Methodology
All GainTally estimates are built on open, verifiable formulas — no black boxes. This page documents the formula, key assumptions, common edge cases, and primary data sources plus authoritative benchmarks (NREL, EIA, DOE, EPA, ENERGY STAR, IRS, SAE, CFPB) for each of the 20 calculators. Every result can be reproduced with publicly available data. If you find an error or want to discuss our approach, email [email protected].
Last validated: August 2026
Technical terms used on this page: Payback Period, LCOE, PVWatts, ROI, Peak Sun Hours. See the full Glossary for all definitions.
Solar ROI Calculator
Formula
INPUT:
system_size_kw (number, 3–15 kW)
annual_sun_hours (kWh/kW/yr, from NREL PVWatts API)
electricity_rate ($/kWh, from EIA state average)
system_cost_per_watt ($/W, default $2.75/W mid-tier)
panel_type (monocrystalline | polycrystalline | thin-film)
state_incentive ($, optional flat-dollar rebate — default $0)
CALCULATION:
gross_cost = system_size_kw × 1000 × system_cost_per_watt
net_cost = gross_cost − state_incentive
base_production = system_size_kw × annual_sun_hours × 0.80 × 0.86 (kWh/yr)
annual_degradation_rate = {Mono: 0.61%/yr, Poly: 0.89%/yr, Thin-film: 1.08%/yr}
year_n_factor = (1 − annual_degradation_rate)^n (no separate year-1 LID step)
year_n_savings = base_production × year_n_factor × electricity_rate × (1 + 2.5%)^n
payback_year = first n where Σ savings ≥ net_cost (max 26)
lcoe = net_cost / Σ 25-year production ($/kWh)
total_savings_25yr = Σ gross_savings − net_cost
OUTPUT:
net_cost ($)
payback_year (yr, 1–26)
total_savings_25yr ($)
lcoe ($/kWh)
yearly_projections (array: year, production_kwh, savings, cumulative_savings)
BENCHMARK:
±5–10% of NREL PVWatts v8 annual production estimate
±1.5 yr payback vs EnergySage Solar CalculatorAssumptions
- Performance ratio: 0.80 (NREL modern system median)
- System losses: 14% (PVWatts v8 default)
- System-level panel degradation — Monocrystalline: 0.61%/yr, Polycrystalline: 0.89%/yr, Thin-film: 1.08%/yr
- No separate first-year LID step — the anchored field rates already include early-life loss
- Electricity inflation: 2.5%/yr (EIA historical average)
- 25-year analysis window; payback reported as 26 if not reached
Edge Cases
- Coastal microclimate (e.g., San Francisco fog belt): annual averages may overstate output by 5–10% versus PVWatts hourly data — cross-check with PVWatts hourly export for shaded sites.
- Leased system (TPO/PPA): the homeowner does not own the system, so federal ITC was claimed by the installer (historical only — 25D is $0 after Dec 31, 2025) and electricity-inflation hedging accrues to the lease holder, not the resident.
- Stacked state-plus-federal incentives (NY-Sun + 25D, historical 2025 only): real-world payback was 1–3 years shorter than calculator default — these stacks no longer apply for 2026+ installations.
Data Sources
- NREL PVWatts v8 — annual sun hours by zip code
- EIA — state electricity rates
- EnergySage — payback benchmark validation
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| NREL PVWatts v8 (annual production) | ±5–10% | 2026-05 |
| EnergySage Solar Calculator (payback) | ±1.5 yr payback | 2026-05 |
Solar Panels Needed Calculator
Formula
INPUT:
monthly_kwh (kWh/mo, typical US home ~900 kWh)
annual_sun_hours (kWh/kW/yr, from NREL PVWatts API)
panel_watts (W, 250–440 W per panel)
system_losses (fraction, default 0.14)
CALCULATION:
annual_kwh = monthly_kwh × 12
system_size_kw = annual_kwh / (annual_sun_hours × 0.80 × (1 − system_losses))
panel_count = ⌈system_size_kw × 1000 / panel_watts⌉ (rounded up — no partial panels)
roof_area_sqft = panel_count × 17.5
OUTPUT:
panel_count (integer)
system_size_kw (kW)
roof_area_sqft (ft²)
BENCHMARK:
±10% of NREL PVWatts module sizing methodology
±15% of EnergySage panel count methodologyAssumptions
- Performance ratio: 0.80; system losses: 14%
- Standard panel footprint: 17.5 ft² (typical 60-cell module)
- Panel count rounded up — partial panels are not possible
- Sun hours sourced from NREL PVWatts API by zip code
Edge Cases
- Heavy shading (>30% derate from trees, chimneys, or neighbors): add 30–50% more panels or use micro-inverters / power optimizers — calculator uses unshaded baseline.
- Split east-west roof orientation: panel count rises ~10–15% versus an ideal south-facing array because per-panel production drops with off-axis azimuth.
- High-efficiency 400–440 W panels reduce panel count by ~40–50% compared to legacy 250 W modules but cost 15–25% more per watt at the module level.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| NREL PVWatts (module sizing) | ±10% | 2026-05 |
| EnergySage panel count methodology | ±15% | 2026-05 |
Solar Installation Cost Calculator
Formula
INPUT:
system_size_kw (kW)
installation_type (roof | ground)
CALCULATION:
system_size_w = system_size_kw × 1000
mount_premium = ground ? ×1.20 : ×1.00
low_estimate = system_size_w × $1.50/W × mount_premium
mid_estimate = system_size_w × $2.75/W × mount_premium
high_estimate = system_size_w × $3.50/W × mount_premium
OUTPUT:
low_estimate ($)
mid_estimate ($)
high_estimate ($)
cost_per_watt ($/W, mid tier)
BENCHMARK:
±10% of SEIA Solar Market Insight national $/W average
±15% of EnergySage state-level marketplace dataAssumptions
- $/W tiers based on SEIA 2024 national installation averages
- Ground-mount adds 20% over roof-mount (additional foundation and racking cost)
- Federal 25D residential solar tax credit: $0 for installations after Dec 31, 2025 (expired per OBBBA, Pub.L. 119-21)
- State incentives and rebates not included — see Solar Tax Credit Calculator
Edge Cases
- Bulk installation discount (>10 kW residential, light-commercial leaning): $/W can drop 10–20% below the Low tier as soft costs amortize over more capacity.
- Premium modules (SunPower Maxeon / LG NeON / REC Alpha, 22%+ efficiency): add 20–40% to $/W versus mainstream 19–20% modules — pays back only if roof area is the binding constraint.
