Solar panel orientation loss calculator

Calculates the annual yield of your roof orientation as a percentage of the site optimum — hour by hour with the Perez model on the PVGIS hourly grid, with terrain horizon, instead of a cosine rule of thumb. In Berlin an east-facing roof at 35° tilt delivers around 79% of the optimum — and more than the west face, because mornings there are clearer on average. Only an hourly simulation can show weather asymmetries like that. Coverage today: the DACH grid at 0.25° — a US grid built on NREL NSRDB data is in preparation.

Input

Input

Place (“Freiburg”) or coordinates (“47.99, 7.84”) · DE / AT / CH

Orientation

0 = south · −90 = east · +90 = west

Result · Live

Relative yield
78.1%of the tilt + azimuth optimum
Annual loss
21.9%vs. the optimal setup
Orientation share
21.7%loss vs. best azimuth at the same tilt
Annual total
1,024kWh/m²plane of array, calibrated
East-west pair
76.8%gable roof: half east, half west

78 % of the site optimum is what your orientation achieves (optimum: 40° tilt, -4° azimuth).

Mean daily profile: your orientation vs. east, south and west
SouthWestYours (-90°)06121823Time (CET)W/m²

East delivers in the morning, west in the evening — the area under each curve is the yield.

Values as table
Time (CET)SouthWestYours (-90°)
0:00000
1:00000
2:00000
3:00000
4:00001
5:007736
6:003423100
7:0010943206
8:0022066309
9:00346119383
10:00438194405
11:00472267371
12:00487330322
13:00462370252
14:00387368175
15:00296336109
16:0018927166
17:009619142
18:003110123
19:007307
20:00000
21:00000
22:00000
23:00000

The polar chart is computed after loading …

Calculation steps
  • Hourly simulation (Perez transposition): Σ_8760h Perez-POA(tilt 35°, az -90°) = 1,102.4 kWh/m²
  • Calibration to the multi-year mean of the real years: POA × mean(2005–2023)/TMY @ 35° S (× 0.929) = 1,024.4 kWh/m²
  • Azimuth sweep (Perez hourly simulation): Σ_8760h Perez-POA × 24 az @ tilt 35° = 1,308.1 kWh/m²
  • Site optimum across tilt and azimuth: argmax_{β,γ} H_a → β* 40°, γ* -4° = 1,312.4 kWh/m²
  • Relative yield: H_a(β, γ) / H_a(β*, γ*) = 78.053 %

The formulas behind the calculator

Every number above can be recomputed: the full calculation path, all assumptions and the data source with retrieval date — plus cross-validation against independent references. Disclosed, not claimed.

An estimate based on the stated assumptions. The final design must be checked by a qualified professional against the rules that apply where you are.

Data as of: 2026-07-30

Every intermediate value with its formula, number and provenance
StepFormulaValueProvenance
Hourly simulation (Perez transposition)Σ_8760h Perez-POA(tilt 35°, az -90°)1,102.4 kWh/m²measured
Calibration to the multi-year mean of the real yearsPOA × mean(2005–2023)/TMY @ 35° S (× 0.929)1,024.4 kWh/m²measured
Azimuth sweep (Perez hourly simulation)Σ_8760h Perez-POA × 24 az @ tilt 35°1,308.1 kWh/m²measured
Site optimum across tilt and azimuthargmax_{β,γ} H_a → β* 40°, γ* -4°1,312.4 kWh/m²measured
Relative yieldH_a(β, γ) / H_a(β*, γ*)78.053 %measured
Formula
R(β, γ) = H_a(β, γ) / H_a(β*, γ*) · hourly POA via Perez · azimuth sweep −180…+180° · each month calibrated to the 2005–2023 multi-year mean
Valid for
DACH grid at 0.25° resolution (1,155 points, PVGIS-SARAH3 2005–2023), tilts 0–90°, all orientations, terrain horizon of the grid point included. Cross-validated against the PVGIS hourly simulation at four reference sites across seven orientations each: relative yield within 1.5 percentage points, typically under 1.
Not covered
Near shading from buildings and trees (only the terrain horizon is included), snow cover, the economics of an east-west layout with twice the module count — and putting a money value on the morning/evening shift for self-consumption; the day profiles are shown in the chart, the economics belong to the self-consumption calculator.
Data sources

The same array at nearby locations

35° tilt, south-facing, identical array — the closest cities around your location, each with its own weather grid point. Every row is computed with the same formulas as your result above.

Location comparison: annual average, P90 and optimal tilt per city
LocationDistancePSH/dayP90 kWh/m²Optimum
Berlin1 km3.581,20840°
Oranienburg19 km3.501,19440°
Blankenfelde-Mahlow20 km3.581,19835°
Potsdam22 km3.591,21540°
Bernau22 km3.521,20935°
Ludwigsfelde26 km3.641,21940°
Königs Wusterhausen29 km3.571,20340°
Strausberg33 km3.631,23240°
Eberswalde45 km3.571,22740°

The sunniest and the dullest nearby place are 4 % apart — location beats tilt optimisation. Clicking a place opens its location page in a new tab.

