Smart Optimization
Important: Solar forecasting must be configured for accurate scheduling — either install the Solcast Solar HA integration (recommended, PowerSync auto-detects it) or enter your Solcast API key directly in PowerSync's Weather & Solar Forecast settings. Without solar forecast data, the optimizer has no visibility on solar production and will make purely price-based decisions — which can result in unnecessary grid imports even when solar is available.
PowerSync includes a built-in linear programming (LP) optimizer that calculates the optimal battery charge/discharge schedule based on electricity prices, solar forecasts, and load patterns. No external dependencies required.
Acknowledgement: The optimization approach was inspired by HAEO (Home Assistant Energy Optimizer).
The optimizer uses scipy's HiGHS LP solver to solve a cost minimization problem over a 48-hour horizon:
Minimize: Sum (import_price[t] * grid_import[t] - export_price[t] * grid_export[t]) * dt
Subject to:
- Power balance: solar[t] + grid_import[t] + battery_discharge[t]
= load[t] + grid_export[t] + battery_charge[t]
- SOC dynamics: soc[t] = soc_0 + Sum(charge*eff - discharge/eff) * dt / capacity
- SOC limits: backup_reserve <= soc[t] <= 1.0
- Rate limits: charge <= max_charge_kw, discharge <= max_discharge_kw
The optimizer runs directly inside PowerSync:
- Collects price, solar, and load forecasts from configured providers
- Overlays EV charging plans into the load forecast (if EV integration is enabled)
- Solves the LP problem in a background thread (typically < 1 second)
- Maps the solution to battery actions (charge, discharge, idle, self-consumption)
- Executes battery commands via the appropriate control method
If scipy is unavailable, a greedy fallback optimizer runs instead.
| Action | What It Does | When It's Used |
|---|---|---|
| CHARGE | Force charge battery from grid | Cheap import periods (overnight off-peak) |
| EXPORT | Force discharge battery to grid | Expensive export periods (evening peak) |
| IDLE | Hold battery at current SOC (sets backup reserve) | Grid is cheaper than battery round-trip |
| SELF_CONSUMPTION | Battery operates naturally | Solar hours, moderate prices |
| OFF_GRID | Physically disconnect from grid (Tesla only) | Negative export prices — avoids paying to export |
| Feature | Description |
|---|---|
| 48-Hour Optimization | Plans battery actions for the next 48 hours |
| 5-Minute Resolution | 576 optimization intervals for fine-grained control |
| Solar Integration | Uses Solcast forecast data for solar predictions |
| Price Integration | Works with Amber, Localvolts, Octopus, Flow Power, AEMO, and TOU tariffs |
| EV Load Awareness | Incorporates planned EV charging into the load forecast |
| Daily Cost Tracking | Actual cost (midnight to now) + predicted cost (now to midnight) |
| Zero Setup | Built-in — no external integrations or HACS repos needed |
| Off-Grid Curtailment | Automatically islands the Powerwall during negative export prices (opt-in, Tesla only) |
When enabled in Battery Setup > Local Control, the optimizer can physically disconnect the Powerwall from the grid during negative export price periods instead of just setting Tesla's export rule to "never". This is a stronger curtailment method — the grid contactor physically opens, guaranteeing zero export.
The optimizer identifies eligible periods as a post-LP overlay: slots where the export price is below 1c/kWh AND the LP already chose SELF_CONSUMPTION or IDLE. Contiguous runs of 3+ eligible slots (15 minutes minimum) are marked as OFF_GRID to avoid rapid contactor cycling. A reconnect buffer is automatically inserted before any upcoming CHARGE window.
Requirements:
- Tesla Powerwall with completed gateway pairing
- Off-grid curtailment enabled in Battery Setup > Local Control
- Optimizer enabled
Safety gates (from the curtailment fallback):
- SOC floor (default 40%) — won't go off-grid below this level
- Daily duration cap (default 6 hours)
When the optimizer is enabled and owns off-grid decisions, the independent price-check curtailment loop is bypassed to prevent conflicts. If the optimizer is disabled (monitoring mode), the independent loop still works.
Solar continues producing while off-grid — it charges the battery and powers the home. The battery is the sole backup when solar is insufficient, which is why the SOC floor is important.
When using dynamic pricing providers (Amber, AEMO, Octopus Agile/Flux, Flow Power), the optimizer receives price forecasts up to 48 hours ahead. Near-term prices are accurate but far-future forecasts are speculative — a predicted 40c/kWh spike at 2am tomorrow might settle at 22c.
Without adjustment, the LP would take those speculative prices at face value. It might charge overnight at 20c for a "spike" 18 hours away that never materializes, when cheaper midday solar charging is available in between.
