PPolySim OS
For Engineers · Renewable Integration

Renewable Integration for a PCB trace

Built for engineers using it for real design work. Go from concept to a running model in the browser, then scale to the cloud when needed. Simulate a PCB trace live below — adjust the inputs and watch it respond, right in your browser.

Wind Turbine PowerLive

Controls

Presets

Wind power scales with the cube of wind speed and the square of rotor diameter — which is why turbines keep getting bigger and why a windy site is worth so much more. No turbine can extract more than 59.3% of the wind's energy (the Betz limit); real machines reach about 45%. Below cut-in and above cut-out speeds they produce nothing.

▶ Run in Python

Data Inspector

Power output1.64 MW
Rated power2.83 MW
Swept area6362 m²
% of Betz limit71%

Governing equation

Reading this result: In the ramp region power climbs with the cube of wind speed, so even a small gust adds a large jump in output.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

Solar PV SystemLive

Controls

Presets

A solar array's output is its rated power (area × efficiency at 1000 W/m²) multiplied by the peak sun hours your location receives — the equivalent full-intensity hours per day. Tilt matters too: aiming the panels near your latitude maximizes annual yield. Real systems lose a bit more to heat, wiring, and inverters.

▶ Run in Python

Data Inspector

System rating4.0 kW
Daily energy19.2 kWh
Annual energy6996 kWh
Homes powered0.7

Governing equation

Reading this result: A 4.0 kW array in 5-sun-hour sun yields about 19.2 kWh/day — roughly 0.7 average homes.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

3

Battery Storage

open full solver →
Battery Energy StorageLive

Controls

Presets

A battery's rated capacity is not all usable: depth-of-discharge limits protect its life, and round-trip efficiency means some energy is lost charging and discharging. What actually reaches your home is capacity × depth-of-discharge × round-trip efficiency. Together with cycle life, these set backup duration and the cost per stored kilowatt-hour.

▶ Run in Python

Data Inspector

Usable capacity12.2 kWh
Delivered / cycle10.9 kWh
Backup time26.2 hr
Lifetime throughput66 MWh

Governing equation

Reading this result: Usable energy is capacity × depth-of-discharge × round-trip efficiency, so only 10.9 of 13.5 kWh (81%) reaches your home each cycle — the discharge limit removes more here than efficiency does.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

or unlock everything with Pro →

More with Renewable Integration

Frequently asked questions

Is this good for engineers?
Yes — this version of "Renewable Integration for a PCB trace" is framed for engineers using it for real design work. Go from concept to a running model in the browser, then scale to the cloud when needed.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.