- Post-2025 installations receive $0 federal 25D credit (expired). Out-of-pocket cost equals the gross install price minus any state-only incentives.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| SEIA Solar Market Insight (national $/W) | ±10% | 2026-05 |
| EnergySage Marketplace state data | ±15% | 2026-05 |
Solar Battery Storage Calculator
Formula
INPUT:
battery_capacity_kwh (kWh, nameplate capacity)
depth_of_discharge (%, per battery model)
round_trip_efficiency (%, per battery model)
household_daily_kwh (kWh/day, your usage)
battery_cost ($)
peak_rate ($/kWh, on-peak electricity rate)
off_peak_rate ($/kWh, off-peak electricity rate)
cycles_per_year (integer, typical 250–365)
battery_life_years (yr, 10–15 per warranty)
CALCULATION:
usable_kwh = battery_capacity_kwh × depth_of_discharge × round_trip_efficiency
shifted_kwh_year = min(usable_kwh × cycles_per_year, household_daily_kwh × 365)
price_spread = max(0, peak_rate − off_peak_rate)
annual_savings = shifted_kwh_year × price_spread
payback_years = battery_cost / annual_savings
lifetime_savings = annual_savings × battery_life_years − battery_cost
cost_per_cycle = battery_cost / (cycles_per_year × battery_life_years)
OUTPUT:
annual_savings ($)
payback_years (yr)
lifetime_savings ($)
cost_per_cycle ($/cycle)
BENCHMARK:
±5% of Tesla Powerwall warranty spec (manufacturer-rated cycles)
±5% of Enphase IQ Battery spec sheetAssumptions
- Time-of-use (TOU) arbitrage model: charges off-peak, discharges at peak
- Negative spread (off-peak rate > peak rate) results in $0 savings
- Usable energy is derived from each model's depth of discharge and round-trip efficiency — nameplate capacity is never used directly
- Annual savings are capped at your household consumption: a battery cannot shift more energy than your home uses
- No battery degradation curve; conservative for long-term projections
Edge Cases
- Backup-only deployments (rare cycling, primarily power-outage resilience): TOU arbitrage savings are near $0; financial payback is essentially never — value is captured in outage avoidance, not bill savings.
- Low rate-spread utilities (<$0.05/kWh peak vs. off-peak): payback exceeds typical 10–15 year warranty; consider whether storage is justified versus a generator.
- LFP (LiFePO4) vs. NMC chemistry: LFP rated ~6,000 cycles, NMC ~4,000 — multiply Cycles × Battery Life inputs accordingly when comparing real specs.
Data Sources
- Tesla Powerwall — capacity and cycle specifications
- Enphase IQ Battery — spec sheets
- NREL — Residential Battery Storage report
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| Tesla Powerwall datasheet (warranty cycles) | ±5% (manufacturer-rated) | 2026-05 |
| Enphase IQ Battery spec sheet | ±5% (manufacturer-rated) | 2026-05 |
Solar Panel Degradation Calculator
Formula
INPUT:
initial_production_kwh (kWh/yr, year-1 baseline output)
panel_type (monocrystalline | polycrystalline | thin-film)
analysis_years (integer, 1–30)
CALCULATION:
annual_rate = {Mono: 0.61%/yr, Poly: 0.89%/yr, Thin-film: 1.08%/yr}
(module median + balance-of-system share; no separate LID step)
year_n_factor = (1 − annual_rate)^n
year_n_production = initial_production_kwh × year_n_factor
total_loss_kwh = Σ (initial_production − year_n_production) for n=1..years
OUTPUT:
yearly_production (array: year, production_kwh, factor)
total_loss_kwh (kWh over analysis period)
BENCHMARK:
±0.1%/yr of the NREL PV Fleet system-level median (0.75%/yr)Assumptions
- No separate LID step — the field-measured rates already include early-life loss
- Annual degradation rates: Monocrystalline: 0.61%/yr, Polycrystalline: 0.89%/yr, Thin-film: 1.08%/yr
- Anchor: NREL PV Fleet system-level median 0.75%/yr (Jordan et al., 2022) — the crystalline-silicon average of the modelled rates lands on it
- Linear degradation model — real-world curves are slightly logarithmic but within ±5%
Edge Cases
- Tier-1 versus Tier-2 modules: NREL field data shows ~0.5%/yr for Tier-1 brands and 0.9–1.0%/yr for unknown / utility-overstock modules — adjust the annual rate input.
- Cold-climate thermal cycling (Northern Plains, Mountain West): freeze-thaw stress can accelerate solder-bond and EVA browning failures by 10–20% versus mild climates.
- Year-25 warranty cliff: most manufacturers guarantee 80–85% of nameplate at year 25; modules continuing past this point operate without a warranty backstop.
Data Sources
- NREL PV Fleet Performance Data Initiative (Jordan et al., 2022) — system-level median
- NREL Photovoltaic Degradation Rates — An Analytical Review (2013) — module-level technology medians
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| NREL PV Fleet system-level median (0.75%/yr) | ±0.1%/yr | 2026-08 |
| NREL module-level technology medians (Jordan & Kurtz, 2013, Table 1) | post-2000 module medians | 2026-08 |
Net Metering Savings Calculator
Formula
INPUT:
system_size_kw (kW)
annual_sun_hours (kWh/kW/yr, from NREL PVWatts API)
monthly_consumption_kwh (kWh/mo, household electricity use)
buy_rate ($/kWh, retail electricity rate)
sell_rate ($/kWh, net metering export credit rate)
CALCULATION:
monthly_production = system_size_kw × annual_sun_hours × 0.80 × 0.86 / 12
self_consumed = min(monthly_production, monthly_consumption_kwh)
export_kwh = max(0, monthly_production − monthly_consumption_kwh)
annual_net_savings = self_consumed × buy_rate × 12
+ export_kwh × sell_rate × 12
OUTPUT:
monthly_production (kWh/mo)
self_consumed_kwh (kWh/mo)
export_kwh (kWh/mo)
annual_net_savings ($)
BENCHMARK:
policy-level: DSIRE state net-metering policy database
exact tariff: CPUC NEM-3 decision (California export rate)Assumptions
- Performance ratio: 0.80; system losses: 14%
- Monthly averages used — seasonal production variation not modeled
- NEM 3.0 sell rate ≈ 20–30% of retail rate (CPUC NEM-3 decision)
- Traditional net metering: sell rate equals the retail buy rate
Edge Cases
- California NEM 2.0 grandfathered customers (interconnected before April 14, 2023) keep full retail-rate export for 20 years from interconnection — payback typically 2–3 years shorter than NEM 3.0.
- Non-NEM states (Hawaii, Mississippi, Tennessee TVA service): no export credit; payback depends entirely on self-consumption — consider sizing the system to match daytime load only.
