Wind Turbine Payback in Dillon County, SC
Wind turbine payback in Dillon County
No. The turbine wears out before it pays for itself.
At 30 m, the height a home turbine tower usually reaches, the wind in Dillon County, SC averages 5 m/s (11.2 mph). A 10 kW turbine there would make about 12,535 kWh a year, worth $1,993 at SC's 15.9¢/kWh. Against an installed cost of about $100,000, that is a payback of 50 years, and the turbine is built to last about 20.
What to do in Dillon County
A home turbine is not worth buying for savings in Dillon County unless your spot is far windier than the county average, 7.6 m/s at the hub against 5 m/s here. Per kW, solar panels would make about 1,329 kWh a year here against the turbine's 1,254, so get a solar quote first.
What would have to change
- Power would have to cost 40¢/kWh, 2.5 times what SC pays now.
- Or the average wind at the hub would have to be 7.6 m/s instead of 5. A taller tower or an exposed ridge can add some of that; a rooftop never will.
Against the rest of SC
Dillon County is the 1,453rd windiest of 3,144 US counties at turbine height; the national middle is 4.79 m/s. The windiest in SC is Beaufort County at 5.71 m/s, payback 36 years.
Month by month in Dillon County
April is the strongest month here, at 5.85 m/s and about 1,531 kWh. August is the weakest, 3.93 m/s and 529 kWh, so the best month makes 2.9 times the worst. November to March brings in 50% of the year's output in Dillon County.
| Month | Wind at 30 m | Output | Worth |
|---|---|---|---|
| January | 5.38 m/s | 1,290 kWh | $205 |
| February | 5.61 m/s | 1,291 kWh | $205 |
| March | 5.73 m/s | 1,506 kWh | $239 |
| April | 5.85 m/s | 1,531 kWh | $243 |
| May | 5.04 m/s | 1,088 kWh | $173 |
| June | 4.32 m/s | 683 kWh | $109 |
| July | 4.15 m/s | 624 kWh | $99 |
| August | 3.93 m/s | 529 kWh | $84 |
| September | 4.73 m/s | 882 kWh | $140 |
| October | 4.93 m/s | 1,023 kWh | $163 |
| November | 5.14 m/s | 1,107 kWh | $176 |
| December | 5.16 m/s | 1,160 kWh | $184 |
What a taller tower would buy
Measured at 10 m the wind in Dillon County averages 3.75 m/s; at 50 m it is 5.71 m/s. That gives a shear exponent of 0.261, typical of ordinary open country. Going from 20 m to 50 m takes output from 9,312 to 17,565 kWh a year, 89% more, before counting the extra cost of the taller tower. Why tower height decides it explains the shear behind these numbers.
| Hub height | Average wind | Output | Payback |
|---|---|---|---|
| 20 m | 4.5 m/s | 9,312 kWh | 68 years |
| 30 m | 5 m/s | 12,516 kWh | 50 years |
| 40 m | 5.39 m/s | 15,226 kWh | 41 years |
| 50 m | 5.71 m/s | 17,565 kWh | 36 years |
Counties around Dillon County
None of the 6 closest counties is windier than Dillon County.
- Marion County, SC: 4.95 m/s, 12,199 kWh, payback 52 years (21 mi)
- Marlboro County, SC: 5 m/s, 12,535 kWh, payback 50 years (23 mi)
- Robeson County, NC: 5 m/s, 12,535 kWh, payback 53 years (23 mi)
- Florence County, SC: 4.98 m/s, 12,400 kWh, payback 51 years (31 mi)
- Scotland County, NC: 4.43 m/s, 8,924 kWh, payback 75 years (32 mi)
- Darlington County, SC: 4.46 m/s, 9,100 kWh, payback 69 years (34 mi)
Sun versus wind in Dillon County
Dillon County gets 4.55 kWh of sunshine per square metre a day on average. One kW of solar panels here would make roughly 1,329 kWh a year; one kW of the turbine above makes 1,254. Kilowatt for kilowatt, panels make 1.1 times as much here as the turbine. Panel output assumes an 80% system performance ratio. Wind or solar runs the same comparison for every county.
How this is worked out
Wind is NASA's Power climate record, the 2001-2025 average at 10 m and 50 m for the county's centre, carried to 30 m with this county's own measured wind shear and spread into hours with a Rayleigh distribution. The turbine is a generic 10 kW, 7 m rotor machine with 10% losses. Cost is $10,000 per kW installed with no tax credit, because the federal one ended in 2025. One county-centre number cannot see your hilltop or your tree line, so treat it as the starting point for a site survey, not a substitute. The full method and its weak spots are in how the numbers are made.