Quick Facts
What Is Peak Sun Hours?
The concept simplifies solar resource description. Instead of saying “today the site received 5.2 kWh/m² of total irradiation spread across 12 hours of daylight with constantly changing intensity,” you can say “today had 5.2 Peak Sun Hours.” The two statements are mathematically identical.
Numerically, PSH is identical to daily Global Horizontal Irradiance (GHI) expressed in kWh/m² per day. The unit conversion makes them the same number:
5 PSH = 5 kWh/m²/day
This metric is intuitive, widely used in solar sizing, and essential for anyone estimating solar savings, from homeowners checking PM Surya Ghar subsidies to EPC engineers sizing megawatt-scale ground-mount parks.
Why the 1,000 W/m² Reference?
Solar module manufacturers rate their products under Standard Test Conditions (STC), which include 1,000 W/m² irradiance, 25°C cell temperature, and Air Mass 1.5 spectrum. PSH uses this same reference, so multiplying module kWp by PSH gives a direct first-order estimate of DC energy output before system losses.
Why Peak Sun Hours Matters
Peak Sun Hours is the single most important location factor in solar plant economics. Two identical 5 kWp systems, one in Jaisalmer and one in Kolkata, will produce very different annual energy because their PSH differs by more than 20%.
- Financial forecasting: PSH drives the revenue model. A 1% error in PSH translates to a 1% error in predicted annual generation and payback period.
- System sizing: Designers use PSH to right-size inverters, estimate cable runs, and calculate battery backup needs for off-grid or hybrid systems.
- Subsidy planning: Under PM Surya Ghar, PSH-based generation estimates help match a proposed system size to the household’s consumption before applying to the DISCOM (UGVCL, MGVCL, PGVCL, DGVCL in Gujarat).
- Lender confidence: Banks and NBFCs financing solar projects rely on PSH-derived generation estimates, often cross-checked against P50/P90/P99 solar yield reports, to structure EMIs and assess debt service coverage ratios.
Important: Gujarat’s average PSH of about 5.3 to 5.7 makes it one of India’s most profitable states for solar investment. An optimally tilted system in Ahmedabad can generate up to about 1,700 kWh/kWp annually (Global Solar Atlas estimate), among the highest in the country.
How Peak Sun Hours Works
Understanding PSH requires following a simple four-step process:
- Measure total daily irradiation: A pyranometer records instantaneous irradiance (W/m²) every minute. The software integrates these readings over 24 hours to produce daily GHI in kWh/m².
- Divide by the STC reference: Divide the daily GHI by 1 kW/m². Because 1 kWh/m² = 1 kW × 1 hour, the result is equivalent hours at peak intensity, Peak Sun Hours.
- Multiply by system kWp: A 5 kWp system at a 5.5 PSH location produces approximately 5 × 5.5 = 27.5 kWh/day at the DC level.
- Apply system losses: Multiply by the Performance Ratio (typically 0.80 to 0.85 in India) to get actual AC energy delivered to the grid or home.
Worked Example: Ahmedabad vs. Kolkata
| Parameter | Ahmedabad | Kolkata |
|---|---|---|
| Annual average daily PSH | 5.5 | 4.6 |
| System size | 5 kWp | 5 kWp |
| Daily DC energy (kWh) | 5 × 5.5 = 27.5 | 5 × 4.6 = 23.0 |
| AC energy at PR 0.82 (kWh/day) | 22.6 | 18.9 |
| Annual AC energy (kWh) | ~8,250 | ~6,900 |
| Annual savings at ₹8/kWh | ₹66,000 | ₹55,000 |
The roughly 20% higher PSH in Ahmedabad produces roughly 20% more annual energy and savings from the same installed capacity.
Visual Explanation
Real-World Example
Heaven Green Energy installed a 7 kWp rooftop system for a textile trader in Surat, Gujarat. The site survey used NIWE Solar Atlas data showing 5.4 PSH annual average. The design team applied a conservative PR of 0.81 to account for Surat’s humid summers and occasional dust.