- Utility-specific aggregate caps and queue freezes: even within a NEM-friendly state, the local utility may be at its cap and route new customers to a successor tariff with reduced credit.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| DSIRE state net-metering policy | policy-level (no numeric margin) | 2026-05 |
| CPUC NEM-3 Decision (California export rate) | exact tariff | 2026-05 |
Solar Panel Tilt Angle Calculator
Formula
INPUT:
latitude_deg (°, 0–60 covers continental US and Alaska)
current_tilt_deg (°, 0–90)
azimuth_deg (°, 0 ≤ azimuth < 360; 180 = true south)
system_size_kw (kW)
CALCULATION:
optimal_tilt_deg = latitude_deg (within ±3° of PVWatts output)
reference_production = system_size_kw × 1,500 × 0.80 × 0.86 (kWh/yr)
tilt_delta_rad = |current_tilt_deg − optimal_tilt_deg| × π / 180
current_efficiency = cos(tilt_delta_rad)
azimuth_deviation = |(azimuth_deg mod 360) − 180| (0° = south, 180° = north)
azimuth_loss(tilt) = north_loss(tilt) × shape(azimuth_deviation)
current_production = reference_production × current_efficiency × (1 − azimuth_loss(current_tilt_deg))
optimal_production = reference_production × (1 − azimuth_loss(optimal_tilt_deg))
production_gain_pct = (optimal_production − current_production) / current_production × 100
AZIMUTH LOSS TABLES (linear interpolation between anchors):
north_loss by tilt 0° → 0.0% 10° → 16.9% 20° → 31.3% 30° → 43.4%
40° → 53.1% 50° → 61.2% 60° → 67.7%
shape by deviation 0° → 0.00 30° → 0.06 60° → 0.21 90° → 0.43
120° → 0.69 150° → 0.91 180° → 1.00
OUTPUT:
optimal_tilt_deg (°)
current_production (kWh/yr, estimate)
optimal_production (kWh/yr, estimate)
production_gain_pct (%)
azimuth_loss_pct (%, at the roof's own pitch — drives the orientation notice)
BENCHMARK:
±3° of NREL PVWatts azimuth/tilt sensitivity analysis
±2° seasonal vs PVWatts V5 Manual tilt methodology
Azimuth loss within the measured site range of live PVWatts v8 runs
(4 ZIPs × 7 tilts × 12 azimuths, August 2026; RMS error 2.2 percentage points)Assumptions
- Simplified model: optimal tilt ≈ local latitude (within ±3° of PVWatts output)
- Reference sun hours: 1,500/yr (US national average used for fair comparisons)
- Valid latitude range: 0°–60° (covers continental US and Alaska)
- Seasonal rule of thumb: summer tilt = latitude − 15°, winter = latitude + 15°
- Northern-hemisphere orientation: 180° azimuth is the reference direction, so the model does not apply south of the equator
- Azimuth loss is symmetric (east ≡ west): the measured east/west gap depends on local weather patterns and reverses direction by site (west worse in Atlanta and Boston, east worse in Los Angeles and Seattle), so a location-independent model cannot represent it
- Azimuth loss scales with pitch: a dead-flat array loses nothing to orientation, a 60° array facing due east or west loses about 29%
Edge Cases
- Flat roof (0° pitch): add a 10–15° minimum mechanical tilt for water drainage and self-cleaning rain — the 'latitude' optimum is impractical without ballast or rails.
- East- or west-facing roof: the orientation penalty grows with pitch, so steepening toward the latitude optimum can lower annual output rather than raise it. The production-gain figure turns negative in that case, and no gain is claimed.
- Adjustable ground mounts (manual seasonal pivot): summer tilt = latitude − 15°, winter = latitude + 15° captures 5–8% more annual production than fixed tilt.
- High-latitude (>45°N) installations: steep winter tilts (60–65°) are impractical due to snow load and wind uplift — fixed tilt near latitude is the practical compromise.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| NREL PVWatts azimuth/tilt sensitivity | ±3° | 2026-05 |
| PVWatts V5 Manual (tilt methodology) | ±2° seasonal | 2026-05 |
Solar vs Grid Cost Calculator
Formula
INPUT:
system_size_kw (kW)
annual_sun_hours (kWh/kW/yr, from NREL PVWatts API)
electricity_rate ($/kWh)
electricity_inflation (fraction, entered by you; default 2.5%)
derived, not entered:
system_cost = system_size_kw × 1000 × $2.75/W (national mid-tier average)
years = 25 (fixed analysis window)
CALCULATION:
annual_production = system_size_kw × annual_sun_hours × 0.80 × 0.86
annual_grid_cost_n = annual_production × electricity_rate × (1 + inflation)^n
cumulative_grid_cost = Σ annual_grid_cost for n=1..years
solar_total_cost = system_cost + $150/yr × years (flat annual maintenance)
savings = cumulative_grid_cost − solar_total_cost
OUTPUT:
cumulative_grid_cost ($)
solar_total_cost ($)
savings ($)
yearly_comparison (array: year, solar_cumulative, grid_cumulative)
BENCHMARK:
±2% of EIA state retail electricity rates (monthly survey)
±15% of EnergySage 25-year solar vs grid comparisonAssumptions
- Annual system maintenance: $150/yr flat, independent of system size (covers inverter monitoring, cleaning)
- Installed cost is derived from system size at $2.75/W — this page does not take a cost input, so a quote that differs materially should be checked on the Cost Estimate calculator
- Production held constant across years in this model (no degradation applied)
- Electricity inflation entered by user; the slider default is 2.5%, matching the EIA historical average this site uses everywhere else
Edge Cases
- Time-of-use (TOU) utility plans: solar savings can be 10–20% higher than flat-rate output suggests, because daytime production aligns with peak-rate hours.
- Heating-dominant homes (cold-climate gas furnace + electric AC): winter heating bill does not shift with solar — sizing should match the summer-electric / annual blended load, not just peak summer.
- Inflation horizon choice matters: EIA 1990–2024 historical average is ~2.5%/yr; the 2008–2024 window is closer to 3.0%/yr — entering 4–5% optimistically overstates 25-year savings.
