Energy flow diagram
See where modeled power comes from and where it goes.
Follow each flow step from source to load without guessing.
Product
Understand how your battery system behaves — before it matters.
PyMox turns your system definition into simulations and dashboards, so you can plan reserve, charging and loads using your own assumptions.
Move from guesswork to a model you can test: one place to define your system, plan ahead and compare strategies.
What is PyMox?
PyMox is a modeling, simulation and planning layer for battery-centered energy systems.
It covers battery, solar, grid and mixed DC/AC setups, so you can see how the parts behave together.
Instead of splitting insight across disconnected tools, PyMox keeps your system model and strategy in one place so decisions stay consistent.
Key features
Built for owners and installers who need clarity without guesswork.
Battery state and history
Track SoC, charging behavior and capacity trends from your recorded data.
Spot battery stress early and protect long-term runtime.
Grid import and export visibility
Review modeled grid pull, export moments and limits.
Make informed decisions around tariffs, caps, and events.
Solar, alternator, and charger inputs
Combine charging sources with a clear priority model.
Coordinate sources in one model instead of manual switching.
Strategy modes
Compare peak shaving, island mode and more.
Choose the behavior that matches your location and constraints.
History and analytics
Review day, week, and month energy performance.
Compare trends and evaluate strategy changes over time.
Bring your own data
Send readings in through scoped API tokens, or enter values manually.
PyMox models and reports on your system; it does not read from or control your equipment.
Strategy modes
PyMox applies a clear priority model so simulated behavior stays predictable.
Configurable settings
- Peak shaving toggle
- Island or off-grid priority mode
- Charge-when-connected behavior
- Minimum SOC reserve threshold
- Import and export limits
What you can plan for
- Plan to reduce grid spikes during peak tariffs
- Check you stay within campsite power limits
- Protect reserve for overnight loads
- Maximize local solar self-consumption in your model
Screenshots and walkthrough
A quick product tour of the core views users rely on every day.
Each view turns your system data into actionable insight so you can protect reserve, reduce grid costs and improve system reliability.
The screenshots below are paired with practical interpretation so you can move from viewing data to making concrete planning decisions.
Off-grid battery outlook dashboard
This view explains if your current reserve strategy can survive the forecast window and which loads are most responsible for battery depletion.
- See when reserve is expected to be reached so you can act before critical hours.
- Identify the top generators and consumers driving your projected uptime.
- Validate whether your current assumptions are conservative enough for off-grid operation.
Grid-connected battery outlook dashboard
For grid-connected systems, this panel clarifies how much performance depends on the grid versus local generation and storage behavior.
- Compare solar and grid contribution at a glance to understand true dependency.
- Check reserve threshold behavior against real load patterns and confidence levels.
- Spot avoidable losses that erode battery efficiency over the planning horizon.
Daily energy balance chart
This chart gives a clean day-by-day balance between production and demand, making trend changes visible before they become operational issues.
- Track daily shifts in generation, consumption, and net energy in one timeline.
- Detect drift in demand or production early instead of relying on weekly averages.
- Measure the impact of strategy changes after load scheduling or hardware updates.
Battery history and deep discharge chart
Battery history exposes how hard the system cycles in practice, so you can protect battery health while keeping enough usable capacity.
- Review SoC volatility and daily min/max behavior across the selected period.
- Quantify deep-discharge frequency to evaluate long-term stress on the battery bank.
- Tune reserve policy and charging windows to reduce avoidable degradation.
Systems PyMox can model
Built to represent common inverter and charger setups. PyMox models these systems; it does not connect to them.
Victron-style inverter and charger setups
Hybrid inverter and battery systems
Shore power and campsite connections
Solar MPPT and alternator charging inputs
Who PyMox is for
Explore detailed scenarios on the use-cases page.
Built in public
PyMox is developed in the open with a transparent roadmap and regular updates.
Start modeling your energy system today.
Start with a clear baseline, test your strategy, and refine the model as your system evolves.