- Estimated daily generation: 7 kWp × 5.4 PSH × 0.81 = 30.6 kWh/day
- Estimated annual generation: 30.6 × 365 = 11,169 kWh
- Actual year-one generation: 11,340 kWh (PR 0.823)
- Annual electricity bill savings: ₹90,720 at ₹8/kWh
- PM Surya Ghar subsidy received: ₹78,000 (₹30,000/kW for the first 2 kW + ₹18,000 for the 3rd kW; capped at ₹78,000 for 3 kW and above)
- Net system cost after subsidy: ₹2,80,000
- Simple payback: 3.1 years
The PSH-based estimate was accurate within 1.5%, validating the design approach and giving the customer confidence in their investment.
Technical Specifications / Benchmarks
| City / Region | Annual Avg Daily PSH | Solar Resource Quality | Typical kWh/kWp/Year |
|---|---|---|---|
| Jaisalmer, Rajasthan | 5.6 | Excellent | 1,765 |
| Bikaner, Rajasthan | 5.3 | Excellent | 1,678 |
| Ahmedabad, Gujarat | 5.5 | Very good | 1,701 |
| Jaipur, Rajasthan | 5.2 | Very good | 1,627 |
| Bhopal, Madhya Pradesh | 5.2 | Very good | 1,598 |
| Hyderabad, Telangana | 5.3 | Very good | 1,589 |
| Bengaluru, Karnataka | 5.3 | Very good | 1,578 |
| Chennai, Tamil Nadu | 5.3 | Good | 1,565 |
| Mumbai, Maharashtra | 5.2 | Good | 1,593 |
| Delhi NCR | 4.7 | Good | 1,466 |
| Kolkata, West Bengal | 4.6 | Moderate | 1,408 |
| Patna, Bihar | 4.7 | Moderate | 1,438 |
| Guwahati, Assam | 4.5 | Moderate | 1,407 |
| Category | Value (kWh/kWp) |
|---|---|
| Jaisalmer | 1,765 kWh/kWp |
| Ahmedabad | 1,701 kWh/kWp |
| Jaipur | 1,627 kWh/kWp |
| Mumbai | 1,593 kWh/kWp |
| Delhi NCR | 1,466 kWh/kWp |
| Kolkata | 1,408 kWh/kWp |
These are long-term annual averages for each city point from the Global Solar Atlas (World Bank / Solargis, accessed October 2026). The kWh/kWp column is the atlas’s PVOUT estimate for an optimally tilted system; rooftop systems with shading, soiling or non-ideal tilt typically produce less. Year-to-year variation is 3% to 6%; seasonal variation is significantly larger.
Benefits / Advantages
- Intuitive comparison: PSH turns complex irradiance data into a single number anyone can understand. A homeowner in Ahmedabad knows 5.5 PSH means “5.5 hours of full noon sun every day on average.”
- Quick sizing: Multiply kWp by PSH for a first-order daily energy estimate. No software required for initial feasibility checks.
- Location benchmarking: PSH allows apples-to-apples comparison between cities, states, and countries regardless of latitude or climate.
- Subsidy planning: Accurate PSH data ensures system sizes match PM Surya Ghar subsidy slabs without oversizing or undersizing.
- Lender communication: Banks understand PSH because it directly links to revenue. A project with 5.6 PSH in western Rajasthan is inherently lower-risk than one with 4.2 PSH in the Northeast.
- Seasonal awareness: Monthly PSH data reveals monsoon dips and summer peaks, helping owners plan cleaning schedules and maintenance windows.
- Equipment selection: High-PSH locations justify premium mono PERC or TOPCon panels because every extra watt of efficiency compounds across more sun hours.
- Battery sizing: Off-grid and hybrid designers use PSH to calculate how many days of autonomy batteries must provide during low-PSH months.
Limitations / Drawbacks
- Horizontal bias: PSH typically refers to GHI on a horizontal surface. Tilted modules receive POA irradiance, which is roughly 3% to 12% higher in India at optimal tilt, depending on latitude. Using PSH directly underestimates tilted-array output.
- No loss accounting: PSH measures available resource, not what reaches the inverter. Temperature, soiling, shading, and cable losses must be applied separately.
- Annual averages hide seasonality: A site with 5.0 annual average PSH may see 6.5 in April and 3.5 in July. Annual averages mislead for monsoon-heavy regions.
- Microclimate blind: PSH datasets have spatial resolution of 1 to 10 km. A site near a dust source, industrial haze, or coastal fog may underperform the atlas value.