Data Sources
- EIA — historical electricity rate inflation
- EnergySage — 25-year solar vs. grid comparison methodology
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| EIA state retail electricity rates | ±2% (monthly) | 2026-05 |
| EnergySage 25-year comparison | ±15% | 2026-05 |
Solar Loan Calculator
Formula
INPUT:
system_cost ($, total installed cost)
down_payment ($, subtracted from system cost — the rest is financed)
loan_rate (APR %; 0% triggers the zero-interest special case)
loan_term (yr)
system_size_kw (kW)
monthly_kwh (kWh/mo, your household consumption — caps the savings)
electricity_rate ($/kWh)
CALCULATION:
loan_amount = max(0, system_cost − down_payment)
monthly_rate = loan_rate / 12 / 100
n_months = loan_term × 12
monthly_payment = P × [r(1+r)^n] / [(1+r)^n − 1] (0% rate: P / n)
total_interest = monthly_payment × n_months − P
savings side — same production and economics as the ROI calculator (B-008):
production = system_size_kw × annual_sun_hours × 0.80 × 0.86
bill_cap = min(1, monthly_kwh × 12 / production)
(solar cannot save more electricity than the home uses)
year_n_savings = production × bill_cap × degradation(n) × electricity_rate × (1 + 2.5%)^n
annual_savings = Σ 25-year savings / 25 (levelized — the loan's break-even basis)
year_1_savings = the first year of that stream (what the monthly cash-flow row shows)
break_even_year = first year where Σ (annual_savings − annual_payments) ≥ 0
net_25yr_savings = annual_savings × 25 − monthly_payment × 12 × loan_term
OUTPUT:
monthly_payment ($)
total_interest ($)
break_even_year (yr)
net_25yr_savings ($)
amortization (per-year principal / interest / balance table)
BENCHMARK:
±$1 monthly payment vs CFPB standard amortization reference
±2 yr break-even versus the ROI calculator for the same system (cross-check)Assumptions
- Standard amortization formula (verified against CFPB mortgage calculator)
- 25-year analysis window for break-even and net savings calculation
- Annual savings are not entered — they are derived from your system size, consumption and rate using the same model as the ROI calculator, including panel degradation and 2.5%/yr electricity inflation
- Savings are capped at your own consumption: a system that produces more than the home uses does not keep accruing bill savings for the surplus
- This page has no ZIP input, so production uses the US average sun-hour figure rather than a location-specific PVWatts run
- No prepayment, refinancing, or loan origination fees modeled
Edge Cases
- Secured solar loan via HELOC or cash-out refinance: interest is potentially deductible under IRS Pub 936 'home acquisition or improvement' rules — consult a licensed CPA or tax professional before assuming a deduction.
- Re-amortization after the 2025-only 25D carry-forward: borrowers who claimed the credit in 2025 (last eligible year) and applied it as a principal paydown can request a re-amortized lower payment — model does not auto-adjust.
- Dealer-fee 'no-money-down' solar loans: an 18–22% dealer fee is rolled into principal, raising effective APR by 4–6 percentage points above the advertised rate — request the cash price and finance separately when possible.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| CFPB amortization reference | ±$1 monthly payment | 2026-05 |
| Bankrate Loan Calculator | ±$1 monthly payment | 2026-05 |
Solar Tax Credit Calculator
Formula
INPUT:
system_cost ($)
include_state_tax_credit (boolean)
state_credit_rate (fraction 0–1; used only if include_state_tax_credit = true)
CALCULATION:
federal_itc_rate = 0.30 if installed ≤ Dec 31 2025, else 0.00
(OBBBA Pub.L. 119-21 — residential 25D credit expired)
federal_credit = system_cost × federal_itc_rate
state_credit = include_state_tax_credit ? system_cost × state_credit_rate : 0
total_credit = federal_credit + state_credit
net_system_cost = max(0, system_cost − total_credit)
OUTPUT:
federal_credit ($)
state_credit ($)
total_credit ($)
net_system_cost ($)
BENCHMARK:
exact statutory: IRS Form 5695 instructions (rate 30% → 0% after 2025)
program-level: DSIRE state incentive databaseAssumptions
- Federal residential solar credit (25D) expired December 31, 2025 per OBBBA (Pub.L. 119-21, July 4, 2025)
- 2025 installations may carry unused credit forward to the 2026 tax year
- State incentive rates sourced from DSIRE database (vary by program year and funding)
- Only direct tax credits modeled; utility rebates and performance payments excluded
Edge Cases
- Installations placed in service after December 31, 2025 receive $0 federal 25D credit. 'Placed in service' generally means the system passes inspection and is operational — confirm with installer documentation and consult a licensed CPA or tax professional.
- 2025 carry-forward of unused 25D credit: any unused portion of a 2025 credit may be carried forward against 2026 tax liability — this is the last year carry-forward is available (no new 25D credit in 2026).
- State and utility incentives are unaffected by the 25D expiration: NY-Sun, MA SMART, CA self-generation rebates, and DSIRE-listed programs continue under their own statutes — federal expiration does not auto-cancel state credit.
Data Sources
- IRS Form 5695 — Residential Energy Credits
- OBBBA Pub.L. 119-21 — credit expiration reference
- DSIRE — state solar incentive database
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| IRS Form 5695 instructions | exact (statutory) | 2026-05 |
| DSIRE state incentive database | program-level (no numeric margin) | 2026-05 |
EV Charging Cost Calculator
Formula
INPUT:
battery_capacity_kwh (kWh, energy added this session = capacity × SoC change)
charging_efficiency (fraction; L1/L2: 0.90, DC Fast: 0.85)
electricity_rate ($/kWh)
miles_per_charge (mi, driving range from this charge)
CALCULATION:
actual_energy_kwh = battery_capacity_kwh / charging_efficiency
cost_per_charge = actual_energy_kwh × electricity_rate
cost_per_mile = cost_per_charge / miles_per_charge
monthly_cost = cost_per_mile × 1,000 (US avg 1,000 mi/mo)
annual_cost = monthly_cost × 12
OUTPUT:
cost_per_charge ($)
cost_per_mile ($/mi)
monthly_cost ($)
annual_cost ($)
BENCHMARK:
±5% of DOE eGallon methodology
±3% kWh vs AFDC Vehicle Cost CalculatorAssumptions
- L1 (120V) charging efficiency: 90%; L2 (240V): 90%; DC Fast: 85%
- DC Fast held conservative vs. EPA range (88–90%) to avoid under-estimating cost
- Average monthly driving: 1,000 miles (US average ~12,000 miles/yr)
- Electricity rate is user-entered or sourced from EIA state averages
Edge Cases
- Time-of-use plans: peak rates ($0.40–$0.50/kWh on PG&E E-TOU-C 4–9 PM) versus super-off-peak ($0.08–$0.12/kWh overnight) can produce a 4–5× cost swing for the same kWh — schedule charging accordingly.
- Apartment / condo drivers without home L2 access: 100% public-charging dependency raises per-mile cost 2–4× over home overnight charging because public DC Fast averages $0.40–$0.60/kWh.
- Highway DC Fast (Electrify America / EVgo road trips): $0.43–$0.56/kWh non-member rates are 3–5× home electricity — the calculator's default home-rate model underestimates road-trip cost.
