PPolySim OS
Use case · powered by Solar PV System

Solar PV System for a hydro dam

Simulate a hydro dam live in your browser. This runs the real Solar PV System solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

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.

2

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.

Levelized Cost of EnergyLive

Controls

Presets

LCOE spreads a power project's lifetime cost over every megawatt-hour it produces, letting wildly different technologies be compared fairly. It rewards high capacity factors and cheap capital, and punishes idle plants. The capital-recovery factor discounts future costs to today. It is the number that has made solar and wind the cheapest new power in most of the world.

▶ Run in Python

Data Inspector

LCOE$52/MWh
Per kWh5.2¢
Capacity factor25%

Governing equation

Reading this result: At a 25% capacity factor the plant sits idle most of the time, so its capital is spread over few MWh — that thin denominator is what pushes LCOE up to $52/MWh.

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

or unlock everything with Pro →

About this simulation

The full Solar PV System tool models a hydro dam with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Solar PV System

Other ways to simulate a hydro dam

Frequently asked questions

How do I simulate a hydro dam?
Open this page and use the live Solar PV System tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?
Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?
Absolutely — every input is adjustable, and with data import you can drive a hydro dam from your own measurements.