Battery Controller

Home battery cost optimization for Home Assistant.

Battery Controller is a Home Assistant custom integration that works out when your home battery should charge and discharge so your electricity bill is as low as possible. It solves the whole planning horizon with dynamic programming rather than reacting to the current price, so it can hold capacity back for a better opportunity later in the day.

This integration is aimed at technically experienced users

It requires setting up and tuning a number of parameters (efficiency, degradation costs, price sensors, control mode) and connecting it to your inverter via automations. Incorrect configuration will not damage your battery, but may result in suboptimal scheduling or no control at all. If you are not comfortable reading diagnostics data and interpreting optimizer output, this integration may not be the right fit — yet.

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Analyze your own setup

Open the Diagnostics Analyzer

Upload your diagnostics.json for a full breakdown of your configuration, optimizer schedule, profitability analysis, and improvement tips — no installation required. The analyzer runs entirely in your browser: nothing is uploaded to a server. It visualizes the current schedule, re-runs the DP optimizer with your data, and explains every charge/discharge decision.

To generate a diagnostics file: Settings → Devices & Services → Battery Controller → three-dot menu → Download diagnostics.

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Start here

• Installation

  Prerequisites, verifying your price and consumption sensors, HACS setup.

• Configuration reference

  Every option in the main entry, battery subentries and PV array subentries.

• Control modes

  Zero-grid, follow-schedule, hybrid, hybrid+ and manual — and which to pick.

• Connecting your inverter

  Which sensor to read, sign conventions, and a working example automation.

• How it works

  The coordinator cascade, the historical price model, and the learning period.

• FAQ

  Real questions from the issue tracker: modes, sensors, signs, forecasts.

• Troubleshooting

  What to check when nothing is scheduled, or the forecast looks wrong.

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What it optimizes on

The schedule is calculated from:

• Electricity price forecasts — Nordpool, ENTSO-E, OMIE, or any price sensor with forecast attributes such as the Dynamic Energy Contract Calculator
• PV production forecasts — from open-meteo.com solar radiation data, or from a PV forecast integration such as Solcast
• Household consumption patterns — learned from your historical energy meter data
• Battery characteristics — capacity, power limits, round-trip efficiency, degradation
• A historical price model — fallback and horizon extension for when day-ahead prices are not yet published

Battery Controller works with any battery inverter and electricity meter. It is a calculated integration that reads sensors and writes setpoints — it does not communicate directly with hardware. Connecting the setpoint to your inverter is your job, via an automation.

flowchart LR
    subgraph IN["Inputs (sensors you configure)"]
        P["Price sensor<br/>+ forecast"]
        C["Energy meters<br/>(gross load)"]
        S["Battery SoC"]
        G["Grid meter (W)"]
    end

    subgraph BC["Battery Controller"]
        W["Weather<br/>open-meteo"] --> F["Forecast<br/>PV + consumption"]
        F --> O["DP optimizer<br/>24-36 h horizon"]
        O --> Z["Zero-grid<br/>controller ~5 s"]
    end

    subgraph OUT["Outputs (entities)"]
        SP["Battery Setpoint (W)"]
        SC["Schedule"]
        SH["Shadow price"]
    end

    P --> F
    C --> F
    S --> O
    G --> Z
    Z --> SP
    O --> SC
    O --> SH
    SP -.->|"your automation"| INV["Your inverter"]

    style BC fill:#0f766e22,stroke:#0f766e
    style INV stroke-dasharray: 5 5

The dashed arrow is the part you build yourself — see connecting your inverter.

Key features

• Price arbitrage — charge during cheap hours, discharge during expensive hours
• Multi-battery support — multiple batteries with independent sensors, treated as one aggregate while setpoints are distributed proportionally
• Multi-array PV — any number of arrays with independent orientation and tilt
• Pre-day-ahead price model — optimize before day-ahead prices are published (typically before 13:00 CET) using a self-learning historical model
• Horizon extension — when live prices cover less than 24 hours, the remainder is filled from the historical model automatically
• PV self-consumption — maximize use of solar energy, minimize feed-in
• DC-coupled PV support — higher efficiency for panels directly on the battery inverter's DC bus (hybrid inverters)
• Zero-grid control — real-time battery control to minimize grid exchange
• Degradation-aware — battery wear is part of the cost function
• Multiple control modes — zero-grid, follow schedule, hybrid, hybrid+, or manual
• Negative price handling — suggests PV curtailment or maximum power consumption during negative prices

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License

Battery Controller is released under the Apache License 2.0. See LICENSE for details.