Data Sources
- DOE eGallon Methodology — charging cost reference
- EPA / FuelEconomy.gov — charging efficiency data
- AFDC Vehicle Cost Calculator — benchmark validation
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| DOE eGallon methodology | ±5% | 2026-05 |
| AFDC Vehicle Cost Calculator | ±3% kWh | 2026-05 |
EV vs Gas Cost Calculator
Formula
INPUT:
ev_purchase_price ($, entered by you)
gas_purchase_price ($, entered by you)
ev_efficiency (kWh/100 mi, EPA rating of the EV model you select;
30 kWh/100 mi — our model list's median — if none is selected)
electricity_rate ($/kWh)
gas_price ($/gal)
gas_mpg (mpg)
annual_miles (mi/yr)
years (integer, 1–15)
ev_tax_credit ($, 30D credit; $0 for 2026+ per OBBBA — so it does
not move the result today)
CALCULATION:
annual_ev_fuel = annual_miles / 100 × ev_efficiency × electricity_rate
annual_gas_fuel = annual_miles / gas_mpg × gas_price
ev_resale_n = ev_purchase_price × (1 − ev_depreciation_5yr)^(n/5)
gas_resale_n = gas_purchase_price × (1 − gas_depreciation_5yr)^(n/5)
ev_cumulative_n = ev_purchase_price
+ (annual_ev_fuel + $600 maintenance + $1,800 insurance) × n
− ev_resale_n
gas_cumulative_n = gas_purchase_price
+ (annual_gas_fuel + $1,200 maintenance + $1,500 insurance) × n
− gas_resale_n
break_even_year = first n where ev_cumulative ≤ gas_cumulative
OUTPUT:
ev_total_cost ($, net of resale value at the end of the hold)
gas_total_cost ($, net of resale value at the end of the hold)
ev_savings ($, positive = EV cheaper over analysis period)
break_even_year (yr, null if the EV never catches up within the hold)
yearly_comparison (array: year, ev_cumulative, gas_cumulative)
BENCHMARK:
±10% of AFDC Vehicle Cost Calculator TCO
resale anchored to the iSeeCars 5-year depreciation study (see below)Assumptions
- Annual maintenance is modeled per vehicle: EV $600, gas $1,200 — a $600/yr difference in the EV's favor. These two figures are our own modeling assumptions, not a published survey result
- Annual insurance is modeled per vehicle: EV $1,800, gas $1,500 — $300/yr against the EV, reflecting higher repair cost and limited bodyshop availability
- Resale value follows measured 5-year depreciation — EV 57.2%, all vehicles 41.8% (iSeeCars' 5-year depreciation study (March 2026, 950,000+ five-year-old used cars sold March 2025 – February 2026)); years past five extrapolate at the same annual rate
- Federal 30D EV tax credit: $0 for 2026+ (expired per OBBBA, Pub.L. 119-21), so the credit line does not reduce the EV purchase price in the model
- Fuel prices held constant across years (no inflation applied)
- Registration, taxes and financing interest are excluded from both vehicles
Edge Cases
- Resale-value divergence runs against the EV: five-year depreciation is 57.2% for EVs versus 41.8% across all vehicles, so the model keeps about 43% of an EV's price and 58% of a gas vehicle's at year five. The all-vehicle figure includes EVs and hybrids (no gasoline-only average is published), and both figures are a used-market snapshot rather than a forward projection. Individual models diverge widely — a Tesla Model 3 and a Jaguar I-Pace sit on opposite ends of the EV range.
- EV insurance can run 15–25% higher than equivalent ICE premiums due to higher repair cost and limited bodyshop availability — consult a licensed insurance agent for accurate quotes.
- Gasoline volatility: $2.30 (April 2020) to $4.85 (June 2022) US average — modeling at a single constant rate masks the realistic 25–40% variance an ICE owner experiences over a 5-year hold.
Data Sources
- AFDC Vehicle Cost Calculator — TCO methodology
- EIA — electricity and gasoline price data
- iSeeCars 5-year depreciation study — resale value anchor
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| AFDC Vehicle Cost Calculator (TCO) | ±10% | 2026-05 |
| iSeeCars 5-year depreciation study (iSeeCars, March 2026) | resale anchor — EV 57.2%, all vehicles 41.8% | 2026-08 |
EV Range Calculator
Formula
INPUT:
battery_capacity_kwh (kWh)
efficiency_miles_per_kwh (mi/kWh, EPA-rated)
temperature_f (°F, −20 to 110)
hvac_usage (none | low | high)
speed_mph (mph, typical 25–85)
CALCULATION:
base_range = battery_capacity_kwh × efficiency_miles_per_kwh
temp_factor = linear_interpolate(temperature_f;
−20°F→0.60, 70°F→1.00, 100°F→0.85)
hvac_factor = {none:1.00, low:0.92, high:0.87}[hvac_usage]
speed_loss = max(0, (speed_mph − 65) / 10) × 0.125 (≤ 0.80 cap)
estimated_range = base_range × temp_factor × hvac_factor × (1 − speed_loss)
OUTPUT:
base_range (mi)
temp_factor (fraction)
hvac_factor (fraction)
estimated_range (mi)
BENCHMARK:
±10% of EPA cold-weather EV range study
±10% of AAA EV Range Anxiety Report (2022)Assumptions
- Temperature model: EPA cold weather study validated against AAA 2022 EV range report
- HVAC impact modeled independently from temperature (additive energy draw)
- Application order: base range → temperature → HVAC → speed adjustment
- Speed loss capped at 80% maximum reduction to prevent extreme extrapolation
Edge Cases
- Cold soak below 20°F (overnight outdoor parking, no preconditioning): observed Tesla / Hyundai Ioniq 5 range loss is 25–35% — heavier than the calculator's smooth interpolation suggests until cabin and battery warm.
- Highway A/C use at 75 mph in 95°F+ heat: speed loss and HVAC loss compound — real-world range can drop 35–40% versus EPA label, far more than each factor alone.
