Plan a photovoltaic system and explore its yield in seconds

We query the European Commission's Photovoltaic Geographical Information System (PVGIS 5.3), the open dataset from the Joint Research Centre (JRC) in Ispra, Italy. PVGIS aggregates satellite-derived solar radiation observations and ground-station measurements across Europe, Africa, and large parts of Asia, and corrects them for terrain shading. The data is updated periodically by the JRC and is the reference dataset used by EU policy bodies and many commercial solar planners.

For mid-latitude European locations the typical PVGIS estimate sits within roughly ±5–10 % of the true long-term annual yield, based on JRC validation against measured plants. Year-to-year variation is larger (often ±10 % around the mean) — a single sunny year can sit well above the average and a cloudy year well below. The simulator gives you the long-term expectation, not a forecast for any specific year. Local micro-effects (chimneys, neighbouring buildings, trees) are not modeled and can reduce yield by several percent.

System losses bundle several DC- and AC-side imperfections: cable resistance, mismatch between modules, dust and snow soiling, inverter conversion losses, and module temperature de-rating. PVGIS uses 14 % as a conservative default; modern installations with high-quality inverters and clean modules can reach 10–12 %, while older or partially shaded systems may exceed 18 %. If you don't know your system, leaving the default value is sensible.

At European latitudes, the optimum fixed tilt for annual yield typically sits between 30° and 40°, and the optimum azimuth is south (180°). Deviations are forgiving: a 45° east-west azimuth costs only about 5 % annual yield versus optimal, and most flat-roof installations on shallow tilts lose less than 10 %. Steep roofs facing north are the worst case — yield can drop by 30 % or more relative to optimal. Two strings on opposite roof faces (east + west) can also be a sensible compromise to flatten the daily curve.

No — the simulator gives the gross AC yield at the inverter output. Whether that energy is self-consumed or fed into the grid, and at what tariff, depends on your country, your contract, and your load profile. For Germany 2026 the typical EEG feed-in tariff for new small residential systems is around 8 cent/kWh, while self-consumed power offsets your retail electricity price (commonly 30–40 cent/kWh) — making self-consumption typically 3–5× more economically valuable than feed-in.

The simulator deliberately stops at production. Battery sizing is a separate exercise that depends on your hourly consumption pattern, the cycling efficiency of the battery (typically 85–95 % round-trip), and the economic gap between buy and sell prices. Adding a battery to a typical household raises the self-consumption rate from around 30 % to 60–70 %, but the marginal kWh of storage gets less and less useful — so it pays to size carefully rather than maximally.