Confidence decay addresses this by pulling above-median prices toward the median as they get further from now:
decayed_price = median + (raw_price - median) × e^(-rate × excess_hours)
| Parameter | Value | Description |
|---|---|---|
| Horizon | 4 hours | Prices within 4h are trusted completely (no decay) |
| Decay rate | 0.15 | Exponential decay coefficient beyond the horizon |
With a median of 21c/kWh and a raw forecast price of 30c/kWh:
| Hours ahead | Excess | Decay factor | Decayed price |
|---|---|---|---|
| 5h | 0h | 1.00 | 30.0c (within horizon) |
| 8h | 2h | 0.74 | 27.7c |
| 12h | 6h | 0.41 | 24.7c |
| 24h | 18h | 0.07 | 21.6c (nearly median) |
The decay is asymmetric — only above-median prices are decayed. Below-median (cheap) prices are preserved because cheap periods are structurally reliable: midday solar dumps and off-peak overnight rates are predictable, not speculative.
This ensures the LP can see that midday at 15c is genuinely cheaper than overnight at 18c, and won't pre-charge overnight for a dubious far-future spike when cheaper daytime charging is available.
Note: Confidence decay is not applied to static TOU providers (GloBird, custom tariffs) where prices are known and fixed.
The hardware backup reserve is a floor that the battery hardware enforces independently of the optimizer. This is useful as a safety net — even if the optimizer schedules a full discharge, the hardware won't go below this level.
- Set via the mobile app: Settings > Optimization > Reserve Levels > Hardware Backup Reserve
- This value is written directly to the battery hardware (e.g. Tesla backup_reserve, FoxESS min_soc)
- The LP optimizer's backup reserve is a separate, software-level floor used during schedule planning
- Typically set the hardware reserve a few percent below the optimizer reserve as a safety margin
Solcast Solar forecast is required. Without it, the optimizer cannot see when solar will be available and will make decisions based only on electricity prices — leading to unnecessary grid imports even when the sun is shining and your battery is full.
Configure one of:
- Solcast Solar HA integration (recommended) — install via HACS, PowerSync auto-detects it. No API key needed in PowerSync.
- Solcast API key in PowerSync — enter directly in the Weather & Solar Forecast settings (in HA config flow or mobile app). Requires a free account at toolkit.solcast.com.au.
- Install Solcast Solar (see prerequisites above)
- Go to Settings > Devices & Services > PowerSync > Configure
- Select Smart Optimization (Built-in LP) as your optimization provider
- Set your backup reserve percentage
- In the mobile app: Controls > toggle Enable on the Smart Optimization card
- View the schedule by tapping View Full Schedule
Use the power_sync.enable_optimizer and power_sync.disable_optimizer services in HA automations. For example, disable the optimizer during a manual force charge window and re-enable afterwards:
automation:
- alias: "Disable optimizer for manual charge"
trigger:
- platform: state
entity_id: input_boolean.manual_charge
to: "on"
action:
- service: power_sync.disable_optimizer
- service: power_sync.force_charge
data:
duration_minutes: 60
- alias: "Re-enable optimizer after manual charge"
trigger:
- platform: state
entity_id: input_boolean.manual_charge
to: "off"
action:
- service: power_sync.enable_optimizer+-----------------------------------------------------------+
| Data Sources |
| - Amber/Localvolts/Octopus/Flow Power/AEMO prices |
| - Solcast solar forecasts |
| - Historical load estimation |
| - EV charging plan overlay |
+-----------------------------------------------------------+
|
v
+-----------------------------------------------------------+
| Built-in LP Optimizer (scipy linprog / HiGHS) |
| Collects forecasts -> LP solve -> Optimal schedule |
| Fallback: Greedy algorithm if scipy unavailable |
+-----------------------------------------------------------+
|
v
+-----------------------------------------------------------+
| Execution Layer |
| Schedule -> Battery commands |
| - Tesla: TOU tariff trick |
| - FoxESS: Remote control registers (46001-46004) |
| - Sigenergy: Remote EMS mode control |
| - Sungrow: Modbus force mode commands |
| - GoodWe: ECO Charge/Discharge modes |
+-----------------------------------------------------------+
PowerSync creates forecast sensors for dashboard visibility:
| Sensor | Description | Unit |
|---|---|---|
sensor.powersync_price_import_forecast |
Grid import price forecast | $/kWh |
sensor.powersync_price_export_forecast |
Feed-in/export price forecast | $/kWh |
sensor.powersync_solar_forecast |
Solar PV generation forecast | W |
sensor.powersync_load_forecast |
Home consumption forecast | W |
Each sensor includes a forecast attribute with up to 576 data points (48 hours at 5-minute intervals).
The optimization screen in the mobile app shows:
| Section | Description |
|---|---|
| Status | Whether optimization is active and the current mode |
| Current/Next Action | What the battery is doing now and what's coming next |
| Predicted Cost | Estimated electricity cost for the day |
| Savings | How much you're saving vs no optimization |
| 48-Hour Chart | Visual timeline of SOC and power |
| Upcoming Actions | List of scheduled charge/discharge periods |