- WLTP-rated (European) vs. EPA-rated (US) vehicles: WLTP figures run 15–25% optimistic — adjust battery capacity input downward when modeling a vehicle quoted under WLTP.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| EPA cold-weather EV range study | ±10% | 2026-05 |
| AAA EV Range Anxiety Report (2022) | ±10% | 2026-05 |
EV Charging Time Calculator
Formula
INPUT:
battery_capacity_kwh (kWh)
current_soc_pct (%, 0–100)
target_soc_pct (%, 0–100)
charger_power_kw (kW; ≥50 kW classified as DC Fast per SAE J1772)
CALCULATION:
energy_to_add = battery_capacity_kwh × (target_soc − current_soc) / 100
if charger_power_kw < 50 (L2):
time_hours = energy_to_add / charger_power_kw
else (DC Fast — taper at 80% SoC):
energy_to_80 = battery_capacity_kwh × max(0, 80 − current_soc) / 100
time_to_80 = energy_to_80 / charger_power_kw
energy_above_80 = max(0, energy_to_add − energy_to_80)
time_taper = energy_above_80 / charger_power_kw × 2 (2× taper factor)
time_hours = time_to_80 + time_taper
OUTPUT:
time_hours (hr)
time_minutes (min)
energy_added_kwh (kWh)
BENCHMARK:
±10% above 80% taper vs CharIN DC Fast charging curve analysis
exact classification: SAE J1772 EV charging level standardAssumptions
- DC Fast charging taper begins at 80% SoC (industry-standard BMS behavior)
- Taper factor of 2× approximates the logarithmic slowdown above 80%
- 50 kW threshold distinguishes DC Fast from L2 charging (SAE J1772 classification)
- Charging time based on battery-side power; wall-to-battery efficiency not applied to duration
Edge Cases
- Cold-battery DC Fast (<50°F) without preconditioning: vehicles throttle peak power 30–60% until the pack warms — observed Tesla Supercharger sessions can stretch from 18 to 35 minutes.
- L1 (120V, 12A continuous) for plug-in hybrid (PHEV) ~10 kWh packs: 8–10 hour full overnight charge is feasible; for full BEVs (60+ kWh), L1 alone is insufficient for daily use.
- 350 kW DC Fast stations capped by the vehicle's onboard BMS: most BEVs peak at 150–250 kW even on a 350 kW dispenser — match expected time to the vehicle's published peak charge curve, not the station's nameplate.
Data Sources
- CharIN — DC Fast charging curve analysis
- SAE J1772 — EV charging level standard
- InsideEVs — real-world DC Fast charging data
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| CharIN DC Fast curve analysis | ±10% above 80% taper | 2026-05 |
| SAE J1772 charging level standard | exact (statutory) | 2026-05 |
EV Charger ROI Calculator
Formula
INPUT:
monthly_kwh (kWh/mo you would move from public charging to home)
public_rate ($/kWh, public DC-fast average)
home_rate ($/kWh, your home rate — prefilled from EIA when your ZIP resolves)
charger_cost ($, hardware purchase)
installation_cost ($, electrician labor)
rebate ($, utility/state EVSE rebate)
CALCULATION:
rate_difference = max(0, public_rate − home_rate)
monthly_savings = monthly_kwh × rate_difference
annual_savings = monthly_savings × 12
net_cost = max(0, charger_cost + installation_cost − rebate)
payback_months = net_cost / monthly_savings (0 when the rebate covers the install)
net_5yr = monthly_savings × 60 − net_cost
cumulative(m) = monthly_savings × m − net_cost (the break-even chart, months 0–60)
OUTPUT:
monthly_savings ($/mo)
annual_savings ($/yr)
payback_months (months; shown as "N months" under two years, "N.N years" beyond)
net_cost ($, after rebate)
five_year_net ($, savings over 60 months minus net cost)
rate_difference ($/kWh, the whole engine of this calculator)
BENCHMARK:
±10% of ChargePoint home charger hardware pricing
±15% of AFDC home charging ROI analysisAssumptions
- Energy moved to home charging is entered directly in kWh per month — this calculator does not derive it from annual mileage or an efficiency assumption
- Savings only accrue when the home rate is below the public rate; when home is the same or more expensive, the calculator says so instead of showing a payback
- Rebates (EVSE utility programs, state incentives) reduce net install cost; a rebate that covers the whole install is reported as immediately profitable
- Charger maintenance and any electrical-panel upgrade are not modeled
Edge Cases
- 100A or smaller residential service panel: a 40A L2 charger may require a 200A panel upgrade ($1,500–$3,500) — model does not include panel upgrade by default; add the upgrade cost to Net Install Cost. Consult a licensed electrician for NEC Article 220 load calculation.
- Federal 30C residential charger credit (30% up to $1,000) terminated after September 30, 2025 — installations placed in service from October 1, 2025 onward receive $0 federal credit. Some state and utility rebates remain.
- Smart L2 chargers ($600–$900) versus basic 40A units ($300–$450): the $300–$500 premium pays back via TOU optimization and load-balancing in households with 2+ EVs or panel-constrained service.
Data Sources
- EIA — residential electricity rates (home rate prefill)
- ChargePoint — home charger hardware cost data
- AFDC — home charging ROI analysis
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| ChargePoint home charger pricing | ±10% | 2026-05 |
| AFDC home charging ROI analysis | ±15% | 2026-05 |
Electric Bill with EV Calculator
Formula
INPUT:
annual_miles (mi/yr)
ev_efficiency (mi/kWh, EPA-rated)
charging_efficiency (fraction; this model applies 1.0 — see assumptions)
electricity_rate ($/kWh)
current_monthly_kwh (kWh/mo, household electricity baseline)
CALCULATION:
monthly_miles = annual_miles / 12
monthly_ev_kwh = monthly_miles / ev_efficiency (charging_efficiency = 1.0)
monthly_increase = monthly_ev_kwh × electricity_rate
new_total_bill = (current_monthly_kwh × electricity_rate) + monthly_increase
annual_increase = monthly_increase × 12
OUTPUT:
monthly_ev_kwh (kWh/mo added by EV charging)
monthly_increase ($)
new_total_bill ($/mo)
annual_increase ($)
BENCHMARK:
±2% of EIA residential monthly electricity consumption survey
±10% of DOE EV home charging analysisAssumptions
- Charging efficiency is NOT applied: the model divides by 1.0, so the kWh shown is the energy delivered to the battery, not the energy drawn from the wall. Real L2 charging loses roughly 10% wall-to-battery, so your actual bill increase runs about 11% higher than this estimate
- EV efficiency entered by user; typical range 2.5 mi/kWh (trucks) to 4.5 mi/kWh (sedans)
- Miles distributed evenly across all 12 months
- Flat electricity rate applied — no time-of-use pricing modeled
Edge Cases
- 100A service-panel limit: a single 40A L2 circuit (32A continuous, 7.7 kW) can saturate available capacity when AC + dryer + EV run simultaneously — a 200A panel upgrade ($1,500–$3,500) is typically required. Consult a licensed electrician for NEC Article 220 calculation.
- Two-EV household: monthly kWh roughly doubles. Households should verify utility EV-time-of-use plan eligibility (PG&E EV2-A, ComEd Hourly) which can offset the cost increase 30–50%.