- Not a design precision tool: For project finance and EPC contracts, PSH alone is insufficient. Detailed PVsyst modelling with hourly data, temperature profiles, and shading analysis is mandatory.
- Confusion with daylight hours: Laypeople often confuse PSH (4 to 6 hours) with total daylight (10 to 14 hours), leading to unrealistic generation expectations.
Comparison: PSH vs. Related Metrics
| Metric | What It Measures | Unit | Use Case |
|---|---|---|---|
| Peak Sun Hours (PSH) | Equivalent hours at 1,000 W/m² | Hours/day | Quick sizing, resource comparison |
| GHI | Total irradiance on horizontal surface | kWh/m²/day | Same as PSH, used in technical reports |
| POA Irradiance | Irradiance on tilted module surface | kWh/m²/day | Precise energy yield calculations |
| DNI | Direct sunlight only | kWh/m²/day | Concentrating solar power (CSP) |
| DHI | Scattered skylight only | kWh/m²/day | Diffuse-dominated climate analysis |
| CUF | Actual output vs. theoretical max | % | Plant utilisation, not quality |
| PR | Actual vs. expected output for irradiance | % | Plant quality metric |
For residential and small commercial sizing, PSH is the right starting point. For utility-scale project finance, POA irradiance with hourly granularity is non-negotiable.
Applications
- Residential rooftop: Homeowners use city-level PSH to estimate savings and choose between 3 kW, 5 kW, or 10 kW systems. Gujarat’s 5.3+ PSH makes even modest systems highly economical.
- Commercial & industrial: Factory owners in Ahmedabad, Surat, and Vadodara use PSH to size commercial solar systems that offset 70%+ of their electricity bills.
- Industrial parks: Large consumers in Gujarat’s GIDC estates use site-specific PSH data to negotiate OPEX vs. CAPEX models with solar developers.
- Ground-mount solar parks: Ground-mount projects in Kutch and Banaskantha leverage about 5.6 PSH, among India’s highest, to achieve a low levelised cost of solar energy.
- Agricultural pumps: PM-KUSUM solar pump designers use PSH to size arrays that deliver sufficient water during peak irrigation months.
- Off-grid & hybrid: Remote sites in Rajasthan and Ladakh use monthly PSH minima to size battery banks for critical load backup during low-sun weeks.
Industry Standards & Regulations
- WMO Guide to Meteorological Instruments: Defines pyranometer calibration and irradiance measurement protocols used to generate PSH datasets.
- ISO 9060: Classifies pyranometers into Secondary Standard, First Class, and Second Class. Lender-grade projects require Secondary Standard instruments.
- IEC 61215:2021: Module qualification standard that references STC conditions (1,000 W/m²), the basis for PSH calculations.
- NIWE solar resource data: The National Institute of Wind Energy (NIWE), under MNRE, publishes India’s solar resource maps and ground-station data, a key source for Indian PSH data.
- Forecasting and scheduling regulations: CERC and state commission regulations require larger solar plants to forecast and schedule generation, which relies on irradiance-based models.
India-Specific Context
India is a high-solar-resource country by global standards. Most of the country averages roughly 4.5 to 5.6 kWh/m²/day of GHI, ahead of Germany (about 2.9 in Berlin), Japan (about 3.9 in Tokyo), and the UK (about 2.8 in London). This resource advantage helps explain why Indian solar has achieved grid parity without subsidies in most states.
Gujarat is among India’s highest-PSH states. The state’s northwestern districts, Kutch, Banaskantha, Patan, and Surendranagar, average about 5.6 PSH, on par with western Rajasthan. This is why Gujarat hosts some of India’s largest solar parks and why Heaven Green Energy ranks as the state’s #1 PM Surya Ghar installer.
State DISCOM integration: Gujarat’s four DISCOMs (UGVCL, MGVCL, PGVCL, DGVCL) process rooftop net metering applications. PSH-based generation estimates help you size a system to your consumption before you apply; overestimating PSH leads to an oversized system and disappointing savings.
Monsoon impact: At South Indian sites the lowest monsoon months (June–September) run roughly 30 to 40% below the March–April PSH peak. Designers in Kerala and coastal Karnataka who need to meet monsoon-month energy needs should size from monthly PSH rather than the annual average.
