AEP — 1.5 MW class in Tamil Nadu
Expected annual MWh from a 1.5 MW class turbine at a typical Tamil Nadu site (7 m/s, k≈2.4).
What should a 1.5 MW class machine (the global mid-fleet standard — GE 1.5, Suzlon S88 and kin, the world's most numerous turbine class) produce in Tamil Nadu? India's oldest wind belt (Muppandal/Aralvaimozhi passes) — monsoon-driven, with June–September delivering half the year's energy. The Weibull integration gives screening AEP and capacity factor — your fleet's underperformers stand out against this number.
AEP integrates a standard cubic power curve (cut-in 3, rated 12, cut-out 25 m/s) over the Weibull wind distribution fitted to your mean speed and shape factor. Screening accuracy ±10% — bankable studies need the OEM curve and on-site met data.
Engineering estimate from published standards and typical equipment data. Site conditions, equipment datasheets and measured data govern the real result — confirm with a qualified engineer.
Use the free AEP — 1.5 MW class in Tamil Nadu online — Expected annual MWh from a 1.5 MW class turbine at a typical Tamil Nadu site (7 m/s, k≈2.4). Runs instantly in your browser: no signup, no upload, mobile-friendly.
About AEP — 1.5 MW class in Tamil Nadu
What should a 1.5 MW class machine (the global mid-fleet standard — GE 1.5, Suzlon S88 and kin, the world's most numerous turbine class) produce in Tamil Nadu? India's oldest wind belt (Muppandal/Aralvaimozhi passes) — monsoon-driven, with June–September delivering half the year's energy. The Weibull integration gives screening AEP and capacity factor — your fleet's underperformers stand out against this number.
How to use AEP — 1.5 MW class in Tamil Nadu
- 1Enter the turbine rating and your site's mean wind speed at hub height.
- 2Adjust the Weibull shape factor for your wind regime.
- 3Read AEP, capacity factor and energy per MW installed.
Why use AEP — 1.5 MW class in Tamil Nadu?
- ✓Weibull statistics — how wind is actually distributed, not just averaged
- ✓Numerical integration over a standard power curve, transparent assumptions
- ✓Regional wind-speed and shape-factor presets
- ✓AEP, CF and per-MW yield for instant comparisons
Frequently asked questions
How is annual energy production estimated from mean wind speed?+
Mean speed alone underestimates badly — energy lives in the distribution's gusty tail. The Weibull fit (mean + shape factor k) reconstructs the full speed histogram, and integrating the power curve over it gives AEP within ±10% of professional screening tools.
What is the Weibull shape factor k?+
It describes wind steadiness: k≈1.6–1.9 means gusty/variable (some temperate sites), k≈2 the common default, k≈2.5–3+ remarkably steady trade winds (Brazil's northeast, parts of Tamil Nadu). Same mean speed, different k, can move AEP 10–15%.
What mean wind speed makes a site viable?+
Rough gates at hub height: below 5.5 m/s rarely pencils for grid-scale; 6.5–7.5 m/s is solid; above 8 m/s excellent. Small wind needs the same speeds at far lower hub heights — which is why most residential sites fail (see the small-wind tools for honest math).
Why does the AEP — 1.5 MW class in Tamil Nadu differ from my consultant's number?+
Screening vs engineering: this integrates a standardized power curve over fitted statistics; bankable studies use the OEM's exact curve, on-site met-mast data, wake and loss models. Expect ±10% agreement — close enough to rank sites and sanity-check claims, not to finance them.
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