- Solar offset: midday solar production can charge the EV directly when home, reducing utility-bill impact — but only with daytime charging and either NEM credit or battery-coupled self-consumption.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| EIA residential consumption (monthly) | ±2% | 2026-05 |
| DOE EV home charging analysis | ±10% | 2026-05 |
Heat Pump Savings Calculator
Formula
INPUT:
home_sqft (ft², heated floor area; entered by you)
climate_zone (ASHRAE/IECC 1–7, resolved from your ZIP code)
current_fuel (gas | oil | propane | electric)
current_efficiency (%, your existing system's AFUE; entered by you)
fuel_price ($/therm for gas, $/gal for oil/propane, $/kWh for electric)
electricity_rate ($/kWh, for heat pump operating cost)
install_cost ($, total installed cost of heat pump system)
CALCULATION:
hdd = CLIMATE_ZONE_HDD[climate_zone] (NOAA CCD annual normal, representative city)
zone 1: 128 · 2: 1,291 · 3: 2,768 · 4: 4,764 · 5: 6,340 · 6: 7,580 · 7: 9,444
hspf = CLIMATE_ZONE_HSPF[climate_zone] (seasonal, not a nameplate rating)
zone 1: 12 · 2: 11 · 3: 10 · 4: 9 · 5: 9 · 6: 8.5 · 7: 8
zone unknown → 5,000 HDD + HSPF 9 (US average) and the result panel says so
annual_btu = home_sqft × 3.5 × hdd (ACCA Manual J simplified load)
afue = current_efficiency / 100, clamped to the band for your fuel type
(gas 50–98%, oil 50–87%, propane 50–95%, electric fixed at 100%)
current_annual_cost per fuel type:
gas: therms = annual_btu / (afue × 100,000) → cost = therms × fuel_price
oil: gallons = annual_btu / (afue × 138,700) → cost = gallons × fuel_price
propane: gallons = annual_btu / (afue × 91,500) → cost = gallons × fuel_price
electric: kwh = annual_btu / 3,412 → cost = kwh × electricity_rate
heat_pump_kwh = annual_btu / (hspf × 1,000)
heat_pump_cost = heat_pump_kwh × electricity_rate
annual_savings = current_annual_cost − heat_pump_cost
payback_years = install_cost / annual_savings
OUTPUT:
current_annual_cost ($)
heat_pump_cost ($)
annual_savings ($)
payback_years (yr)
10yr_net_savings ($)
BENCHMARK:
±15% of ENERGY STAR ASHP Savings Calculator
code-baseline: DOE Building Energy Codes ProgramAssumptions
- Current system AFUE comes from your input (default 0.80, a typical older gas furnace) — it is not a fixed assumption
- AFUE is capped at the ceiling for the fuel you pick: gas 98%, oil 87%, propane 95%; electric resistance is always 100% (COP = 1), so the slider does not apply to it
- Heating load comes from your climate zone, not a national average: representative annual heating degree days per zone are NOAA Comparative Climatic Data normals (1981–2010, the latest published edition) for the ASHRAE 90.1 prototype city of that zone
- Heat pump efficiency is the seasonal HSPF expected in your zone (12 in zone 1 down to 8 in zone 7), anchored to ENERGY STAR typical values — nameplate HSPF/HSPF2 is rated in a single test climate (AHRI Region IV), so it is not applied unchanged to every location
- Zones 4 and 5 both use HSPF 9 because Region IV — the rating climate — sits between them; intermediate zones are not interpolated arithmetically
- Your climate zone is assigned from your ZIP code's state (with metro-level corrections such as Chicago), so variation inside a large state — West Texas vs. the Gulf Coast, coastal vs. inland California — is not resolved; treat a borderline result as an estimate and check your own heating bill
- Fuel prices held constant — 10-year projection uses the same annual savings figure
- 25C heat pump tax credit: $0 for 2026+ (expired per OBBBA, Pub.L. 119-21)
Edge Cases
- Cold-climate operation below −15°F: standard HSPF ratings degrade sharply — specify a cold-climate ASHP (HSPF2 ≥ 8.5, NEEP ccASHP-listed) or plan for resistance backup. Consult a licensed HVAC contractor for a Manual J sized to your design temperature.
- Dual-fuel hybrid (heat pump + gas furnace, switchover ~25°F): captures heat-pump efficiency above 25°F and gas economics below — model the heat-pump portion at full load above switchover only.
- Ductless mini-split single zone versus central ducted: mini-splits avoid duct losses (10–25% in unconditioned attics) but cover only the conditioned zone — sum multiple heads when comparing to a whole-house central system.
Data Sources
- ENERGY STAR ASHP Savings Calculator — ±15% benchmark
- ACCA Manual J 8th Edition — heating load methodology
- DOE FEMP — heat pump payback validation
- NOAA NCEI Comparative Climatic Data — normal heating degree days by station
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| ENERGY STAR ASHP Savings Calculator | ±15% | 2026-05 |
| DOE Building Energy Codes Program | code-baseline (no numeric margin) | 2026-05 |
Insulation ROI Calculator
Formula
INPUT:
current_r_value (R-value, 0–60)
target_r_value (R-value, 0–60)
annual_heating_cooling_cost ($, combined annual HVAC spend)
installation_cost ($, material + labor)
CALCULATION:
if current_r = 0: savings_fraction = 1.00
elif target_r ≤ current_r: savings_fraction = 0.00
else: savings_fraction = 1 − (current_r / target_r)
annual_savings = annual_heating_cooling_cost × savings_fraction
payback_years = installation_cost / annual_savings
10yr_net_savings = annual_savings × 10 − installation_cost
OUTPUT:
savings_fraction (fraction)
annual_savings ($)
payback_years (yr)
10yr_net_savings ($)
BENCHMARK:
code-baseline: DOE Insulation R-Value guide by climate zone
±15% of ENERGY STAR insulation savings guidanceAssumptions
- R-value ratio model: thermal conductivity ∝ 1/R-value (standard building physics)
- Applies to attic insulation; wall and floor assemblies use the same math but different baseline R-values
- Heating and cooling cost entered by user as a combined annual spend
- Moisture control, air sealing, and thermal bridging effects are not modeled
Edge Cases
- Climate-zone-specific attic targets: DOE recommends R-30 in Zone 1 (Miami) versus R-49–R-60 in Zone 7 (Duluth) — use the appropriate target R-value for your IECC climate zone, not a national default.
- Air-sealing before insulation: blower-door testing identifies leaks that insulation alone cannot fix — uncontrolled air infiltration can negate 30–50% of insulation gain. Consult a certified home energy auditor (BPI or RESNET).