Future Trends
- Satellite dataset refinement: Newer geostationary satellites and processing methods are delivering higher-resolution, more frequent irradiance data, capturing microclimates that coarse datasets miss.
- AI-driven forecasting: Machine learning models trained on satellite imagery and ground-station data are improving next-day irradiance forecasts, enabling dynamic cleaning and maintenance scheduling.
- Bifacial gain integration: PSH calculations for bifacial modules will increasingly include rear-side irradiance, which matters most in high-albedo environments like the white salt flats of Gujarat’s Rann of Kutch.
- Climate change adaptation: Changes in humidity, cloud cover and aerosols may shift effective PSH in some regions over coming decades.
- Agrivoltaics: Dual-use solar-over-crop systems will require crop-specific PSH models that account for partial shading from panel rows, a new frontier in solar resource assessment.
Common Mistakes & Misconceptions
- Using a single annual PSH for projects with strong seasonal variation: Monsoon-heavy regions need monthly PSH analysis. A 5.2 annual average in Mumbai masks a July average near 3.5.
- Treating PSH (horizontal) as POA (tilted): POA is roughly 3 to 12% higher for optimally tilted, south-facing modules in India. Using PSH directly underestimates output.
- Ignoring shading and obstruction: PSH measures available resource, not what reaches panels after shading from buildings or trees.
- Using outdated data: Solar resource varies year-to-year. Multi-year averages from current datasets (Solargis, Meteonorm) are essential for project finance.
- Confusing PSH with daylight hours: PSH is equivalent full-sun hours (4 to 6), not total daylight (10 to 14). This confusion causes massive overestimation of generation.
- Applying PSH without Performance Ratio: Multiplying kWp by PSH gives DC energy. For AC energy and savings, PR must be applied.
- Forgetting temperature derating: High-PSH locations are often hot. A 5.6 PSH site at 55°C module temperature loses 10 to 12% to heat, offsetting some of the sun advantage.
- Using generic tables for site-specific decisions: City-level PSH is a starting point. Site-specific surveys with on-site pyranometers are needed for projects above 100 kWp.
Key Takeaways
- Peak Sun Hours (PSH) is the equivalent daily hours at 1,000 W/m² that would deliver the same solar energy as actual variable sunlight.
- PSH equals daily GHI in kWh/m²: the two numbers are numerically identical.
- India’s PSH ranges from about 4.0 (parts of the Northeast) to about 5.7 (Kutch and western Rajasthan), with Gujarat and Rajasthan at the top.
- Gujarat averages about 5.3 to 5.7 PSH, making it one of India’s most profitable states for solar investment.
- Quick sizing formula: Daily AC energy ≈ kWp × PSH × PR (0.80 to 0.85).
- PSH is for rough estimates; POA irradiance with PVsyst is for precision design.
- Monthly PSH data is essential for monsoon-heavy regions and seasonal load matching.
- Always pair PSH with shading analysis and temperature correction for accurate financial projections.
Related Glossary Terms
Related Resources
- PM Surya Ghar Complete Guide, Subsidy slabs, eligibility, and application steps
- Home Solar System Size Guide, How to size based on PSH and consumption
- 3kW vs 5kW vs 10kW Home Solar, System comparison for Gujarat homes
- Solar Installation Day-by-Day, What to expect during installation
- Solar Payback Period, ROI calculations using PSH data
- Residential Solar, Heaven Green Energy’s home solar solutions
- Solar Calculator, Instant savings estimate for your location
- Solar Cost Ahmedabad, Pricing breakdown for Gujarat’s solar capital
Sources & References
- NIWE Solar Atlas, Ministry of New and Renewable Energy, India
- IEC 61215:2021, Terrestrial photovoltaic (PV) modules, Design qualification and type approval
- WMO Guide to Meteorological Instruments and Methods of Observation (WMO-No. 8)
- NREL National Solar Radiation Database (NSRDB), Free satellite-derived irradiance data
- Global Solar Atlas (World Bank / Solargis), free high-resolution solar resource dataset
- MNRE / PM Surya Ghar Operational Guidelines for CFA (7 June 2024)
- PVsyst SA, Photovoltaic System Design Software, user manual v7.4
- MNRE Annual Report 2024 to 25, Solar resource and installed capacity statistics