Yield by orientation: major cities (DE / AT / CH)

Relative yield per compass direction at 35° tilt, as a percentage of each site’s optimum — computed per city from the hourly simulation, not from the usual one-size-fits-all table. The two columns those tables always miss: the east-west pair (gable roof, both sides used) and an honest north figure.

Relative solar yield by orientation in major cities of Germany, Austria and Switzerland: south, southeast, southwest, east, west, east-west pair and north at 35° tilt
CitySouthSoutheastSouthwestEastWestEast-west pairNorth
BerlinDE100 %94 %92 %78 %76 %77 %50 %
HamburgDE100 %95 %93 %80 %78 %79 %53 %
MünchenDE100 %94 %93 %79 %78 %78 %53 %
KölnDE100 %95 %93 %80 %78 %79 %53 %
Frankfurt am MainDE100 %95 %94 %80 %79 %80 %54 %
DüsseldorfDE100 %94 %93 %79 %78 %79 %54 %
StuttgartDE100 %93 %94 %78 %79 %78 %53 %
EssenDE100 %95 %94 %80 %80 %80 %56 %
DortmundDE100 %95 %94 %80 %79 %80 %55 %
DresdenDE100 %94 %93 %78 %77 %78 %51 %
WienAT100 %95 %92 %80 %77 %79 %55 %
GrazAT100 %93 %93 %77 %77 %77 %51 %
LinzAT100 %93 %95 %77 %79 %78 %52 %
SalzburgAT100 %94 %94 %79 %79 %79 %54 %
ZürichCH100 %94 %93 %78 %78 %78 %52 %
GenfCH100 %93 %94 %77 %78 %78 %51 %
BaselCH100 %94 %94 %80 %79 %79 %54 %
LausanneCH99 %89 %95 %72 %79 %75 %49 %

100% = the best tilt/orientation pair for each site. All values at 35° tilt, terrain horizon included, hourly PVGIS SARAH3 data (2005–2023). East-west pair: half the array east, half west — the self-consumption benefit of the double peak comes on top (see FAQ). Click a city to open its data page.

Frequently asked questions

How do I find out which direction my roof faces?

Fastest via the satellite view of Google Maps: orient the map north-up, read the direction of your roof ridge — the eaves side of your PV roof faces perpendicular to it. A compass app held at the window works too, but metal in the facade often skews it by several degrees. For this calculator, knowing your direction to within ±10 degrees is plenty: the polar chart below shows how little single degrees matter. Convention here: 0° = south, −90° = east, +90° = west.

How much yield does an east- or west-facing roof cost versus south?

In Berlin an east-facing roof at 35° tilt delivers around 79% of the site optimum, a west-facing one around 76% — a loss of 21–24%. The number depends on site and tilt: the flatter the surface, the smaller the difference between orientations. The calculator runs your exact combination hour by hour for your grid point instead of showing a generic table value.

Why does east beat west in Berlin?

Because mornings there are clearer on average than afternoons — fog burns off, convective clouds build up later in the day. The hourly simulation over the typical meteorological year captures that; PVGIS's own calculation shows the same 3–4% difference. A geometry or cosine model cannot see such weather asymmetries by construction — it always treats east and west as equal.

My roof faces southeast or southwest — should I worry?

No. At 35° tilt, southeast in Berlin sits at around 95% of the optimum and southwest at around 92% — a single-digit loss that in practice is dwarfed by shading, soiling or a poor inverter operating point. Deviations of up to 45° from south are almost always uncritical.

Is a north-facing surface pointless for solar?

Not pointless, but costly: a north-facing surface at 35° tilt reaches around 51% of the optimum in Berlin. The high diffuse share of the central European climate rescues more than the rule of thumb suggests — diffuse light comes from the whole sky and lands on north faces too. The flatter the tilt, the smaller the penalty; at 0° it disappears entirely.

So is east-west worse than south?

Per square metre, yes: an east-west pair (half east, half west) delivers around 77% of the optimum in Berlin at 35°. But a gable roof fits nearly twice as many modules east-west, and the day profile gets wider — generation shifts into the morning and evening hours when electricity is actually used. Since a self-consumed kilowatt-hour is worth a multiple of the feed-in rate, east-west often wins economically. The day-profile chart below the result shows exactly this shift.

Where do the numbers come from, and how accurate are they?

From the committed TMY hourly grid (PVGIS-SARAH3, 2005–2023, 1,155 grid points across the DACH region): for each of the 8,760 hours the irradiance is transposed into the module plane with the Perez model, the terrain horizon is subtracted, and the level is calibrated to the multi-year mean. Cross-validated against the PVGIS hourly simulation at four reference sites across seven orientations each: relative yield agrees within 1.5 percentage points, typically better than 1.

Does this calculator work outside Germany, Austria and Switzerland?

Not yet. The hourly grid currently covers the DACH region (1,155 grid points at 0.25°). For other regions the official tools are the best choice: PVGIS by the European Commission (worldwide except polar regions) or NREL PVWatts for the United States. A US grid built on NSRDB hourly data is in preparation — with the same per-direction analysis and day profiles as here.