- Retrofit phasing: attic insulation typically returns 30–50% versus 10–20% for wall retrofits — sequence attic first, then air sealing, then walls only if the budget remains.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| DOE Insulation R-Value guide | code-baseline (no numeric margin) | 2026-05 |
| ENERGY STAR insulation guidance | ±15% | 2026-05 |
Carbon Footprint Calculator
Formula
INPUT:
monthly_kwh (kWh/mo, household electricity)
natural_gas_therms (therms/mo, household natural gas)
vehicle_type (gas | ev)
vehicle_miles (mi/yr)
vehicle_mpg (mpg; ignored when vehicle_type = ev)
flight_hours (hr/yr, time in the air — your own flights)
diet_type (heavy meat | average | vegetarian | vegan)
household_size (people sharing the home, 1–8; default 1)
CALCULATION: (all figures in kg CO₂/yr)
electricity_kg = monthly_kwh × 12 × 0.348
natural_gas_kg = natural_gas_therms × 12 × 5.3
transport_kg = vehicle_miles / vehicle_mpg × 8.89
(0 for an EV — its charging already sits in electricity_kg)
flight_kg = flight_hours × 90
diet_kg = {heavy meat: 3300, average: 2500,
vegetarian: 1700, vegan: 1500}
shared_kg = electricity_kg + natural_gas_kg + transport_kg (household items)
personal_kg = flight_kg + diet_kg (already per person)
household_kg = shared_kg + personal_kg
per_person_kg = shared_kg / household_size + personal_kg
vs_us_average = (per_person_kg / 1000 − 16) / 16 × 100 (%)
tree_equivalent = per_person_kg / 21.77
OUTPUT:
household_tons (t CO₂/yr, everyone under this roof)
per_person_tons (t CO₂/yr, the figure compared to the US average)
category_split (electricity, natural gas, vehicle, flights, diet — per person)
vs_us_average (%, above or below 16 t per person)
tree_equivalent (trees needed to absorb one person's footprint)
BENCHMARK:
±5% of EPA eGRID national emission factor (utility-reported)
±10% of EPA Greenhouse Gas Equivalencies calculatorAssumptions
- US average grid intensity: 0.348 kg CO₂/kWh (~0.77 lbs) — EPA eGRID2023 Revision 2, 767.209 lb CO₂/MWh; state values vary significantly
- Shared household items (electricity, natural gas, the car) are divided by household size; flights and diet are NOT divided, because both constants are already defined per person — diet is 2500 kg per person-year at the average setting and the flight hours you enter are your own
- The figure compared to the US average is the per-person one, because the 16 t benchmark is itself per person — comparing a whole household against it would overstate every multi-person home
- EV transportation CO₂ = 0 in the transportation category — charging is already captured in the electricity row
- Gasoline combustion: 8.89 kg CO₂/gal; natural gas: 5.3 kg CO₂/therm; flights: 90 kg CO₂/hr (EPA Greenhouse Gas Equivalencies — eGRID covers electricity only)
- 1 tree sequesters approximately 21.77 kg CO₂/yr (EPA Greenhouse Gas Equivalencies)
- Solar production is not an input here — lowering your monthly kWh is what shows a rooftop system's effect in this calculator
Edge Cases
- Regional grid-factor extremes: Washington and Idaho (hydro-dominant) average ~0.05 kg CO₂/kWh while West Virginia and Kentucky (coal-dominant) exceed 0.75 kg CO₂/kWh — using a national average masks a 15× spread.
- Operational versus lifecycle emissions: this model captures operational only — solar panel and EV battery manufacturing contribute a one-time embodied carbon cost (typically paid back within 1–3 years of clean operation).
- Result accuracy: household-level estimates carry ±20–30% uncertainty because behavior (driving, thermostat, plug load) varies more than the input model can capture. For audit-grade analysis, consult a certified climate consultant.
Data Sources
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| EPA eGRID state factors | ±5% (utility-reported) | 2026-05 |
| EPA Greenhouse Gas Equivalencies | ±10% | 2026-05 |
Appliance Energy Cost Calculator
Formula
INPUT:
appliances[] (up to 15 rows; each row: label, watts, hours_per_day)
electricity_rate ($/kWh)
CALCULATION: (per appliance row)
daily_kwh = watts / 1,000 × hours_per_day (hours clamped to 0–24)
monthly_kwh = daily_kwh × 30
monthly_cost = monthly_kwh × electricity_rate
annual_cost = monthly_cost × 12
(so a year is 30 × 12 = 360 operating days, not 365)
total_monthly_cost = Σ monthly_cost over all rows
total_annual_cost = Σ annual_cost over all rows
top_energy_user = row with the highest monthly cost
energy_vampire = hours_per_day ≥ 20 AND watts ≤ 25
OUTPUT:
per_appliance (daily kWh, monthly kWh, monthly $, annual $ — sorted by cost)
total_monthly_cost ($/mo)
total_annual_cost ($/yr)
total_monthly_kwh (kWh/mo)
top_energy_user (the single most expensive device)
vampires (always-on low-draw devices worth unplugging)
BENCHMARK:
±10% of ENERGY STAR Appliance Calculator energy estimates
±5% (survey-level) of EIA Residential Energy Consumption Survey (RECS)Assumptions
- Watt rating represents active power draw (as shown on ENERGY STAR yellow EnergyGuide labels)
- A month is billed as 30 days and a year as 12 of those months — 360 operating days, about 1.4% below the calendar year, so annual figures read slightly low for a device that truly runs every day
- Seasonal appliances should be entered with adjusted daily hours rather than a full-year average
- Energy vampire flag identifies always-on low-draw devices (routers, modems, standby chargers)
- Flat electricity rate applied — no demand charges or time-of-use pricing
- This calculator prices what your appliances cost to run; it does not model a replacement purchase or its payback
Edge Cases
- Comparing an upgrade: this calculator gives you the running cost of the appliance you have. To judge a replacement, enter the new unit's wattage as a second row and read the difference — a working high-efficiency unit rarely repays its replacement, a broken or pre-2000 unit nearly always does.
- Standby and phantom load: always-on devices (routers, set-top boxes, smart speakers, instant-on TVs) typically represent 5–10% of a household's monthly kWh — flag all >20 hr/day items.
- Time-of-use peak-window heavy use (cooktop, oven, EV charger, AC during 4–9 PM) can run 3–5× a flat rate — TOU savings require shifting these loads, not just upgrading them.
Data Sources
- ENERGY STAR Appliance Calculator — energy use benchmarks
- EIA RECS — Residential Energy Consumption Survey
Benchmark References
| Benchmark | Acceptance Margin | Last Checked |
|---|---|---|
| ENERGY STAR Appliance Calculator | ±10% | 2026-05 |
| EIA Residential Energy Consumption Survey (RECS) | ±5% (survey-level) | 2026-05 |