do detailed research from a more informed starting point.
Data Source 1: NREL PVWatts API
The foundation of our solar calculations is NREL's PVWatts API — a free, authoritative government resource from the National Renewable Energy Laboratory.
PVWatts simulates the energy production of grid-connected photovoltaic energy systems at any location in the US (and globally). It uses 30 years of weather data to calculate annual solar irradiance — the average daily sunlight energy available per square meter.
For each state, we query PVWatts using coordinates at or near the population center to get a representative irradiance value. We use the standard parameters:
- System capacity: 6 kW (representative residential system)
- Module type: Standard (crystalline silicon)
- Array type: Fixed roof-mount
- Tilt: Latitude-optimized
- Azimuth: 180° (south-facing)
- System losses: 14% (accounts for wiring, inverter, temperature, shading, and soiling)
This produces an estimated annual kWh output — the electricity your system would generate in an average year.
Data Source 2: EIA Electricity Rate Data
Solar savings are directly proportional to your electricity rate. Generating 1 kWh is worth $0.40 in Hawaii but only $0.11 in Washington — a 3.6x difference that dominates the ROI math.
We pull residential electricity rates from the US Energy Information Administration's state electricity profiles. The EIA publishes average retail electricity prices by state, updated monthly. We use the most recent 12-month average to smooth out seasonal variation.
These are state averages. Your actual utility may charge more or less. In deregulated markets like Texas, rates vary significantly by provider and plan.
The ROI Model
Given irradiance and electricity rates, the ROI calculation is built around a simple financial model:
System Cost
We use state-level average installed costs per watt from NREL's annual U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks report. These are real transaction prices, not installer quotes — they reflect what homeowners actually paid after installer markup.
For states without specific NREL data, we interpolate from regional averages. The national median for a 6kW residential system in 2026 is around $15,800 before incentives.
Annual Production
Annual kWh = System capacity (kW) × irradiance (kWh/m²/day) × 365 × performance ratio
We use a 0.80 performance ratio, which accounts for the system losses modeled in PVWatts plus a small degradation factor. Actual modern panels degrade about 0.5% per year, so this is slightly conservative for newer installations.
Annual Savings
Annual savings = Annual production (kWh) × electricity rate ($/kWh)
This is simplified — it assumes net metering at retail rates. In states with unfavorable net metering (like California post-NEM 3.0), actual savings may be 15–25% lower for systems that export significant excess. We note this in our California page.
ROI Score
ROI score = (Total 25-year savings) ÷ (Net system cost after 30% ITC)
A score of 3.0 means you get $3 back for every $1 you invested. We present this as the primary metric because it combines payback speed and total return in a single intuitive number.
Methodology Choices and Limitations
Every simplification in a model involves trade-offs. Here's what we chose and why:
State Averages vs. ZIP Code Data
We present state-level averages rather than ZIP code-level data for two reasons: (1) NREL irradiance data is relatively smooth within most states — local differences within a state are typically 5–15%, not the 2–3x differences between states; (2) electricity rates are regulated at the state level, so intra-state variation is limited except in deregulated markets.
For California and Texas specifically, we note that local rates and conditions vary significantly.
Fixed Panel Size
We model a 6kW system, which is close to the US national average residential installation size. In high-electricity states like Hawaii, the optimal system size for a typical household is actually 8–10kW. Our interactive calculator lets you adjust system size for your specific usage.
No Battery Storage
Our baseline model excludes battery storage, which adds $10,000–$15,000 to system cost and changes the economics significantly. Adding storage makes sense in California and other states with time-of-use rates or unfavorable net metering, but it's a separate decision from basic grid-tied solar ROI.
Technical Implementation
The site is built as a static Astro site — all pages are pre-generated at build time from JSON data files. There's no server-side rendering; everything is HTML, CSS, and minimal JavaScript.
The data pipeline runs quarterly to refresh NREL irradiance estimates (they update their weather datasets) and monthly to pull new EIA electricity rates. Updated data triggers a rebuild and redeployment via Cloudflare Pages.
The interactive calculator on the state pages is pure client-side JavaScript — it reads the state data baked into the page and recalculates in real time based on your monthly bill input. No API calls, no server, instant response.
What We're Working On
The current version covers state-level averages. Planned improvements include:
- ZIP code-level irradiance data for the continental US
- Utility-specific electricity rate data for the top 50 largest utilities
- State incentive stacks (rebates, SRECs, utility programs) integrated into the ROI model
- Battery storage add-on calculator
Questions, corrections, or suggestions? The methodology above is our starting point — real-world solar economics are complex, and we're committed to making our data as accurate and useful as possible.